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Abstract Exosomes, a specific subset of extracellular vesicles, have diverse functions in various biological processes. In the field of cancer research, there has been a growing interest in the potential of exosomes to act as versatile vehicles for targeted tumor imaging and therapy. In this study, we constructed a targeted delivery platform using hypoimmunogenic exosomes by genetically modifying β2‐microglobulin knocking‐out HEK‐293F cells to express a fusion protein, referred to as αMUC1‐Exo, which comprises the exosomal membrane‐enriched platelet‐derived growth factor receptor, intracellular nanoluciferase, and extracellular anti‐MUC1 single‐chain variable fragment. The findings of this study indicate that αMUC1‐Exos exhibited notable drug delivery properties toward MUC1‐positive pancreatic cancer cells, resulting in a substantial inhibition of tumor growth. Moreover, these exosomes demonstrated a high level of biosafety and the absence of any adverse effects. The application of engineered exosomes as a vehicle for drug delivery holds promise for enhancing the immunogenicity of neoplastic cells following treatment, thereby inducing antitumor immune memory in mice with intact immune systems, and also improving the response to anti‐PD1 therapy. This approach utilizing engineered exosomes for Gemcitabine administration holds promise as a potential strategy for overcoming drug resistance in pancreatic carcinoma thereby improving the overall treatment efficacy.

Abstract Effective inhibition of intestinal lipid uptake is an efficient strategy for the treatment of disorders related to lipid metabolism. Sterol O‐acyltransferase 2 (SOAT2) is responsible for the esterification of free cholesterol and fatty acids into cholesteryl esters. We found that intestine‐specific SOAT2 knockout (Soat2I‐KO) mice was capable to prevent the development of dietary induced obesity due to reduced intestinal lipid absorption. Soat2 siRNA/CS‐PLGA nanoparticle system was constructed to enable intestinal delivery and inhibition of Soat2. This nanoparticle system was composed of PLGA‐block‐PEG and chitosan specifically delivering Soat2 siRNAs into small intestines in mice, effectively inhibit intestinal lipid uptake and resolving obesity. In revealing the underlying mechanism by which intestinal SOAT2 regulating fatty acid uptake, enhanced CD36 ubiquitination degradation was found in enterocytes upon SOAT2 inhibition. Insufficient free cholesterol esterification promoted endoplasmic reticulum stress and recruitment of E3 ligase RNF5 to activate CD36 ubiquitination in SOAT2 knockdown enterocytes. This work demonstrates a potential modulatory function of intestinal SOAT2 on lipid uptake highlighting the therapeutic effect on obesity by targeting intestinal SOAT2, exhibiting promising translational relevance in the siRNA therapeutic–based treatment for obesity.

Understanding the impact-induced ignition properties and energy release behavior of polymer-bonded explosives (PBXs) is critical for the safety of explosive systems. In this study, a new impact test component was designed using a light gas gun to quantify the ignition mechanism and chemical reaction of micro-damaged PBXs under different inertial loading conditions. A constitutive model was developed to describe the mechanical-thermal-chemical response of the PBXs. This model was employed to further investigate the correlation between microcracks, debonding, hot spots, and chemical reactions. The results show that the stress state of the material is not uniformly distributed due to the micro-inhomogeneities and structural defects of PBXs. The shear friction of the microcracks contributes to localized hot spots, thereby inducing ignition. The critical loading condition for ignition is the length of the steel pillar is 32 mm. The damage and hotspot temperatures of the anterior lateral and posterior lateral regions are greater than those of other locations. The ignition response is accentuated with longer steel pillars, resulting in a more violent release of energy.

Polyphenols are a group of naturally occurring compounds that possess a range of biological properties capable of potentially mitigating or preventing the progression of age-related cognitive decline and Alzheimer’s disease (AD). AD is a chronic neurodegenerative disease known as one of the fast-growing diseases, especially in the elderly population. Moreover, as the primary etiology of dementia, it poses challenges for both familial and societal structures, while also imposing a significant economic strain. There is currently no pharmacological intervention that has demonstrated efficacy in treating AD. While polyphenols have exhibited potential in inhibiting the pathological hallmarks of AD, their limited bioavailability poses a significant challenge in their therapeutic application. Furthermore, in order to address the therapeutic constraints, several polymer nanoparticles are being explored as improved therapeutic delivery systems to optimize the pharmacokinetic characteristics of polyphenols. Polymer nanoparticles have demonstrated advantageous characteristics in facilitating the delivery of polyphenols across the blood–brain barrier, resulting in their efficient distribution within the brain. This review focuses on amyloid-related diseases and the role of polyphenols in them, in addition to discussing the anti-amyloid effects and applications of polyphenol-based polymer nanoparticles.

Extraction of anthocyanins from Lycium ruthenicum Murr. (L. ruthenicum) is a notable challenge in food production, requiring methods that balance efficiency and safety. In this study, we conducted a comparative analysis the extraction of anthocyanins by natural air drying (NAD), vacuum freeze drying (VFD), hot air drying (HAD), and vacuum microwave drying (MVD) combined with ultrasonic-assisted enzymolysis extraction (UAEE). The results demonstrated that the extraction yield and antioxidant activity of anthocyanins were significantly higher in VFD. This phenomenon can be attributed to the modification of raw material’s microstructure, leading to an increased extraction yield of specific anthocyanins such as Cyanidin-3-galactoside, Delphinidin chloride, Cyanidin, and Petunidin. According to the pretreatment results, the extraction process of anthocyanins was further optimized. The highest yield (3.16 g/100 g) was obtained in following conditions: 0.24 % pectinase, 48 °C, solid:liquid = 1:21, and 21 min ultrasonic time. This study improves the commercial value and potential application of L. ruthenicum in food industry.

ObjectivesWilson disease (WD) is a rare autosomal recessive disorder caused by a mutation in the ATP7B gene. Neurological symptoms are one of the most common symptoms of WD. This study aims to construct a model that can predict the occurrence of neurological symptoms by combining clinical multidimensional indicators with machine learning methods.MethodsThe study population consisted of WD patients who received treatment at the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine from July 2021 to September 2023 and had a Leipzig score ≥ 4 points. Indicators such as general clinical information, imaging, blood and urine tests, and clinical scale measurements were collected from patients, and machine learning methods were employed to construct a prediction model for neurological symptoms. Additionally, the SHAP method was utilized to analyze clinical information to determine which indicators are associated with neurological symptoms.ResultsIn this study, 185 patients with WD (of whom 163 had neurological symptoms) were analyzed. It was found that using the eXtreme Gradient Boosting (XGB) to predict achieved good performance, with an MCC value of 0.556, ACC value of 0.929, AUROC value of 0.835, and AUPRC value of 0.975. Brainstem damage, blood creatinine (Cr), age, indirect bilirubin (IBIL), and ceruloplasmin (CP) were the top five important predictors. Meanwhile, the presence of brainstem damage and the higher the values of Cr, Age, and IBIL, the more likely neurological symptoms were to occur, while the lower the CP value, the more likely neurological symptoms were to occur.ConclusionsTo sum up, the prediction model constructed using machine learning methods to predict WD cirrhosis has high accuracy. The most important indicators in the prediction model were brainstem damage, Cr, age, IBIL, and CP. It provides assistance for clinical decision-making.

Abstract Background Traditional nanodrug delivery systems have some limitations, such as eliciting immune responses and inaccuracy in targeting tumor microenvironments. Materials and methods Targeted drugs (Sorafenib, Sora) nanometers (hollow mesoporous silicon, HMSN) were designed, and then coated with platelet membranes to form aPD-1-PLTM-HMSNs@Sora to enhance the precision of drug delivery systems to the tumor microenvironment, so that more effective immunotherapy was achieved. Results These biomimetic nanoparticles were validated to have the same abilities as platelet membranes (PLTM), including evading the immune system. The successful coating of HMSNs@Sora with PLTM was corroborated by transmission electron microscopy (TEM), western blot and confocal laser microscopy. The affinity of aPD-1-PLTM-HMSNs@Sora to tumor cells was stronger than that of HMSNs@Sora. After drug-loaded particles were intravenously injected into hepatocellular carcinoma model mice, they were demonstrated to not only directly activate toxic T cells, but also increase the triggering release of Sora. The combination of targeted therapy and immunotherapy was found to be of gratifying antineoplastic function on inhibiting primary tumor growth. Conclusions The aPD-1-PLTM-HMSNs@Sora nanocarriers that co-delivery of aPD-1 and Sorafenib integrates unique biomimetic properties and excellent targeting performance, and provides a neoteric idea for drug delivery of personalized therapy for primary hepatocellular carcinoma (HCC).

Abstract Introduction Pancreaticobiliary reflux (PBR) can induce gallstone formation; however, its pathogenic mechanism remains unclear. In this study, we explored the mechanism of PBR by the non-targeted metabolomic analysis of bile in patients with PBR. Objective The aim of this study was to investigate the pathogenic mechanism in PBR by the non-targeted metabolomic analysis of bile collected during surgery. Methods Sixty patients who underwent gallstone surgery at our center from December 2020 to May 2021 were enrolled in the study. According to the level of bile amylase, 30 patients with increased bile amylase ( > 110 U/L) were classified into the PBR group, and the remaining 30 patients were classified into the control group (≤ 110 U/L). The metabolomic analysis of bile was performed. Results The orthogonal projections to latent structure-discriminant analysis of liquid chromatography mass spectrometry showed significant differences in bile components between the PBR and control groups, and 40 metabolites were screened by variable importance for the projection value (VIP > 1). The levels of phosphatidylcholine (PC) and PC (20:3(8Z,11Z,14Z)/14:0) decreased significantly, whereas the levels of lysoPC (16:1(9z)/0:0), lysoPC (15:0), lysoPC (16:0), palmitic acid, arachidonic acid, leucine, methionine, L-tyrosine, and phenylalanine increased. Conclusions Significant differences in bile metabolites were observed between the PBR and control groups. Changes in amino acids and lipid metabolites may be related to stone formation and mucosal inflammation.

A benzothiazole-based derivative aggregation-induced emission (AIE) fluorescent ‘turn-on’ probe named 2-(2-((4-(4,4,5,5-tetramethyl-1,3,2-dioxaborolan-2-yl)benzyl)oxy)phenyl)benzo[d]thiazole (probe BT-BO) was developed and synthesized successfully for detecting hydrogen peroxide (H2O2) in living cells. The synthesis method of probe BT-BO is facile. Probe BT-BO demonstrates a well-resolved emission peak at 604 nm and the ability to prevent the interference of reactive oxygen species (ROS), various metal ions and anion ions, and good sensitivity. Additionally, the probe boasts impressive pH range versatility, a fast response time to H2O2 and low cytotoxicity. Finally, probe BT-BO was applied successfully to image A549 and Hep G2 cells to monitor both exogenous and endogenous H2O2.

Abstract Geochemical reactions are crucial for in situ CO2 mineralization underground associated with CO2‐enhanced oil recovery (CO2‐EOR) in a hydrocarbon reservoir. However, the presence of formation water and adsorbed oil on rocks generates physical barriers to CO2's access to mineral surfaces, which may yield impedance to CO2 mineral trapping that has yet to be accounted for. In this study, we mimic the dynamic oil detachment process using molecular dynamic (MD) simulation and analyze the influence of an adsorbed oil film on supercritical CO2 (scCO2) diffusion toward the mineral surface in the presence and absence of a water phase. Our results demonstrated a negative impact of water on oil film detachment by scCO2, which may weaken mineral reactions and is unfavorable for mineralized CO2 storage underground.

Abstract Background In Wilson’s disease (WD) patients, network connections across the brain are disrupted, affecting multidomain function. However, the details of this neuropathophysiological mechanism remain unclear due to the rarity of WD. In this study, we aimed to investigate alterations in brain network connectivity at the whole-brain level (both intra- and inter-network) in WD patients through independent component analysis (ICA) and the relationship between alterations in these brain network functional connections (FCs) and clinical neuropsychiatric features to understand the underlying pathophysiological and central compensatory mechanisms. Methods Eighty-five patients with WD and age- and sex-matched 85 healthy control (HC) were recruited for resting-state functional magnetic resonance imaging (rs-fMRI) scanning. We extracted the resting-state networks (RSNs) using the ICA method, analyzed the changes of FC in these networks and the correlation between alterations in FCs and clinical neuropsychiatric features. Results Compared with HC, WD showed widespread lower connectivity within RSNs, involving default mode network (DMN), frontoparietal network (FPN), somatomotor network (SMN), dorsal attention network (DAN), especially in patients with abnormal UWDRS scores. Furthermore, the decreased FCs in the left medial prefrontal cortex (L_ MPFC), left anterior cingulate gyrus (L_ACC), precuneus (PCUN)within DMN were negatively correlated with the Unified Wilson’s Disease Rating Scale-neurological characteristic examination (UWDRS-N), and the decreased FCs in the L_MPFC, PCUN within DMN were negatively correlated with the Unified Wilson’s Disease Rating Scale-psychiatric symptoms examination (UWDRS-P). We additionally discovered that the patients with WD exhibited significantly stronger FC between the FPN and DMN, between the DAN and DMN, and between the FPN and DAN compared to HC. Conclusions We have provided evidence that WD is a disease with widespread dysfunctional connectivity in resting networks in brain, leading to neurological features and psychiatric symptoms (e.g. higher-order cognitive control and motor control impairments). The alter intra- and inter-network in the brain may be the neural underpinnings for the neuropathological symptoms and the process of injury compensation in WD patients.

Abstract Background Hepatocellular carcinoma still has a high incidence and mortality rate worldwide, and further research is needed to investigate its occurrence and development mechanisms in depth in order to identify new therapeutic targets. Ferritinophagy is a type of autophagy and a key factor in ferroptosis that could influence tumor onset and progression. Although, the potential role of ferritinophagy-related genes (FRGs) in liver hepatocellular carcinoma (LIHC) is unknown. Methods Single-cell RNA sequencing (scRNA-seq) data of LIHC were obtained from the Gene Expression Omnibus (GEO) dataset. In addition, transcriptome and clinical follow-up outcome data of individuals with LIHC were extracted from the The Cancer Genome Atlas (TCGA) dataset. FRGs were collected through the GeneCards database. Differential cell subpopulations were distinguished, and differentially expressed FRGs (DEFRGs) were obtained. Differential expression of FRGs and prognosis were observed according to the TCGA database. An FRG-related risk model was constructed to predict patient prognosis by absolute shrinkage and selection operator (LASSO) and COX regression analyses, and its prognosis predictive power was validated. Ultimately, the association between risk score and tumor microenvironment (TME), immune cell infiltration, immune checkpoints, drug sensitivity, and tumor mutation burden (TMB) was analyzed. We also used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to validate the expression of key genes in normal liver cells and liver cancer cells. Results We ultimately identified 8 cell types, and 7 differentially expressed FRGs genes (ZFP36, NCOA4, FTH1, FTL, TNF, PCBP1, CYB561A3) were found among immune cells, and we found that Monocytes and Macrophages were closely related to FRGs genes. Subsequently, COX regression analysis showed that patients with high expression of FTH1, FTL, and PCBP1 had significantly worse prognosis than those with low expression, and our survival prediction model, constructed based on age, stage, and risk score, showed better prognostic prediction ability. Our risk model based on 3 FRGs genes ultimately revealed significant differences between high-risk and low-risk groups in terms of immune infiltration and immune checkpoint correlation, drug sensitivity, and somatic mutation risk. Finally, we validated the key prognostic genes FTH1, FTL, using qRT-PCR, and found that the expression of FTH1 and FTL was significantly higher in various liver cancer cells than in normal liver cells. At the same time, immunohistochemistry showed that the expression of FTH1, FTL in tumor tissues was significantly higher than that in para-tumor tissues. Conclusion This study identifies a considerable impact of FRGs on immunity and prognosis in individuals with LIHC. The collective findings of this research provide new ideas for personalized treatment of LIHC and a more targeted therapy approach for individuals with LIHC to improve their prognosis.

Extensive neuroimaging abnormalities in subcortical regions build the pathophysiological basis of Wilson’s disease (WD). Yet, subcortical topographic organization fails to articulate, leaving a huge gap in understanding the neural mechanism of WD. Thus, how functional abnormalities of WD subcortical regions influence complex clinical symptoms and response to treatment remain unknown. Using resting-state functional MRI data from 232 participants (including 130 WD patients and 102 healthy controls), we applied a connectivity-based parcellation technique to develop a subcortical atlas for WD. The atlas was further used to investigate abnormalities in subcortical function (ASF) by exploring intrasubcortical functional connectivity (FC) and topographic organization of cortico-subcortical FC. We further used support vector machine (SVM) to integrate these functional abnormalities into the ASF score, which serves as a biomarker for characterizing individual subcortical dysfunction for WD. Finally, the baseline ASF score and one-year treatment data of the follow-up WD patients were used to assess treatment response. A group set of subcortical parcellations was evaluated, in which 26 bilateral regions well recapitulated the anatomical nuclei of the subcortical areas of WD. The results of cortico-subcortical FC and intrasubcortical FC reveal that dysfunction of the somatomotor networks-lenticular nucleus-thalamic pathways is involved in complex symptoms of WD. The ASF score was able to characterize disease progression and was significantly associated with treatment response of WD. Our findings provide a comprehensive elaboration of functional abnormalities of WD subcortical regions and reveal their association with clinical presentations, improving our understanding of the functional neural underpinnings in WD. Furthermore, abnormalities in subcortical function could serve as a potential biomarker for understanding the disease progression and evaluating treatment response of WD.

In the wake of the dual-carbon objective, the call for low-carbon attributes in integrated energy systems is ascending, with an amplified imperative to integrate wind and solar power efficiently. This study introduces an advanced low-carbon optimization framework for integrated energy systems, incorporating a sophisticated time-differentiated carbon accounting mechanism attentive to consumer emissions. A nuanced carbon accounting model is crafted to assess consumer emissions with greater accuracy. Predicated on these emissions, a refined low-carbon demand response model is articulated, factoring in the influence of carbon emission factors pertinent to electricity and heat procurement on user conduct. This model integrates the consideration of heat reclaimed from methanation processes, which in turn informs the carbon emission factors associated with purchased heat, and evaluates the subsequent optimization impact on the system. The proposed model is designed to curtail the system’s operational expenditures and is operationalized via the CPLEX solver. Through the establishment of various scenarios for evaluative comparison, the model is corroborated to substantially augment the system’s proficiency in assimilating wind and solar energy, markedly curtail carbon emissions, and facilitate a sustainable and cost-efficient operation of the integrated energy system.

Since microgrids can effectively integrate renewable energy, energy storage devices, and controllable loads, this advantage promotes the rapid development and application of microgrid technology. However, with the high proportion of renewable energy access, only considering how energy is optimally distributed in microgrids can no longer meet the actual demand. How to aggregate user-side controllable loads to form regulation resources has become a research hotspot, and the users, as a passive party in the load scheduling process, should also be an important consideration in their perception of the use of electricity. First, a control model for temperature-controlled loads and a time-shift model for time-shiftable loads are developed. Then, the comprehensive electricity satisfaction model of users is established, and the two-layer optimal scheduling model of microgrids considering users’ satisfaction is proposed, with users as the upper layer and microgrids as the lower layer, and the two-layer model is transformed into a single-layer model according to the KKT condition for solving. Finally, the effect of the weighting factor for satisfaction on the economy is discussed through the analysis of examples, which verifies the effectiveness of the two-layer model.

Regional Integrated Energy Systems (RIESs) and Shared Energy Storage Systems (SESSs) have significant advantages in improving energy utilization efficiency. However, establishing a coordinated optimization strategy between RIESs and SESSs is an urgent problem to be solved. This paper constructs an operational framework for RIESs considering the participation of SESSs. It analyzes the game relationships between various entities based on the dual role of energy storage stations as both energy consumers and suppliers, and it establishes optimization models for each stakeholder. Finally, the improved Differential Evolution Algorithm (JADE) combined with the Gurobi solver is employed on the MATLAB 2021a platform to solve the cases, verifying that the proposed strategy can enhance the investment willingness of energy storage developers, balance the interests among the Integrated Energy Operator (IEO), Energy Storage Operator (ESO) and the user, and improve the overall economic efficiency of RIESs.

The northern regions of China face the challenges of the mismatch of the power supply and demand, as well as serious wind curtailment issues, caused mainly by the limitation of the “with heat to determine electricity” mode for combined heat and power generation during the winter season. To further absorb the surplus wind power and alleviate restrictions, a comprehensive energy system optimization method for parks based on coordinated scheduling between sources and loads is proposed in this paper. First, the implementation of a heat-storage electric boiler on the source side further achieves the decoupling of heat and power. Second, an optimized scheduling method for electric vehicles combining incentive scheduling and orderly scheduling is proposed on the load side, which helps flatten the load curve. Finally, a tiered carbon trading mechanism is introduced and a community integrated energy system (CIES) optimization scheduling model is established with the aim of minimizing the total cost of the CIES, and the problem is solved using the CPLEX commercial solver. The simulation results indicate that the overall system efficiency is significantly improved through the coordinated scheduling of power sources and loads. Specifically, the integration rate of wind power increases by 3.91% when compared to the sole consideration of the integrated demand response. Furthermore, the peak shaving and off-peak filling effect is considerably enhanced compared to the utilization of only thermal-storage electric boilers. Additionally, the implementation of coordinated scheduling leads to a reduction in the total system cost by 2764.32 yuan and a decrease in total carbon emissions by 3515.4 kg. These findings provide compelling evidence that the coordinated scheduling of power sources and loads surpasses the limitations of thermal power units, strengthens the demand response capability of electric vehicles, and enhances the economic benefits of the CIES.

Hydrogen peroxide (H2O2), a significant member of reactive oxygen species, plays a crucial role in oxidative stress and cell signaling. Abnormal levels of H2O2 in the body can induce damage or even impair body function, leading to the development of certain diseases. Therefore, real-time monitoring of H2O2 in living cells is very important. In this work, the aggregation-induced emission fluorescence probe 2-(2-((4-(4,4,5,5-tetramethyl-1,3,2-dioxaborolan-2-yl) benzyl) oxy) phenyl) imidazo [1,2-a] pyridine (B2) was designed and synthesized, which enables the long-term tracing of H2O2 in living cells. The addition of H2O2 to probe B2 results in a dramatic fluorescence enhancement around 500 nm. Notably, B2 can visualize both exogenous and endogenous H2O2 in living cells. The synthesis method for B2 is simple, has a high yield, and utilizes readily available materials. It exhibits advantages such as low toxicity, photostability, and good biocompatibility. Consequently, the developed fluorescent probe in this study has great potential as a reliable tool for determining H2O2 in living cells.

The microstructure transformation of oxide metallurgy steel was studied by deforming to strains of 0.1–1 at strain rates of 1 s−1 at 900 °C. The variation trends of AF laths and M-A islands size with increasing strain were investigated. The kernel average misorientation(KAM) data obtained by EBSD are used to calculate the geometrically necessary dislocation(GND) density of AF laths (ρAFGND) induced by inclusions and matrix (ρAveGND). The results showed that the large number of dispersed spherical inclusions in experimental steel can effectively induce the nucleation of AF under different strains, which is composed of Al–Ti–Mg–Zr–O and MnS. With the increase of strain, the deformation-induced ferrite transformation(DIFT) behavior dominates the microstructure evolution, the nucleation and growth of more ferrite led to the gradual increase of HAGBs and decrease of ρAveGND, and the microstructure transformed from granular bainite(GB) to granular structure(GS). The size and aspect ratio of AF laths and M-A islands gradually decreased, and the M-A islands gradually replaced by more carbides distributed inside the grains and on the grain boundaries. The growth of AF laths induced by inclusions is hindered by the influence of pre-nucleated proeutectoid ferrite, resulting the increasing of ρAFGND. Meanwhile, the AF laths nucleated on inclusions satisfies the K–S orientation relationship with parent austenite.

In this paper, a Ti-deoxidized low carbon high strength steel plate with different Nb content was obtained by thermal mechanical control processing (TMCP) methods. The coarse-grain heat-affected zone (CGHAZ) under high heat input of 300 kJ/cm conditions was simulated. The effects of Nb on microstructure and mechanical properties in base metal (BM) and CGHAZ were analyzed. The results showed that high content of Nb addition is not conducive to the improvement of toughness, especially in high heat input CGHAZ. A certain amount of Nb inhibites the formation of ferrite, while promotes the bainite transformation with coarse carbides during high heat input welding process. Although high-angle grain boundary has a certain hindrance to the crack propagation, the coarse carbides caused by the enhanced hardenability in Nb-bearing steels stimulates the crack initiation sensitively. Besides, the uneven prior austenite grains may also take responsibility to the deterioration of toughness in Nb-bearing CGHAZ. In general, the content of Nb should be carefully added when impact toughness of CGHAZ is considered during high heat input welding in Ti-deoxidized low carbon high strength steel.

The effects of multi-layer graphene (MLG) on the properties of tungsten carbide-11 cobalt (WC-11Co) cemented carbides were studied by transmission electron microscopy (TEM), scanning electron microscopy (SEM), X-ray diffraction analysis (XRD) and other methods. The results show that when the MLG content is 0.1 wt%, the density, hardness and fracture toughness are 3%, 14.5% and 71.8% higher, respectively, compared with the sample without MLG. Bridging and deflection of cracks by MLG improve the fracture toughness of WC-11Co. In addition, MLG inhibits the transformation of the Co phase into Co3C during the sintering process and makes Co phase maintain FCC structure at room temperature, thus enhancing the fracture toughness of the matrix. MLG prevent the matrix from generating W3Co3C and Co3C, thus improving wear resistance. Furthermore, MLG improves the thermal conductivity of cemented carbide and greatly reduces the degree of oxidative wear of the matrix during friction tests. The wear volume of the sample with 0.1 wt% MLG is 98% smaller than that of the sample without MLG, but its mean friction coefficient is 8.8% higher during stable stage. It is because the solid lubricating effect of the wear debris is greater than that of the MLG after 900s.

In order to solve the safety problems that exist in traditional charging technology, a new visible light-curing 3D printing platform and energetic slurry formula were designed. Within them, the formula of light-curing slurry is 60.46% EA/PUA (prepolymer), 37.21% PETA/HDDA/BA (active diluent monomer), 0.47% CQ (visible light initiator), 0.93% DMT (curing accelerator), and 0.93% additive. The curing time of visible light-curing paste is 7.5 s, the viscosity is 22 6 mPa·s, the curing hardness is 2 H, the gel rate is 96.67%, the shrinkage rate is 98.35%, and the curing depth is 9.41 mm. The optimal formulation of energetic slurry is 20% visible light-curing slurry, 57.72% AP, 15.28% Al and 7% RDX. The 3D printing energetic powder column has a smooth surface, uniform filler distribution, a flat surface, no protrusions or other defects, and good matching. The average burning rate is 1.165 mm·s−1, the combustion is stable, and the maximum burning light intensity is 2.053 cd.

Objectives. To assess A-kinase anchor protein 95 (AKAP95), B-Raf, extracellular regulated protein kinases 1/2 (ERK1/2), and Elk-1 expression in colon cancer tissue, and characterize AKAP95 associations with B-Raf, ERK1/2, Elk-1, and colon cancer clinicopathological indices. Methods. The immunohistochemistry streptavidin-perosidase (SP) method was used to determine protein expression levels in 64 colon cancer and 32 para-carcinoma tissue specimens. Results. (1) Positive AKAP95 expression rates in colon cancer tissue were higher when compared with para-carcinoma tissue (92.19% vs. 59.38%, P0.05); however, in The Cancer Genome Atlas and Gene Expression Omnibus datasets, AKAP95 was closely related to immune infiltration, and highly expressed AKAP95 was negatively associated with overall survival and relapse free survival rates in colon cancer patients. (3) Correlations were observed between AKAP95 and ERK1/2, AKAP95 and Elk-1, B-Raf and ERK1/2, B-Raf and Elk-1, and ERK1/2 and Elk-1 (all P0.05). Conclusions. AKAP95 may affect immune infiltration levels in colon cancer by participating in ERK1/2–Elk-1 signal transduction.

BackgroundConventionally, serum ceruloplasmin levels below the lower reference limit (0. 20 g/L) is considered a diagnostic cutoff point for Wilson's disease (WD). However, the lower reference limit varies with assay methodologies and the individuals in the included studies. The objective of this study was to determine the optimal cutoff value of serum ceruloplasmin levels for the diagnosis of WD in a large Chinese cohort and to identify factors associated with serum ceruloplasmin.MethodsThe cutoff value of ceruloplasmin levels was developed based on a retrospective derivation cohort of 3,548 subjects (1,278 patients with WD and 2,270 controls) and was validated in a separate validation cohort of 313 subjects (203 patients with WD and 110 controls). The performance of immunoassay was tested by receiver operating characteristic curve (ROC) analysis, and differences among the groups were analyzed by using the Mann–Whitney U-test and the Kruskal–Wallis test.ResultsThe conventional cutoff of serum ceruloplasmin levels of

Abstract Background Pancreaticobiliary reflux (PBR) causes chronic inflammation of the gallbladder mucosa and changes in the bile components, which are known to promote gallstone formation. This study aimed to investigate the bile biochemistry changes in gallstone patients with PBR and provide new clues for research on the involvement of PBR in gallstone formation. Methods Patients undergoing surgery for gallstones between December 2020 and May 2021 were eligible for inclusion. The bile biochemistry (including amylase, lipase, triglyceride, cholesterol, free fatty acids [FFAs], alanine aminotransferase [ALT], aspartate aminotransferase [AST], alkaline phosphatase [ALP], and γ-glutamyl transferase [γ-GT]) of the included gallstone patients was analysed to determine correlations with PBR. Results In this study, 144 gallstone patients who underwent surgery were enrolled. Overall, 15.97 % of the patients had an increased bile amylase level, which was associated with older age and significantly higher bile levels of ALP, lipase, triglyceride, and FFAs. Positive correlations were observed between amylase and lipase, triglyceride, FFAs levels in the gallbladder bile. However, the bile levels of triglyceride, FFAs, and lipase were positively correlated with each other only in the PBR group and showed no significant correlation in the control (N) group. In addition, elevated bile FFAs levels were found to be an independent risk factor for gallbladder wall thickening. Conclusions In conclusion, PBR-induced increase in FFAs and triglyceride in the gallbladder bile is a cause of gallstone formation, and an increase in bile ALP suggests the presence of cholestasis in PBR.

The under-performance of mergers and acquisitions (M&As) resulting from impairment of goodwill is of great interest to regulators and investors. This study investigates the performance of M&As from the perspective of home bias. The results indicate that (1) Post-merger performance is worse when purchased companies are in high-level executives’ hometowns. (2) When located in the executives’ hometown, listed companies pay higher premiums, and further loss of goodwill occurs in the following years. Integration efficiency after M&As is lower, as reflected in the higher degree of excess employees. (3) Cross-sectional analyses indicate that M&A under-performance only occurs when the province has a low level of market development, listed companies are non-state-owned enterprises, or listed companies’ executives are older. (4) Interactive effect test results suggest that fund holding, analyst following and media coverage can alleviate the negative impact of home bias on long-term performance.

Graphical Abstract

Studies show that non-coding RNAs, especially microRNAs (miRNAs) and circular RNAs (circRNAs), and protein-coding genes are involved in the pathophysiology of multi-organ damage caused by Wilson’s disease (WD). However, circRNA expression profiles and their role in initiation and progression of WD kidney injury remain largely unclear at present. Here, we explored potential critical protein-coding genes, miRNAs, and circRNAs, as well as identify competitive endogenous RNAs (ceRNAs) in a WD mouse model by high-throughput sequencing. We investigated the expression profiles of circRNAs, miRNAs, and protein-coding genes, and identified 32 DEcircRs, 45 DEmiRs, and 1623 DEPs. Identified DEcircRs, DEmiRs, and DEPs were used to construct a ceRNA network, which consisted of 15 DEcircRNAs (four upregulated and 11 downregulated), 18 DEmiRNAs (14 upregulated and four downregulated), and 352 DEmRNAs (205 upregulated and 147 downregulated). Further experiments proved that mmu_circ_0001333 and mmu_circ_0000355 acted as sponges of miR-92b-5p, miR-107-3p, and miR-187-3p to regulate the expression of genes including Smad9, Mapk10, and Aldh3a2, which may participate in WD-related kidney injury. Taken together, this study identified the circRNA/miRNA/mRNA network involved in kidney failure in WD, which may serve as a potential biomarker for the pathogenesis of WD.

Injecting power plant flue gas into a goaf stores CO2 in the flue gas and effectively prevents the spontaneous combustion of the coal remaining in the goaf. Here, we investigated the adsorption behavior of three types of coal at normal temperature and pressure using a self-developed adsorption experimental device. We used a specific surface area and porosity analyzer to study the effects of pore structure, mineral content, and moisture content on CO2 adsorption in coal. Based on the experimental data, we designed a multifactor CO2 adsorption prediction model based on a backpropagation (BP) neural network. The results indicated that the pore size of most micropores in coal was in the range of 0.5–0.7 and 0.8–0.9 nm. The specific surface area and pore volume were positively correlated with the CO2-saturated adsorption capacity, whereas the mean pore diameter, mineral content, and moisture content were inversely associated with the CO2-saturated adsorption amount. The accuracy of the multifactor BP neural network prediction model was satisfactory: the determination coefficients (R2) of the training and test sets were both above 0.98, the root mean square error (RMSE) and mean absolute error (MAE) of the test set were both less than 0.1, and the prediction results satisfied the requirements. To optimize the prediction performance of the model, we used the random forest algorithm to calculate the importance of each factor. The sum of the importance weights of the specific surface area, moisture content, and pore volume was 91.6%, which was much higher than that of the other two factors. Therefore, we constructed an optimization model with specific surface area, moisture content, and pore volume as input variables. The R2 values of the training and test sets in the simplified model were improved compared with those of the multifactor model, the RMSE and MAE were reduced, and the fitting effect was ideal. The prediction model of CO2 adsorption in coal based on the BP neural network can predict the CO2 adsorption capacity of coal under different physical and chemical conditions, thereby providing theoretical support for the application of CO2 storage technology in goafs.

Precipitation stable isotopes (2H and 18O) are adequately understood on their climate controls in the Tibetan Plateau, especially the north of Himalayas via about 30 years’ studies. However, knowledge of controls on precipitation stable isotopes in Nepal (the south of Himalayas), is still far from sufficient. This study described the intra-seasonal and annual variations of precipitation stable isotopes at Kathmandu, Nepal from 10 May 2016 to 21 September 2018 and analysed the possible controls on precipitation stable isotopes. The enriched δD and δ18O values were identified during non-monsoon season and depleted values were found during monsoon season, showing remarkable intra-seasonal characteristics of monsoon influence. The local meteoric water line suggested a strong influence of evaporation during rainfall in non-monsoon season and significant impact of non-equilibrium processes on precipitation during monsoon season. Temperature–δ18O exhibited negative correlation for overall samples and showed no significant correlation in seasonal scales, which was attributed to the influence of monsoon moisture. The positive correlation was observed between δ18O and outgoing longwave radiation (OLR) in monsoon season, suggesting the significant impact of convective activity on temporal variations of precipitation stable isotopes. During April, and May of 2016 and 2017, variation of precipitation stable isotopes are probably related with the mixing of multi-moisture combined with the westerlies transport. Our study suggested that the moisture transport processes are the main controls of precipitation stable isotopes at Kathmandu.

Coal samples from the Shanxi Shaping coal mine were selected to investigate the occurrence of H2S in low sulfur coal seams. The adsorption mechanism of coal to H2S was explored, and an occurrence equation for H2S in coal seams was fitted through adsorption experiment results. The results showed that under ambient temperature and pressure conditions, the H2S adsorbed by coal reached equilibrium within 24 h. The increase in H2S concentrations and the moisture content of coal samples resulted in an increase in the adsorption capacity of H2S. Chemical adsorption of H2S by the coal also occurred. The total sulfur content in the coal increased, and water promoted the conversion from H2S to sulfur in coal. After adsorption, most of the H2S remains in the coal structure in the form of inorganic sulfur, such as sulfur hydride, iron sulfide sulfur, and monomeric sulfur, and a small proportion of H2S is bonded in the structure of the coal in the form of organic sulfur such as thiophene, C-S-C, and C-SH. Therefore, the higher the total sulfur content in coal, the greater the occurrence of H2S. The total amount of H2S increased exponentially with the concentration of free H2S and the moisture content of coal at equilibrium. This meant that the total amount of H2S in the coal seam could be estimated by fitting an equation according to the concentration of free H2S and the moisture content of coal seams. The concentration of free H2S decreased linearly with the increase in moisture content of the coal, therefore, the concentration of H2S in space could be reduced by injecting water into coal seams.

With the development of additive manufacturing (AM), the Ti-6Al-4V alloy manufactured by laser powder bed fusion (LPBF) is becoming more widely studied. Fatigue fracture is the main failure mode of such components. During LPBF processing, porosity defects are unavoidable, which hinders the exploration of the relationship between fatigue performance and microstructure. In this study, a laser remelting method was used to reduce porosity defects inside the Ti-6Al-4V alloy. Three annealing treatments (AT) and three solution-aging treatments (SAT) were used to study the effect of the two-phase zone (α + β) microstructure on fatigue life and fatigue crack growth behavior. Fatigue life and crack growth rate (CGR) curves were obtained, and fatigue fracture surface and crack growth fracture surface were analyzed. The results show that microstructure influences fatigue life but has little effect on CGR. Compared with the as-built specimen, the fatigue life of the AT and SAT specimens increased significantly at 850℃ by 101 and 63.7 times, respectively. The thickness of the α lath and the location of crack nucleation together affect the fatigue life. In the stable growth stage, the layered microstructure of α colonies is the most resistant to crack growth.

Dysfunction of the lenticular nucleus is thought to contribute to neurological symptoms in Wilson’s disease (WD). However, very little is known about whether and how the lenticular nucleus influences dystonia by interacting with the cerebral cortex and cerebellum. To solve this problem, we recruited 37 WD patients (20 men; age, 23.95 ± 6.95 years; age range, 12–37 years) and 37 age- and sex-matched healthy controls (HCs) (25 men; age, 25.19 ± 1.88 years; age range, 20–30 years), and each subject underwent resting-state functional magnetic resonance imaging (RS-fMRI) scans. The muscle biomechanical parameters and Unified Wilson Disease Rating Scale (UWDRS) were used to evaluate the level of dystonia and clinical representations, respectively. The lenticular nucleus, including the putamen and globus pallidus, was divided into 12 subregions according to dorsal, ventral, anterior and posterior localization and seed-based functional connectivity (FC) was calculated for each subregion. The relationships between FC changes in the lenticular nucleus with muscle tension levels and clinical representations were further investigated by correlation analysis. Dystonia was diagnosed by comparing all WD muscle biomechanical parameters with healthy controls (HCs). Compared with HCs, FC decreased from all subregions in the putamen except the right ventral posterior part to the middle cingulate cortex (MCC) and decreased FC of all subregions in the putamen except the left ventral anterior part to the cerebellum was observed in patients with WD. Patients with WD also showed decreased FC of the left globus pallidus primarily distributed in the MCC and cerebellum and illustrated decreased FC from the right globus pallidus to the cerebellum. FC from the putamen to the MCC was significantly correlated with psychiatric symptoms. FC from the putamen to the cerebellum was significantly correlated with muscle tension and neurological symptoms. Additionally, the FC from the globus pallidus to the cerebellum was also associated with muscle tension. Together, these findings highlight that lenticular nucleus–cerebellum circuits may serve as neural biomarkers of dystonia and provide implications for the neural mechanisms underlying dystonia in WD.

Gandouling (GDL) Pill is a novel Traditional Chinese medicinal drug to treat Wilson’s disease in clinics. It is composed of six separate herbal medicines, including Rhei Radix ET Rhizoma, Coptidis Rhizoma, Salviae Miltiorrhizae Radix ET Rhizoma, Spatholobi Caulis, Curcumae Rhizoma, and Curcumae Longae Rhizoma. In this study, a strategy was proposed to investigate the chemical constituents and to quantify the potential bioactive components in GDL Pill. Firstly, the mass fragmentation behaviors of representative compounds were investigated, and, in total, 69 compounds were characterized in GDL Pill using full scan/dd-MS2 scan mode by ultra-high-performance liquid chromatography (UPLC)/Q-Orbitrap mass spectrometry (MS). These compounds included 18 alkaloids, 18 ketones, 16 phenolic compounds, 11 organic acids, and 6 tanshinones. Seventeen of the compounds were unambiguously identified by comparison with reference standards. Secondly, the absorption components of GDL Pill in rat plasma were investigated by using target-Selected Ion Monitoring (t-SIM) scan mode built in Q-Orbitrap MS. A total of 18 components were detected, which were considered as potential bioactive components of GDL Pill. Thirdly, 10 major absorption components were simultaneously determined in six batches of samples by UPLC/diode array detector (DAD). The method was fully validated with respect to linearity, precision, repeatability, stability, and recovery. Alkaloids from Coptidis Rhizoma, such as coptisine (8), berberine (18), palmatine (19), were the most abundant bioactive compounds for GDL Pill that possess the potential be used as quality markers. The proposed strategy is practical and efficient for revealing the material basis of GDL Pill, and also provides a simple and accurate method for quality control.

Unlike prior studies that investigate research and development (R&D) accounting as a dichotomous choice between capitalizing vs. expensing, this study identifies low-reliability R&D capitalization by the occurrence of ex post impairment of capitalized R&D costs. I find that low-reliability capitalization is associated with higher discretionary accruals but fails to signal future innovation, whereas normal capitalization without subsequent impairment lacks earnings aggressiveness and predicts future innovation positively, compared to expensing firms. Next, this study shows that Big 4 and industry specialist auditors improve reliability by notably decreasing the likelihood of low-reliability R&D capitalization. The results remain robust after controlling for R&D investment intensity and potential endogeneity in the capitalization decision. Additional tests show that managers strategically time the recognition of impairment for big-bath and earnings-smoothing purposes, and that analyst coverage does not help differentiate between low-reliability and normal R&D capitalization. Collectively, this paper increases our understanding of R&D accounting and auditing and contributes to the debate on the reliability of R&D capitalization. Keywords: R&D capitalization, Reliability, Impairment, Accounting choice

In this study, Cu matrix composites reinforced with reduced graphene oxide-coated submicron spherical Cu (SSCu@rGO) exhibiting both high-strength plastic product (UT) and high electrical conductivity (EC) were prepared. SSCu@rGO results in the formation of Cu4O3 and Cu2O nanotransition layers to optimize the interface combination. In addition, as a flow carrier, SSCu@rGO can also render graphene uniformly dispersed. The results show that SSCu@rGO has a significant strengthening effect on the Cu matrix composites. The relative density (RD) of the SSCu@rGO/Cu composites exceeds 95%, and the hardness, UT, and yield strength (YS) reach 106.8 HV, 14,455 MPa% (tensile strength (TS) 245 MPa, elongation (EL) 59%), and 119 MPa; which are 21%, 72%, and 98% higher than those of Cu, respectively. Furthermore, EC is 95% IACS (International Annealed Copper Standard), which is also higher than that of Cu. The strength mechanisms include transfer load strengthening, dislocation strengthening, and grain refinement strengthening. The plastic mechanisms include the coordinated deformation of the interface of the Cu4O3 and Cu2O nanotransition layers and the increase in the fracture energy caused by graphene during the deformation process. The optimized EC is due to SSCu@rGO constructing bridges between the large-size Cu grains, and graphene on the surface provides a fast path for electron motion. This path compensates for the negative influence of grain refinement and the sintering defects on EC. The reduced graphene oxide-reinforced Cu-matrix composites were studied, and it was found that the comprehensive performance of the SSCu@rGO/Cu composites is superior to that of the rGO/Cu composites in all aspects.

During micro-scale tracer flow in porous media, the permeability and fluid velocity significantly affect the fluid dispersion properties of the media. However, the relationships between the dispersion coefficient, permeability, and fluid velocity in core samples are still not clearly understood. Two sets of experiments were designed to study the effects of tracer fluid flow velocity and porous medium permeability on the dispersion phenomenon in a core environment, using natural and sand-filled cores, respectively. From experimental data-fitting by a mathematical model, the relationship between the dispersion coefficient, flow velocity, and permeability was identified, allowing the analysis of the underlying mechanism behind this phenomenon. The results show that a higher volumetric flow rate and lower permeability cause a delay in the tracer breakthrough time and an increase in the dispersion coefficient. The core experimental results show that the dispersion coefficient is negatively correlated with the permeability and positively correlated with the superficial velocity. The corresponding regression equations indicate linear relations between the dispersion coefficient, core permeability, and fluid velocity, resulting from the micron scale of grain diameters in cores. The combination of high velocity and low permeability yields a large dispersion coefficient. The effects of latitudinal dispersion in porous media cannot be ignored in low-permeability cores or formations. These findings can help to improve the understanding of tracer flow in porous media, the design of injection parameters, and the interpretation of tracer concentration distribution in inter-well tracer tests.

Foam-assisted steam flooding is a promising technique to alleviate gas channeling and enhance sweep efficiency in heterogeneous heavy-oil reservoirs. However, long-term foam stabilization remains problematic at high temperatures. Three-phase foam (TPF), containing dispersed solid particles, has been proposed to improve foam stability under harsh reservoir conditions. We fabricated a novel TPF system by adding ultrafine fly ash particles, as well as high-temperature resistant microspheres with an adhesive coating layer. This work aims at assessing the ability of the generated TPF in controlling steam channeling and enhancing oil recovery. Static and core flood tests were performed to evaluate foam strength and stability. Our results suggested a stronger foamability at a lower consolidation agent concentration, while a longer half-life period of foam and settling time of solid particles at a larger consolidation agent concentration were observed. Bubbles suspended independently in the liquid phase, with sizes varying from 10 to 100 μm, smaller than that of the conventional foam, suggesting a significant enhancement of foam dispersity and stability. The plugging rate was close to 90% when the temperature was as high as 300 °C, demonstrating a well-accepted plugging effect under high temperatures. A larger pore volume injection of TPF yielded a higher EOR in parallel cores, which substantiated the effectiveness of the three-phase foam system in sealing high-permeability channels.

Supercritical carbon dioxide (SC-CO2) jet is capable of decreasing the threshold pressure of rock breakage and mitigating formation damage, owing to its low viscosity, high diffusivity, and extremely-low surface tension. The swirling-round jet holds the advantages of both a swirling jet and a round jet. Therefore, the comprehensive technique, swirling-round SC-CO2 (SR-SC-CO2) jet, is expected to substantially enhance rock-breaking efficiency. However, theoretical analysis of the flow field characteristics of SR-SC-CO2 has not been reported yet. This work aims to lay a theoretical foundation for employing SR-SC-CO2 in drilling and fracturing. The flow field is simulated using Naiver-Stokes equations and the RNG k-ε turbulence model. Sensitivity analysis, regarding pressure drop of the nozzle, confining pressure, fluid temperature, jetting distance, the diameter of the nozzle’s central hole, and grooving area, are performed. We show that the combined swirling-round SC-CO2 jet flow could maintain a relatively larger axial as well as tangential velocity compared to a single approach of swirling jet or round jet, enabling one to acquire a deeper oillet and expand the perforation area effectively. The simulation results substantiate the enormous potential of SR-SC-CO2 in improving rock-breaking efficiency and clarify the influence of relevant parameters on the impact pressure of the jet flow.

Hole defects and uneven membrane thicknesses can lead to poor performance, especially in the separation stability of ceramic membranes. This paper uses a one-step sintering method, which avoids hole defects and uneven membrane thicknesses, for the preparation of high-performance and defect-free ceramic membranes. For this purpose, two kinds of ceramic membrane slurry with high or low viscosities were prepared by alumina particles, as raw materials. Both the effects of the two coating process with a one-step coating method for low-viscosity slurry, and the two-step coating method with a high viscosity flush after a low viscosity coating, on the surface properties of a ceramic membrane, were studied in detail. The result shows that the properties of ceramic membranes can be improved by a two-step coating method, with a high viscosity flush after a low viscosity coating, A high-performance and defect-free ceramic membrane was obtained by one-step sintering at 1450 °C for 2 hr with 7 wt % solid content and a coating time of 11 s.

TiO2 is usually used as a sintering aid to lower the sintering temperature of porous alumina membrane support. Two ways of the addition of TiO2 are chosen: in-situ precipitation and in-situ hydrolysis. The results show that the distribution status of TiO2 has an important effect on the property of porous alumina membrane support. In in-situ hydrolysis method, the nano-meter scale TiO2 distributes evenly on the alumina particles’ surface. The bending strength of the support increases sharply and the pore size distribution changes more sharply along with the content of TiO2 which slightly increases from 0.3 wt.% to 0.4 wt.%. The distribution of the nano-meter scale TiO2 is not so even added by in-situ precipitation method. Neither the bending strength nor the pore size distribution of the support is worse than that of the support added by in-situ hydrolysis even if the content of TiO2 is high to 2 wt.%. The permeating flux has a similar tendency. Consequently, the porous alumina membrane support has the porosity of 30.01% and the bending strength of 77.33 MPa after sintering at 1650 °C for 2 h with the optimized TiO2 content of 0.4 wt.% added by the in-situ hydrolysis method.

Remote sensing image segmentation is a crucial technique in the field of land management. However, existing semantic segmentation networks require a large number of floating-point operations (FLOPs) and have long run times. In this paper, we propose a dual-path feature aggregation network (DPFANet) specifically designed for the low-latency operations required in land management applications. Firstly, we use four sets of spatially separable convolutions with varying dilation rates to extract spatial features. Additionally, we use an improved version of MobileNetV2 to extract semantic features. Furthermore, we use an asymmetric multi-scale fusion module and dual-path feature aggregation module to enhance feature extraction and fusion. Finally, a decoder is constructed to enable progressive up-sampling. Experimental results on the Potsdam data set and the Gaofen image data set (GID) demonstrate that DPFANet achieves overall accuracy of 92.2% and 89.3%, respectively. The FLOPs are 6.72 giga and the number of parameters is 2.067 million. [ABSTRACT FROM AUTHOR]