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Water inrush from high-position separation layers in the Jurassic coal field represents a novel type of hydraulic disaster, inflicting substantial damage upon coal mines. This study, using Zhaoxian Coal Mine in the Huanglong Coalfield as a case study, introduces a regional risk forecasting methodology that integrates aspects of subjectivity, objectivity, and variable weight theory. Eight principal factors were identified for this analysis:coal seam thickness, aquifer permeability coefficient, distance of the aquifer from the coal seam, aquifer thickness, aquifer’s unit water intake, head height of the aquifer, geological structure, and the cumulative thickness of mudstone in the Yan’an and Zhiluo formations.The study employed the Variable Weight Method (VWM) to adjust the normal weights determined by the Analytic Hierarchy Process (AHP) and the Entropy Weight Method (EWM). This led to the development of a mathematical model for water inrush risk assessment in the Zhaoxian No. 1 mining area, culminating in a comprehensive evaluation index for water inrush risk. In conjunction with the engineering geological conditions of Zhaoxian, surface extraction and drainage holes were utilized to precisely manage the water sources of the hazard. The results indicate that the AHP−EWM−VWM method can accurately pinpoint areas at high risk of water inrush. The comprehensive weight evaluation underscores that reducing the aquifer water level is a crucial strategy for preventing and controlling water damage. The implemented surface pumping holes have been effective in mitigating the risk of water inrush in the mining area, demonstrating the study’s significant value in guiding the effective prevention and control of water inrush in the Jurassic coal field.

Objective: This study aimed to investigate the effects of fermitin family member 1 (FERMT1) on epithelial-mesenchymal transition (EMT) in hepatocellular carcinoma (HCC) via the EGFR/AKT/β-catenin and EGFR/ERK pathways. Methods: The expression of FERMT1 encoding protein kindlin-1 in HCC tissues was determined by immunohistochemistry, and FERMT1 mRNA expression in HCC tissues and cell lines was analyzed by qRT-PCR. After the FERMT1 expression of SNU182 and SNU387 interfered with siRNA, the cell viability, invasion, migration, and EMT were tested by CCK-8, transwell invasion, scratching, immunofluorescence/WB, respectively. Similarly, the effects of FERMT1 on the viability and metastasis of HCC were investigated in transplanted tumor and lung metastasis mouse models. The protein expressions of EGFR/AKT/β-catenin and EGFR/ERK pathways were analyzed by WB. In addition, the relationship between FERMT1 and EGFR was further determined by immunofluorescence double staining and Co-IP. Results: FERMT1 was significantly upregulated in HCC, and silencing FERMT1 inhibited the viability, invasion, migration, and EMT of HCC. Silencing FERMT1 also inhibited the activation of EGFR/AKT/β-catenin and EGFR/ERK pathways. In addition, inhibition of EGFR, AKT, or ERK confirmed that EGFR/AKT/β-catenin and EGFR/ERK pathways were involved in the promoting effects of FERMT1 on HCC. Co-IP and immunofluorescence experiments confirmed the targeting relationship between FERMT1 and EGFR. Conclusion: FERMT1 was highly expressed in HCC and promoted viability, invasion, migration, and EMT of HCC by targeting EGFR to activate the EGFR/AKT/β-catenin and EGFR/ERK pathways. Our study revealed the role of FERMT1 in HCC and suggested that FERMT1 exerts biological effects through activating the EGFR/AKT/β-catenin and EGFR/ERK pathways.

Abstract Single image super‐resolution (SISR) is a promising research direction in computer vision and image processing for improving the visual perception of low‐quality images. In recent years, deep learning algorithms have driven tremendous development in SR, and SR methods based on various network architectures have significantly improved the quality of reconstructed images. Although there has been a large amount of reviews focusing on SISR, few studies have focused specifically on network architectures for SISR. This paper aims to provide a systematic overview of the design ideas of SISR using multiple architectures, including Convolutional Neural Networks (CNN), Generative Adversarial Networks (GAN), Transformer, and Diffusion model. In addition, an experimental analysis and comparison of state‐of‐the‐art SR algorithms have been performed on publicly available quantitative and qualitative datasets. Finally, some future directions are discussed that may help other community researchers.

Abstract Enhancing immune response activation through the synergy of effective antigen delivery and immune enhancement using natural, biodegradable materials with immune-adjuvant capabilities is challenging. Here, we present NAPS L.p that can activate the Toll-like receptor 4 (TLR4) pathway, an amphiphilic exopolysaccharide, as a potential self-assembly adjuvant delivery platform. Its molecular structure and unique properties exhibited remarkable self-assembly, forming a homogeneous nanovaccine with ovalbumin (OVA) as the model antigen. When used as an adjuvant, NAPS L.p significantly increased OVA uptake by dendritic cells. In vivo imaging revealed prolonged pharmacokinetics of NAPS L. p -delivered OVA compared to OVA alone. Notably, NAPS L.p induced elevated levels of specific serum IgG and isotype titers, enhancing rejection of B16-OVA melanoma xenografts in vaccinated mice. Additionally, NAPS L.p formulation improved therapeutic effects, inhibiting tumor growth, and increasing animal survival rates. The nanovaccine elicited CD4+ and CD8+ T cell-based immune responses, demonstrating the potential for melanoma prevention. Furthermore, NAPS L.p -based vaccination showed stronger protective effects against influenza compared to Al (OH)3 adjuvant. Our findings suggest NAPS L.p as a promising, natural self-adjuvanting delivery platform to enhance vaccine design across applications.

The occurrence of mine water inrushes is common and poses significant hazards in various mining areas throughout China. However, the existing regulations lack of specific engineering geological and hydrogeological exploration guidelines tailored to the water inrush from separation layers (WISL). Exploring the methods of engineering geological and hydrogeological exploration and assessment for the WISL can contribute to further enhancing the prevention and control of mine water disasters in China. This paper begins by examining the mechanism behind WISL in coal mines. It analyzes the geological conditions governing the progression of WISL from its inception to full-scale occurrence and categorizes three prevalent types of WISL in China, i.e., dynamic water inrush, hydrostatic water inrush, and mud and sand-carrying water inrush, all originating from separation layers. Subsequently, it identifies “water source”“channel”“force source”and “material source” as pivotal concealed factors dictating the nature and severity of WISL. Then, the concept of a “inrush separation zone” referring to composite stratigraphic layers situated above traditional water-conducting fractured zones is introduced, where the WISL may transpire during mining activities. Furthermore, it presents a method for delineating “inrush separation zone” in coal mines, outlining exploration stages and specifying crucial investigative focal points. The exploration of water damage in upper strata of coal mine should include two stages: first, the exploration of basic engineering geology and hydrogeological conditions of overlying rock should be carried out to evaluate the possibility of water damage in the exploration area and determine the horizon of potential mining overlying rock ; second, regarding the “inrush separation zone” and “source” layer as the exploration target layer, the special investigation of the hidden disaster factors of the upper layer water damage should be conducted to assess the type and intensity of the water damage in the upper layer. The hydrodynamic conditions and the evolution of overburden fractures are investigated during the mining period. Lastly, a comprehensive forecast evaluation model is proposed and constructed on the coordinated evolutionary mechanisms arising from the interaction of causative factors like “water source”“channel”“force source”and “material source”. This model predicts and evaluates the types, locations, and inflows of water inrush at mining faces before operations commence.

The rpl1001 gene encodes 60S ribosomal protein L10, which is involved in intracellular protein synthesis and cell growth. However, it is not yet known whether it is involved in the regulation of cell mitosis dynamics. This study focuses on the growth, spore production, cell morphology, the dynamics of microtubules, chromosomes, actin, myosin, and mitochondria of fission yeast (Schizosaccharomyces pombe) to investigate the impact of rpl1001 deletion on cell mitosis. RNA-Seq and bioinformatics analyses were also used to reveal key genes, such as hsp16, mfm1 and isp3, and proteasome pathways. The results showed that rpl1001 deletion resulted in slow cell growth, abnormal spore production, altered cell morphology, and abnormal microtubule number and length during interphase. The cell dynamics of the rpl1001Δ strain showed that the formation of a monopolar spindle leads to abnormal chromosome segregation with increased rate of spindle elongation in anaphase of mitosis, decreased total time of division, prolonged formation time of actin and myosin loops, and increased expression of mitochondrial proteins. Analysis of the RNA-Seq sequencing results showed that the proteasome pathway, up-regulation of isp3, and down-regulation of mfm1 and mfm2 in the rpl1001Δ strain were the main factors underpinning the increased number of spore production. Also, in the rpl1001Δ strain, down-regulation of dis1 caused the abnormal microtubule and chromosome dynamics, and down-regulation of hsp16 and pgk1 were the key genes affecting the delay of actin ring and myosin ring formation. This study reveals the effect and molecular mechanism of rpl1001 gene deletion on cell division, which provides the scientific basis for further clarifying the function of the Rpl1001 protein in cell division.

Regarding the issue of determining the thickness of the protective layer for waterproof and safe coal (rock) pillars in mining near water bodies, Appendix 4-3 of the “Code for Retaining and Mining Coal Pillars in Buildings, Water Bodies, Railways, and Main Tunnels” (hereinafter referred to as the “Three Underground Mining Code”) is only applicable to coal mining under “loose aquifers”. As for how to determine the thickness of the protective layer for coal mining under bedrock aquifers and mining under goaf water bodies, it is not involved; The main content of commonly used roof water hazard risk assessment techniques and methods includes water abundance evaluation, conductivity evaluation, and water filling strength evaluation. When the water abundance of the aquifer is known, only “conductivity” can be evaluated, and the evaluation method can be further simplified. Based on the above two points, this article attempts to construct a simple criterion similar to the coefficient of water inrush from the bottom plate to evaluate the risk of roof water damage, starting from the “Three Underground Mining Standards”. Firstly, based on the scientific connotation of the term “protection”, it is proposed that the impermeable rock layers between the top interface of the water conducting fracture zone and the overlying aquifer have protective functions and should be collectively referred to as the protective layer (Hb); Based on the practice of selecting a certain multiple of mining height (A) for the thickness of the protective layer in the “Three Lower Mining Standards”, the concept of protection coefficient (Bs) is proposed, which is the ratio of the thickness of the protective layer to the mining height (Bs=Hb/A). Secondly, based on the provisions of Appendix 4-3 of the “Three Underground Mining Specification” regarding the thickness of the protective layer for waterproof coal pillars, the threshold value of the protection coefficient zoning for coal mining under loose aquifers is proposed to be Bi=(0，2、3、4、5、6、7); The coal bearing strata under the bedrock aquifer are generally composed of sand and mudstone interbedded sedimentary formations, where mudstone has a water blocking function (equivalent to the cohesive soil layer under the loose layer), and the total thickness of mudstone is generally greater than the cumulative mining thickness. The thickness of the protective layer can be selected according to the condition of “the thickness of the cohesive soil layer at the bottom of the loose layer is greater than the cumulative mining thickness” in Appendix 4-3 of the “Three Underground Mining Specifications” and selected according to the maximum value, Therefore, the threshold value of the protection coefficient zoning for evaluating the bedrock aquifer is Bi=(0,4). According to the protection coefficient and zoning threshold, the evaluation area can be divided into water inrush zone (Bs≤0), danger zone (0

In addressing challenges associated with the constrained enhancement of range performance in pure electric tractors, the difficulty in achieving genuinely eco-friendly agricultural machinery with hybrid powertrains, and the outdated approaches to energy optimization in hydrogen fuel cell tractors, a comprehensive methodology covering the entire spectrum of system design, optimization, and validation is presented. This method constructs an integrated electromechanical and hydraulic power bond graph model for an agricultural tractor, encompassing energy systems, drive systems, and lifting systems. It achieves rapid interaction between 20-sim software and Matlab/Simulink software through a script toolbox. In order to tackle the real-time applicability challenges of dynamic programming, a hierarchical dynamic programming is proposed. The dynamic programming strategy results serve as the upper-level output. At the lower layer, preprocessing of impact value variables is carried out to filter the input variables for the general regression neural network. This enables the real-time application of the dynamic programming algorithm and significantly reduces training time. Finally, validation is conducted through both model-in-the-loop and hardware-in-the-loop. The results demonstrate the correctness and superiority of the designed tractor simulation model and energy management strategy model compared to the power-following strategy. Specifically, in plowing conditions, the dynamic programming and hierarchical dynamic programming strategies exhibited reductions of 10.278% and 6.728%, respectively, in equivalent hydrogen consumption compared to power-following strategy. In transportation conditions, the reductions are 16.02% for dynamic programming strategy and 4.87% for hierarchical dynamic programming strategy, both relative to power-following strategy. This study lays the theoretical groundwork for modeling dynamic systems of tractors and optimizing energy management.

The wheat harvesting boundary line is vital reference information for the path tracking of an autonomously driving combine harvester. However, unfavorable factors, such as a complex light environment, tree shade, weeds, and wheat stubble color interference in the field, make it challenging to identify the wheat harvest boundary line accurately and quickly. Therefore, this paper proposes a harvest boundary line recognition model for wheat harvesting based on the MV3_DeepLabV3+ network framework, which can quickly and accurately complete the identification in complex environments. The model uses the lightweight MobileNetV3_Large as the backbone network and the LeakyReLU activation function to avoid the neural death problem. Depth-separable convolution is introduced into Atrous Spatial Pyramid Pooling (ASPP) to reduce the complexity of network parameters. The cubic B-spline curve-fitting method extracts the wheat harvesting boundary line. A prototype harvester for wheat harvesting boundary recognition was built, and field tests were conducted. The test results show that the wheat harvest boundary line recognition model proposed in this paper achieves a segmentation accuracy of 98.04% for unharvested wheat regions in complex environments, with an IoU of 95.02%. When the combine harvester travels at 0~1.5 m/s, the normal speed for operation, the average processing time and pixel error for a single image are 0.15 s and 7.3 pixels, respectively. This method could achieve high recognition accuracy and fast recognition speed. This paper provides a practical reference for the autonomous harvesting operation of a combine harvester.

To solve the problems of the low driving efficiency of a fuel cell tractor power source and the high hydrogen consumption caused by the irrational power allocation of the energy source, the power system was divided into two parts, power source and energy source, and a dual-source cooperative optimization energy management strategy was proposed. Firstly, a general energy efficiency optimization method was designed for the power source composed of a traction motor and PTO motor, and the energy source was composed of a fuel cell and power battery. Secondly, the unified objective function and constraint conditions were established, and the instantaneous optimization algorithm was used to construct the weight factor. The instantaneous optimal drive efficiency energy management strategy and the instantaneous optimal equivalent hydrogen consumption energy management strategy were designed, respectively. Finally, with the demand power as the transfer parameter, the instantaneous optimal drive efficiency energy management strategy and the instantaneous optimal equivalent hydrogen consumption energy management strategy were integrated to form a dual-source collaborative optimal energy management strategy. In order to verify the effectiveness of the proposed strategy, a rule-based energy management strategy was developed as a comparison strategy and tested in an HIL test under plowing and rotary plowing conditions. The results show that the average fuel cell efficiency of the proposed strategy increased by 7.86% and 8.17%, respectively, and the proposed strategy’s equivalent hydrogen consumption decreased by 24.21% and 9.82%, respectively, compared with the comparison strategy under the two conditions. It can significantly reduce the SOC fluctuation of the power battery and extend the service life of the power battery.

Abstract With the development of display technology, more displays can cover the wider gamut, but most of the content they show is based on a small gamut. It is significant to employ gamut expansion (GE) to expand the small gamut images to a wider target gamut. Most of the existing GE methods only use global or local operations to realize the mapping from small gamut to wide gamut. However, the utilization of both global information and local feature is important for GE. In this article, the authors propose a combined global‐local gamut expansion network (G‐LGENet) for mapping the input standard RGB (sRGB) images to wider ProPhoto RGB space. In G‐LGENet, the global colour mapping module first extracts and fuses the global colour priors and learns the mapping of colour information for the corresponding pixels. And then, the local enhancement (LE) is designed to extract the local colour information between the corresponding pixel and neighbourhood pixels. The experimental results on a sRGB‐to‐ProPhoto dataset have demonstrated that the proposed G‐LGENet outperforms the other excellent GE methods qualitatively and visually.

Over the past decade, surface ozone has emerged as a significant air pollutant in China, especially in the North China Plain (NCP). For effective ozone management in the NCP, it is crucial to accurately estimate the surface ozone levels and identify the primary influencing factors for ozone pollution in this region. This study utilized ozone precursors such as volatile organic compounds (VOCs) and nitrogen oxides (NOX), meteorological data, land cover, normalized difference vegetation index (NDVI), terrain, and population data to build an extreme gradient boosting (XGBoost)-based ozone estimation model in the NCP during 2019 to 2021. Four ozone estimation models were developed using different NO2 and formaldehyde (HCHO) datasets from the Sentinel-5 TROPOMI observations and Copernicus Atmosphere Monitoring Service (CAMS) reanalysis data. Site-based validation results of these four models showed high accuracy with R2 values above 0.86. Among these four models, two models with higher accuracy and higher spatial coverage ratio were selected, and their results were averaged to produce the final ozone estimation products. The results indicated that VOCs and NOX were the two main pollutants causing ozone pollution in the NCP, and their relative contributions accounted for more than 23.34% and 10.23%, respectively, while HCHO also played a significant role, contributing over 5.64%. Additionally, meteorological factors also had a notable impact, contributing 28.63% to ozone pollution, with each individual factor contributing more than 2.38%. The spatial distribution of ozone pollution identified the Hebei–Shandong–Henan junction as a pollution hotspot, with the peak occurring in summer, particularly in June. Therefore, for this hotspot region in the NCP, promoting the reduction in VOCs and NOx can play an important role in the mitigation of O3 pollution and the improvement in air quality in this region.

Context: Cardiomyocyte hypertrophy due to hemodynamic overload eventually leads to heart failure. Hirudin has been widely used in the treatment of cardiovascular diseases and NLRP3 inflammasome was proven to induce cardiomyocyte pyroptosis. However, the mechanism by which it inhibits cardiomyocyte hypertrophy remains unclear. Objective: To explore the mechanism of hirudin inhibiting cardiomyocyte hypertrophy based on NLRP3 inflammasome activation and mitophagy. Materials & methods: 1 μM AngII was used for cardiac hypertrophy modeling in H9C2 cells, and cell viability was quantified by CCK-8 assay to screen the appropriate action concentrations of hirudin. After that, we cultured AngII induced-H9C2 cells for 24 h with 0, 0.3, 0.6, and 1.2 mM hirudin, respectively. Next, we marked H9C2 cells with phalloidine and observed them using fluorescence microscope. IL-1β, IL-18, IL-6, TNF-α, ANP, BNP, β-MHC, and mtDNA were analyzed by qRT-PCR; ROS were quantified by Flow cytometry; SOD, MDA, and GSH-Px were detected by ELISA; and proteins including NLRP3, ASC, caspase-1, pro-caspase-1, IL-1β, IL-18, PINK-1, Parkin, beclin-1, LC3-Ⅰ, LC3-Ⅱ, p62, were quantified by western blotting. Results: It was discovered that hirudin reduced the superficial area of AngII-induced H9C2 cells and inhibited the AngII-induced up-regulation of ANP, BNP, and β-MHC. Besides, hirudin down-regulated the expressions of NLRP3 inflammasome-related cytokines, containing IL-1β, IL-18, IL-6, TNF-α. It also down-regulated the expression of mtDNA and ROS, decreased the expression levels of NLRP3 inflammasome activation related proteins, including NLRP3, ASC, caspase-1, pro-caspase-1, IL-1β, IL-18; and increased the expressions of PINK-1, Parkin, beclin-1, LC3-Ⅱ/LC3-Ⅰ, p62 in AngII-induced H9C2 cells. Discussion: Hirudin promoted the process of mitophagy, inhibited the development of inflammation and oxidative stress, and inhibited the activation of the NLRP3 inflammasome and the PINK-1/Parkin pathway. Conclusion: Hirudin has the activity to suppress cardiac hypertrophy may benefit from the inhibition of NLRP3 inflammasome and activating of PINK-1/Parkin related-mitophagy.

To address the issues of tractors using too much fuel and not being energy efficient, a predictive control strategy based on Pontryagin's minimum principle integrating working condition prediction is proposed for agricultural hybrid tractors. The Dongfanghong 1804 tractor is being used for research. Firstly, the main parameters of the hybrid drive system are determined and modeled. Secondly, based on the adaptive cubic exponential forecasting method, the working condition information for a period of time in the future is predicted through historical working condition information. Furthermore, combining the predicted working conditions information, the goal is to minimize the total energy consumption cost of the entire machine. Motor power and diesel engine power are control variables. The battery state of charge is a state variable. Subsequently, a predictive control strategy based on Pontryagin's minimum principle integrating working condition prediction is proposed. Finally, the simulation test is carried out based on the MATLAB simulation platform. Research indicates: under plowing conditions, compared with the power following control strategy, the proposed predictive control strategy can effectively manage the performance of the diesel engine and motor, ensuring they operate at their most efficient level. The total energy consumption costs of the power following control and predictive control strategies are 37.17 China Yuan (CNY) and 33.67 CNY, respectively. The cost of energy used is decreased by 9. 42%, which helps make tractor field plowing more efficient and economical.

IntroductionZhilong Huoxue Tongyu Capsule (ZL) is a Chinese medicine used for the treatment of cardio-cerebral diseases. However, the pharmacological mechanisms underlying its regulation of myocardial ischemia/reperfusion injury (MI/RI) remain unclear.PurposeThis study aims to investigate the effects and mechanisms of ZL on MI/RI in mice.Materials and methodsC57BL/6J mice were randomly assigned to four groups: Sham group, I/R group, ZL group, and ZLY group. The MI/RI mouse model was established by ligation of the left anterior descending coronary artery for 30 minutes, followed by reperfusion for 120 minutes to restore blood perfusion. Cardiac function was evaluated using cardiac ultrasound. Histopathological changes and myocardial infarction area were assessed using Hematoxylin and eosin (H&E) staining and triphenyltetrazolium chloride (TTC) staining. The changes in oxidative stress- and ferroptosis-related markers were detected. RT-qPCR, Western blot, and ELISA were conducted to further explore the mechanism of ZL in improving MI/RI.ResultsOur findings demonstrated that ZL exerted a protective effect against MI/RI by inhibiting ferroptosis, evidenced by the upregulation of antioxidant enzymes such as GSH and GPX4, coupled with the downregulation of ACSL4, a pro-ferroptosis factor. Furthermore, ZL positively impacted the PI3K/AKT/Nrf2 pathway by promoting ATPase activities and enhancing the relative protein expression of its components. Notably, the administration of a PI3K/AKT inhibitor reversed the antioxidant and anti-ferroptosis effects of ZL to some extent, suggesting a potential role for this pathway in mediating ZL's protective effects.ConclusionsZL protects against MI/RI-induced ferroptosis by modulating the PI3K/AKT signaling pathway, leading to increased Nrf2 expression and activation of the HO-1/GPX4 pathway. These findings shed light on the potential therapeutic mechanisms of ZL in the context of cardiovascular diseases.

Objective: Zhilong Huoxue Tongyu capsule (ZL) is a Chinese patent medicine for treating cardio-cerebral diseases. However, the pharmacological mechanism by which it regulates blood lipids and treats atherosclerosis (AS) is unclear. Therefore, the purpose of this study is to explore the mechanism of ZL inhibiting hyperlipidemia and treating AS through NF-κB/NLRP3 signaling pathway. Methods: Fifty New Zealand white rabbits were divided into control, model, model + ZL (3.12 g/kg/d, i.g.), model + atorvastatin (0.51 mg/kg/d, i.g.), and model + ZL + atorvastatin groups. Except for the control group, all other groups underwent carotid intima air drying and received a high-fat diet for 28 days to establish hyperlipidemia AS model, and drug treatment was given for the same period of time after modeling. Pathological changes and blood lipids were detected, NF-κB/NLRP3-related protein or gene expression levels were analyzed in carotid tissue. Results: ZL significantly reduced blood lipids and delayed the progression of AS. TC, TG, and LDL-C were decreased while HDL-C was increased in blood, IMT thickening and plaque formation of carotid arteries were inhibited, VRI was alleviated, and pathological features were improved. NF-κB, NLRP3 and IL-1β in the carotid artery were significantly down-regulated after intervention with ZL. RT-PCR and western blot analysis showed that NF-κB (p-NF-κB), NLRP3, caspase-1, IL-1β and IL-18 were significantly downregulated by ZL. Conclusions: ZL can be used effectively as adjuvant therapy for hyperlipidemia and AS, combining it with atorvastatin yielded more optimized efficacy, but its anti-inflammatory and pharmacological mechanisms of inhibiting pyroptosis should be studied further.

Abstract Hepatocellular carcinoma (HCC) has the sixth-highest new incidence and fourth-highest mortality worldwide. Transarterial chemoembolization (TACE) is one of the primary treatment strategies for unresectable HCC. However, the therapeutic effect is still unsatisfactory due to the insufficient distribution of antineoplastic drugs in tumor tissues and the worsened post-embolization tumor microenvironment (TME, e.g., hypoxia and reduced pH). Recently, using nanomaterials as a drug delivery platform for TACE therapy of HCC has been a research hotspot. With the development of nanotechnology, multifunctional nanoplatforms have been developed to embolize the tumor vasculature, creating conditions for improving the distribution and bioavailability of drugs in tumor tissues. Currently, the researchers are focusing on functionalizing nanomaterials to achieve high drug loading efficacy, thorough vascular embolization, tumor targeting, controlled sustained release of drugs, and real-time imaging in the TACE process to facilitate precise embolization and enable therapeutic procedures follow-up imaging of tumor lesions. Herein, we summarized the recent advances and applications of functionalized nanomaterials based on TACE against HCC, believing that developing these functionalized nanoplatforms may be a promising approach for improving the TACE therapeutic effect of HCC.

The competition for shared resources in printing manufacturing system may lead to deadlock, which could cause unnecessary downtime and bring vast economic loss for enterprises. Supervisor is widely studied in the literature to solve the deadlock control problem. With the objective of improving the robustness of reconfigurable printing manufacturing system (RPMS), this paper designs a new Agent- Resource- Workstation (ARW) model with a supervisor. A new reconfiguration of workstation models (NRWMs) is proposed based on ARW model. The supervisors can control reconfiguration behavior of NRWMs by limiting the time and frequency of interaction between workstation models. Then, formal verification is performed by process algebra to show its external behavior. We use the mCRL2 tool to carry out simulation experiments on NRWMs and provide the experimental results. The results show that robust deadlock control policy for the RPMS is secure and effective.

In order to reduce the influence of ground vibration generated by tractors during driving and operation on driving stability and driver ’s ride comfort, this paper proposes a tractor active seat suspension control method based on model predictive control (MPC). Through the establishment of three degrees of freedom tractor active seat suspension model, electromagnetic actuator (linear motor) model and ground excitation input model, the inner and outer loop control strategy of linear motor active seat suspension based on outer loop MPC control and inner loop current hysteresis comparison control is proposed. The influence of MPC parameters on the vibration performance and control cost of seat suspension is compared and analyzed through experiments. The appropriate system parameters are selected through optimization analysis. The simulation and experimental results show that compared with the passive seat suspension and PID seat suspension, the tractor active seat suspension based on model predictive control improves the ride comfort and vibration reduction characteristics of the tractor, and on this basis, it reduces the energy consumption required for the seat suspension system to achieve active control, while ensuring the timeliness of MPC control.

Abstract Background Pancreatic cancer is one of the most aggressive malignancies without effective targeted therapies. MUC1 has emerged as a potential common target for cancer therapy because it is overexpressed in a variety of different cancers including the majority of pancreatic cancer. However, there are still no approved monoclonal antibody drugs targeting MUC1 have been reported. Recently, we generated a humanized MUC1 antibody (HzMUC1) specific to the interaction region between MUC1-N and MUC1-C. In this study, we generated the antibody drug conjugate (ADC) by conjugating HzMUC1 with monomethyl auristatin (MMAE), and examined the efficacy of HzMUC1-MMAE against the MUC1-positive pancreatic cancer in vitro and in vivo. Methods Western blot and immunoprecipitation were used to detect MUC1 in pancreatic cancer cells. MUC1 localization in pancreatic cancer cells was determined by confocal microscopy. HzMUC1 was conjugated with the monomethyl auristatin (MMAE), generating the HzMUC1-MMAE ADC. Colony formation assay and flow cytometry were used to assess the effects of the HzMUC1-MMAE cell viability, cell cycle progression and apoptosis. Capan-2 and CFPAC-1 xenograft model were used to test the efficacy of HzMUC1-MMAE against pancreatic cancer. Results HzMUC1 antibody binds to MUC1 on the cell surface of pancreatic cancer cells. HzMUC1-MMAE significantly inhibited cell growth by inducing G2/M cell cycle arrest and apoptosis in pancreatic cancer cells. Importantly, HzMUC1-MMAE significantly reduced the growth of pancreatic xenograft tumors by inhibiting cell proliferation and enhancing cell death. Conclusion Our results indicate that HzMUC1-ADC is a promising novel targeted therapy for pancreatic cancer. HzMUC1-ADC should also be an effective drug for the treatment of different MUC1-positive cancers.

In response to the issues of hybrid tractors’ energy management strategies, such as reliance on experience, difficulty in achieving optimal control, and incomplete analysis of typical operating conditions of tractors, an energy management strategy based on dynamic programming is proposed in combination with various typical operating conditions of tractors. This is aimed at providing a reference for the modeling and energy management strategies of series hybrid tractors. Taking the series hybrid tractor as the research object, the tractor dynamics models under three typical working conditions of plowing, rotary tillage, and transportation were established. With the minimum total fuel consumption of the tractor as the optimization target, the engine power as the control variable, and the state of charge of the power battery as the state variable, an energy management strategy based on a dynamic programming algorithm was established and simulation experiments were conducted. The simulation results show that, compared with the power-following energy management strategy, the energy management strategy based on the dynamic programming algorithm can reasonably control the operating state of the engine. Under the three typical working conditions of plowing, rotary tillage, and transportation, the battery SOC consumption increased by approximately 8.37%, 7.24%, and 0.77%, respectively, while the total fuel consumption decreased by approximately 25.28%, 21.54%, and 13.24%, respectively.

Unmanned tractors under ploughing conditions suffer from body tilting, violent shaking and limited hardware resources, which can reduce the detection accuracy of unmanned tractors for field obstacles. We optimize the YOLOv8 model in three aspects: improving the accuracy of detecting tilted obstacles, computational reduction, and adding a visual ranging mechanism. By introducing Funnel ReLU, a self-constructed inclined obstacle dataset, and embedding an SE attention mechanism, these three methods improve detection accuracy. By using MobileNetv2 and Bi FPN, computational reduction, and adding camera ranging instead of LIDAR ranging, the hardware cost is reduced. After completing the model improvement, comparative tests and real-vehicle validation are carried out, and the validation results show that the average detection accuracy of the improved model reaches 98.84% of the mAP value, which is 2.34% higher than that of the original model. The computation amount of the same image is reduced from 2.35 billion floating-point computations to 1.28 billion, which is 45.53% less than the model computation amount. The monitoring frame rate during the movement of the test vehicle reaches 67 FPS, and the model meets the performance requirements of unmanned tractors under normal operating conditions.

Transmission efficiency is a key characteristic of Hydro-mechanical Continuously Variable Transmission (HMCVT), which is related to the performance of heavy-duty tractors. Predicting the HMCVT transmission efficiency is beneficial for the real-time adjustment of transmission ratio during heavy-duty tractor operations, so as to obtain better performance. Aiming at the problems of accurate method, low accuracy, and high noise in the prediction of HMCVT transmission efficiency, this paper proposes a method based on Variational Mode Decomposition (VMD), Particle Swarm Optimization (PSO), and Back Propagation (BP) neural networks to improve the quality of transmission efficiency prediction. Firstly, a simple theoretical model was established to obtain the influencing factors of transmission efficiency. Then, based on these factors, the transmission efficiency was tested on the bench under multiple conditions and the influence degree of each factor on transmission efficiency was divided using Partial Least Squares (PLS) method. Finally, the VMD method was used to denoise the test data, and a BP model, which was improved using the PSO method, was established to predict the processed data. The results showed that transmission efficiency of HMCVT is most affected by output speed, followed by power, and least by input speed. The VMD method can accurately extract effective signals and noise signals from the original data, and reconstruct signals, reducing the noise proportion. Using three conditions, the prediction regression accuracy of the PSO–BP model is 7.02%, 7.88%, and 9.26% higher than that of the BP model, respectively. In the three prediction experiments, the maximum differences in the MAE, the MAPE, and the RMSE of the PSO–BP model are 0.002, 0.463%, and 0.004, respectively, which are 0.006, 0.796%, and 0.003 lower than those of the BP model.

When shifting gears around a tractor’s power shift transmission, it is necessary to coordinate the control of multiple clutches and formulate a reasonable clutch engagement law to ensure the reliability and power of the power system. This paper explores the impact of different clutch engagement patterns on shifting characteristics in a power-shift tractor with multiple clutches. Shifting performance is comprehensively evaluated using indicators such as shifting time, impact degree, slip energies, and transmission output torque. The aim is to enhance the quality of power shifting, operational efficiency, and the service life of the transmission system. This paper takes the YTO TX4A transmission system as the research object, analyzes its working principle, and establishes a mathematical model of a power shift transmission system under different clutch engagement rules. This model of power shift transmission is established based on Matlab2021/Simulink and the AMESim2021 software platform. A simulation analysis is carried out for four clutches working simultaneously in a tractor’s advance gear II and lift gear III. The simulation results indicate that switching rule C is superior to switching rule A and switching rule B. Compared with the engagement scheme in which the torque exchange overlap time for both sets of clutches is 0.3 s, the scheme with a torque exchange overlap time of 0.15 s indicated a shifting time increase of 0.2 s, a slip energy increase of 4%, and a minimum output torque of the transmission increase of 2%. In the scheme with a torque exchange overlap time of 0 s, the shifting time increased by 0.15 s, the slip energy decreased by 13.5%, and the minimum output torque of the transmission decreased by 17%. Through the study of shifting performance under three different clutch engagement patterns, it is concluded that, during the shift from forward gear II to gear III in the YTO TX4A transmission system, appropriately reducing the torque exchange overlap time for both sets of clutches and avoiding simultaneous torque exchange can reduce the complexity of clutch control. This leads to smoother, more powerful, and more comfortable power shifting, effectively prolonging the service life of the transmission system.

Myocardial ischemia/reperfusion (I/R) injury is the main cause of increasing postischemic heart failure and currently there is no definite treatment for myocardial I/R injury. It has been suggested that oxidative stress-induced mitochondrial dysfunction plays an important role in the pathological development of myocardial I/R. In this study, Yiqi Huoxue (YQHX) prescription, as a kind of Chinese herbal formula, was developed and shown to alleviate I/R injury. Network analysis combined with ultrahigh-performance liquid chromatography-high resolution mass spectrometry expounded the active components of YQHX and revealed the mitophagy-regulation mechanism of YQHX treating I/R injury. In vivo experiments confirmed YQHX significantly alleviated I/R myocardial injury and relieved oxidative stress. In vitro experiments validated that YQHX could relieve hypoxia/reoxygenation injury and attenuate oxidative stress via improving the structure and function of mitochondria, which was strongly related to regulating mitophagy. In summary, this study demonstrated that YQHX, which could alleviate I/R injury via targeting mitophagy, might be a potential therapeutic strategy for myocardial I/R injury.

BackgroundThe incidence of heart failure (HF) is increasing year by year, posing a great threat to human health. Although pharmacotherapy has been able to significantly prolong patient survival, pharmacotherapy for HF still has limitations due to its complex pathogenesis and considerable individual variability, there is a great need to explore complementary and alternative therapies to slow down the progression of HF. Danshen decoction is used to treat several cardiovascular diseases including HF, but the efficacy of stabilization is uncertain. This meta-analysis evaluated the clinical efficacy of Danshen Decoction for the treatment of HF.MethodsThe registration number assigned to this meta-analysis on the PROSPERO platform is CRD42022351918. Four databases were searched, and randomized controlled trials (RCTs) of Danshen decoction combined with conventional treatment (CT) of HF were screened, CT included medical treatments other than Danshen Decoction to which the patient was treated (including but not limited to angiotensin converting enzyme inhibitor, angiotensin receptor blocker, angiotensin receptor neprilysin inhibitors, β-blockers, diuretics, mineralcorticoid recept antagonist etc.). The clinical efficacy rate (CER), left ventricular ejection fraction (LVEF), left ventricular end-diastolic dimension (LVEDD), left ventricular end-systolic diameter (LVESD), brain natriuretic peptide (BNP), N-terminal pro-B type natriuretic peptide (NT-proBNP) and hypersensitive C-reactive protein (hs-CRP) were included as outcome indicators. The GRADE grading scale was used to grade the above indicators. The Cochrane risk-of-bias tool and the Jadad quality scale were used to assess the methodological quality of RCTs. Finally, RevMan V.4.5 software was used for data synthesis, 95% confidence intervals (CI) for dichotomous data, risk ratios (RR), and mean differences (MD) for continuous variables were calculated, Chi-square and I2 were used for heterogeneity assessment.ResultsNine RCTs with a total of 855 patients were included in this study, and all included RCTs had a low overall quality risk of bias and high quality of reported information. The results of the meta-analysis showed that compared with the use of CT, CER (%) was significantly improved due to Danshen decoction combined with CT (MD = 3.95, 95% CI [2.58, 6.04], P < 0.00001), LVEF (%) was significantly improved (MD = 5.46, 95% CI [5.32, 5.60], P < 0.00001), LVEDD (mm) was significantly reduced (MD = -5.27, 95% CI [-6.21, -4.32], P < 0.00001), LVESD (mm) was significantly reduced (MD = -4.60, 95% CI [-5.87, -3.32], P < 0.00001), BNP (pg/mL) was significantly reduced (MD = -88.61, 95% CI [-121.98, -55.24], P < 0.00001), NT-proBNP (pg/mL) was significantly decreased (SMD = -3.33, 95% CI [-5.92, -0.73], P = 0.01), hs-CRP (mg/L) was significantly decreased (MD = -2.73, 95% CI [-4.11, -1.34], P = 0.0001). The quality of the GRADE evidence for all outcomes was moderate to low and no RCTs reported adverse events.ConclusionOur research demonstrates that Danshen decoction is an effective and safe treatment option for HF. Nevertheless, considering the limitations of methodological and the quality of RCTs, more rigorous, large-scale, multicenter randomized clinical trials are needed to further evaluate the efficacy and safety of Danshen decoction in the treatment of HF patients.

Aiming at the unreasonable determination of the power coupling device speed ratio and the power battery capacity in the initial design stage of the dual-motor electric tractor, a dual-motor drive system is designed, and a parameter optimization method based on driving cycles (POMBDC) is proposed. By analyzing the driving characteristics requirements and actual working conditions of the tractor, the dynamic model of the dual-motor drive system under different working modes is established, and the parameters of the dual-motor, transmission and maximum service mass are designed. On this basis, based on the driving cycles and aiming at the lowest power consumption, the POMBDC is formed, this method can collaboratively optimize the power coupling device speed ratio and the power battery capacity. In order to verify the rationality of the POMBDC, the instantaneous optimization-constant speed ratio design method (IO-CSRDM), rule-optimization speed ratio design method (R-OSRDM) and rule-constant speed ratio design method (R-CSRDM) are developed as comparison methods, and simulation experiments are carried out. Under plowing conditions, the power battery capacity of the POMBDC is 3.08%, 5.71%, and 8.73% lower than those of the IO-CSRDM, R-OSRDM, and R-CSRDM, respectively. The power consumption resulting from the POMBDC is reduced by 3.11%, 5.74%, and 8.8%, compared with those of the IO-CSRDM, R-OSRDM and R-CSRDM, respectively. Under rotary tillage conditions, the power battery capacity of the POMBDC is 6%, 8.64%, and 11.11% lower than those of the IO-CSRDM, R-OSRDM, and R-CSRDM, respectively. The power consumption resulting from the POMBDC is reduced by 6.05%, 8.66%, and 11.13%, compared with those of the IO-CSRDM, R-OSRDM and R-CSRDM, respectively. The POMBDC can effectively increase the operating mileage of pure electric tractors and reduce costs.

Summary: Chemoautotrophic bacteria play an important role in combating the rise in global CO2. However, recently it was found that extracellular free organic carbon (EFOC) generated by chemoautotrophic bacteria inhibits their CO2 fixation. Although continuous-flow membrane bioreactor can remove EFOC and enrich bacteria, it may also remove beneficial bio-factors for bacterial growth. Finding out the main inhibitory factors and inhibitory mechanisms in EFOC can provide theoretical guidance for the development of targeted inhibitory component removal technology. The results show a significant negative correlation between the increasing proportion of small-molecule EFOC and the decreasing trend of CO2 fixation efficiency, and simulation experiments confirm that the small molecule organics such as amino acids and organic acids are the main components of EFOC that inhibit CO2 fixation by inhibiting ribulose bisphosphate carboxylase/oxygenase (RuBisCO) gene (cbb) transcription efficiency. Therefore, amino acids and organic acids are suggested to be recovered to promote efficient CO2 fixation of autotrophic bacteria.

Zhilong Huoxue Tongyu capsule (ZHTC) is an effective traditional Chinese medicine compound for the treatment of ischemic stroke, which is widely used in clinical ischemic stroke patients. However, it is uncertain whether ZHTC affects ischemic stroke through gut microbiota and serum metabolites. In this study, a rat model of middle cerebral artery occlusion (MCAO) was prepared. By evaluating motor nerve function score, cerebral infarct size, brain tissue damage and intestinal barrier damage, it was found that ZHTC improved stroke-related symptoms in MCAO rats. Using 16S rRNA gene sequencing, fecal microbial transplantation (FMT), untargeted metabolomics, and spearman correlation analysis of gut microbiota and serum metabolites, we found that ZHTC can regulate the abundance of p_Firmicutes, p_Bacteroidota,p_Proteobacteria, g_Prevotella, and g_Lactobacillus, and regulated 23 differential metabolites. Spearman correlation analysis found that Arginine was positively correlated with p_Firmicutes, o_Clostridiales, c_Clostridia, and negatively correlated with p_Bacteroidetes, c_Bacteroidia,o_Bacteroidales; L-Lysine was negatively correlated with f_Christensenellaceae; L-methionine was positively correlated with o_Lactobacillales, f_Lactobacillaceae, and g_Lactobacillus. Altogether, this study shows for the first time that ZHTC can ameliorate ischemic stroke by modulating gut microbiota and metabolic disturbances. This lays the foundation for further revealing the causal relationship between ZHTC, gut dysbiosis, plasma metabolite levels and ischemic stroke, and provides a scientific explanation for the ameliorating effect of ZHTC on ischemic stroke.

Energy management strategies are crucial for improving fuel economy and reducing the exhaust emissions of hybrid tractors. The authors study a series diesel-electric hybrid tractor (SDEHT) and propose a multi-operating point Fuzzy PID control strategy (MOPFPCS) aimed to achieve better fuel economy and improved control. To further improve the vehicle economy, the adaptive particle swarm optimization method is used to optimize the key parameters of the Fuzzy PID controller. A co-simulation model in AVL-Cruise and Matlab/Simulink environment is developed for plowing mode and transportation mode. The simulation results show that under the two operation modes, the equivalent fuel consumption of the adaptive particle swarm optimization multi-operating points Fuzzy PID control strategy (APSO-MOPFPCS) is reduced by 18.3% and 15.0%, respectively, compared to the engine single-operating point control strategy (ESOPCS). Also, it was found to be reduced by 9.5% and 4.6%, respectively, compared to the MOPFPCS.

In light of the challenges posed by the complex structural characteristics and significant coupling of vibration signals in rotating machinery, this study proposes an adaptive noise reduction method called Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN). Additionally, an enhanced threshold screening Singular Value Decomposition (SVD) algorithm is introduced to address the issues pertaining to noise identification and feature extraction in the context of vibration signals from rotating machinery, which are subjected to complex noise interference. The effectiveness of the proposed approach is substantiated through the evaluation of key metrics, such as the signal-to-noise ratio (SNR), as well as the utilization of advanced signal analysis techniques, including Short Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT). The experimental results validate the finding that the combination of the improved CEEMDAN and the enhanced threshold screening SVD algorithm effectively reduces noise interference in vibration signals from rotating machinery. This integrated denoising approach successfully preserves the informative characteristics of the vibration signals, thereby laying a foundation for the subsequent fault diagnosis of rotating machinery.

To overcome the limitations of the hybrid tractor bumping tests, which include extended cycle times, high costs, and impracticality for single-part reliability verification, this study focuses on the exhaust system mounting bracket of a hybrid tractor. A novel approach that combines multi-objective particle swarm optimization (MOPSO) and wavelet decomposition algorithms was employed to enhance the reconstruction of shock vibration signals. This approach aims to enable the efficient acquisition of input signals for subsequent shaker table testing. The methodology involves a systematic evaluation of the spectral correlation between the original signal and the reconstructed signal at the stent’s response position, along with signal compression time. These parameters collectively constitute the objective function. The multi-objective particle swarm optimization algorithm is then deployed to explore a range of crucial parameters, including wavelet basic functions, the number of wavelet decomposition layers, and the selection of wavelet components. This exhaustive exploration identifies an optimized signal reconstruction method that accurately represents shock vibration loads. Upon rigorous screening based on our defined objectives, the optimal solution vector was determined, which includes the utilization of the dB10 wavelet basic function, employing a 12-layer wavelet decomposition, and selecting wavelet components a12 and d3~d11. This specific configuration enables the retention of 95% of the damage coefficients while significantly compressing the test time to just 46% of the original signal duration. The implications of our findings are substantial as the reconstructed signal obtained through our optimized approach can be readily applied to shaker excitation. This innovation results in a notable reduction in test cycle time and associated costs, making it particularly valuable for engineering applications, especially in tractor design and testing.

This paper presents a proposed global optimal energy management strategy based on dynamic programming to enhance the energy consumption efficiency of an agricultural hybrid tractor that is equipped with a continuously variable transmission (CVT). Firstly, using a diesel-electric parallel agricultural hybrid tractor as the research object, a tractor-rotary tillage coupling dynamics model is constructed. Secondly, with the torque and speed of the motor, the torque and speed of the diesel engine, and the CVT speed ratio as the control variables, the state of charge (SOC) of the power battery as the state variable, and the goal of minimizing the total energy consumption of the whole machine, a global optimal energy management model based on dynamic programming is established. Finally, the field operation measured data is injected into the MATLAB simulation model, and experiments are carried out to verify the effectiveness of the energy management strategy. The results show that compared with the power-following energy management strategy, the proposed energy management strategy can make the diesel engine and electric motor work in the optimal area, and effectively reduce the total cost of energy consumption of the tractor during field operations. Under the condition of rotary tillage, the total cost of energy consumption is decreased by 16.89%.

Background: Myocardial hypertrophy is a complex pathological process, which is a common manifestation during the development of various cardiovascular diseases. Hirudin has been shown to have therapeutic effects on a variety of cardiovascular diseases, however, its therapeutic effect on myocardial hypertrophy is still unknown, and its chemical and pharmacological characteristics remain to be elucidated.Methods: In this study, the network pharmacology method was used to characterize the mechanism of hirudin on myocardial hypertrophy. The potential protein targets of hirudin and myocardial hypertrophy were both obtained from the Genecards database, and potential pathways associated with genes were identified by Gene Ontology and pathway enrichment analysis, and the data were displayed in a visual manner. Subsequently, the potential mechanism of action of hirudin on myocardial hypertrophy predicted by network pharmacology analysis was verified by molecular docking, and finally, the main findings were further verified by in vitro experiments by molecular biology techniques. Based on the results obtained from the study of H9c2 cell line, the inhibitory effect of hirudin on myocardial hypertrophy was further proved in the primary rat cardiomyocytes.Results: A total of 250 targets of hirudin, and 5,376 targets related to myocardial hypertrophy after deduplication were collected. The drug-disease network showed the relationship between hirudin, myocardial hypertrophy, and the targets. Further, systematic analysis from the PPI network indicated that blood coagulation, vesicle lumen, and signaling receptor activator activity may be the potential mechanisms of hirudin in the treatment of myocardial hypertrophy, and the PI3K/AKT signaling pathway may be the most relevant to the therapeutic effect of hirudin. Then, three therapeutic targets that were highly related to myocardial hypertrophy were extracted. Hirudin can be highly bound to STAT3, IL-6, and MAPK1 and found by molecular docking, which may be the basis for its inhibitory effect on myocardial hypertrophy. In addition, in vitro experiments showed that hirudin could inhibit AngII-induced hypertrophy and death of H9c2 cells, and significantly reduce the mRNA and protein expression levels of STAT3, MAPK1, and IL-6. The above conclusions were verified in primary rat cardiomyocytes.Conclusion: Hirudin can be used to treat myocardial hypertrophy through a complex mechanism. The application of network pharmacology and experimental validation can promote the application of hirudin in cardiovascular diseases and the interpretation and understanding of molecular biological mechanisms.

Interacting with aquatic environments in blue spaces is believed to benefit mental well-being. Relevant understanding is limited to regional pilot studies using self-reported emotions on questionnaires. We assessed emotional response by rating facial expressions on a large geographical scale with the purpose of detecting a relationship to microclimates. A total of 920 facial photographs were collected from Sina Weibo from 20 wetland parks in 14 eastern cities of China during 2020. Daily average air temperature, rainfall, average relative humidity (RH), and wind velocity were also recorded from the days when photographs were posted online. We found that happy expressions were higher in wetlands of eastern cities than in northern and inland cities. Sad expressions varied statistically among wetland locations. Weather records differed between temperate and subtropical climatic zones and were highly varied among cities. Happy and sad scores were driven by the change in average air temperature. Combined multivariable regression and binomial correlation suggested that increasing air temperature would not evoke positive emotions unless higher than 11.5°C, and an air temperature range of 17.5–22.3°C will be optimum to induce the presentation of a smiling face. Air humidity generally imposed a negative effect on expressions of positive emotions. Further verification of our findings is suggested on a larger geographical scale using more powerful big-data to obtain more robust conclusions.

The herpes virus entry mediator (HVEM) is an immune checkpoint molecule regulating immune response, but its role in tissue repair remains unclear. Here, we reported that HVEM deficiency aggravated hepatobiliary damage and compromised liver repair after 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC)-induced injury. A similar phenotype was observed in B and T lymphocyte attenuator (BTLA)-deficient mice. These were correlated with impairment of neutrophil accumulation in the liver after injury. The hepatic neutrophil accumulation was regulated by microbial-derived secondary bile acids. HVEM-deficient mice had reduced ability to deconjugate bile acids during DDC-feeding, suggesting a gut microbiota defect. Consistently, both HVEM and BTLA deficiency had dysregulated intestinal IgA responses targeting the gut microbes. These results suggest that the HVEM-BTLA signaling may restrain liver injury by regulating the gut microbiota.

Methamphetamine (METH), an amphetamine-type psychostimulant, is highly abused worldwide. Chronic abuse of METH causes neurodegenerative changes in central dopaminergic neurons with numerous neuropsychiatric consequences. Neuronal apoptosis plays a critical role in METH-induced neurotoxicity and may provide promising pharmacological targets for preventing and treating METH addiction. In recent years, accumulating evidence has revealed that natural products may possess significant potentials to inhibit METH-evoked neuronal apoptosis. In this review, we summarized and analyzed the improvement effect of natural products on METH-induced neuronal apoptosis and their potential molecular mechanisms on modulating dopamine release, oxidative stress, mitochondrial-dependent apoptotic pathway, endoplasmic reticulum stress-mediated apoptotic pathway, and neuroinflammation. Hopefully, this review may highlight the potential value of natural products in modulating METH-caused neuronal apoptosis and provide useful information for future research and developments of novel and efficacious pharmacotherapies in this field.

In order to detect the assembly quality of the combine harvester accurately and effectively, a method for the assembly quality inspection of the combine harvester based on the improved whale algorithm (IWOA) to optimize the least square support vector machine is proposed. Aiming at the characteristics of whale optimization algorithm’s weak search ability and easy maturity, this paper introduces the cosine control factor and the sine time-varying adaptive weight to improve it and uses the benchmark function to verify the general adaptability of the algorithm. Combined with the local mean decomposition (LMD), the assembly quality inspection model of the combine harvester was established and applied to the Dongfanghong 4LZ-9A2 combine harvester for experimental verification. The experimental results show that the IWOA proposed in this paper has better optimization ability and adaptability. The average accuracy of the IWOA model proposed in this paper reaches 90.5%, which is 4% higher than that of the WOA model, and the standard deviation of the average accuracy is reduced by 0.15%, which indicates that the IWOA model has better stability.

In this study, an energy-saving control strategy based on instantaneous optimization is proposed to improve the energy efficiency of hybrid tractors. Using a parallel diesel–electric hybrid tractor as the research object, the topological and working characteristics were analyzed, and a coupled dynamic model of rotary tillage and tractor plow was constructed. Aiming to minimize the equivalent fuel consumption of the entire machine, the motor and diesel engine torques were taken as the control variables, and the state of charge of the power battery was taken as the state variable. Subsequently, an energy-saving control strategy based on instantaneous optimization is proposed. Finally, a simulation experiment was carried out using MATLAB to verify the effectiveness of the energy-saving control strategy based on instantaneous optimization. Compared with the energy-saving control strategy based on power-following, the results show that energy-saving control strategy based on instantaneous optimization can reasonably control the operating state of the diesel engine and motor. Therefore, the diesel engine and motor work in the high-efficiency area, and effectively reduce the equivalent fuel consumption of the tractor during field operation. Under rotary tillage and plowing conditions, equivalent fuel consumption is reduced by 4.70% and 6.31%, respectively.

With the application of new energy technology, hybrid agricultural machinery has been developed. This article designs a hybrid tractor energy management method to solve the problem of high energy consumption caused by significant load fluctuation of the tractor in field operation. This article first analyzes the characteristics of the hydrogen fuel cell, power battery, and ultracapacitor and designs a hybrid energy system for the tractor. Second, the energy management strategy (EMS) of multi-layer decoupling control based on the Haar wavelet and logic rule is designed to realize the multi-layer decoupling of high-frequency, low-frequency, and steady-state signals of load demand power. Then, the EMS redistributes the decoupled power signals to each energy source. Finally, a hardware-in-loop simulation experiment was carried out through the model. The results show that, compared with single-layer control strategies such as fuzzy control and power-following control, the multi-layer control strategy can allocate the demand power more reasonably, and the efficiency of the hydrogen fuel cell is the highest. The average efficiency of the hydrogen fuel cell was increased by 2.87% and 1.2%, respectively. Furthermore, the equivalent hydrogen consumption of the tractor was reduced by 17.06% and 5.41%, respectively, within the experimental cycle. It is shown that the multi-layer control strategy considering power fluctuation can improve the vehicle economy based on meeting the power demanded by the whole vehicle load.

The mismatch of geometric parameters in a nanotomography system bears a significant impact on the reconstructed images. Moreover, projection image noise is increased due to limitations of the X-ray power source. The accuracy of the existing self-calibration method, which uses only the grayscale information of the projected image, is easily affected by noise and leads to reduced accuracy. This paper proposes a geometric parameter self-calibration method based on feature matching of mirror projection images. Firstly, the fast extraction and matching feature points in the mirror projection image are performed by speeded-up robust features (SURF). The feature triangle is then designed according to the stable position of the system’s rotation axis to further filter the feature points. In turn, the influence of the mismatched points on the calculation accuracy is reduced. Finally, the straight line where the rotation axis is located is fitted by the midpoint coordinates of the filtered feature points, thereby realizing geometric parameter calibration of the system. Simulation and actual data from the experimental results show that the proposed method effectively realizes the calibration of geometric parameters, and the blurring and ghosting caused by geometric artifacts are corrected. Compared with existing methods, the image clarity can be improved by up to 14.4%.

Biofilm is a crucial virulence factor for microorganisms that causes chronic infection. After biofilm formation, the bacteria present improve drug tolerance and multifactorial defense mechanisms, which impose significant challenges for the use of antimicrobials. This indicates the urgent need for new targeted technologies and emerging therapeutic strategies. In this review, we focus on the current biofilm-targeting strategies and those under development, including targeting persistent cells, quorum quenching, and phage therapy. We emphasize biofilm-targeting technologies that are supported by blocking the biofilm life cycle, providing a theoretical basis for design of targeting technology that disrupts the biofilm and promotes practical application of antibacterial materials.

The resolution of 3D structure reconstructed by laboratory nanoCT is often affected by changes in ambient temperature. Although correction methods based on projection alignment have been widely used, they are time-consuming and complex. Especially in piecewise samples (e.g., chips), the existing methods are semi-automatic because the projections lose attenuation information at some rotation angles. Herein, we propose a fast correction method that directly processes the reconstructed slices. Thus, the limitations of the existing methods are addressed. The method is named multiscale dense U-Net (MD-Unet), which is based on MIMO-Unet and achieves state-of-the-art artifacts correction performance in nanoCT. Experiments show that MD-Unet can significantly boost the correction performance (e.g., with three orders of magnitude improvement in correction speed compared with traditional methods), and MD-Unet+ improves 0.92 dB compared with MIMO-Unet in the chip dataset.

A self-correction method for the drift artifacts of laboratory cone-beam nanoscale X-ray computed tomography (nano-CT) based on the trajectory of projection centroid (TPC) is proposed. This method does not require additional correction phantoms, simplifying the correction process. The whole TPC is estimated by the partial TPC in the optimal projection set. The projection drift is calculated by the measured TPC and the estimated TPC. The interval search method is used so that the proposed method can adapt to the case of a truncated projection due to drift. The fixed-angle scanning experiment of the Siemens star and the partial derivative analysis of the projection position show the necessity of correcting drift artifacts. Further, the Shepp–Logan phantoms with different drift levels are simulated. The results show that the proposed method can effectively estimate the horizontal and vertical drifts within the projection drift range of ±2 mm (27 pixels) with high accuracy. Experiments were conducted on tomato seed and bamboo stick to validate the feasibility of the proposed method for samples with different textures. The correction effect on different reconstructed slices indicates that the proposed method provides performance superior to the reference scanning method (RSM) and global fitting. In addition, the proposed method requires no extra scanning, which improves the acquisition efficiency, as well as radiation utilization.

The design objectives of the structural parameters of the tractor drive motor are diverse, and the constraints are complex. It is difficult to optimize the overall performance of the unit by using the empirical method and single-objective optimization method. This paper proposes a multi-objective optimization method for tractor drive motors based on an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II). Constraints are formulated according to the inherent characteristics of the motor itself and the characteristics of the tractor’s working conditions. The objective function was established with the heat loss of the drive motor and the total efficiency of the drive system. Based on the designed solution process of NSGA-II algorithm, an example optimization was carried out, and the tractor electromechanical drive system was carried out with the single-objective optimization results of the optimal energy use efficiency of the drive motor and the optimal mechanical transmission efficiency of the transmission system as the control group. The test results show that compared with the control group, the proposed multi-objective optimization method can make the overall tractor system efficiency the highest, and the maximum and rated values of the total efficiency ηq of the drive system of the multi-objective optimization design scheme. Compared with the optimal design scheme with ηme as a single objective, it was increased by 2% and 1.4%, respectively, and compared with the optimal design scheme with ηtr as a single objective, it is improved by 26.5% and 73.6%, respectively. It can provide an effective calculation method for the motor design problem in the subsequent development of the tractor electromechanical drive system.