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Abstract Rapid glucose supply is crucial for animal survival during stress response. How the timescale of stress-induced glucose release precisely controlled by hypothalamic corticotropin-releasing hormone (CRH) neurons remains unclear. Here, we show that stress-induced hyperglycemia can be divided into at least two stages in male mice: the first fast stage is mediated by hypothalamus (paraventricular to ventromedial hypothalamus)-sympathetic (raphe pallidus nucleus to intermediolateral nucleus)-liver (HSL) axis activity; the second delayed stage is mediated by adrenal activity. Blocking the activity of HSL axis impairs predatory evoked flight responses, indicating that the HSL pathway activity is necessary for stress coping. We further reveal the intracellular signal cascade for CRH signal in the hypothalamus, which is mediated by GABAA receptor β3 subunit phosphorylation at S408/409, results in prevention of GABAA receptor membrane recruitment. Thus, we uncovered the precise timescale of glucose supply during stress which is mediated by adrenal independent HSL and adrenal dependent pathway respectively.

When considering agricultural commodity transaction data, long sampling intervals or data sparsity may lead to small samples. Furthermore, training on small samples can lead to overfitting and makes it hard to capture the fine-grained fluctuations in the data. In this study, a multi-scale forecasting approach combined with a Generative Adversarial Network (GAN) and Temporal Convolutional Network (TCN) is proposed to address the problems related to small sample prediction. First, a Time-series Generative Adversarial Network (TimeGAN) is used to expand the multi-dimensional data and t-SNE is utilized to evaluate the similarity between the original and synthetic data. Second, a greedy algorithm is exploited to calculate the information gain, in order to obtain important features, based on XGBoost. Meanwhile, TCN residual blocks and dilated convolutions are used to tackle the issue of gradient disappearance. Finally, an attention mechanism is added to the TCN, which is beneficial in terms of improving the forecasting accuracy. Experiments are conducted on three products, garlic, ginger and chili. Taking garlic as an example, the RMSE of the proposed method was reduced by 1.7% and 1% when compared to the SVR and RF models, respectively. Its R2 accuracy was also improved (by 4.3% and 3.4%, respectively). Furthermore, TCN-attention and TCN were found to require less time compared to GRU and LSTM. The accuracy of the proposed method increased by about 5% when compared to that without TimeGAN in the ablation study. Moreover, compared with TCN, the Gated Recurrent Unit (GRU), and the Long Short-term Memory (LSTM) model in the multi-scale price forecasting task, the proposed method can better utilize small samples and high-dimensional data, leading to improved performance. Additionally, the proposed model is compared to the Transformer and TimesNet models in terms of its accuracy, deployment cost, and other metrics.

Key points Microvascular impairment correlated with native T1 of remote myocardium. Native T1 values of remote myocardium changed dynamically. Native30D T1 and LGE were joint independent predictors of MACE.

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.

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.

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.

Quinoa bran is a by-product during quinoa processing, which is not well used due to its high content of antinutritional factors. The nutritional, antinutritional, antioxidative and mineral content were analyzed in quinoa bran from five producing areas (Hebei, Shanxi, Qinghai, Inner Mongolia and Gansu Province) in China. The results showed that the mean values of protein, starch, fat, fiber, reducing sugar, ash, moisture and energy in quinoa bran were 9.35%, 47.37%, 8.26%, 10.74%, 3.68%, 6.25%, 9.29% and 360.2 kcal/100 g, respectively. Although the protein content in quinoa bran is lower than that in quinoa grain, it is comparable to that in other grains (rice, corn, millet and sorghum) and brans (wheat, oat and rice), so it has the commercial potential to be processed into animal feed or other edible food. The contents of antioxidant flavonoids (460.9 mg/100g) and polyphenols (477.8 mg/100 g) in quinoa bran were higher than those in quinoa grain, suggesting that quinoa bran had better antioxidant capacity. The contents of saponins, tannins and phytic acid in quinoa bran were 18.65, 0.30 and 0.73%, respectively. The content of saponins was nearly one times higher than that in quinoa grain, the contents of tannins and phytic acid, however, were lower than those in quinoa grain. Therefore, the removal of saponins is the key to eliminate the antinutritional properties of quinoa bran. The contents of macroelements (sodium, potassium, calcium, magnesium, phosphorus) and microelements (iron, manganese, copper, zinc, cobalt, molybdenum, selenium, barium) in quinoa bran were generally higher than those in quinoa grain, which was consistent with the results of ash determination. In summary, quinoa bran was found to be a rich source of nutritional and bioactive components and minerals. If the antinutritional problem can be overcome, quinoa bran has great potential for application in the food industry.

Activation of mTORC1 is essential for anti-tumor function of iNKT cells. The mechanisms underlying impaired mTORC1 activation in intratumoral iNKT cells remain unclear. Via generating Vam6+/- mice and using flow cytometry, image approach, and RNA sequencing, we studied the role of Vam6 in controlling mTORC1 activation and intratumoral iNKT cell functions. Here, we find that increased Vam6 expression in intratumoral iNKT cells leads to impaired mTORC1 activation and IFN-γ production. Mechanistically, Vam6 in iNKT cells is essential for Rab7a-Vam6-AMPK complex formation and thus for recruitment of AMPK to lysosome to activate AMPK, a negative regulator of mTORC1. Additionally, Vam6 relieves inhibitory effect of VDAC1 on Rab7a-Vam6-AMPK complex formation at mitochondria-lysosome contact site. Moreover, we report that lactic acid produced by tumor cells increases Vam6 expression in iNKT cells. Given the key roles of increased Vam6 in promoting AMPK activation in intratumoral iNKT cells, reducing Vam6 expression signifificantly enhances the mTORC1 activation in intratumoral iNKT cells as well as their anti-tumor effificacy. Together, we propose Vam6 as a target for iNKT cell-based immunotherapy.

Objective Acupuncture is emerging as a potential therapy for relieving pain, but the effectiveness of acupuncture for relieving low back and/or pelvic pain (LBPP) during the pregnancy remains controversial. This meta-analysis aims to investigate the effects of acupuncture on pain, functional status and quality of life for women with LBPP pain during the pregnancy.Design Systematic review and meta-analysis.Data sources The PubMed, EMBASE databases, Web of Science and Cochrane Library were searched for relevant randomised controlled trials (RCTs) from inception to 15 January 2022.Eligibility criteria for selecting studies RCTs evaluating the effects of acupuncture on LBPP during the pregnancy were included.Data extraction and synthesis The data extraction and study quality assessment were independently performed by three reviewers. The mean differences (MDs) with 95% CIs for pooled data were calculated. We assessed the confidence in the evidence using the Grading of Recommendations Assessment, Development and Evaluation framework.Main outcomes and measures The primary outcomes were pain, functional status and quality of life. The secondary outcomes were overall effects (a questionnaire at a post-treatment visit within a week after the last treatment to determine the number of people who received good or excellent help), analgesic consumption, Apgar scores >7 at 5 min, adverse events, gestational age at birth, induction of labour and mode of birth.Results This meta-analysis included 10 studies, reporting on a total of 1040 women. Overall, acupuncture significantly relieved pain during pregnancy (MD=1.70, 95% CI: (0.95 to 2.45), p

Mindfulness has long been concerned and emphasized by scholars in the field of psychology, but there is still a lack of research on mindfulness in management in China. In this study, a questionnaire survey was conducted among 483 employees in the new media industry in Beijing, Shanghai, Guangzhou, Shenzhen, and Hangzhou, China. After modeling and analysis, it was found that employee mindfulness has a positive influence on innovative behavior. Employee mindfulness and innovative behavior are mediated by positive emotions. Employee mindfulness and innovative behavior are mediated by work engagement. Employee mindfulness and innovative behavior are mediated by a chain of positive emotions and work engagement. Enterprise managers should improve the level of mindfulness of employees in the new media industry through mindfulness training and courses for mindfulness training, create an organizational environment that can arouse positive emotions and improve the positive emotions of employees, pay attention to arousing the enthusiasm of the staff, and promote the innovative behavior of staff while enhancing work engagement.

Background: Hepatocellular carcinoma (HCC) is a highly lethal cancer and is the second leading cause of cancer-related deaths worldwide. Unlike apoptosis, necroptosis (NCPS) triggers an immune response by releasing damage-related molecular factors. However, the clinical prognostic features of necroptosis-associated genes in HCC are still not fully explored.Methods: We analyzed the single-cell datasets GSE125449 and GSE151530 from the GEO database and performed weighted co-expression network analysis on the TCGA data to identify the necroptosis genes. A prognostic model was built using COX and Lasso regression. In addition, we performed an analysis of survival, immunity microenvironment, and mutation. Furthermore, the hub genes and pathways associated with HCC were localized within the single-cell atlas.Results: Patients with HCC in the TCGA and ICGC cohorts were classified using a necroptosis-related model with significant differences in survival times between high- and low-NCPS groups (p < 0.05). High-NCPS patients expressed more immune checkpoint-related genes, suggesting immunotherapy and some chemotherapies might prove beneficial to them. In addition, a single-cell sequencing approach was conducted to investigate the expression of hub genes and associated signaling pathways in different cell types.Conclusion: Through the analysis of single-cell and bulk multi-omics sequencing data, we constructed a prognostic model related to necroptosis and explored the relationship between high- and low-NCPS groups and immune cell infiltration in HCC. This provides a new reference for further understanding the role of necroptosis in HCC.

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.

Abstract Background Tumor‐infiltrating immune cells participate in the initiation and progression of prostate adenocarcinoma (PRAD). However, it is not fully known how immune infiltration affects the development of PRAD and its clinical presentation. Methods Herein, we investigated the immune infiltration phenotypes in PRAD based on transcriptome profiles, methylation profiles, somatic mutation, and copy number variations. We also developed an immune prognostic model (IPM) to identify unfavorable prognosis. To verify this model, immunohistochemistry staining was performed on a cohort of PRAD samples. Moreover, we constructed a nomogram to assess the survival of PRAD incorporating immune infiltration and other clinical features. Results We categorized PRAD patients into high and low‐level clusters based on immune infiltration phenotypes. The patients in the high‐level clusters had worse survival than their low‐level counterparts. Gene set enrichment analysis indicated that both anti‐ and pro‐tumor terms were enriched in high‐level cluster. Moreover, we identified a positive correlation between anti‐ and pro‐tumor immune cells in PRAD microenvironment. Notably, Somatic mutation analysis showed patients in high‐level cluster had a higher somatic mutation burden of KMT2D, HSPA8, CHD7, and MAP1A. In addition, we developed an IPM with robust predictive ability. The model can distinguish high‐risk PRAD patients with poor prognosis from low‐risk PRAD patients in both training and another three independent validation datasets. Besides, we constructed a nomogram incorporating Gleason score, pathological T stage, and IPM for the prognosis prediction of PRAD patients, which displayed robust predictive ability and might contribute to clinical practice. Conclusion Our work illustrated the immune infiltration phenotypes strongly related to the poor prognosis of PRAD patients, and highlighted the potential of the IPM to identify unfavorable tumor features.

Leadership styles, especially empowering leadership, affect the psychological relationship between employees and organizations, and then affect employees’ positive behavior in the organization. In this research, we studied the effects of empowering leadership and psychological distance on employees’ pro-environmental behavior and explored the mechanism of green organizational climate (GOC). By adopting correlation analysis, statistical analysis, and regression analysis, we conducted a multisource field study of 873 valid employee questionnaires to verify our theoretical model. The results showed that empowering leadership had a significant positive impact on psychological distance and employees’ pro-environmental behavior; and psychological distance played a partly intermediation role in the relationship between empowering leadership and employees’ pro-environmental behavior. Moreover, GOC can promote employees’ pro-environmental behavior, but it cannot regulate between psychological distance and employees’ pro-environmental behavior. The findings obtained some intriguing insights that could help to better guide employees toward pro-environmental behavior.

Background: Gastric cancer (GC) is the second leading cause of cancer-related mortality and the fifth most common cancer worldwide. However, the underlying mechanisms of competitive endogenous RNAs (ceRNAs) in GC are unclear. This study aimed to construct a ceRNA regulation network in correlation with prognosis and explore a prognostic model associated with GC.Methods: In this study, 1,040 cases of GC were obtained from TCGA and GEO datasets. To identify potential prognostic signature associated with GC, Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression were employed. The prognostic value of the signature was validated in the GEO84437 training set, GEO84437 test set, GEO15459 set, and TCGA-STAD. Based on the public databases, TargetScan and starBase, an mRNA-miRNA-lncRNA regulatory network was constructed, and hub genes were identified using the CytoHubba plugin. Furthermore, the clinical outcomes, immune cell infiltration, genetic variants, methylation, and somatic copy number alteration (sCNA) associated with the ceRNA network were derived using bioinformatics methods.Results: A total of 234 prognostic genes were identified. GO and GSEA revealed that the biological pathways and modules related to immune response and fibroblasts were considerably enriched in GC. A nomogram was generated to provide accurate prognostic outcomes and individualized risk estimates, which were validated in the training, test dataset, and two independent validation datasets. Thereafter, an mRNA-miRNA-lncRNA regulatory network containing 4 mRNAs, 22 miRNAs, 201 lncRNAs was constructed. The KCNQ1OT1/hsa-miR-378a-3p/RBMS1 ceRNA network associated with the prognosis was obtained by hub gene analysis and correlation analysis. Importantly, we found that the KCNQ1OT1/miR-378a-3p/RBMS1 axis may play a vital role in the diagnosis and prognosis of GC patients based on Cox regression analyses. Furthermore, our findings demonstrated that mutations and sCNA of the KCNQ1OT1/miR-378a-3p/RBMS1 axis were associated with increased immune infiltration, while the abnormal upregulation of the axis was primarily a result of hypomethylation.Conclusion: Our findings suggest that the KCNQ1OT1/miR-378a-3p/RBMS1 axis may be a potential prognostic biomarker and therapeutic target for GC. Moreover, such findings provide insights into the molecular mechanisms of GC pathogenesis.

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.

In the early stages of aircraft design, a scaled model of the aircraft is installed in a wind tunnel for dynamic semi-free flight to approximate real flight, and the test data are then used to identify the aerodynamic parameters. However, the absence of the translational motion of the test model makes its flight dynamics different from those in free flight, and the effect of this difference on parameter identification needs to be investigated. To solve this problem, a 3-DOF wind tunnel virtual flight test device is built to fix the test model on a rotating mechanism, and the model is free to rotate in three axes through the deflection of the control surfaces. The flight dynamics equations for the wind tunnel virtual flight test are established and 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. The differences between wind tunnel virtual flight and free flight are analysed to develop a model for the identification of aerodynamic parameters. The selection of the lateral-directional excitation signal and the design method of its parameters are established based on the requirements for the identifiability of the aerodynamic derivatives, and a step-by-step method for the identification of aerodynamic force and moment derivatives is established. The aerodynamic parameter identification results of a blended wing body aircraft show that the identification method proposed in this paper can obtain results with high accuracy, and the response of the modified motion model is consistent with that of the free flight motion model.

In the context of promoting the construction of an energy-saving and environment-friendly society, it is crucial to promote the sustainable development of residents’ energy-saving behaviors, determine how attributional styles of behavior outcome affect residents’ energy-saving behaviors, and examine how different residents respond to intervention policies. Based on the attribution theory, this study constructs a theoretical model of the impact mechanism of the attributional style of behavior outcome on residents’ energy-saving behaviors. Regression analysis and the quadratic response model were used to test all 1254 valid questionnaires. The results show that the residents’ degrees of understanding, support, and implementation of the energy-saving policies presented inconsistent situations. Residents’ degrees of understanding and support of energy-saving policies positively promote the degree of implementation of energy-saving policies. The consistency of understanding and support has a non-linear influence on the degree of implementation of energy-saving policies. Additionally, the public’s understanding, support, and implementation of energy-saving policies have significant differences in the attribution style of behavioral outcomes. Finally, some relevant policy recommendations are put forward.

The stall aerodynamic model based on Kirchhoff’s theory of flow separation is widely used in the identification and modeling of stall aerodynamic parameters. However, it has two defects. First, its model structure is significantly different from the pre-stall model used for a small attack angle, meaning the identification results cannot be combined with the pre-stall model to form the full flight envelope model. Second, the pitching moment model, which is used in conjunction with the Kirchhoff lift model, cannot accurately describe the aircraft stall pitching moment characteristics. To ensure the compatibility of the two models, this paper proposes a method to determine some unknown parameters in the stall model. The mechanism for the pitching moment generation of the aircraft stall is analyzed, and two high-order correction terms are added to the pitching moment model to better describe the longitudinal stall aerodynamic characteristics. Based on the identification of aerodynamic parameters, a longitudinal stall aerodynamic modeling method used for the aircraft stall process is developed. The identification and simulation validation results based on the quasi-steady stall flight data of a civil aircraft show that the improved stall model can accurately describe the quasi-steady stall pitching moment. The established stall aerodynamic model can accurately characterize the longitudinal quasi-steady stall aerodynamic characteristics of aircraft under different stall degrees.

Antisense oligodeoxynucleotide (ASODN) can directly interfere a series of biological events of the target RNA derived from tumor cells through Watson-Crick base pairing, in turn, plays antitumor therapeutic roles. In the study, a novel HIF-1α ASODN-loaded nanocomposite was formulated to efficiently deliver gene to the target RNA. The physicochemical properties of nanocomposite were characterized using TEM, FTIR, DLS and zeta potentials. The mean diameter of resulting GEL-DGL-FA-ASODN-DCA nanocomposite was about 170–192 nm, and according to the agarose gel retardation assay, the loading amount of ASODN accounted for 166.7 mg/g. The results of cellular uptake showed that the nanocomposite could specifically target to HepG2 and Hela cells. The cytotoxicity assay demonstrated that the toxicity of vectors was greatly reduced by using DCA to reversibly block the cationic DGL. The subcellular distribution images clearly displayed the lysosomal escape ability of the DCA-modified nanocomposite. In vitro exploration of molecular mechanism indicated that the nanocomposite could inhibit mRNA expression and HIF-1α protein translation at different levels. In vivo optical images and quantitative assay testified that the formulation accumulated preferentially in the tumor tissue. In vivo antitumor efficacy research confirmed that this nanocomposite had significant antitumor activity and the tumor inhibitory rate was 77.99%. These results manifested that the GEL-DGL-FA-ASODN-DCA nanocomposite was promising in gene therapeutics for antitumor by interacting directly with target RNA.

Abstract Background Aerobic vaginitis (AV) is a reproductive tract infection that affects health of women. The objective of this study was to analyze the characteristics of simple and mixed AV patients in Xi’an district and provide reference data for the clinical treatment of AV. Methods Patients were recruited from the outpatient Department of Obstetrics and Gynecology in the First Affiliated Hospital of Xi’an Jiaotong University from September 2014 to April 2019 in strict accordance with inclusion and exclusion criteria. The study principally examined the vaginal ecosystem, age distribution, levels of functional enzymes, and changes in pH levels in these women. Differences within groups were analyzed. Results A total of 284 AV patients were enrolled to investigate the distribution of simple and mixed AV infection. AV infection was found to be mainly simple infection. Simple AV patients were generally aged 50–60 years, while mixed AV patients were mostly aged 30–40 years. In the present study, the density of vaginal bacteria (OR = 13.294, 95% CI = 5.869–30.115, P

Lipid metabolism has been linked to iNKT function largely as it impacts processing and presentation of lipids they recognize. Here the authors show that iNKT-intrinsic lipid biosynthesis is important for their function but is impaired in tumors, and its restoration with PPARγ agonist drugs promotes anti-tumor iNKT response.

Release-type communication is a common way to guide the public to reduce food waste. It is of great significance to clarify the intervention effect of release-type communication on residents’ waste behavior and reveal the time evolution law of public response to reduce food waste. This study obtains 13,958 comments on food waste through big data mining and explores characteristics of public response to food waste behavior in different time and space from two dimensions of support intention and implementation intention. Through statistical analysis, empirical mode decomposition method, and cross-analysis, we find that: Public concern about release-type communication to stop food waste has experienced five stages: Incubation period, outbreak period, recession period, second outbreak period, and fading period. Overall, the support intention presents a down-up-down trend, the implementation intention rises and then descends, both appear inflection point in recession period. The trend term of empirical mode decomposition shows that the support intention goes down, the implementation intention goes up. Besides, the support intention and implementation intention of release-type communication to stop food waste are generally higher in western China. In particular, the support intention is significantly reduced in Beijing, Guangdong, and Fujian. The implementation intention is significantly increased in Shanghai, while it’s reduced notably in Shandong. This study provides important implications for guiding the public to reduce food waste, the government should formulate differentiated governance strategies to guide the public to reduce food waste according to the time change characteristics and spatial territorial differences of the public on release-type communication.

Low-carbon purchasing behavior is the core part of low-carbon consumption behavior. Its impact on low-carbon use behavior, recycling behavior, and garbage sorting behavior needs to be further clarified. Based on self-perception theory and cognitive dissonance theory, this paper constructs a theoretical model of the spillover effect of low-carbon purchasing behavior on low-carbon use behavior, recycling behavior and garbage sorting behavior through self-efficacy and environmental self-identity. This paper uses the Bootstrap method to analyze 494 valid questionnaires empirically. The results show that: low-carbon purchasing behavior has a significantly positive effect on low-carbon use behavior, recycling behavior, and garbage sorting behavior. Self-efficacy and environmental self-identity play partially parallel mediating roles in the spillover effect. The mediating effect of environmental self-efficacy is stronger than environmental self-identity between low-carbon purchasing behavior and low-carbon use behavior. The mediating effect of self-efficacy is weaker than environmental self-identity between low-carbon purchasing behavior and recycling behavior or garbage sorting behavior. The spillover effects are different in demographic variables. The spillover effect of men is more substantial than women. The spillover effect of residents in 18–44 years old is more significant than residents in other age groups. The spillover effect of married residents is the largest. Residents with a bachelor’s degree have the most significant spillover effects on recycling behavior and garbage sorting behavior than residents with other educational levels. Professional and technical personnel have the most considerable spillover effect than other occupation types. The spillover effect is the largest when the family have three members. The spillover effect of residents with a monthly household income of 6,000–8,000 yuan is the largest between low-carbon purchasing behavior and low-carbon use behavior.

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.

Abstract Background Computer-aided diagnosis (CAD) in the medical field has received more and more attention in recent years. One important CAD application is to detect and classify breast lesions in ultrasound images. Traditionally, the process of CAD for breast lesions classification is mainly composed of two separated steps: i) locate the lesion region of interests (ROI); ii) classify the located region of interests (ROI) to see if they are benign or not. However, due to the complex structure of breast and the existence of noise in the ultrasound images, traditional handcrafted feature based methods usually can not achieve satisfactory result. Methods With the recent advance of deep learning, the performance of object detection and classification has been boosted to a great extent. In this paper, we aim to systematically evaluate the performance of several existing state-of-the-art object detection and classification methods for breast lesions CAD. To achieve that, we have collected a new dataset consisting of 579 benign and 464 malignant lesion cases with the corresponding ultrasound images manually annotated by experienced clinicians. We evaluate different deep learning architectures and conduct comprehensive experiments on our newly collected dataset. Results For the lesion regions detecting task, Single Shot MultiBox Detector with the input size as 300×300 (SSD300) achieves the best performance in terms of average precision rate (APR), average recall rate (ARR) and F1 score. For the classification task, DenseNet is more suitable for our problems. Conclusions Our experiments reveal that better and more efficient detection and convolutional neural network (CNN) frameworks is one important factor for better performance of detecting and classification task of the breast lesion. Another significant factor for improving the performance of detecting and classification task, which is transfer learning from the large-scale annotated ImageNet to classify breast lesion.

Abstract Zinc‐air batteries (ZABs) could be an ideal candidate for challenging energy conversion and storage technology. Usually, the crucial oxygen reduction reaction and oxygen evolution reaction are naturally lethargic and require efficient catalysts to kinetically boost the energy conversion processes to achieve the practicable ZABs application. Transition‐metal/carbon hybrid catalysts show excellent potentials in electrocatalysis, and they have been developed into cost‐effective and scalable oxygen electrocatalyst alternatives for expensive and scarcer noble metal ones in rechargeable ZABs. Herein we summarize recent achievements in transition metal/carbon hybrids for oxygen electrocatalysis. These catalysts mainly fall into two categories by the integrated metal/metal oxides nanoparticles and atomically dispersed transition metal/carbon matrix. We focus on the relationship between structure and performance with their synthesis strategies. Their application in rechargeable ZABs are also comprehensively discussed. Finally, the perspectives on transition metal/carbon hybrids for oxygen electrocatalysis are presented for the future challenges in rechargeable ZABs.

For aircraft employing the fly-by-wire technique, the closed-loop dynamic characteristics are determined by both the configuration design and the flight control system. As the capacity of the control system has certain limitations, the configuration parameters are also constrained by the requirements of the closed-loop flying qualities. This paper presents an aircraft configuration parameter boundaries determination method based on closed-loop flying qualities requirements independent of the actual flight control law design, mainly aiming at the parameters that affect the stability and control characteristics. First, a nonlinear dynamic inversion-based flight control law is adopted to decouple the control law gains from the configuration parameters and to study the relationship between the configuration parameters and closed-loop flying qualities. Second, a flying qualities evaluation scheme is established by selecting the most severe flight conditions and the evaluation criteria that are most sensitive to changes in the parameters. Finally, the parameter boundaries according to the requirements of Level 1 flying qualities are determined by searching for the critical values that lead to degradation of the flying qualities. The proposed method is verified by an application example of the design ranges of a sample aircraft’s wing position, horizontal tail area, center of gravity, vertical tail area and vertical tail position.

In this paper, a comprehensive study of controlled laser-induced oxidation marking, which is used as a reliable solution to submillimeter unique identification, is conducted. The experimental statistics indicate that the recognition method for submillimeter unique identification tags is reproducible. The size of tags could be precisely controlled and minimized to 0.5 x 0.5 mm2. Different laser-induced oxidation modules are obtained and divided into 15 groups for different tags. In addition, it is found that module oxidation increases with laser power and decreases with Q frequency, scan speed, and hatch spacing. However, the sensitivity of oxidation to laser parameter differs for different oxidation modules. Even so, the reproducibility and stability of the method are valid by properly limiting deviation of the laser parameters. The aging test reveals that the detected results of the laser-induced oxidation modules are stable in a natural corrosion environment, and applying a transparent coating based on polyester polyurethane on the tags can ensure durability in a severe corrosion environment. The fabricated submillimeter unique identification tags, which can be read reliably by an X-ray fluorescence scanner, show that the proposed marking method is convenient and efficient with high repeatability and controllability.

NK cells are a major component of the antitumour immune response that limits tumour progression. However, it has been reported that tumour-infiltrating NK (TINK) cells from patients with non-small-cell lung carcinoma (NSCLC) exhibit profound defects in degranulation and IFN-γ production. In support of this notion, we report a novel mechanism associated with tumour escape from NK cell-mediated antitumour immunity in lung carcinoma. In this study, we investigated the phenotypic profile of TINK cells based on the expression of the NK-cell maturation markers CD11b and CD27. Interestingly, we found a substantial CD11b(-)CD27(-) (DN) NK-cell population harboured within the tumour tissues. The presence of this CD11b(-)CD27(-) NK subset indicated that the TINK cells were of an immature and inactive phenotype. Remarkably, we determined that the presence of DN NK cells had an impact on the clinical outcomes of patients with NSCLC, as the frequency of tumour-infiltrating DN NK cells was positively correlated with the tumour stage and tumour size. We further used a murine Lewis lung cancer (LLC) model to confirm the correlation between the frequency of tumour-infiltrating DN NK cells and the progression of lung carcinoma. Together, our findings demonstrate that the tumour microenvironment may render TINK cells less tumouricidal and thereby contribute to cancer progression.

Segmented psychological counselling and physical exercise exert a beneficial influence on narrative psychology, fostering enhanced comprehension and reconstruction of personal narratives among individuals. Consequently, this facilitates the advancement of psychological well-being and developmental processes. A retrospective analysis was undertaken to identify 50 young and middle-aged patients exhibiting mild depression. These patients were subsequently randomized into two groups: an observation group and a control group, each comprising 25 cases. The control group received standard medication treatment, while the observation group received additional psychological counselling and exercise alongside standard medication, mirroring the treatment protocol of the control group. Regarding self-esteem, anxiety, and depression, the participants in the experimental cohort demonstrated notable improvements following the intervention, suggesting that engagement in taekwondo sports can effectively enhance self-esteem and bolster the mental health status of middle school students. The novelty of the research lies in uncovering the combined influence of segmental psychological guidance and exercise on narrative psychology. This innovative approach provides a distinct method for fostering personal development and enhancing well-being by amalgamating cognitive and physical interventions. Implications and Taekwondo exercise demonstrates a greater efficacy in diminishing depression compared to anxiety among middle school students. Hence, the combination of segmental psychological counselling and exercise is more beneficial in alleviating depression levels and fostering students' willingness to engage in active psychological narration. Consequently, the utilization of segmental psychological guidance and exercise holds promise in enhancing the efficacy of narrative psychology towards facilitating personal growth and promoting well-being. [ABSTRACT FROM AUTHOR]