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Abstract Korla pear has a unique taste and aroma and is a breeding parent of numerous pear varieties. It is susceptible to Valsa mali var. pyri, which invades bark wounded by freezing injury. Its genetic relationships have not been fully defined and could offer insight into the mechanism for freezing tolerance and disease resistance. We generated a high-quality, chromosome-level genome assembly for Korla pear via the Illumina and PacBio circular consensus sequencing (CCS) platforms and high-throughput chromosome conformation capture (Hi-C). The Korla pear genome is ~ 496.63 Mb, and 99.18% of it is assembled to 17 chromosomes. Collinearity and phylogenetic analyses indicated that Korla might be derived from Pyrus pyrifolia and that it diverged ~ 3.9-4.6 Mya. During domestication, seven late embryogenesis abundant (LEA), two dehydrin (DHN), and 54 disease resistance genes were lost from Korla pear compared with P. betulifolia. Moreover, 21 LEA and 31 disease resistance genes were common to the Korla pear and P. betulifolia genomes but were upregulated under overwintering only in P. betulifolia because key cis elements were missing in Korla pear. Gene deletion and downregulation during domestication reduced freezing tolerance and disease resistance in Korla pear. These results could facilitate the breeding of novel pear varieties with high biotic and abiotic stress resistance.

Abstract Background Quercetin is a flavonol compound widely distributed in plants that possesses diverse biological properties, including antioxidative, anti-inflammatory, anticancer, neuroprotective and senescent cell-clearing activities. It has been shown to effectively alleviate neurodegenerative diseases and enhance cognitive functions in various models. The immune system has been implicated in the regulation of brain function and cognitive abilities. However, it remains unclear whether quercetin enhances cognitive functions by interacting with the immune system. Results In this study, middle-aged female mice were administered quercetin via tail vein injection. Quercetin increased the proportion of NK cells, without affecting T or B cells, and improved cognitive performance. Depletion of NK cells significantly reduces cognitive ability in mice. RNA-seq analysis revealed that quercetin modulated the RNA profile of hippocampal tissues in aging animals towards a more youthful state. In vitro, quercetin significantly inhibited the differentiation of Lin−CD117+ hematopoietic stem cells into NK cells. Furthermore, quercetin promoted the proportion and maturation of NK cells by binding to the MYH9 protein. Conclusions In summary, our findings suggest that quercetin promotes the proportion and maturation of NK cells by binding to the MYH9 protein, thereby improving cognitive performance in middle-aged mice. Graphical abstract

Abstract Creatine kinases are essential for maintaining cellular energy balance by facilitating the reversible transfer of a phosphoryl group from ATP to creatine, however, their role in mitochondrial ATP production remains unknown. This study shows creatine kinases, including CKMT1A, CKMT1B, and CKB, are highly expressed in cells relying on the mitochondrial F1F0 ATP synthase for survival. Interestingly, silencing CKB, but not CKMT1A or CKMT1B, leads to a loss of sensitivity to the inhibition of F1F0 ATP synthase in these cells. Mechanistically, CKB promotes mitochondrial ATP but reduces glycolytic ATP production by suppressing mitochondrial calcium (mCa2+) levels, thereby preventing the activation of mitochondrial permeability transition pore (mPTP) and ensuring efficient mitochondrial ATP generation. Further, CKB achieves this regulation by suppressing mCa2+ levels through the inhibition of AKT activity. Notably, the CKB‐AKT signaling axis boosts mitochondrial ATP production in cancer cells growing in a mouse tumor model. Moreover, this study also uncovers a decline in CKB expression in peripheral blood mononuclear cells with aging, accompanied by an increase in AKT signaling in these cells. These findings thus shed light on a novel signaling pathway involving CKB that directly regulates mitochondrial ATP production, potentially playing a role in both pathological and physiological conditions.

Abstract Background Mesenchymal stem cells (MSCs) hold a great promise for cell-based therapy in the field of regenerative medicine. In this study, we aimed to evaluate the safety and efficacy of intravenous infusion of human umbilical cord-derived MSCs (HUC-MSCs) in patients with aging frailty. Methods In this randomized, double-blind, placebo-controlled trial, participants diagnosed with aging frailty were randomly assigned to receive intravenous administrations of HUC-MSCs or placebo. All of serious adverse events and AEs were monitored to evaluate the safety of treatment during the 6-month follow-up. The primary efficacy endpoint was alteration of physical component scores (PCS) of SF-36 qualities of life at 6 months. The secondary outcomes including physical performance tests and pro-inflammatory cytokines, were also observed and compared at each follow-up visits. All evaluations were performed at 1 week, 1, 2, 3 and 6 months following the first intravenous infusion of HUC-MSCs. Results In the MSCs group, significant improvements in PCS of SF-36 were observed from first post-treatment visit and sustained throughout the follow-up period, with greater changes compared to the placebo group (p = 0.042). EQ-VAS scores of MSCs group improved significantly at 2 month (p = 0.023) and continued until the end of the 6-month visit (p = 0.002) in comparison to the placebo group. The timed up and go (TUG) physical performance test revealed significant group difference and showed continual enhancements over 6 months (p

The lack of reliable negative samples is an important factor limiting the quality of machine learning-based debris flow susceptibility mapping (DFSM). The purpose of this paper is to propose multiple negative-sample acquisition strategies for DFSM considering different sample representation forms. The sample representation forms mainly include a single grid, multi-grid, and watershed unit, and the negative-sample acquisition strategies are based on support vector machine (SVM), spy technique, and isolation forest (IF) methods, respectively. These three strategies can assign a value to all the samples based on different assumptions, and reliable, negative samples can be generated from samples with values below a predefined threshold. Combining different sample representation forms with negative sample acquisition strategies, nine datasets were then involved in random forest (RF) modeling. The receiver operating characteristic (ROC) curves and related statistical results were used to evaluate the models. The results show that the strategy based on the spy technique is suitable for multiple datasets, while the IF-based strategy is well-adapted to the watershed unit datasets. This study can provide more options for improving the quality of datasets in DFSM, which can further improve the performance of machine learning models.

Abstract Background Metformin, a type 2 diabetes treatment, improves the cognitive function of aged mice; however, whether the protective effects of metformin on cognitive function in aged mice are associated with the gut microbiome is poorly understood. Although some studies suggest that the gut microbe composition influences cognitive function and that manipulating the gut microbiota might protect against age-related cognitive dysfunction, there is no direct evidence to validate that the gut microbiota mediates the effect of metformin on cognitive improvement. Results In this study, we show that the gut microbiota is altered by metformin, which is necessary for protection against ageing-associated cognitive function declines in aged mice. Mice treated with antibiotics did not exhibit metformin-mediated cognitive function protection. Moreover, treatment with Akkermansia muciniphila, which is enriched by metformin, improved cognitive function in aged mice. Mechanistically, A. muciniphila decreased pro-inflammatory-associated pathways, particularly that of the pro-inflammatory cytokine interleukin (IL)-6, in both the peripheral blood and hippocampal profiles, which was correlated with cognitive function improvement. An IL-6 antibody protected cognitive function, and an IL-6 recombinant protein abolished the protective effect of A. muciniphila on cognitive function in aged mice. Conclusion This study reveals that A. muciniphila, which is mediated in the gut microbiota by metformin, modulates inflammation-related pathways in the host and improves cognitive function in aged mice by reducing the pro-inflammatory cytokine IL-6. Video Abstract Graphical Abstract

Flight control law parameters should be designed to provide a sufficient stability margin for closed-loop aircraft while ensuring command tracking accuracy. The singular perturbation margin (SPM) and generalized gain margin (GGM), which are generalizations of the classical phase margin (PM) and gain margin (GM), respectively, from a linear time-invariant system to a nonlinear time-varying system, can be used to quantitatively characterize the maximum singular perturbation and regular perturbation allowed to maintain system stability. In this paper, the sliding mode flight control structure and the design parameters of the sliding mode control law are first introduced for an oblique wing aircraft (OWA), the SPM-gauge and GGM-gauge are added to this closed-loop aircraft model, and the analytical expressions of the SPM and GGM are derived with respect to the control law parameters. Second, the stability margin design requirements of closed-loop aircraft in flight control system design specifications are converted into limitations on the SPM and GGM to determine the value range of the flight control law parameters. Then, with the goal of reducing the sum of the approaching time and sliding time, the parameter value combination is selected within the control law parameter range that meets the stability margin requirements, thus forming a flight control law design method for OWA during the wing skewing process. Finally, the designed control law parameters are applied to a sample OWA, and the stability margin of closed-loop aircraft during the wing skewing process is verified.

ABSTRACTThe gut-joint axis, one of the mechanisms that mediates the onset and progression of joint and related diseases through gut microbiota, and shows the potential as therapeutic target. A variety of drugs exert therapeutic effects on rheumatoid arthritis (RA) through the gut-joint axis. However, the anti-inflammatory and immunomodulatory effect of novel photobiomodulatory therapy (PBMT) on RA need further validation and the involvement of gut-joint axis in this process remains unknown. The present study demonstrated the beneficial effects of PBMT on RA, where we found the restoration of gut microbiota homeostasis, and the related key pathways and metabolites after PBMT. We also discovered that the therapeutic effects of PBMT on RA mainly through the gut-joint axis, in which the amino acid metabolites (Alanine and N-acetyl aspartate) play the key role and rely on the activity of metabolic enzymes in the target organs. Together, the results prove that the metabolites of amino acid from gut microbiota mediate the regulation effect on the gut-joint axis and the therapeutic effect on rheumatoid arthritis of PBMT.

Bacterial nicotinamidase/pyrazinamidase PncA increases host nicotinamide adenine dinucleotide (NAD+) levels and ameliorates diet-induced non-alcoholic fatty liver disease (NAFLD) in mice.

Abstract Background Glycyrrhizic acid (GA), a saponin compound often used as a flavoring agent, can elicit anti-inflammatory and anti-tumor effects, and alleviate aging. However, the specific mechanism by which GA alters immune cell populations to produce these beneficial effects is currently unclear. Results In this study, we systematically analyzed single-cell sequencing data of peripheral blood mononuclear cells from young mice, aged mice, and GA-treated aged mice. Our in vivo results show that GA reduced senescence-induced increases in macrophages and neutrophils, and increased numbers of lymphoid lineage subpopulations specifically reduced by senescence. In vitro, GA significantly promoted differentiation of Lin−CD117+ hematopoietic stem cells toward lymphoid lineages, especially CD8+ T cells. Moreover, GA inhibited differentiation of CD4+ T cells and myeloid (CD11b+) cells by binding to S100 calcium-binding protein 8 (S100A8) protein. Overexpression of S100A8 in Lin− CD117+ hematopoietic stem cells enhanced cognition in aged mice and the immune reconstitution of severely immunodeficient B-NDG (NOD.CB17-Prkdcscid/l2rgtm1/Bcgen) mice. Conclusions Collectively, GA exerts anti-aging effects by binding to S100A8 to remodel the immune system of aged mice.

The upset state is an unexpected flight state, which is characterized by an unintentional deviation from normal operating parameters. It is difficult for the pilot to recover the aircraft from the upset state accurately and quickly. In this paper, an upset recovery strategy and pilot assistance system (PAS) based on reinforcement learning is proposed. The man–machine closed-loop system was established and the upset state, such as a high angle of attack and large attitude angle, was induced. The upset recovery problem was transformed into a sequential decision problem, and the Markov decision model of upset recovery was established by taking the deflection change of the control surface as the action. The proximal policy optimization (PPO) algorithm was selected for the strategy training. The adaptive pilot model and the reinforcement learning method proposed in this paper were used to make the aircraft recover from the upset state. Based on the correspondence between the flight state, the recovery method, and the recovery result, the aircraft upset recovery safety envelopes were formed, and the four-level upset recovery PAS with alarm warning, coordinated control, and autonomous recovery modes was constructed. The results of the digital virtual flight simulation and ground flight test show that compared with a traditional single pilot, the aircraft upset recovery strategy, the upset recovery safety envelopes, and the PAS established in this study could reduce the handling burden of the pilot and improve the success rate and effect of upset recovery. This research has certain theoretical reference values for flight safety and pilot training.

This paper introduces a facile solution route to fabricate MoTe2 grain nano-domains for hybrid polymer heterojunction solar cells and photodetectors. Fabricated MoTe2 structures were investigated using Raman and XRD, and surface morphologies characterized using FE-SEM and TEM. We subsequently assembled a non-fullerene polymer heterojunction device using the PBDB-T:ITIC active layer for ITO/HTL/active-layer/LiF/Al architype solar cells and photodetectors. We also investigated effects from different MoTe2 nanostructure proportions embedded in the PBDB-T:ITIC polymer matrix as active layers to assemble solar cell and photodetector devices. Maximum power conversion efficiency ≈8.94% with improved carrier mobility ≈9.23 × 10−4 cm2 V−1 s−1 was achieved for 10 vol% MoTe2 nanostructure inclusion with PBDB-T:ITIC active layer. A fabricated photodetector using 10 vol%-MoTe2@PBDB-T:ITIC film achieved maximum detectivity ≈2.62 × 1010 Jones with 0.706 A W−1 responsivity at 755 μW cm−2 light density under 656 nm laser source. The proposed facile approach to fabricate 2D MoTe2 atomic layer infusion with polymer heterojunction offers a credible mechanism to progress interfacial characteristics for future organic semiconducting devices.

Background The pain induced by postoperative dressing changes adversely influence recovery and quality of life. In this study, we try to evaluate the pain alleviation effect of virtual reality (VR) distraction during postoperative dressing changes of patients who received surgical drainage of perianal abscess. Methods This was a prospective, randomized clinical trial. A total of 172 patients with perianal abscess were randomly assigned into control (only analgesics) and VR groups (VR distraction + analgesics). The pain and physiological measurements of all patients were collected before, during, and after the first dressing change following surgery. The difference in pain intensity and physiological parameters measurement between control and VR group was analyzed. Results The baseline characteristics of VR and control group were comparable (all P > 0.05). There was no significant difference in mean pain scores prior to and after dressing change between groups (both P > 0.05). Mean pain scores of 5, 10, 15, and 20 min measuring points during the first dressing change were significantly lower in the VR group compared with the control group (all P

In numerical analysis, the pile equivalent calculation method plays a key role in foundation pit calculation results. However, the effect and mechanism of different pile equivalent calculation methods in the foundation pit has remained unclear. To solve this question, based on FLAC3D, four pile equivalent calculation methods were introduced into a typical pile–anchor pit. This research was carried out from the perspective of soil displacement and stress, special points’ stress paths, and the plastic zone. The results revealed that there was a remarkable influence on the calculation results for different pile equivalent calculation methods. Specifically, compared with structural pile elements, displacements near the pile were smaller in solid pile element mode. Moreover, with the increase in excavation depth, stress concentration appeared in the solid pile element mode. The solid support pile with the interface, compared to that without the interface, had less displacement but more stress concentration around the pile, which led the special points’ stress paths around the solid pile to become irregular. Regarding the structural pile elements, it is suggested that both modeling approaches had a similar effect. These findings could help to provide a deeper insight into pile–anchor foundation pit numerical analysis.

Using a nonlinear pilot-induced oscillation prediction method based on digital virtual flight simulation calculations, digital experiments on predicting lateral-directional nonlinear pilot-induced oscillations due to landing configuration switching of fly-by-wire civil aircraft with different closed-loop dynamic characteristics are carried out. It is proposed that the lateral-directional pilot-induced oscillations due to the landing configuration switch can be evaluated using the changes in dynamic characteristic parameters before and after the configuration switch. The quantitative boundaries of the dynamic characteristic parameters of an example aircraft are determined, and a criterion suggestion is formed to predict the lateral-directional nonlinear pilot-induced oscillations due to landing configuration switching. This study provides a reference for the optimal design of the lateral-directional flight control law of fly-by-wire aircraft during the approach stage and provides suggestions for the formulation of evaluation criteria for other nonlinear pilot-induced oscillation phenomena.

Sarcopenia, a disorder characterized by age-related muscle loss and reduced muscle strength, is associated with decreased individual independence and quality of life, as well as a high risk of death. Skeletal muscle houses a normally mitotically quiescent population of adult stem cells called muscle satellite cells (MuSCs) that are responsible for muscle maintenance, growth, repair, and regeneration throughout the life cycle. Patients with sarcopenia are often exhibit dysregulation of MuSCs homeostasis. In this review, we focus on the etiology, assessment, and treatment of sarcopenia. We also discuss phenotypic and regulatory mechanisms of MuSC quiescence, activation, and aging states, as well as the controversy between MuSC depletion and sarcopenia. Finally, we give a multi-dimensional treatment strategy for sarcopenia based on improving MuSC function.

When considering the robust control of fixed-wing Unmanned Aerial Vehicles (UAVs), a conflict often arises between addressing nonlinearity and meeting fast-solving requirements. In existing studies, the less nonlinear robust control methods have shown significant improvements that parallel computing and dimensionality reduction techniques in real-time applications. In this paper, a nonlinear fast Tube-based Robust Compensation Control (TRCC) for fixed-wing UAVs is proposed to satisfy robustness and fast-solving requirements. Firstly, a solving method for discrete trajectory tubes was proposed to facilitate fast parallel computation. Subsequently, a TRCC algorithm was developed that minimized the trajectory tube to enhance robustness. Additionally, considering the characteristics of fixed-wing UAVs, dimensionality reduction techniques such as decoupling and stepwise approaches are proposed, and a fast TRCC algorithm that incorporates the control reuse method is presented. Finally, simulations verify that the proposed fast TRCC effectively enhances the robustness of UAVs during tracking tasks while satisfying the requirements for fast solving.

This paper presents a monolithic microwave integrated circuit (MMIC) low noise amplifier (LNA) that is compatible with n257 (26.5–29.5 GHz) and n258 (24.25–27.5 GHz) frequency bands for fifth-generation mobile communications system (5G) and millimeter-wave radar. The total circuit size of the LNA is 2.5 × 1.5 mm2. To guarantee a trade-off between noise figure (NF) and small signal gain, the transmission lines are connected to the source of gallium nitride (GaN)-on-SiC high electron mobility transistors (HEMT) by analyzing the nonlinear small signal equivalent circuit. A series of stability enhancement measures including source degeneration, an RC series network, and RF choke are put forward to enhance the stability of designed LNA. The designed GaN-based MMIC LNA adopts hybrid-matching networks (MNs) with co-design strategy to realize low NF and broadband characteristics across 5G n257 and n258 frequency band. Due to the different priorities of these hybrid-MNs, distinguished design strategies are employed to benefit small signal gain, input-output return loss, and NF performance. In order to meet the testing conditions of MMIC, an impeccable system for measuring small has been built to ensure the accuracy of the measured results. According to the measured results for small signal, the three-stage MMIC LNA has a linear gain of 18.2–20.3 dB and an NF of 2.5–3.1 dB with an input–output return loss better than 10 dB in the whole n257 and n258 frequency bands.

Glycyrrhiza uralensis contains many secondary metabolites with a wide range of pharmacological activities. Drought stress acts as a positive regulator to stimulate the production of medicinal active component in G. uralensis, however, the underlying mechanism remains unclear. The aim of this work is to investigate the accumulation and regulatory mechanism of pharmaceutical active ingredients in G. uralensis under drought stress. The materials of the aerial and underground parts of G. uralensis seedlings treated by 10% PEG6000 for 0, 2, 6, 12, and 24 h were used for RNA sequencing and determination of phytohormones and pharmaceutical active ingredients. PEG6000, ibuprofen (IBU), and jasmonic acid (JA) were utilized to treat G. uralensis seedlings for content detection and gene expression analysis. The results showed that, the contents of glycyrrhizic acid, glycyrrhetinic acid, and flavonoids (licochalcone A, glabridin, liquiritigenin, isoliquiritigenin, and liquiritin) were significantly accumulated in G. uralensis underground parts under drought stress. Kyoto Encyclopedia of Genes and Genomes analysis of the transcriptome data of drought-treated G. uralensis indicated that up-regulated differentially expressed genes (UDEGs) involved in glycyrrhizic acid synthesis in the underground parts and flavonoids synthesis in both aerial and underground parts were significantly enriched. Interestingly, the UDEGs participating in jasmonic acid (JA) signal transduction in both aerial and underground parts were discovered. In addition, JA content in both aerial and underground parts under drought stress showed the most significantly accumulated. And drought stress stimulated the contents of JA, glycyrrhizic acid, and flavonoids, coupled with the induced expressions of genes regulating the synthesis and transduction pathway. Moreover, In PEG6000- and JA-treated G. uralensis, significant accumulations of glycyrrhizic acid and flavonoids, and induced expressions of corresponding genes in these pathways, were observed, while, these increases were significantly blocked by JA signaling inhibitor IBU. JA content and expression levels of genes related to JA biosynthesis and signal transduction were also significantly increased by PEG treatment. Our study concludes that drought stress might promote the accumulation of pharmaceutical active ingredients via JA-mediated signaling pathway, and lay a foundation for improving the medicinal component of G. uralensis through genetic engineering technology.

Alternative splicing (AS) is a post-transcriptional regulatory mechanism that increases protein diversity. There is growing evidence that AS plays an important role in regulating plant stress responses. However, the mechanism by which AS coordinates with transcriptional regulation to regulate the drought response in Glycyrrhiza uralensis remains unclear. In this study, we performed a genome-wide analysis of AS events in G. uralensis at different time points under drought stress using a high-throughput RNA sequencing approach. We detected 2,479 and 2,764 AS events in the aerial parts (AP) and underground parts (UP), respectively, of drought-stressed G. uralensis. Of these, last exon AS and exon skipping were the main types of AS. Overall, 2,653 genes undergoing significant AS regulation were identified from the AP and UP of G. uralensis exposed to drought for 2, 6, 12, and 24 h. Gene Ontology analyses indicated that AS plays an important role in the regulation of nitrogen and protein metabolism in the drought response of G. uralensis. Notably, the spliceosomal pathway and basal transcription factor pathway were significantly enriched with differentially spliced genes under drought stress. Genes related to splicing regulators in the AP and UP of G. uralensis responded to drought stress and underwent AS under drought conditions. In summary, our data suggest that drought-responsive AS directly and indirectly regulates the drought response of G. uralensis. Further in-depth studies on the functions and mechanisms of AS during abiotic stresses will provide new strategies for improving plant stress resistance.

ABSTRACT Oral antibiotics remain the therapy of choice for severe bacterial infections; however, antibiotic use disrupts the intestinal microbiota, increasing the risk of colonization by intestinal pathogens. Currently, our understanding of antibiotic-mediated disturbances of the microbiota remains at the level of bacterial families or specific species, and little is known about the effect of antibiotics on potentially beneficial and pathogenic bacteria under the conditions of gut microbiota dysbiosis. Additionally, the question of whether the effects of antibiotics on the gut microbiota are temporary or permanent is controversial. In this study, we used 16S rRNA gene sequencing to evaluate the short- and long-term effects of ampicillin, vancomycin, metronidazole, and neomycin on the murine intestinal microbiota. We found that the changes in the intestinal microbiota reflected the antibiotics’ mechanisms of action and that dysbiosis of the intestinal microbiota led to competition between different bacterial communities. In particular, an increase in Enterococcus, which accompanies a decrease in probiotics-related genera such as Lactobacillus, is commonly seen across antibiotic treatments. In addition, we found that these oral antibiotics had long-term negative effects on the intestinal microbiota and promoted the development of antibiotic-resistant bacterial strains. These results indicate that ampicillin, vancomycin, metronidazole, and neomycin have long-term negative effects and can cause irreversible changes in the diversity of the intestinal microbiota, thereby increasing the risk of host disease. IMPORTANCE The intestinal microbiota is a dynamic community of hundreds of millions of microorganisms that play important roles in human health. However, treatment with antibiotics can disrupt the delicate balance of this community, leading to deleterious effects on the host such as inflammation and enhanced susceptibility to infection. To date, most studies of the effects of antibiotic treatment on the microbiota have focused on specific intestinal pathogens and bacterial families. However, few studies have investigated the effects of antibiotic treatment on the relative abundance of probiotic bacteria, pathogenic bacteria, and opportunistic bacterial pathogens in the gut.

The current research into decision-making strategies for air combat focuses on the performance of algorithms, while the selection of actions is often ignored, and the actions are often fixed in amplitude and limited in number in order to improve the convergence efficiency, making the strategy unable to give full play to the maneuverability of the aircraft. In this paper, a decision-making strategy for close-range air combat based on reinforcement learning with variable-scale actions is proposed; the actions are the variable-scale virtual pursuit angles and speeds. Firstly, a trajectory prediction method consisting of a real-time prediction, correction, and judgment of errors is proposed. The back propagation (BP) neural network and the long and short term memory (LSTM) neural network are used as base prediction network and correction prediction network, respectively. Secondly, the past, current, and future positions of the target aircraft are used as virtual pursuit points, and they are converted into virtual pursuit angles as the track angle commands using angle guidance law. Then, the proximity policy optimization (PPO) algorithm is applied to train the agent. The simulation results show that the attacking aircraft that uses the strategy proposed in this paper has a higher win rate during air combat and the attacking aircraft’s maneuverability is fully utilized.

Traditional pathological diagnoses and clinical methods are insufficient to accurately predict the prognosis of lung adenocarcinoma (LUAD). Epithelial-mesenchymal transition (EMT) process is closely related to tumor cell migration. However, the prognostic value of EMT-related genes in LUAD is still unclear. In this study, we collected bulk RNA-sequencing (RNA-seq) and microarray data of LUAD patients from public databases and identified different expressed EMT-related genes in tumor and normal tissues. Then, we used the least absolute shrinkage and selection operator Cox regression model to develop a multigene signature in the cancer genome atlas (TCGA) cohort and validated the model in the OncoSG (Singapore Oncology Data Portal) cohort as well as other datasets. Finally, we constructed a 12-gene signature to divide LUAD patients into high-risk and low-risk groups of overall survival (OS), which has a better stability and accuracy in predicating the OS of patients compared with some other published signatures of LUAD. In addition, evaluation of the risk model using the time-related receiver operating characteristic (ROC) curve confirmed the predictive ability of the model. Functional analysis showed that these genes are related to immunity. CD8 T cell and CD4 T cell types were significantly negatively correlated with the risk score in the analysis of immune infiltration. In general, our model provides useful information that may help clinicians better predict the prognosis of LUAD patients and provides potential targets for immunotherapy of LUAD.

The wind tunnel virtual flight test realizes the dynamic semi-free flight of the model in the wind tunnel through the deflections of the control surface and uses the test data to identify the aerodynamic derivatives. The difference in dynamics between the wind tunnel virtual flight and the free flight leads to discrepancies between the identification and theoretical results. To solve the problems, a step-by-step identification and correction method for aerodynamic derivatives is established based on the difference between the equations of motion of wind tunnel virtual flight and free flight to identify and correct the lift, drag derivatives, pitch moment derivatives, and velocity derivatives, respectively. To establish an aerodynamic parameter identification model, the flight dynamics equation is expressed as a decoupled form of the free flight force and the influence of the test support frame force on the model’s motions through linearization. To ensure the identification accuracy of each aerodynamic derivative, an excitation signal design method based on amplitude–frequency characteristic analysis is proposed. The longitudinal aerodynamic parameter identification results of a blended-wing-body aircraft show that identification results with higher accuracy can be obtained by adopting the proposed identification and correction method.

Debris flow susceptibility mapping (DFSM), which has proven to be one of the most effective tools for risk management, faces a variety of problems. To realize the rational use of debris flow sample resources and improve the modeling efficiency, a unified model based on transfer learning was established for cross-regional DFSM. First, samples with 10 features collected from two debris flow-prone areas were separately used to perform factor prediction ability analysis (FPAA) based on the information gain ratio (IGR) method and then develop traditional machine learning models based on random forests (RF). Secondly, two feature matrices representing different areas were projected into a common latent feature space to obtain two new feature matrices. Then, the samples with new features were used together for FPAA and developing a unified machine learning model. Finally, the performance of the models was obtained and compared based on the area under curves (AUC) and some statistical results. All the conditioning factors played different roles in debris flow prediction in the two study areas, based on which two traditional models and a unified model were established. The unified model based on feature transferring realized efficient cross-regional modeling, solved the unconvincing problem of limited sample modeling, and enabled more accurate identification of some debris flow samples.

In this paper, we investigate the characteristics of the colorless polyimide (CPI) film-based flexible organic X-ray detector. The CPI film can be applied to various applications, because it shows excellent visible light transmittance by removing the yellow color of polyimide (PI) film, which has the advantage of physical and chemical stability. In addition, the deformation curvature of the CPI substrate according to temperature showed similar characteristics to that of the glass substrate. For the organic active layer of the proposed detector, PBDB-T was fixed as a donor, and PC71BM and ITIC were used as acceptors. To evaluate the mechanical stability of the flexible detector, the degradation sensitivity was measured as bending curvature and bending cycle. The sensitivity of the detector with ITIC acceptor showed a 46.82% higher result than PC71BM acceptor on bending curvature (R = 10); and at the same curvature, when the bending cycle was 500 times, a 135.85% higher result than PC71BM acceptor.