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Recent scientific investigations have revealed the intricate mechanisms underlying bone formation, emphasizing the essential role of long non-coding RNAs (lncRNAs) as critical regulators. This process, essential for skeletal strength and functionality, involves the transformation of mesenchymal stem cells into osteoblasts and subsequent deposition of bone matrix. lncRNAs, including HOX transcript antisense RNA (HOTAIR), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), differentiation antagonizing non-coding RNA (DANCR), and maternally expressed gene 3 (MEG3), have emerged as prominent players in this regulatory network. HOTAIR modulates osteoblast differentiation by interacting with chromatin-modifying enzymes, while MALAT1 regulates osteogenic differentiation through microRNA interactions. DANCR collaborates with Runx2 to fine-tune osteoblast differentiation, and MEG3 orchestrates multiple signaling pathways crucial for bone formation. Moreover, other lncRNAs such as H19, lncRNA for enhancing osteogenesis 3, rhabdomyosarcoma 2-associated transcript, urothelial cancer associated 1, taurine up-regulated gene 1, and nuclear enriched abundant transcript 1 contribute to the complex regulatory network governing osteoblast activities. Understanding the precise roles of these lncRNAs offers promising avenues for developing innovative therapeutic strategies targeting bone-related disorders like osteoporosis. Overall, this review summarizes the pivotal role of lncRNAs in bone formation, highlighting their potential as targets for future research endeavors aimed at advancing therapeutic interventions in bone diseases.

Objective In order to improve train operational efficiency, it is necessary to monitor metro traction power consumption and establish a relevant energy consumption model for prediction analysis of metro traction power consumption. Method The basic principles of grey prediction model and BP (backpropagation) neural network are introduced. Taking the traction daily electricity consumption data for a typical metro station in Tianjin in June 2021 as example, the grey correlation analysis method is used to select the influencing factors with high correlation to the daily traction power consumption of metro. Based on the GM (1,1) grey prediction model, the short-term traction daily power consumption is predicted. The selected influencing factors with high correlation, the short-term traction daily power consumption predicted by GM (1,1) grey model, and the adjacent historical traction daily power consumption data are used as input for training in BP neural network model to establish the GM-BP grey neural network model. The required short-term metro traction daily power consumption prediction data is generated. Result & Conclusion Compared with conventional GM (1,1) grey prediction model and BP neural network model, the prediction error of short-term traction daily power consumption predicted by the GM-BP grey neural network model shows significant improvement, and can be used as effective metro traction power consumption data for short-term prediction data analysis.

Abstract Sepsis is a severe disease characterized by high mortality rates. Our aim was to develop an early prognostic indicator of adverse outcomes in sepsis, utilizing easily accessible routine blood tests. A retrospective analysis of sepsis patients from the MIMIC-IV database was conducted. We performed univariate and multivariate regression analyses to identify independent risk factors associated with in-hospital mortality within 28 days. Logistic regression was utilized to combine the neutrophil-to-lymphocyte ratio (NLR) and the neutrophil-to-platelet ratio (NPR) into a composite score, denoted as NLR_NPR. We used ROC curves to compare the prognostic performance of the models and Kaplan–Meier survival curves to assess the 28 day survival rate. Subgroup analysis was performed to evaluate the applicability of NLR_NPR in different subpopulations based on specific characteristics. This study included a total of 1263 sepsis patients, of whom 179 died within 28 days of hospitalization, while 1084 survived beyond 28 days. Multivariate regression analysis identified age, respiratory rate, neutrophil-to-lymphocyte ratio (NLR), neutrophil-to-platelet ratio (NPR), hypertension, and sequential organ failure assessment (SOFA) score as independent risk factors for 28 day mortality in septic patients (P

Introduction: Sessile plants engage in trade-offs between growth and defense capacity in response to fluctuating environmental cues. MYB is an important transcription factor that plays many important roles in controlling plant growth and defense. However, the mechanism behind how it keeps a balance between these two physiological processes is still largely unknown. Objectives: Our work focuses on the dissection of the molecular mechanism by which GhMYB33 regulates plant growth and defense. Methods: The CRISPR/Cas9 technique was used to generate mutants for deciphering GhMYB33 functions. Yeast two-hybrid, luciferase complementary imaging, and co-immunoprecipitation assays were used to prove that proteins interact with each other. We used the electrophoretic mobility shift assay, yeast one-hybrid, and luciferase activity assays to analyze GhMYB33 acting as a promoter. A β-glucuronidase fusion reporter and 5′ RNA ligase mediated amplification of cDNA ends analysis showed that ghr-miR319c directedly cleaved the GhMYB33 mRNA. Results: Overexpressing miR319c-resistant GhMYB33 (rGhMYB33) promoted plant growth, accompanied by a significant decline in resistance against Verticillium dahliae. Conversely, its knockout mutant, ghmyb33, demonstrated growth restriction and concomitant augmentation of V. dahliae resistance. GhMYB33 was found to couple with the DELLA protein GhGAI1 and bind to the specific cis-elements of GhSPL9 and GhDFR1 promoters, thereby modulating internode elongation and plant resistance in V. dahliae infection. The ghr-miR319c was discovered to target and suppress GhMYB33 expression. The overexpression of ghr-miR319c led to enhanced plant resistance and a simultaneous reduction in plant height. Conclusion: Our findings demonstrate that GhMYB33 encodes a hub protein and controls the expression of GhSPL9 and GhDFR1, implicating a pivotal role for the miR319c-MYB33 module to regulate the trade-offs between plant growth and defense.

In high-penetration wind power generation systems， accurately assessing the support potential for virtual inertia of energy storage and fully releasing its energy reserves to render the systems active in grid frequency regulation are crucial for ensuring the systems’ frequency safety and stability. To achieve this， a dynamic frequency response model for wind-storage power generation systems to calculate the system’s time of safe frequency rise and fall and the extreme values of frequency deviation. Next， considering the constraints on the safe operating condition of the state of charge （SOC） during energy storage， the virtual inertia of energy storage during the time of safe frequency rise and fall is quantitatively evaluated. Moreover， an active frequency support technology for energy storage based on fixed-frequency control is introduced， aiming to fully exploit the frequency support capability of energy storage during the frequency drop and recovery periods. Finally， a simulation model of high-penetration wind power generation systems is constructed for validation. Under the proposed control strategy， energy storage can provide effective inertia support and offer sustained frequency response， thereby significantly enhancing the systems’ frequency stability.

Objective To explore the surgical techniques and experiences in the treatment of Peyronie's disease using electric rotary grinding of tunica albuginea plaques followed by graft repair with tunica vaginalis or bovine pericardium under a microscope. Methods A retrospective cohort study was performed on 21 patients with severe penile curvature due to Peyronie's disease admitted in our department from January 2021 and May 2023. All of them underwent microscopic electric rotary grinding of tunica albuginea plaques followed by graft repair surgery. Short-term and mid-term outcomes were observed. Results For the 21 enrolled patients, 12 (57.1%) underwent repair using unilateral tunica vaginalis, 3 (14.3%) underwent repair using bilateral tunica vaginalis, and 6 (28.6%) underwent repair using bovine pericardium. The operation time was 170~385 (average 272±69) min, and the average postoperative follow-up duration was 3~24 (average 12.1±7.2) months. Seventeen patients (81.0%) had their penis fully extended, while 4 patients (19.0%) had slight dorsal curvature, which was less than 10°. All patients were satisfied with the shape of their penis during erection. The change in penile length was +(1.1±0.5) cm, and 9 patients (42.9%) reported early postoperative penile head numbness, which spontaneously resolved after an average duration of 3.2±1.9 months. All patients were able to successfully engage in sexual activity, with an average penile erection hardness score of 3.8. The overall satisfaction rate was 90.5% postoperatively. Conclusion Meticulous dissection of Buck's fascia under a microscope is advantageous in reliably preserving dorsal neurovascular structures. Application of an electric grinding drill for plaque ablation allows for more precise release of the tunica. Graft repair of tunica albuginea defects with testicular tunica vaginalis or bovine pericardium for Peyronie's disease yields overall favorable clinical outcomes and obtains high satisfaction. It is worthy of promotion in clinical practice.

Currently, there is a high latency problem in the transmission of video surveillance data in coal mines, and the main cause of video transmission delay is encoding delay. In order to solve the above problems, a intelligent monitoring video transmission method for coal mines based on media supplemental enhancement information(SEI) without video encoding is proposed. This method caches a copy of the compressed video frame obtained by demultiplexing the video stream, and decodes the compressed video frame to obtain the decoded video frame. The method stores the AI model analysis results in the decoded video frame through SEI, writes the custom SEI into the network extraction layer unit corresponding to the compressed video frame copy of the decoded video frame based on the timestamp correspondence. The method multiplexes the compressed video frame copy to achieve real-time transmission of coal mine intelligent monitoring videos. Experimental testing of this method is conducted on a 24 core CPU. The results show that for videos with a resolution of 1280×720, the overall CPU utilization rate for video processing using this method decreases from 24.7% to 36.3% when using traditional methods to 20.3% to 23.9%. The end-to-end delay decreases from 1946 ms to 345 ms. For videos with a resolution of 1920×1080, the overall CPU utilization rate for video processing using this method decreases from 29.2% to 41.8% using traditional methods to 18.5% to 26.3%. The end-to-end latency decreases from 6204 ms to 479 ms. This method reduces the transmission delay of coal mine intelligent monitoring videos by avoiding the video encoding process, saves CPU or GPU resources required for video encoding, and reduces the hardware cost of the intelligent video monitoring system.

[ Objective ] This study aims to explore the protective mechanism of exogenous silicon on water metabolism and photosynthesis of Cucurbita pepo L. seedlings under salt stress , and to provide theoretical reference for salt resistance of C . pepo L.. [ Methods ] Using “ Hanlu 7042 ” C . pepo L. variety as the test material and hydroponic experiment , four treatments were set : Control , silicon treatment ( 0.3 mmol / L Na 2 SiO 3 · 9H 2 O ), salt stress ( 150 mmol / L NaCl ), salt stress+silicon treatment ( 0.3 mmol / L Na 2 SiO 3 · 9H 2 O+150 mmol / L NaCl ) . After 10 days of treatment , root morphology and activity , leaf water con- tent and water potential , photosynthetic parameters , chlorophyll content , chlorophyll fluorescence param- eters , and expression of aquaporin genes were determined. [ Results ] Salt stress inhibited the growth of C . pepo L. seedling roots , and decreased root activity , leaf water content , and leaf water potential and tran- spiration. Salt stress also affected the photosynthetic system , net photosynthetic rate , stomatal conduct- ance , chlorophyll content , and PSⅡ photochemical efficiency. Exogenous silicon improved the root mor- phology and activity of C . pepo L. seedlings under salt stress , also improved plant water status , and leaf water content , leaf water potential , and transpiration by promoting the expression of genes PIP1 ; 2 , PIP1 ; 3 , PIP1 ; 5 , PIP1 ; 7 , PIP2 ; 1 , PIP2 ; 4 , PIP2 ; 6 , and PIP2 ; 8 , PIP2 ; 9 and PIP2 ; 12 . The exogenous silicon also increased the stomatal conductance , chlorophyll content , net photosynthetic rate , PSⅡ maximum photochemical efficiency , PSⅡ actual photochemical efficiency , and photochemical quenching coefficient , decreased intercellular carbon dioxide concentration and non-photochemical quench- ing coefficient , enhanced the photosynthesis of seedlings under salt stress. [ Conclusion ] 0.3 mmol / L sili- con could improve the water metabolism and photosynthesis of C . pepo L. seedlings under salt stress , and thus enhance the ability of C . pepo L. seedlings to resist salt stress.

Virtual power plants （VPPs） represent a tangible implementation in the construction of modern power systems. Addressing the current challenges of limited applicable technical standards and a lag in the development of a standardized system for VPPs， this paper， based on the collection and organization of relevant standards， conducts a comprehensive analysis of the standardization status across various facets of VPPs， including basic general standards， planning and construction， operation and maintenance， supporting technologies， and energy efficiency assessments. Adopting both top-down and bottom-up approaches of system engineering and guided by the principles of directive， coordinating， systematic， and open VPP standard system construction， a system architecture has been designed. The architecture encompasses 15 subcategories and 52 standard series. Furthermore， based on a future demand analysis， key layout recommendations have been proposed to provide reference for the establishment and revision of VPP standards.

Objective To investigate the nutritional status of patients undergoing concurrent chemoradiotherapy for malignant tumor and its influencing factors. Methods A self-designed questionnaire was used to collect related clinical data of the patients who underwent concurrent chemoradiotherapy for malignant tumor in Beijing Cancer Hospital from March to May, 2019. Patient-generated Subjective Global Assessment (PG-SGA) was used to investigate the nutritional status of these patients and related influencing factors. Results A total of 150 usable questionnaires were collected. The median PG-SGA score was 6.0 (3.0,11.0) for all 150 patients. Among these 150 patients, 56 (37.3%) had severe malnutrition and 49 (32.7%) had moderate malnutrition. The univariate analysis showed that old age, esophageal cancer or head and neck cancer, stage Ⅳ tumor, more than 15 sessions of radiotherapy, more than 4 sessions of chemotherapy, and paclitaxel+platinum regimen or platinum monotherapy were influencing factors for malnutrition in these patients (Z=-3.839--2.087,P

Abstract Using data from the World Values Survey (1990–2012), this article attempts to describe and analyze the changing trends in public values during social transformations in China. It is found that public attitudes toward authority tend to be increasingly favorable over time, values in the private sphere tend to be more open, while postmaterialist values show a trend of first rising and then falling. The most salient feature of the cohort effect is that the generations born after the reform and opening-up in 1978 identify more closely with the value of respect for authority, while their recognition of postmaterialist values tends to decline. The change in values is related to China's modernization process, global cultural diffusion, and important historical events and is also deeply influenced by the two-way interaction between tradition and modernity.

BackgroundU3Si2 is regarded as one of the most promising accident-tolerant nuclear fuels for light water reactors and is expected to replace the UO2 nuclear fuel in the future. Currently, spark plasma sintering (SPS) is an advanced technique for preparing U3Si2 pellets; however, the influence of SPS parameters on the performance of the pellets is unclear.PurposeThis study aims to investigate the effects of different sintering parameters (temperature and pressure) on the mechanical and thermal properties of the U3Si2 pellets prepared using SPS technology.MethodsThe thermal diffusivity of U3Si2 pellets was measured using a laser flash apparatus, and the thermal conductivity of the pellets was calculated. The mechanical properties of the pellets, including hardness, Young's modulus, and fracture toughness, were measured using nanoindenter. Thereafter, the influence of different sintering temperatures in the range of 1 000~1 300 ℃ and pressures in the range of 30~90 MPa on the mechanical and thermal properties of U3Si2 pellets were carefully examined.ResultsThe measurement results show that the thermal conductivity of the as-synthesized pellets increases linearly with temperature in the range 27~700 ℃. Moreover, increasing the sintering temperature and pressure improves the thermal conductivity of the U3Si2 pellets. The hardness and Young's modulus of the pellets increase with an increase in sintering temperature. They also exhibit a trend of first increasing and then stabilizing with increasing pressure, and tend to fully stabilize at 60 MPa. Moreover, the fracture toughness of the pellets decreases with the increase of sintering temperature and increases with increasing pressure.ConclusionsBased on the above results, optimized SPS parameters for the U3Si2 pellets are proposed, and this study provides a reference for the preparation of high-performance U3Si2 pellets.

Carbendazim and acetamidine are pesticides that widely used to control pests and diseases in oilseed rape. In this paper, a rapid, accurate and reliable method was proposed for the detection of carbendazim and acetamidine with SERS microfluidic chip technology. Ag-ps(Polystyrene microspheres) microsphere SERS substrate was prepared by spin coating and magnetron sputtering deposition of Ag. The enhancement factor of prepared SERS substrate was 2.4 × 1010. The SERS detection working curves were well fitted and the linear parameters R2 were 0.987 and 0.994, respectively. The limit of detection was 0.01 mg/mL. The use of SERS microfluidic chip to detect carbendazim and acetamidine is expected to provide a way for the detection of pesticide residues in crops, which has broad application prospects in the field of food safety.

OTULIN deficiency is a complex disease characterized by a wide range of clinical manifestations, including skin rash, joint welling, lipodystrophy to pulmonary abscess, and sepsis shock. This disease is mechanistically linked to mutations in the OTULIN gene, resulting in an immune disorder that compromises the body’s ability to effectively combat pathogens and foreign stimuli. The OTULIN gene is responsible for encoding a deubiquitinating enzyme crucial for hydrolyzing Met1-poly Ub chains, and its dysfunction leads to dysregulated immune responses. Patients with OTULIN deficiency often exhibit an increase in monocytes, including neutrophils and macrophages, along with inflammatory clinical features. The onset of symptoms typically occurs at an early age. However, individuals with OTULIN haploinsufficiency are particularly susceptible to life-threatening staphylococcal infections. Currently, the most effective treatment for patients with OTULIN biallelic mutations involves the use of TNF-blocking agents, which target the dysregulated immune response. In conclusion, OTULIN deficiency presents a complex clinical picture with diverse manifestations, attributed to mutations in the OTULIN gene. Understanding the underlying mechanisms is crucial for developing targeted therapeutic interventions to address this challenging condition. Further research into the pathophysiology of OTULIN deficiency is essential for improving clinical management and outcomes for affected individuals.

Abstract Background Although Traditional Chinese Medicine (TCM) has been used for treating asthma for centuries, the understanding of its mechanism of action is still limited. Thus, the purpose of this study was to explore the possible therapeutic effects, and underlying mechanism of baicalein in the treatment of asthma. Methods Freely availabled atabases (e.g. OMIM, TTD, Genecards, BATMAN-TCM, STITCH 5.0, SEA, SwissTargetPrediction) and software (e.g. Ligplot 2.2.5 and PyMoL) were used for disease drug target prediction and molecular docking by network pharmacology. The efficacy and mechanism of action of baicalein in the treatment of asthma were validated using an ovalbumin (OVA)-induced asthma mouse model and molecular biology techniques. Results A total of 1655 asthma-related genes and 161 baicalein-related targets were identified from public databases. Utilizing common databases and software for network pharmacology and molecular docking analysis, seven potential target proteins for the therapeutic effects of baicalein on asthma were selected, including v-akt murine thymoma viral oncogene homolog 1 (AKT1), vascular endothelial growth factor A (VEGFA), epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase Src (SRC), mitogen-activated protein kinase 3 (MAPK3), matrix metallopeptidase 9 (MMP9), and MAPK1. In vivo, baicalein treatment via intraperitoneal injection at a dose of 50 mg/kg significantly reduced airway inflammation, collagen deposition, smooth muscle thickness, lung interleukin (IL)-4 and IL-13 levels, peripheral blood immunoglobulin (Ig)E levels, as well as the count and ratio of eosinophils in bronchoalveolar lavage fluid (BALF) in an OVA-induced asthma mouse model. Further validation by reverse transcription quantitative polymerase chain reaction (RT-qPCR) and western blotting analysis revealed that the VEGF and EGFR signaling pathways involving VEGFA, MAPK1, MAPK3, and EGFR were inhibited by baicalein in the asthma mouse model. Conclusion Baicalein attenuates airway inflammation and airway remodeling through inhibition of VEGF and EGFR signaling pathways in an OVA-induced asthma mouse model. This will provide a new basis for the development of baicalein as a treatment for asthma and highlights the potential of network pharmacology and molecular docking in drug discovery and development.

The RGB image of coal foreign objects lacks target space and edge information, the color and texture between the object to be detected and the background are similar, the contrast is low, and there are overlapping and occlusion phenomena among the objects to be detected, resulting in insufficient feature extraction of coal foreign objects, and the existing foreign object detection methods are difficult to achieve ideal results. In order to solve the above problems, a coal foreign object detection method based on cross modal attention fusion is proposed. By introducing Depth images to construct a dual feature pyramid network (DFPN) for RGB images and Depth images, a shallow feature extraction strategy is adopted to extract low-level features of Depth images. Basic features such as deep edges and deep textures are used to assist deep features of RGB images, effectively obtaining complementary information between the two features. It thereby enriches the spatial and edge information of foreign object features and improves detection precision. A cross modal attention fusion module (CAFM) based on coordinate attention and improved spatial attention is constructed to synergistically optimize and fuse RGB features and Depth features. It enhances the network's attention to the visible parts of occluded foreign objects in the feature map, and improves the precision of occluded foreign object detection. Finally, regional convolutional neural network (R-CNN) is used to output the classification, regression, and segmentation results of coal foreign objects. The experimental results show that in terms of detection precision, the average segmentation precision AP of the proposed method is 3.9% higher than the better Mask transformer in the two-stage model. In terms of detection efficiency, the proposed method has a single frame detection time of 110.5 ms, which can meet the real-time requirements of foreign object detection. The coal foreign object detection method based on cross modal attention fusion can assist color, shape, and texture features with spatial features. It accurately recognizes the differences between coal foreign objects and between coal foreign objects and conveyor belts, effectively improves the detection precision of complex feature foreign objects. It reduces false alarms and missed detections, and achieves precise detection and pixel level segmentation of coal foreign objects under complex features.

Abstract Early metastasis is the primary factor in the very poor prognosis of pancreatic ductal adenocarcinoma (PDAC), with liver metastasis being the most common form of distant metastasis in PDAC. To investigate the mechanism of PDAC liver metastasis, we found that PDAC cells can promote the formation of pre-metastatic niches (PMNs) through exosomes to facilitate liver metastasis in the early stage. In our study, hepatic stellate cells (HSCs) were treated with PDAC-derived exosomes (PDAC-exo), and the activation of HSCs was detected. A novel transfer RNA-derived fragment, the tRF-GluCTC-0005 was obtained by small RNA sequencing from serum exosomes of PDAC patients. Bioinformatics analysis and RNA pull-down assays revealed the interaction between WDR1 and tRF-GluCTC-0005. A KPC transgenic mouse model and an AAV-mediated sh-WDR1 mouse model were used to detect the mechanism of liver metastasis in vivo. Finally, the dual luciferase reporter assay, protein mutation truncation assay, Co-IP assay, and flow cytometry assay were used to explore the molecular mechanism in HSCs activation and PMNs formation. We found that the tRF-GluCTC-0005 in exosomes binds to the 3’ untranslated region of the mRNA of the WDRl in HSCs and increases mRNA stability. The N-terminals of WDR1 bind to the YAP protein directly, inhibit YAP phosphorylation, and promote the expression of YAP transcription factors. The tRF-GluCTC-0005 in PDAC-exo significantly recruits myeloid-derived suppressor cells (MDSCs) in the liver, creating a PMNs immunosuppressive microenvironment and further advancing liver metastasis from PDAC. Our results suggest that the key of PDAC liver metastasis is the activation of HSCs through upregulation of WDR1 by tRF-GluCTC-0005 in exosomes, which mediates the infiltration of MDSCs to form PMNs.

BackgroundThe conversion of UF6, which is a primary nuclear product, to UF4 in fluoride molten salt phase is expected to be used in the preparation or reconstitution of nuclear fuel salt for molten salt reactors, thus simplifying the process of molten salt reactor fuel production. Determination of the concentration of the key intermediate UF3 plays an important role in obtaining the reaction parameters.PurposeThis study aims to establish a method for measuring UF3 concentration in solid fluoride molten salts.MethodsThe X-ray diffraction (XRD) was employed to test the homemade standards and obtain the internal standard curve of UF3. Firstly, the α-Al2O3 was taken as the internal standard to obtain the XRD peak height internal standard curve (R=0.986) and peak area internal standard curve of LiF-BeF2-UF3 molten salt. Then, these two internal standard curves were applied to measuring the known content of LiUF5 and UF3 solid mixed samples to compare their accuracies. Finally, measurements were conducted on rapidly cooled LiF-BeF2-UF3 solid molten salt samples and naturally cooled LiF-BeF2-UF3-LiUF5 solid molten salt samples to evaluate the stability and accuracy of the curve, and the relative error was obtained.ResultsIn the UF3 concentration range of 1.00~10.00 wt%, the correlation coefficient of the internal standard curve based on the peak area determined for of LiF-BeF2-UF3 molten salt is 0.995. Measuring results of solid mixed samples of LiUF5 and UF3 with known concentrations indicate that the peak area internal standard curve achieves better accuracy with a relative measurement error of no more than 8.7%. In addition, the results of the same content samples with different cooling methods confirm the good stability and accuracy of the proposed method with less than 5.4% relative standard deviation.ConclusionsThe established method can be used for the quantitative analysis of solid LiF-BeF2-UF3 and LiF-BeF2-UF3-LiUF5 molten salts with good measurement accuracy and repeatability.

Sepsis is a common and deadly syndrome that despite all the progress in its control, the death rate caused by it is high. Sepsis is a serious problem that needs immediate attention and treatment. This infection, especially if it is caused by bacteria resistant to several drugs, causes high mortality. About two-thirds of sepsis cases occur in hospitalized patients. Several factors such as increasing the age of the population, increasing the duration of chronic diseases, high consumption of antibiotics and corticosteroids, use of mechanical devices and intravascular devices play a role in increasing its incidence. We herein demonstrate the biogenic procedure for the in situ immobilizing gold nanoparticles over lignin (Lig)-modified Fe3O4 magnetic nanoparticles mediated by Cydonia leaf extract (Fe3O4@Lig-Ag NPs) and its catalytic activity on the acetylation of alcohols using acetic anhydride and subsequent biological performances. The successful synthesis of Fe3O4@Lig-Ag NPs was assessed using an array of advanced techniques like field emission scanning electron microscopy, fourier transformed infrared spectroscopy, transmission electron microscopy EDX, elemental mapping, vibrating-sample magnetometer, and X-ray diffraction. Cecal ligation and puncture was used for inducing the sepsis model in rats. Several doses of Fe3O4@Lig-Ag NPs (45, 15, and 5 µg/kg) on oxidant–antioxidant, inflammatory mediators mRNA such as IL-1 and TNF-α, and its effects on the levels of expression were assessed in the kidney, liver, duodenum, lung, and stomach. When septic rats kidney, liver, duodenum, lung, and stomach were compared with those of the control group, it was found that Fe3O4@Lig-Ag NPs dose-dependent administration raised glutathione levels and superoxide dismutase activity and significantly reduced the levels of malondialdehyde. The Fe3O4@Lig-Ag NPs (45 µg/kg) indicated greater anti-oxidative effects than the 5 and 15 µg/kg doses for all the assessed parameters. In addition, the expression of TNF-α mRNA in the CLP + 45 µg/kg group was decreased in comparison with the control group. Fe3O4@Lig-Ag NPs reduced oxidative stress by enhancing the free radicals scavenging effects and supporting endogenous antioxidants. The Fe3O4@Lig-Ag NPs potent antioxidant property may be related to the cytokine cascade suppression during sepsis. The above findings offer that Fe3O4@Lig-Ag NPs administration may indicate a modern treatment for the inhibition of liver, kidney, lung, duodenum, and stomach tissues damage caused by septic conditions.

Magnesium alloy as the most potential light structural material, has the advantages of high specific strength, specific stiffness and easy recycling, which contributes to the realization of lightweight in the industrial field. Compared with the traditional manufacturing technologies, the new and advanced manufacturing technology of additive manufacturing represent for high manufacturing efficiency, excellent performance, and forming complex structures. The technology of additive manufacturing for magnesium alloy, which has broad application prospects in the industrial field, is urgently required to be studied. In this paper, the recent studies of the three major additive manufacturing technologies for magnesium alloy: selective laser melting, wire+arc additive manufacturing, and friction stir additive manufacturing were summarized and analyzed from the aspects of forming characteristic, defect control, and features of microstructure and property.Finally, the developments in shape and performance control of the additive manufacturing technology for magnesium alloy: simulation analysis, process control, and heat source regulation were discussed.

Introduction: More than two billion tons of oil reserves have been discovered in the fractured-cavity type carbonate reservoirs in Tarim Basin, which is a key field for increasing reserves and production in the future. This type of oil reservoirs is characterized by extremely high heterogeneity, and waterflood huff-puff oil displacement is generally used for secondary development of the oil reservoirs. The conventional methods are dominated by qualitative evaluation, which are insufficient to predict the oil production increase by waterflood huff-puff in various karst zones.Methods: The new method developed in this study involves four aspects, i.e., establishing a standard well database, optimally selecting the key development indicators, equivalent classification of reservoir space type, and optimally selecting the classification and evaluation methods for oil production increase by waterflood huff-puff. From the perspective of reservoir space type, the result of waterflood huff-puff oil displacement of multi-cave type reservoir (large scale) is better than that of relatively isolated cave type reservoir, followed by the fractured-vuggy type reservoir.Results and discussion: The new method shows advantages in the following aspects: 1) The differences in reservoir geological genesis and spatial structure characteristics in various karst zones are involved; 2) The difference in internal filling features of the same type of reservoir is integrally determined based on the changes in production performance; 3) The actual development characteristics of waterflood huff-puff oil displacement wells in various karst zones are systematically analyzed, and the criteria for selecting standard wells is formulated; 4) The violin plot is introduced as the main study tool for predicting and discriminating oil production increase by waterflood huff-puff displacement. Therefore, the new method is more capable of predicting the oil production increase by waterflood huff-puff in various karst zones.

Aiming at the small imaging, complex background and crowded distribution of remote sensing image targets, a remote sensing image target detection algorithm (HQ-S2ANet) based on perceptual extension and anchor frame optimal matching is proposed by using the rotating target detection method S2ANet as a baseline network. Firstly, a cooperative attention(SEA) module is built to capture the relationship among the feature pixels when extending the model perception area to realize the relationship modeling between the target and the global. Secondly, the feature pyramid (FPN) feature fusion process is improved to form a perceptual extension feature pyramid module (HQFPN), which guarantees the low-level detail position information in the down sampling process when extending the perception area to enhance the model information capturing capability. Finally, a high-quality anchor frame is used to detect the target by using the high quality anchor frame as the baseline network. The high-quality anchor frame matching method (MaxIoUAssigner_HQ) is used to control the anchor frame truth value assignment by using a constant factor to ensure the recall rate while preventing the generation of low-quality anchor frame matching. The experimental results show that, under the DOTA dataset, the average accuracy(mAP) of HQ-S2ANet is improved by 3.1%, the parameters number increased by only 2.61M and the average recall(recall) is improved by 1.6% compared with the S2ANet algorithm, and the present algorithm effectively enhances the detection capability of the remote sensing image target.

Carotid free⁃floating thrombus (CFFT) is significantly associated with ischemic stroke. Thrombosis occludes the artery or falls off, leading to massive cerebral infarction or multiple embolism. In severe cases, cerebral hernia or even death may occur. The diagnosis of CFFT is gradually based on CT angiography (CTA). Early identification can help in etiological treatment. This article reviews the progress of the diagnosis and treatment of CFFT, in order to improve chinical diagnosis and treatment.

Wind power generation has uncertainty due to the high fluctuation of wind speed. In traditional wind power prediction models, the uncertainty is measured by normal distribution with zero mean and constant variance. However, the variance may vary with time, which means the variance has heteroscedasticity. To improve the prediction accuracy, this paper proposes a new integrated probabilistic wind power prediction model for wind farm considering heteroscedasticity based on online least absolute shrinkage and selection operator and vector autoregression (LASSO VAR) and the exponential generalized autoregressive conditional heteroskedasticity (EGARCH) model. First, online LASSO VAR is used to forecast power output. Then, heteroscedasticity of residuals is validated by autoregressive conditional heteroskedasticity test. Considering heteroscedasticity, the news impact curve and dynamic significance line verify that positive and negative residuals affect future volatility asymmetrically. Thus, the EGARCH model is used to forecast the residuals to obtain the conditional variance of point prediction results. Finally, the probabilistic result of total power output is obtained by summing the power output of turbines in the wind farm considering the correlation of the active wind power of wind turbines. This method is applied to forecast the power output of a wind farm in East China and is proved effective in improving the prediction accuracy.

Abstract Background Blood–brain barrier (BBB) is a crucial but dynamic structure that functions as a gatekeeper for the central nervous system (CNS). Managing sufficient substances across the BBB is a major challenge, especially in the development of therapeutics for CNS disorders. Methods To achieve an efficient, fast and safe strategy for BBB opening, an acoustofluidic transwell (AFT) was developed for reversible disruption of the BBB. The proposed AFT was consisted of a transwell insert where the BBB model was established, and a surface acoustic wave (SAW) transducer realized using open-source electronics based on printed circuit board techniques. Results In the AFT device, the SAW produced acousto-mechanical stimulations to the BBB model resulting in decreased transendothelial electrical resistance in a dose dependent manner, indicating the disruption of the BBB. Moreover, SAW stimulation enhanced transendothelial permeability to sodium fluorescein and FITC-dextran with various molecular weight in the AFT device. Further study indicated BBB opening was mainly attributed to the apparent stretching of intercellular spaces. An in vivo study using a zebrafish model demonstrated SAW exposure promoted penetration of sodium fluorescein to the CNS. Conclusions In summary, AFT effectively disrupts the BBB under the SAW stimulation, which is promising as a new drug delivery methodology for neurodegenerative diseases. Graphical Abstract

Objective To improve the early management of penile amputation injury by analyzing and summarizing our microreplantation experience of 4 cases of complete penile amputation. Methods Clinical data of 4 patients with complete penile amputation admitted to our hospital from March 2018 to October 2022 were collected, and their related clinical features, microsurgical procedures, post-operative treatment and follow-up outcomes were retrospectively analyzed. Results Meticulous anatomical microreplantation was successfully performed on all the 4 patients. Two of them received successfully bilateral penile dorsal arteries anastomosis, and the other two got only one dorsal artery anastomosis. All patients completed anastomosis of deep dorsal penile vein, and 3 of them had superficial dorsal vein anastomosis. Anastomosis of 4~6 dorsal nerves on both sides of the back of the penis were completed in all the patients. The operation time ranged from 6.5 to 7.5 h, with an average of 6.9 h. The warm ischemia period was 1~4 h, averagely 1.9 h. During the follow-up, 3 cases obtained successful penis replantation, although 2 of them had partial necrosis of foreskin, which healed naturally after 2~3 months. These 3 patients had normal urinations after operation, and had an erectile hardness score of 3~4 in 3~6 months after operation, with satisfactory self-reported recoveries. Conclusion For the patients with short warm ischemia period after complete penile amputation, microreplantation should be carried out as soon as possible in order to obtain satisfactory appearance and functional recovery of the penis.

In vivo magnetic resonance vessel size imaging at 7 T high field was used to explore the changes in cerebral vascular plasticity after spinal cord hemisection injury in rats. Region of interest (ROI) analysis showed that four weeks after injury, mean vessel diameter (mVD), microvascular density (Density) and vessel size index (VSI) values were significantly increased in the contralateral side compared with the ipsilateral pyramid of the injury site, suggesting angiogenesis or vascular activation in the white matter region of the contralateral corticospinal tract (CST). Immunofluorescence results showed that the intensity of staining for platelet endothelial cell adhesion molecule 1 (CD31) and glial fibrillary acidic protein (GFAP) also increased significantly in the contralateral pyramid four weeks after injury. These results suggested that magnetic resonance vessel size imaging could provide valuable information on neovascularization in brain after spinal cord injury and may be a novel tool to diagnose brain vascular pathologies in spinal cord injury patients.

Driven by the current teaching management situation, teaching administrators at all levels generally hope to build a more complete teaching data operation center and data analysis system by using advanced information technology to provide teaching management personnel with a more comprehensive historical data analysis function. In the graph and improvement of the educating administration facts evaluation machine in this paper, the information warehouse and facts mining science used in the gadget are deeply studied. First of all, the troubles in the current instructing administration machine are analyzed in a centered manner, the technical framework of the entire teaching management data analysis system is designed and planned, and the various components of the framework are described and described in detail according to actual needs. Then, after the comparative evaluation of the facts warehouse and records mining strategies extensively used in more than a few fields in the present fields, the more than a few classical algorithms that can be utilized to the educating administration information evaluation device is improved, and the algorithms and algorithms are used to analyze the course grades and employment of the graduated alumni respectively, and the decision tree model is established, and finally the algorithm efficiency comparison chart is concluded that the improved C4.5 algorithm is better than the other three algorithms in terms of accuracy and time efficiency, and shows good classification performance.

Tobacco companies a fast-moving consumer goods wholesale enterprises in the storage, procurement, logistics, and distribution of all aspects of the close relationship with warehouse management. This paper takes RFID technology as the theoretical basis and explains the introduction. It finds that FRID is composed of a reader, electronic tag, antenna, and local server as its main components. Then, it proposes to apply RFID technology to manufacturing enterprises and describes the application mode of the relevant manufacturing enterprise system based on RFID. At the same time, based on RFID algorithms and technology, the system of the tobacco enterprise was tested and analyzed, completing the function test and performance test. In the performance test, RFID and PLC technology and industrial Ethernet automatic control system to do the data comparison found that RFID in the system with the increase of the user command response time is still very flexible, to do in more than 18000/s. Subsequently, with the support of RFID, the application in tobacco production was experimentally analyzed to verify the practicality of RFID manufacturing technology in the tobacco production process.

With the development of the times, traditional innovation and entrepreneurship education exist in the backwardness of education concept and learning concept. This paper proposes a model for entrepreneurship innovation that incorporates multi-source data fusion technology. From both online and offline sources, we obtain multi-source data about the education and teaching methods of the entrepreneurship innovation education concept in higher vocational colleges and universities. In the process of multi-source data fusion, data is preprocessed to improve its quality and efficiency during data fusion. Using the least squares method to complete the multi-source data fusion operation, combined with the concept of entrepreneurship innovation education, co-designed a data fusion-driven innovative entrepreneurship education teaching model that integrates interactive and targeted teaching methods. The model underwent validation and analysis. The data show that after some time of adopting the targeted teaching method to teach students innovative and entrepreneurial concepts, the difference between the mean value of the level of creative and entrepreneurial concepts of the students in the experimental group mean value (43.79) and the control group mean value (43.79) is 4.55. The sig value is 0.019

This study investigates the role of non-electrical protective devices in forecasting hazards for large 300Mvar class phase shifter units, which face overvoltage and overcurrent stresses under severe faults, distorting their internal magnetic fields. Utilizing migration learning, the research extracts target and auxiliary data to train autoencoders with sparse constraints. A deep learning-based DSAE-BP online recognition network is constructed using a backpropagation neural network. This network predicts potential safety hazards in large-scale phase-regulating units by analyzing data signals from connected sensors. Experimental results show delay time errors of less than 20ms and ripple rates between 1.40%-1.65% across varied current and voltage conditions, demonstrating the device’s accuracy and stability in fault prediction.

In innovative sports, integrating new-generation technologies is revolutionizing how we approach and analyze athletic performance. Our research focuses on developing a sophisticated middle and long-distance running system that harnesses the power of modern communication tech, including LoRa connectivity and 5G edge computing. By applying the IMF method, we effectively minimize data noise, enhancing the fidelity of sports signal analysis. Our system’s prowess is evident in its low latency (2.97 ms at 100 nodes), high accuracy (rating of 6.8), and impeccable anti-collision capabilities during competitive events. In practical tests over 1000 meters, it dramatically reduced timing errors to a mere fraction of manual methods, demonstrating its precision and potential to transform physical training and education. This innovation stands as a beacon for the future of sports, driving the integration of technology and athletics.

As the growth of automated detection technology, traditional manual detection has gradually been replaced. To improve the effectiveness of defect detection, a HPLC/dual mode portable sorting device with deep learning and image processing is raised for apparent defect detection. The product image is segmented using flood filled mean shift method, and defect detection is achieved using Yolo v3 algorithm. An LME2918 chip is the main component of the communication module in the portable device. Based on experimental data, image segmentation accuracy can range from 80% to 100%, and image matching accuracy can range from 85% to 95%. Under the power line carrier mode, the average success rate of apparent defect detection in portable sorting devices can reach 85%, and the change in success rate is not significant, indicating that the detection is relatively stable; Under wireless communication mode, the average success rate can reach 83%, and the change in success rate is relatively obvious, because wireless communication is easily affected by the external environment. The experimental data shows that the defect detection effect of the HPLC/dual mode portable sorting device based on deep learning and image processing meets the design requirements.

Exploring effective logistics machinery and equipment fault diagnosis and prediction technology to achieve efficient and stable operation of logistics machinery and equipment. In this paper, starting from the logistics machinery and equipment fault diagnosis technology, we optimize the hyperparameters of the recurrent gate unit neural network by using the improved second-order oscillatory particle swarm algorithm and then construct the IPSO-GRU logistics machinery and equipment fault prediction model. The IPSO-GRU model is used to test the prediction effect of the hydraulic lift table and logistics hoist by using the historical data of the hydraulic lift table as training data. The prediction accuracy of the IPSO-GRU model was improved by 6% compared with BP neural network. From the prediction results of the logistic hoist, only 6 out of 250 data samples failed to achieve accurate prediction. This shows that the IPSO-GRU model can effectively achieve the prediction of logistics machinery and equipment fault diagnosis and also provides a proven method for predictive maintenance of logistics equipment.

This paper selects the evaluation indexes that fit with the teaching mode and evaluation objectives of university innovation and entrepreneurship education in the new media environment. The limitations of the existing evaluation indexes are analyzed and combined with the characteristics of students’ physical and mental development and cognitive level; the indexes are screened and integrated, and a new evaluation system is constructed. Based on the improved particle swarm algorithm, the BP neural network is optimized to establish the evaluation model of students’ innovation ability and improve the defects of the particle swarm algorithm, covering the selection of the network topology, the number of neurons in each layer, the setting of the parameters of the improved particle swarm algorithm, and the dynamic adjustment of the weights and thresholds, so as to build the evaluation model. Analyzing the influencing factors of college innovation and entrepreneurship education in terms of college factors and individual factors, 45.7% of students want college innovation and entrepreneurship education courses to focus on entrepreneurial opportunities or environment analysis in the teaching process, 41.4% of students feel average in terms of teaching resources, and more than 50% of college students are conservative in the direction of employment or entrepreneurship in terms of personal factors. Comprehensive analysis shows that the influencing factors, such as inflexible teaching methods, unsound curriculum systems, imperfect practice platforms, and college students’ own ideological awareness, are very significant and worth noting.

The purpose of exploring the new theoretical system of college education development is to improve college students’ quality in all aspects. This paper constructs a new theoretical system of college education development based on the new theory of college education development--”three comprehensive education” theory. The fuzzy credibility measure and credibility distribution are used to explain the fuzzy processing theory, and the uncertainty index of the fuzzy processing model is optimized based on the cross-rhombus search algorithm to improve the search speed of the fuzzy processing model. Data experimental analysis is conducted for the fuzzy ICDS multi-optimization principle. Regarding search speed, the average search speed improvement of the algorithm in this paper relative to the CD algorithm saves about 1.37 to 4.69 points per block. It improves classification accuracy by 12.02% and 7.65% compared to the best fuzzy and GFCM algorithms, respectively. This shows that using the fuzzy ICDS multi-optimization principle can help analyze the effectiveness of the “three holistic education” theory in constructing the education development system and provide a reference for planning and implementing the new education development system.

In this paper, the overall architecture design of the platform is proposed, and the data architecture and business architecture of the platform are discussed. On this basis, the logistics path planning method of digital collaboration is proposed, including the aspects of path demand splitting and distribution vehicle spatio-temporal network, and the demand splittable logistics path planning model is considered. Finally, the simulation of the workshop logistics dynamic scheduling example is designed, and the dynamic scheduling optimization results are analyzed and verified. The results show that: through optimization, its time penalty cost f1 = 801.38, the total distance traveled by the delivery trolley f2 = 1709m, and the total distance of empty load is 692.15 m, and the dispatching scheme increases the distance of empty load by 59 m . The research results of this paper can provide a reference for digital management and collaboration platform for civil aircraft manufacturing enterprises and provide a reference for research in related fields.

This paper introduces the concept of dominance degree in ecology and constructs a model of the dominant degree of inbound tourism flow gathering and dispersal in Chinese provinces and cities along the Belt, and Road advocated based on the optimization of the entropy value method. In order to further analyze the model, the obtained tourism flow gathering and dispersal dominance degrees are first integrated into a fuzzy set of tourism flow gathering and dispersal dominance degrees. The natural sequence of fuzzy numbers is obtained by screening the fuzzy set, and the fuzzy indexes are obtained after the distribution fuzzy calculation, and finally, the evaluation model of tourism flow gathering and dispersal advantage degree is constructed based on the index matrix and the combination assignment method. After analysis, it is obtained that the inbound tourism distribution of Chinese provinces and cities along the route from 2005 to 2020, the fourth tier of provinces and cities increased, the proportion by 41.02%, the number of the third tier decreased, the proportion decreased to 29.33%, and the uneven distribution of the advantage of inbound tourism distribution was strengthened.

Objective To explore whether oral sodium bicarbonate tablets combined with hydration therapy during the perioperative period of coronary angiography in patients with coronary heart disease (CHD) and mild to moderate renal insufficiency have a preventive effect on contrast induced nephropathy (CIN). Methods A total of 100 patients with CHD and mild to moderate renal insufficiency admitted to Beijing Jingmei Group General Hospital from June 2020 to December 2022 were selected. They were randomly divided into two groups, the experimental group（n=46） received hydration therapy combined with oral sodium bicarbonate tablets during the perioperative period, and the control group(n=54) received hydration therapy alone. The hydration rate in both groups was 1 mL/(kg·min). The incidence of CIN was compared between the two groups. Results Both groups of patients successfully completed the surgery, and no serious events such as emergency hemodialysis, acute myocardial infarction, or acute heart failure occurred during the perioperative period. There were no statistically significant differences in gender, age, preoperative creatinine, diabetes, or contrast agent dose between two groups (P＞0.05). In the experimental group, none of the 46 patients developed CIN, while in the control group, 8 out of 54 patients developed CIN (incidence rate of 14.8%). The difference between the two groups was statistically significant (χ2=5.531，P＜0.05). Conclusion Perioperative administration of sodium bicarbonate tablets combined with hydration therapy in CHD patients with coronary angiography has a protective effect on renal function and can reduce the occurrence of CIN.

In order to study the heat transfer characteristics of bituminous coal under the condition of variable oxygen volume fraction, the long-flame coal, medium-clay coal and gas-fat coal were used. Three kinds of coal samples were used as the research objects. The LFA457 laser thermal conductivity meter was used to measure the thermal diffusivity, specific heat capacity and thermal conductivity of the coal samples. And the coal samples were studied in three different oxygen concentrations（5%, 13%, 21%）. The coal samples were heated from room temperature to 300 ℃ under three different oxygen volume fractions, and the changes in thermal physical parameters of coal from 30 - 300 ℃ were detected. By analyzing the heat conduction characteristics under different oxygen volume fraction conditions, with the increase of oxygen volume fraction, the critical temperature of the thermal diffusivity steadily moved into the low temperature area. When the temperature rises over the critical temperature, the specific heat capacity at the same temperature decreases as oxygen volume fraction rises, whereas the change in thermal conductivity is determined by thermal diffusivity. The analysis of temperature sensitivity reveals that the effect of oxygen volume fraction on the thermal property parameters is small before the temperature reaches the critical temperature; while the effect of oxygen volume fraction starts to become larger after the temperature exceeds the critical temperature.

A three-dimensional simulation model of the electromechanical control system was built using the fuzzy control proportional–integral–derivative (PID) adjustment algorithm after an automatic electromechanical control system based on programmable logic controller (PLC) technology was optimized to achieve the practical use of electromechanical program control. First, the hardware of the electromechanical control system is discussed and designed. The findings demonstrate the viability of the mechanical and electrical integration PLC program optimization solution based on three-dimensional (3D) model. The system has a higher control and management efficiency, which is 30% greater than that of the conventional system. The mechatronic manufacturing system’s continuous operation efficiency enhancement can significantly lower the investment costs and boost the financial gains of industrial organizations. Traditional systems have a control and management efficiency of around 30%, but automatic electromechanical control systems based on PLC technology and created using 3D models have a control and management efficiency between 60 and 70%.

Abstract Background Cancer-associated fibroblasts (CAFs), an important component of the tumor microenvironment (TME), play crucial roles in tumor stemness. It has been shown in various cancer studies that stanniocalcin-1 (STC1) is secreted by CAFs, however, its function in HCC is still not clear. Methods The serum concentration and intracellular expression level of STC1 were quantified by ELISA and western blotting, respectively. The role of CAF-derived STC1 in HCC stemness was investigated by sphere formation, sorafenib resistance, colony formation, and transwell migration and invasion assays in vitro and in an orthotopic liver xenograft model in vivo. An HCC tissue microarray containing 72 samples was used to evaluate the expression of STC1 and Notch1 in HCC tissues. Coimmunoprecipitation (CoIP) and dual-luciferase reporter assays were performed to further explore the underlying mechanisms. ELISAs were used to measure the serum concentration of STC1 in HCC patients. Results We demonstrated that CAFs were the main source of STC1 in HCC and that CAF-derived STC1 promoted HCC stemness through activation of the Notch signaling pathway. In HCC patients, the expression of STC1 was positively correlated with Notch1 expression and poor prognosis. The co-IP assay showed that STC1 directly bound to Notch1 receptors to activate the Notch signaling pathway, thereby promoting the stemness of HCC cells. Our data further demonstrated that STC1 was a direct transcriptional target of CSL in HCC cells. Furthermore, ELISA revealed that the serum STC1 concentration was higher in patients with advanced liver cancer than in patients with early liver cancer. Conclusions CAF-derived STC1 promoted HCC stemness via the Notch1 signaling pathway. STC1 might serve as a potential biomarker for the prognostic assessment of HCC, and the stromal-tumor amplifying STC1-Notch1 feedforward signal could constitute an effective therapeutic target for HCC patients.

At present, there are some problems in the construction of the intelligent mine, such as the non-uniform interface protocol and the formation of new 'information island'. They lead to the difficulty of data fusion and sharing in mines and the difficulty of realizing the high-quality development of intelligent mine. It is pointed out that the key problem of mine intelligent construction lies in the lack of standardized and unified data acquisition, transmission and sharing standards. According to the core specification, application specification, and operation and maintenance specification, the technology system of intelligent mine communication interface and protocol is designed. The communication interface and protocol model of intelligent mine is proposed. The perception layer, transmission layer and application layer of the model are defined. The model of intelligent mining equipment is constructed, and the communication interface is described formally. The intelligent mine data is divided into perception data, text data and audio-visual data. The message structures of the three kinds of data are defined. According to the current mining equipment, technology application and development direction, the intelligent mine data acquisition modes are divided into equipment direct acquisition, protocol conversion acquisition, and system transfer acquisition. The application scenarios of three data acquisition modes are pointed out. The acquisition and transmission process of perception data, text data, and audio-visual data are described. The technical specification of intelligent mine communication interface and protocol covers the whole process of mine data fusion communication. It provides unified interface mode and communication protocol specification for intelligent mine data acquisition, transmission, fusion and sharing. And it realizes interconnection and intercommunication among various systems of the mine.

Abstract Raman spectroscopy can quickly achieve non-destructive, qualitative and quantitative detection, and analysis the molecular structure of substances. Herein, a facile and low-cost method for preparation of highly sensitivity SERS substrates was implemented through the displacement reaction of copper foam immersed in AgNO3 ethanol solution. Due to the 3D structure of copper film and homogenous displacement, the Ag–Cu substrate showed high performance SERS enhancement (1.25 × 107), and the lowest detection concentration for R6G reached 10–10 Mol/L. For glucose detection, mixed decanethiol (DT)/mercaptohexanol (MH) interlayer was used to enable glucose attach to the substrate surface, and the limit of detection reached to 1 uM/L. SERS substrate makes the Ag–Cu SERS substrate promising for biological applications.

Engine, internal combustion engine, steam turbine rotors and other high-temperature components were often subjected to high and low cycle composite fatigue loads during operation. A new method by the curves of strain ratio(εHCF/εLCF)-life ratio(NLCF/HCF/NLCF) to predict the life of high and low cycle composite fatigue was advanced. The analysis of experimental data of three different materials showed that this method had certain versatility. The estimated values of life were within the error tolerance range by comparing the life estimation value with the experimental results, indicating that this method can better predict the life of high and low cycle composite fatigue for high temperature equipment materials.

The application of hydraulic fracturing technology on rock fracturing for hard and complete roof, and destressing for roadways with high stresses is increasingly widespread. Based on a top coal caving working face with extra-thick coal seam and complete roof layers in the Caojiatan coal mine in Shaanxi Province, the roof rock geomechanical measurements, compressibility tests, theory of hydraulic fracture propagation, and 3D numerical simulation were carried out, and the determination approaches for fracturing rock horizon above a working face, fracturing borehole layout and parameters, and fracturing technology were put forward. The underground industrial trial and a comprehensive surface microseismic monitoring with actual time were conducted, and the spatial distribution characteristics of hydraulic fractures in roof were obtained. Meanwhile, shield resistance, periodic weighting step distance and duration distance, weighting dynamic load coefficient, and roof breaking energy were monitored and analyzed, and the hydraulic fracturing effect was synthetically evaluated. A complete set of technology for hydraulic fracturing with directional boreholes in underground coal mines were preliminarily established, which includes determination of fracturing rock horizon and parameter design, fracturing technology and equipment with directional boreholes, monitoring of hydraulic fracture spatial distribution, and comprehensive evaluation of hydraulic fracturing effect. The underground trial pointed out that: on the in-situ stress regime in the Caojiatan coal mine, that is the minimum principal stress is vertical stress, the hydraulic fractures were mainly horizontal fractures with a propagation distance of about 80 m on both sides of boreholes, the hard and complete roofs above the working face were effectively weakened, and regional roof reconstruction was achieved. The intensive ground pressure appearance of the working face was obviously reduced in the fracturing area, and production safety was ensured. Finally, the existing issues associated with hydraulic fracturing were discussed, and technical developments were envisaged.

According to the intelligent green development strategy of coal mine in our country, the research status of intelligent coal gangue sorting system at home and abroad is deeply analyzed. It is pointed out that the development of multi-arm coal gangue intelligent sorting robot suitable for underground is an important development direction to solve the problem of coal gangue sorting. The three key common technical problems of “accurate recognition, accurate tracking and reliable grasp of coal gangue, multi-target task and multi-arm collaborative sorting” which directly affect and restrict the high quality development of intelligent sorting of coal gangue in China have been condensed, and the solutions are given. For the problem that coal gangue is badly encapsulated by coal slime in underground coal mine, the method of “X-ray and visual” recognition and matching of coal gangue, the method of extracting feature of coal gangue based on point cloud data are put forward to realize fast recognition and optimal feature extraction of target gangue. An efficient FLANN dynamic target matching method based on the fusion of ORB and BEBLID features, an accurate dynamic target tracking method based on FDSST, and a synchronous tracking trajectory planning method for manipulator based on three-loop PID are proposed to realize the stable grasping of dynamic gangstone with high-speed transmission by manipulator. For the random distribution of coal gangue and difficult task allocation of multi-manipulators with obstacles, a dynamic space cooperative sorting method of multi-manipulators based on improved Hungarian algorithm was proposed, which realized efficient cooperative work of multi-manipulators in dynamic space on the premise of ensuring system revenue. The results of field industrial experiment show that the proposed method for the three key common technologies can effectively solve the problems of efficient recognition and grasping feature extraction of coal gangue, synchronous tracking and stable grasping of dynamic targets of manipulators, efficient cooperative sorting of multi-manipulators, and construct a complete multi-manipulator intelligent sorting robot system for coal gangue. It improves the reliability and efficiency of the gangue intelligent sorting system.

Aiming at the problem of poor imaging quality of coal and gangue surface features and low identification rate of coal and gangue caused by insufficient illumination conditions in the process of online coal separation,a new high-quality coal gangue image acquisition that integrates multiple factors such as light source distribution, color temperature, and light intensity is proposed. First of all, in view of the uneven illumination caused by the complexity of the illumination conditions in the actual washing process of coal gangue, the influence of different incident angles on the uniformity of illumination is studied based on the nine-point sampling method, and the best incident angle suitable for coal flow is determined. Then, in view of the problem of coal gangue image distortion caused by different color temperatures caused by different color reproducibility, indicators such as MSE, PSNR, and SSIM are used to quantitatively analyze the image distortion of multi-sample single type coal gangue, and the TOPSIS algorithm is used to study the effect of light sources with different color temperatures on coal and gangue. And the influence of the image distortion of the three different working conditions of mixed coal gangue to determine the color temperature with the best image quality. Finally, considering that online light intensity changes affect the expression of coal gangue surface feature information, based on the response curve of coal gangue surface characteristics under different illuminances, the correlation relationship between exposure time, belt speed and ambient light intensity is established to quantify the illuminance interval with greater surface discrimination.and determine the optimal light conditions. The coal gangue recognition system is established by fusion of high-quality image acquisition methods under multi-factor lighting conditions, and the SSD and Faster-RCNN target detection models are experimentally verified. The results show that this method has greatly improved the image quality of coal gangue, and the accuracy of coal gangue identification has been increased by 10.5%, providing more accurate data support for the intelligent coal gangue sorting system, and has certain application and promotion value for improving the raw coal selection rate.

In order to truly reflect actual stress level borne by equipment, improve inherent reliability of product and reduce maintenance cost of product in the later period, in view of the problem that it is difficult to select test temperature level in the existing climate environment and reliability test standards, this paper analyzes thermal fatigue mechanism of products at measured ambient temperature and proposes a method for constructing test profiles. Through data processing, fatigue damage calculation and fatigue equivalence of the measured temperature data, test profile equivalent to the measured temperature data is finally obtained. Accelerated model is used to accelerate the equivalent test profile to obtain the accelerated test profile. Accelerated test results show that the error between test and computation results is 8.9%,which verifies the effectiveness of the proposed environmental test profile construction method based on measured temperature data.

Ring chain is the most important part of the scraper conveyor, whose motion characteristics directly affect the capacity and efficiency of the conveyor. Sprocket chain ring of SGZ 1000/3*1000 scraper conveyor is selected as the research object to analyze characteristics of circular chain drive of heavy scraper conveyors. The ring chain drive system is modeled using the SolidWorks software. The kinematics and dynamics simulation of the meshing process of the sprocket and chain ring under different working conditions are carried out using the Adams software. The influence of different working conditions on the ring chain drive system of the scraper conveyor is analyzed. The results show that the deformation of the ring chain and the fluctuation of the load lead to the relative sliding of flat rings in meshing contact, which is the main cause of chain socket wear. Different rotational speeds will affect the stability of the ring chain transmission. Under normal operating conditions, when the speed is maintained at 1.8 m/s, the chain transmission is relatively stable. The results could provide a theoretical foundation in optimizing the design of ring chains of heavy scraper conveyors.