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To study the in vitro cleavage effect of a recombinant lysin from bacteriophage vB_VpP_1 on Vibrio parahaemolyticus, the gp32 gene fragment of vB_VpP_1 was identified as a lysin gene according to the results of whole-genome sequencing (WGS) and functional analysis. The amino acid sequence and structure of gp32 were analyzed by various tools such as Expasy. Primers were designed using Primer 5.0 software and cloned into the pET-28a(+) vector for prokaryotic expression. The lytic activity of the purified lysin against the host bacterium before and after being treated with ethylene diamine tetraacetic acid (EDTA) was measured. Tertiary structure analysis showed that the lysin was a spherical hydrophilic protein, which was predicted to contain two catalytic domains. This was consistent with the basic characteristics of Gram-negative phage lysins. The lysin had no transmembrane region or signal peptide. The purified bacteriophage vB_VpP_1 had a lysin activity of approximately (1 487 ± 182) U/mg, which showed a strong capacity to lyse V. parahaemolyticus with damaged cell walls but not V. parahaemolyticus with intact cell walls. The prokaryotic expression vector for bacteriophage vB_VpP_1 lysin was successfully constructed, and the expressed and purified lysin could lyse V. parahaemolyticus with damaged cell walls.

In the context of the power and carbon trading markets， addressing the flexibility requirements of power systems with a high penetration of renewable energy while minimizing investments and construction costs is crucial. This paper proposes a collaborative planning method for source-grid-load-storage， incorporating electricity-carbon coupling and flexible supply-demand balance. First， the electricity-carbon coupling relationship is established by considering electricity prices and carbon trading prices. Second， the adjustable potential of flexible load is analyzed， and a price-based demand response model is developed based on adaptive time-sharing tariffs under electricity-carbon coupling. Third， the flexibility supply capacity of various resources within the power system is assessed， leading to the formulation of a flexibility supply-demand equilibrium model. This model is further refined using a full life-cycle theory. Subsequently， a two-layer source-grid-load-storage cooperative planning model is proposed， with the upper layer aimed at minimizing the integrated cost of construction investment using the equal annual value method， while the lower layer seeks to minimize the sum of the annual operational cost of the power system and the annual carbon trading cost. Finally， the improved adaptive genetic algorithm is used to solve the model. The case study results demonstrate that the proposed method provides a valuable reference for the collaborative planning of source-grid-load-storage systems.

To ascertain the interactions between the major acids and esters in nongxiangxing Baijiu and the underlying mechanisms, the effects of different types and concentrations of acids on the aroma release of Baijiu model systems containing ethanol (52%, V/V), four acids (acetic acid, lactic acid, butyric acid, an hexanoic acid) and four esters (ethyl hexanoate, ethyl lactate, ethyl acetate, and ethyl butyrate). Electronic nose and sensory evaluation showed that the response intensity and aroma profile of Baijiu model systems varied with different concentrations of acetic acid, lactic acid, butyric acid and hexanoic acid, being most pronouncedly affected by lactic acid. Furthermore, we studied the effect of lactic acid concentration on the volatility and ultraviolet (UV) absorption of Baijiu model systems. The results showed that the volatility was reduced by adding lactic acid. UV spectra demonstrated that there was an interaction between lactic acid and other substances in Baijiu model systems. The volatilization curves of binary systems of lactic acid and esters showed that lactic acid could promote the release of ethyl acetate and ethyl lactate but inhibited the release of ethyl hexanoate and ethyl butyrate. UV spectroscopy showed that the characteristic absorption peaks of the binary system varied with increasing concentration of lactic acid. The thermodynamic parameters showed that the interactions between lactic acid and four esters were spontaneous; the primary interaction force with ethyl hexanoate was hydrophobic interaction, while the interaction forces with the other three esters were hydrogen bond and van der Waals force. This study provides a theoretical basis for the flavor regulation of nongxiangxing Baijiu.

To improve the solubility, stability and bioactivity of rice bran protein (RBP) and its hydrolysates and to enhance their utilization as biological carriers, this study prepared binary nanoparticles composed of rice bran protein hydrolysates and gum arabic (GA) by taking advantage of the interaction between proteins and polysaccharides. Trypsin hydrolysate (R-t) and alkaline protease hydrolysate (R-a) of RBP were prepared and their physicochemical and structural properties were determined. Subsequently, each hydrolysate was combined with GA to prepare binary nanoparticles, which were characterized using intermolecular interaction analysis, transmission electron microscopy (TEM), X-ray diffraction (XRD), and Fourier transform infrared (FTIR) spectroscopy. The results showed that the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging capacity of R-t and R-a were (72.82 ± 1.95)% and (66.83 ± 2.34)%, respectively, which were significantly higher than that of RBP. R-t-G nanoparticles with good stability were obtained at pH 1.4, R-t/GA ratio of 1:1 (m/m), and total polymer concentration of 4 mg/mL. R-a-G nanoparticles with good stability were obtained at pH 1.4, R-a/GA ratio of 1:2.5 (m/m), and total polymer concentration of 4 mg/mL. Electrostatic interaction played a significant role in the binding of R-t and R-a to GA, thereby stabilizing the structure of nanoparticles, and R-t-G exhibited a more stable system compared with R-a-G, with superior dispersion, thermal stability and a stronger crystal structure.

To accurately measure carbon emissions from open-pit mines in alpine ecologically fragile areas, a rigorous and comprehensive accounting method is essential. This method must account for both direct emissions from mining operations and indirect emissions from ecological disturbances. The unique challenges of high-altitude environments require a sophisticated carbon accounting approach that tracks emissions from both mining activities and their broader ecological impacts on carbon sinks and sources. This study begins by examining the carbon cycle mechanisms unique to open-pit mines in these fragile regions, characterized by high altitudes, low temperatures, and delicate ecosystems susceptible to disturbances. Leveraging life cycle theory, we define the accounting boundaries to encompass all stages of the mining life cycle, namely extraction, transportation, beneficiation, and auxiliary processes. A key aspect of this research is the meticulous examination of direct and indirect carbon emissions across various mining stages. The energy-intensive nature of mining, along with the substantial transportation requirements over challenging terrains, significantly contributes to the carbon footprint. Additionally, beneficiation processes involving the separation and refinement of raw materials are highly energy-consuming, increasing indirect emissions. By mapping these processes and analyzing their carbon emission contributions, we enhance the understanding of the carbon cycle’s impact owing to high-altitude mining. The study also elucidates the structure of carbon sources and sinks within these fragile ecosystems. We compile a detailed carbon emission source inventory for open-pit mines, providing a comprehensive reference for emission sources and natural carbon sinks, such as soil and vegetation, potentially compromised by mining activities. This inventory is instrumental in developing a more precise accounting model. We have developed a carbon emission accounting model that integrates mining production stages with changes in carbon sinks owing to mining-induced disturbances. This model specifically accounts for the increased energy consumption of mining equipment at high altitudes, leading to higher carbon emissions owing to reduced operational efficiency. The model offers a nuanced estimate of total emissions by incorporating these factors. The model was validated using a case study of an open-pit metal mine in Tibet, a region renowned for its alpine ecology and environmental fragility. Applying the model revealed total carbon emissions of 1.76295×105 t CO2 for 2023, reflecting the combined direct and indirect impacts of mining on the ecosystem. This case study demonstrates the model’s effectiveness and underscores the considerable carbon footprint of mining in alpine regions. This research provides a theoretical foundation for carbon emission accounting and management in high-altitude, ecologically sensitive mining areas. It presents a detailed and scientifically rigorous accounting method supporting sustainable mining practices. The findings and model offer practical insights for industry stakeholders and a data-driven framework for policymakers aiming to reduce the environmental footprint of mining in vulnerable ecosystems. This study paves the way for sustainable resource extraction in ecologically sensitive zones, supporting efforts to minimize the carbon footprint of mining operations in high altitudes.

In recent years, the Chinese government has proposed the “dual carbon” goal of achieving a carbon peak by 2030 and carbon neutrality by 2060. In achieving this goal, the petrochemical industry is experiencing the urgent challenge regarding its development and transformation vis energy conservation and emission reduction. Biobased aviation kerosene is a sustainable and environmentally friendly alternative for reducing carbon emissions in the aviation industry, offering a notable promise for widespread adoption. This study comprehensively reviews the process for producing aviation kerosene from biomass. Vegetable oil, oil from inedible oil crops, pyrolysis oil, lignocellulosic residues, sugar, and starch biomass can be used as raw materials for the production of bioaviation kerosene. Biobased aviation kerosene can be classified into the following types according to its production technology: oil to jet (OTJ), gas to jet (GTJ), alcohol to jet (ATJ), and sugar to jet (STJ) fuels. With the rapid development of China’s bioethanol industry and abundant production, the energy supply-diversification strategy represented by ethanol and other alternative energy sources has become a guide for energy policies in various countries. The use of bioethanol as a raw material for preparing aviation kerosene is important for the environment, economy, and sustainability. This study focuses on the process of converting bioethanol into aviation fuel. It analyzes and summarizes the reaction conditions and catalysts involved in the three main reactions: ethanol dehydration to ethylene, olefin oligomerization, and hydrogenation. Currently, the ATJ process still suffers several disadvantages, such as long process flow and low conversion efficiency. The conversion route from ethanol to jet kerosene is complex and requires three different catalysts. We must develop a catalyst that can catalyze both the dehydration reaction and oligomerization hydrogenation reaction, increase the conversion efficiency, and reduce the production cost. This study introduces the carbon–carbon coupling of ethanol and hydrodeoxidation for the production of aviation kerosene, including discussions on reaction mechanisms and catalysts for the preparation of high-carbon alcohol. The Guerbet condensation reaction of ethanol is hindered by the presence of water as a by-product. Therefore, a catalyst is proposed for carbon–carbon coupling reaction of aqueous ethanol to produce high-carbon alcohols. The catalyst, with its satisfactory water resistance, can retain its activity and selectivity for high-carbon alcohols even in the presence of water and effectively inhibit the interference of water molecules, thereby increasing the efficiency and stability of the catalytic reaction. Jet kerosene is obtained via hydrodeoxidation of high-carbon alcohols, in which noble metal- and molybdenum-based catalysts exhibit satisfactory catalytic performance. Transition metals combined with Mo2C catalysts can selectively break the C–O bonds in polyols and avoid C–C bond breakage. Research and development of efficient hydrodeoxidation catalysts can facilitate the conversion of high-carbon alcohols into hydrocarbons, providing important support for the development of alternative aviation fuels. This study highlights the current challenges facing the production of ethanol-based jet fuel, such as the high production cost and the need for new catalysts. Furthermore, it proposes future development directions, offering valuable insights for the industrialization of bioethanol-based aviation kerosene production.

The SsPmp seismic phase is a seismic phase in which the downward P-wave excited by the far-field direct S-wave is reflected on the Moho surface. It has the advantages of high signal energy, high signal-to-noise ratio, and is not easily affected by the disturbance of near surface sedimentary layers and small-scale crustal structures. Virtual deep seismic sounding method (VDSS) is a detection method developed in recent years that uses the arrival time difference between SsPmp seismic phase and direct Ss wave seismic phase to study crustal thickness (or Moho depth). This article introduces the principles, advantages, and practical applications of the VDSS method. Research has shown that the VDSS method has significant advantages in improving detection accuracy, reducing costs, and environmental impact, and has been successfully applied in different geological environments such as the craton, orogenic belts and sedimentary basins, and the Emeishan large igneous province. It has shown great potential and application value in crustal structure detection. However, the accuracy of the VDSS method is highly dependent on the quality of seismic data, especially the clarity of far-field S-waves and the range of epicenter distance, which greatly limits the appliation of this method in areas with complex geological structures. In the future, the combination of VDSS with traditional receiver function methods, seismic tomography, gravity measurements, and other geophysical methods is expected to provide more comprehensive constraints for crustal structure exploration.

[Objective] To evaluate the efficacy and practicality of autologous platelet-rich plasma (aPRP) in patients undergoing total aortic arch replacement for aortic dissection. [Methods] A retrospective analysis was performed on 483 patients diagnosed with type A aortic dissection who underwent total aortic arch replacement between January 2016 and November 2023. Patients were categorized into two groups based on whether they received aPRP. Baseline characteristics, intraoperative blood product usage and postoperative outcomes were compared between the two groups. [Results] The aPRP group exhibited reduced usage of allogeneic platelets (1.55±1.04 vs 1.60±1.27)U, allogeneic plasma (480.89±432.49 vs 746.50±508.81)mL, allogeneic RBC (red blood cell)(5.95±1.91 vs 6.17±3.52)U, bivalirudin (2.66±1.51 vs 3.31±1.59)U and coagulation factor Ⅶ (0.67±1.03 vs 1.22±1.43)mg compared to the non-aPRP group (P0.05). [Conclusion] The application of aPRP in total aortic arch replacement effectively diminishes intraoperative blood product usage and the incidence of lung injury-related complications. However, it does not demonstrate significant benefits in terms of mortality, cerebral infarction and other complications.

An energy-saving optimization operation strategy based on maintaining the high-energy-efficiency operation of chillers is proposed to address the prevalent issue of increased energy consumption in the application of cold-storage technology for economic optimization in the current air-conditioning industry. This strategy involves the storage and release of cooling using small cold-storage tanks to actively control the load ratio of the water chiller, thus ensuring that the unit operates efficiently for an extended period to achieve energy savings. A physical model of the air-conditioning system is established and simulated using operational data from the central air-conditioning system of a hospital. Performance curves of the water chiller under different environmental conditions are obtained to accurately depict the high-efficiency operational states of the unit at each moment. On a typical day with a peak cooling load of 9 979 kW, using an active chilled-water storage system, as compared with using the conventional chiller operation strategy without active storage, can reduce 2 777 kW·h of daily electricity consumption, which constitutes 6.0% of the daily electricity usage of the central air-conditioning system. Over the entire cooling season, this approach can save 2.35% of the total electricity consumption of the central air-conditioning system and 4.45% of the electricity consumption of the chiller.

The annual trading declaration of the electricity market for Kaidu River Cascade Hydropower Station depends on an accurate assessment of their power generation capacity. In order to fully tap the power generation dispatching potential of the hydropower station, rationally declare the annual power generation plan, and guarantee the economic benefits of the hydropower station, it is imperative to carry out research on the power generation dispatching potential of Kaidu River Cascade Hydropower Station. This study focused on Kaidu River Cascade Hydropower Station, aiming to minimize water shortage rates and maximize power generation. A multi-objective optimization dispatching model was created, and it was solved by using an improved NSGA-II algorithm. The model results were compared with simulated dispatching to tap the power generation of optimization dispatching. The results show that: ① Compared with simulation dispatching, optimization dispatching improves output reliability and increases power generation. Under simulation dispatching, the annual average power generation of Kaidu River Cascade Hydropower Station is 1.678 billion kW·h. Optimization dispatching obtains an additional 133 million kW·h (8% increase) in the annual average power generation; ② in different typical years, optimization dispatching has different effects on power generation dispatching potential exploitation of Kaidu River Cascade Hydropower Station, especially in extreme dry years, where the increase is 1.95 times that of normal years and 6.68 times that of extreme wet years. These results provide a decision-making basis for annual trading plan declarations of cascade hydropower stations and ensure the economic benefits of cascade hydropower stations.

ObjectiveTo compare the long-term survival outcomes of patients with T1-2N0M0 duodenal neuroendocrine tumor (DNET) after endoscopic resection (ER) or surgical resection (SR). MethodsPatients diagnosed with T1-2N0M0 DNET between January 1, 2004, and December 31, 2015, were extracted from the SEER database. Kaplan-Meier survival curve and log-rank test were used to compare overall survival (OS) rate and cancer-specific survival (CSS) rate between patients undergoing ER or SR. Propensity score matching (PSM) was used to reduce grouping differences, and multivariate Cox regression was used to analyze factors affecting OS and CSS before and after PSM. ResultsA total of 656 patients were included, with 457 in ER group and 199 in SR group. Before PSM, there was no significant difference in the 5-year OS rate between the ER and SR groups (88.9% vs 89.6%), but there was a significant difference in the 5-year CSS rate (99.3% vs 96.9%, P＝0.017). Before PSM, multivariate Cox regression analysis showed advanced age was an independent risk factor for decreased OS (P＜0.001). After PSM, there was no significant difference between the ER group (n＝187) and SR group (n＝187) in 5-year OS rate (90.2% vs 88.9%) or CSS rate (98.9% vs 96.7%). After PSM, multivariate Cox regression also showed advanced age was an independent risk factor for decreased OS, while resection method was not an independent factor for OS or CSS. ConclusionsThere is no significant difference in OS or CSS after endoscopic treatment and surgical treatments for patients with T1-2N0M0 DNET, and advanced age is an independent factor for OS.

This is an article in the field of structural geology. In this article, the strain characteristics and tectonic significance of the tile shear zone of Motianling are discussed through macro-microstructure, finite strain measurement of rocks and EBSD structural analysis of quartz. The results show that the Motianling ductile shear zone has typical macro-micro ductile deformation fabrics, including mylonite foliation, rotating porphyry system, S-C fabric, domino structures, asymmetric ocular sphere, quartz dynamic recrystallization, core-mantle structure, mica fish, feldspar mechanical twinning and asymmetric pressure shadow. The finite strain measurement and macro-micro structure shows that the Motianling ductile shear zone extends over 65 km in NNE direction, and its width is 8～12 km. The C-foliation tendency of the mylonite is 220°～356°, the dip angle is 10°～74°, and the extremely dense point occurrence is 285°∠22°. The Motianling ductile shear zone has kinematic characteristics of early sinistral thrust shear and late dextral normal slip shear. The rock strain of Motianling ductile shear zone is mainly flattening strain and tensile strain. At the same time, it shows the shear property of pure shear and simple shear. Quartz EBSD fabric analysis show that the Motianling ductile shear zone is characterized by the late middle-low temperature deformation ( 300～450 ℃ ) superimposed on the early middle-high temperature deformation ( 400～600 ℃ ). The paleo differential stress and strain rate of Motianling ductile shear zone are relatively low, ranging from 10.59～36.31 MPa and 0.63×10-13～87.18×10-13 s-1, respectively. In combination with the above studies and regional geological data, it is considered that the Motianling ductile shear zone was formed in the tectonic setting of recoil after extrusion of the Cathaysia block from SE to the Yangtze block. In the early extrusion and collision stage, the Motianling ductile shear zone has the property of mid-high temperature sinistral thrust shear. After the late orogenic extension, the Motianling ductile shear zone has the property of dextral normal slip shear at mid-low temperature. The above understanding reveals the occurrence, strain characteristics, rheology and dynamics setting of the Motianling ductile shear zone and provides new data for deepening the understand of Caledonian tectonic movement in South China.

Environmental pollution and climate change have caused freshwater scarcity and there is an urgent need for green freshwater preparation technologies. Solar-driven water evaporation, as a low-carbon, environmentally friendly, and efficient desalination technology, is a new strategy to solve the freshwater shortage problem. The key to high-performance solar evaporation technology lies in the rapid photothermal conversion, water transportation, and vapor dispersion of the evaporation materials. Inspired by the porous structure of natural biomass materials, biomass-derived carbonized corn stalk evaporators with high photothermal conversion and water supply capacity were constructed by freeze-drying and carbonization processes. The evaporation performance was studied. The results showed that the porous biomass evaporator under wetting condition could absorb up to 91.6% of sunlight, and the water evaporation rate and the photothermal conversion efficiency under the solar irradiation of 1 kW/m2 could reach 1.31 kg/(m2·h) and 89%, respectively. In addition, the enhanced effects of 3D structures with different heights on the evaporation performance were investigated. The evaporation rate and efficiency of the evaporator were elevated to 3.41 kg/(m2·h) and 90%, respectively, based on the 3D structural design, with excellent evaporation/desalination abilities.

In order to effectively solve the problems of hole collapse, clamping, sticking, waterway blockage and exhaust channel blockage caused by the combination of coal powder and water to form slime in wet drilling operation, three dispersants were optimized and compounded with inorganic salt additives by using the methods of static sedimentation experiment, contact angle experiment and surface tension test experiment of coal powder, and the optimum mass fraction of each reagent was finally determined. The results showed that the optimum ratio of the composite solution was 0.6 % FSJ-01 + 0.8 % NaCl; the wetting suspension dispersion effect of the three dispersants was ranked as FSJ-01 > FSJ-02 > FSJ-03. When the mass fraction of FSJ-01 was 0.6 %, the contact angle reached a minimum of 31.2 °, which was 61.72 % lower than that of water on the surface of pulverized coal. After adding NaCl with a mass fraction of 0.8 %, the surface tension of the composite solution reached a minimum of 26.3 mN/m, which was 64.75 % lower than that of water and 36.17 % lower than that of a single dispersant solution.

To investigate the mechanism for the effect of rice false smut on rice grain quality, this study used two high-quality japonica rice varieties, Liaogeng 433 and Liaogeng 2501, moderately susceptible to rice false smut. Through non-targeted metabolomics analysis, 271 metabolites were identified in rice grains, and the relative contents of 49 metabolites were affected by rice false smut. The relative contents of gallocatechin, 3-hydroxybenzoic acid, chlorogenic acid, sinapinic acid, spermine, α-tocopherol, nicotinamide, dodecanoic acid, and palmitic acid were significantly reduced, while the relative contents of 1-monoolein, 2-monoolein, 1-monostearin, fructose, erythritol, galactose, maltose, tagatose, shikimic acid, and α-ketoglutaric acid were significantly increased. These changes led to disorders in sugar metabolism, the tricarboxylic acid cycle, fatty acid synthesis and secondary metabolism in rice, thereby increasing the chalkiness or chalky gain percentage of rice and reducing the head rice percentage, antioxidant capacity and nutritional quality.

Background Insulin resistance (IR) is associated with atrial fibrillation (AF) and atrial remodeling, and the correlation of triacylglycerol glucose (TyG) index, a novel, simple, and valuable indicator of IR, with the development of AF in patients with chronic heart failure (CHF) has been poorly studied. Objective To investigate the correlation between TyG index and AF in patients with CHF. Methods A total of 417 CHF patients hospitalized in the Department of Cardiovascular Medicine of the Second Affiliated Hospital of Zhengzhou University from January 2021 to January 2022 were retrospectively selected for the study, and the CHF patients were divided into two groups according to whether they developed AF: the AF group (138 patients) and the non-AF group (279 patients). The TyG index was categorized into four levels based on quartiles: Q1 (TyG index ≤8.20), Q2 (8.208.84). Patients' baseline data, including TyG index and basic information, laboratory test indexes, and echocardiographic data, were collected through the hospital's electronic medical record system. The LASSO regression algorithm was used for variable screening, and multivariate Logistic regression was used to analyze the correlation between TyG index and the risk of AF occurrence in patients with CHF and to construct a regression model. The predictive value of TyG index for the occurrence of AF in CHF patients was also analyzed using the subject work characteristics curve. Restricted cubic spline plots of the correlation between TyG index and the risk of developing AF in CHF patients were plotted. Results Patients in the AF group had higher BMI, New York Heart Association cardiac function class Ⅲ-Ⅳ, proportion of hypertension, serum uric acid (SUA), triacylglycerol, blood urea nitrogen (BUN), fasting blood glucose, N-terminal B-type natriuretic peptide precursor, TyG index, left atrial diameter (LAD), the proportions of β-blockers, calcium antagonists, and diuretics were higher than those in the non-AF group; total cholesterol (TC), endogenous creatinine clearance (Ccr), left ventricular ejection fraction, and the proportion of angiotensin-converting enzyme inhibitors/angiotensin Ⅱ receptor blockers (ACEI/ARB) class of drug use was lower than that of the non-AF group (P

Background With the rapid development of the society, the detection rate of dyslipidemia in children has gradually increased. At present, there are few data on the application of traditional Chinese medicine (TCM) constitution identification in sub-health of children, and there is a lack of clinical correlation data analysis. Objective To observe the trend of changes in TCM constitution and blood lipid metabolism in children, and to analyze the correlation between them, thus providing relevant basis for subsequent continuous monitoring research. Methods Sourced from the Shanghai Child and Adolescent Health Cohort (SCAHC), a total of 2 080 healthy primary school students in the second and third grade from Pudong New Area, Shanghai were selected as the research subjects. Using the＂Zhaoming System＂that was independently developed by Shanghai University of Traditional Chinese Medicine, physical information of included subjects in 2021 (first year) and 2022 (second year) was collected. Based on the TCM constitution classification of facial complexion and tongue appearance, clinical symptoms and signs and questionnaire information, children were divided into five types of constitution, including the spleen-deficiency constitution, balanced constitution, Qi-stagnation constitution, deficiency-heat constitution, and excess heat constitution (unbalanced constitution referred to all constitutions except for the balanced constitution). Blood samples were collected to detect on triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and total cholesterol (TC). To analyze and compare the incidence of blood lipid abnormalities in children of different genders, as well as the distribution characteristics and changes of TCM constitution in different ages and genders. Multivariate Logistic regression analysis was performed to explore the correlation between TCM constitution and dyslipidemia in children. Results Among the 2 080 children, 1 122 (53.9%) were males and 958 (46.1%) were females, with an average age of (8.2±0.4) years. There were 522 children with dyslipidemia (25.09%), including 272 males (52.1%) and 250 females (47.9%). In 2021, there were 815 (39.2%) cases of the balanced constitution and 1 265 (60.8%) cases of the unbalanced constitution. In 2022, 764 (36.7%) children had a balanced constitution and 1 316 (63.3%) had a unbalanced constitution. There was a statistically significant difference in the distribution of TCM constitution in children between 2021 and 2022 (χ2=106.28, P

To explore whether Dendrobium officinale, Polygonatum sibiricum, and Ziziphus jujuba can be used as active pharmaceutical ingredient (APIs), a functional snack that is easy to carry and eat was developed. In this study, the design of experiment (DOE) scheme was used to determine the optimal ratio of D. officinale, P. sibiricum, and Z. jujuba based on the measured mass fractions of polysaccharides, flavonoids, and polyphenols in the drug. A single-factor experiment was used to study the effects of excipients on the appearance, taste, hardness, and weight difference of chewable tablets, and the optimal formula was selected by combining the response surface optimization and multi-index weight methods. Results showed that the optimal compound ratio of the main ingredients of D. officinale chewable tablets (mass fraction) was D. officinale:P. sibiricum:Z. jujuba=35%:10%:5%, and the corresponding total mass fractions of polysaccharides, flavonoids, and polyphenols were 159.64±0.14, 79.44±0.35, and 78.10±0.28 mg/g, respectively. The mass fraction ratios of erythritol, mannitol, and whey protein in the excipient fractions were 13%, 13%, and 6%, respectively. The differences in appearance, taste, hardness, and weight of D. officinale chewable tablets under the optimal formula were 7.80±0.63 points, 7.80±0.42 points, 23.72±0.15 N, and 2.57%±0.13%, respectively. The comprehensive score was 21.87±0.83 points. Results of physical property evaluation and the dissolution test of D. officinale chewable tablets showed that the water content, adhesion, elasticity, and chewiness were 2.23%±0.92%, 12.75±0.54 mJ, 7.08±0.58 mm, and 0.41±0.67 mJ, respectively, and the cumulative dissolution reached 79.80%±0.75% at 60 min. Chewable tablets made from D. officinale, P. sibiricum, and Z. jujuba have a high active ingredient content, good sensory evaluation, and easy dissolution.

In order to meet the widespread application of 85Kr thickness gauge sources in the new energy lithium battery industry，an application study was conducted on the thickness gauge's use in measuring the coating areal density of lithium battery electrodes. The influence of the source window material，thickness，active area，and activity size on the beta ray output of different specifications of 85Kr thickness gauge was compared and analyzed. The quantitative calibration，temperature compensation calibration，position compensation calibration，and source activity decay compensation calibration of the 85Kr thickness gauge's beta ray absorption value in the actual production process of lithium battery electrodes were completed.The relationship curve between the areal density of the electrode and the beta ray absorption value was obtained，as well as the relationship between the surface density of the electrode and temperature，position，and source activity decay. The research results show that The 85Kr thickness gauge source with a thickness of 25 μm titanium window，a large bottom area and low height of the active zone，and a loading activity of 18.5 GBq has a large betaray output，and the repeatable measurement precision is 0.02%；The linear correlation between the attenuated absorption value of the beta ray after the transmission pole piece and the areal density is 0.999. Measuring the air temperature of the gap compensates for the effect of changes in air density on beta ray absorption. The position change of the pole piece distance detector is linearly related to the measured areal density，compensates for the measured areal density by measuring the position of electrodes. Correct I0 at least every 5 days to compensate for the deviation of the measurement system caused by the activity attenuation of the 85Kr thickness gauge source.The thickness gauge using 85Kr as the radiation source can meet the actual application needs of the super intelligent manufacturing line of lithium-ion batteries.

In non-inductive radar vital sign monitoring, frequency-modulated radars (such as Frequency Modulated Continuous Wave (FMCW) and Ultra-WideBand (UWB)) are more effective than Continuous Wave (CW) radars at distinguishing targets from clutter in terms of distance. Using range Fourier transform, the heartbeat and breathing signals can be extracted from quasi-static targets across various distance intervals, thereby improving monitoring accuracy. However, the commonly used range Fast Fourier Transform (FFT) presents certain limitations: The breathing amplitude of the subject may cross the range bin boundary, compromising signal integrity, while breathing movements can cause amplitude modulation of physiological signals, hindering waveform recovery. To address these reasons, we propose an algorithm architecture featuring range tap reconstruction and dynamic demodulation. We tested the algorithm performance in simulations and experiments for the cross range bin cases. Simulation results indicate that processing signals crossing range bins with our algorithm improves the signal-to-noise ratio by 17±5 dB. In addition, experiments recorded Doppler Heartbeat Diagram (DHD) signals from eight subjects, comparing the consistency between the DHD signals and the ballistocardiogram. The root means square error of the C-C interval in the DHD signal relative to the J-J interval in the BallistoCardioGram (BCG) signal was 21.58±13.26 ms (3.40%±2.08%).

Bioaccessibility is a prerequisite for 5-methyltetrahydrocalcium folate (5-MTHF) to perform their health functions and is susceptible to the influence of food components. Through in vitro simulated digestion, the effects of whey protein concentrate (WPC) on the bioaccessibility of 5-MTHF under various circumstances (concentration, processing technique, gastrointestinal pH, and digesting duration) were examined. The changes of particle microstructure before and after digestion were observed by colloid particle size potentiometer and laser confocal. According to the findings, 5-MTHF could be securely wrapped, shielded by WPC throughout the stomach stage of digestion, and then moved to the small intestine for full release. Additionally, during the digestive process, the bioaccessibility of WPC-5-MTHF tended to rise in all groups. In the meanwhile, several factors such as WPC concentration, WPC processing technique, gastrointestinal pH, and digestion duration had varied effects on the bioaccessibility of 5-MTHF as well as the particle size and potential of WPC-5-MTHF during the digestive process. Among them, the bioaccessibility was 0 and no 5-MTHF was found in any WPC-5-MTHF group throughout the stomach digesting stage. When compared to the 5-MTHF group, the bioaccessibility of the WPC-5-MTHF group improved by 11.1% to 19.61% during the intestinal digestion stage, exhibiting a positive connection trend with the WPC concentration. When compared to the unprocessed treatment group, the bioaccessibility of the ultrasonic, high pressure homogenization groups was reduced by 8.49%, 9.52%, and 8.75%, respectively. At an intestinal pH of 7 and a digestion time of 5 hours, the WPC-5-MTHF group displayed the best bioaccessibility, which was twice as high as that of the 5-MTHF group, at 45.17% and 42.32%, respectively. The results of particle size and zeta potential showed that the WPC-5-MTHF group had smaller particle size, larger absolute value of zeta potential, and the structural changes of WPC-5-MTHF would cause changes in digestibility characteristics. Theoretical support for the use of 5-methyltetrahydrofolate calcium in dairy products is provided by this work.

In order to develop probiotics fermented chopped chili with good flavor and certain nutrition and health effects, the traditional fermented chopped chili was collected from Hunan and utilized as raw material to screen probiotic strains that could be tolerant to gastrointestinal digestion in this study. The influence of probiotics fermentation on the physicochemical properties, safety, and sensory properties of chopped chili was investigated using physicochemical analysis, sensory evaluation, and non-targeted metabolomics techniques. Results indicated that three strains tolerant to gastrointestinal digestion were obtained, identified as Lactiplantibacillus plantarum JEB2, Lactobacillus brevis JEB7, and Saccharomyces cerevisiae JEE2, respectively. Among them, L. plantarum JEB2 and L. brevis JEB7 completely degraded 0.25 mg/mL of sodium nitrite within 24 h and S. cerevisiae JEE2 exhibited a cholesterol assimilation rate of 50.79% within 24 h. Chopped chili fermented with all the three strains exhibited a pH0.6%, and obviously lower nitrite content and coliform count compared to naturally fermented chopped chili. Notably, the sensory score of chopped chili fermented with a combination of L. plantarum JEB2 and L. brevis JEB7 reached the highest value of 19.50 (full marks of 20). Furthermore, the non-targeted metabolomics results revealed a downregulation in the expression levels of irritant substances (4-acetamido-2-amino butanoic acid and sparteine) in this chopped chili sample, whereas the expression levels of aromatic substances (4-methyl benzaldehyde, ethyl brassylate, D-sorbitol, etc.) and bioactive compounds (phytol, diosgenin, kaempferol, etc.) were upregulated. Therefore, the chopped chili fermented with a combination of L. plantarum JEB2 and L. brevis JEB7 was beneficial to reduce the irritancy, improve the product flavor, safety and health-promoting properties, which was expected to be further developed as fermentation starters for the production of fermented products.

To develop plant-based protein 3D-printed food suitable for patients with swallowing difficulties, this study explored the use of a composite polysaccharide comprising flaxseed gum and konjac glucomannan at a mass ratio of 2:3. The composite polysaccharide was combined with pea protein isolate (PPI) under shearing treatment to investigate the effects of different concentrations (0.5%, 0.7%, 0.9%, 1.1%, and 1.3%) on the particle size, rheological properties, and 3D printing performance of emulsion gels. Additionally, the emulsion gels were evaluated using the International Dysphagia Diet Standardization Initiative (IDDSI) framework. The results indicated that the composite polysaccharide exhibited varying effects on the improvement of emulsion gels depending on its concentration. Particle size analysis revealed a decreasing trend in the particle size of PPI emulsion gel with increasing polysaccharide concentration. Rheological properties showed that the addition of polysaccharides endowed the gels with viscoelastic properties, as evidenced by G' > G'' for all samples. At a concentration of 1.1%, the emulsion gel exhibited the smallest particle size, the highest G' and G'' values, and optimal viscoelasticity. Furthermore, the printed structures displayed the most distinct textures, stable frameworks, and superior printing adaptability. The IDDSI evaluation indicated that emulsion gels containing 1.1% and 1.3% polysaccharides could be classified as Level Ⅳ transitional foods. In conclusion, the composite polysaccharide at a concentration of 1.1% significantly enhanced the 3D printing performance of PPI-based emulsion gels, providing a theoretical basis for developing plant-based 3D printing inks.

This paper discussed the optimization of the corn starch saccharification process using the glucoamylase GluM3, and explored its impact on the structure of starch granules to further promote the industrial application of GluM3 in starch sugar production. The study first determined the optimal saccharification process for low transglycosylation activity glucoamylase GluM3 through single-factor experiments and response surface experiments. Structural characterization of starch granules was conducted using methods such as scanning electron microscopy, X-ray diffraction, and infrared spectroscopy. The results showed that the optimal saccharification conditions were a liquefaction DE value of 16%, temperature at 66 ℃, pH at 3.7, time at 3 h, enzyme dosage at 450 U/g with pullulanase dosage at 1.25 U/g. After optimization, the glucose content (DX value) in corn starch saccharification liquid reached 92.68%. After saccharification reaction, corn starch changed from smooth intact particles to fragmented debris state. There was a certain degree of damage to internal crystalline structure during saccharification. A decrease in short-range order degree after saccharification reaction was observed. Furthermore, various maltodextrins were produced after corn starch enzymatic hydrolysis reaction while maltodextrins were further converted into glucose by GluM3 with a proportion as high as 99.34%. This study establishes the optimal saccharification process for low transglycosylation activity GluM3 on corn starch and investigates changes in microstructure and physical properties during the saccharification process, providing theoretical basis for subsequent industrial applications of GluM3.

The aero engine is crucial for the safe flight of aircraft. Predicting its remaining useful life allows for timely maintenance, thereby preventing potential flight accidents. Deep learning’s powerful data mining capabilities provide a novel approach to predicting the remaining useful life of aero engines using vast amounts of historical data. However, traditional deep learning methods often only analyze temporal data correlations, overlooking the complex non-Euclidian spatial relationship between multiple sensor data. In addition, they seldom address the uncertainties in data or the prediction process, which impacts the reliability of their results. To solve these problems, we propose a probabilistic prediction method for aero engines that leverages Bayesian networks and the graph attention transformer. First, sensor data undergo preprocessing using a convolutional denoising autoencoder. Then, to extract the complex non-Euclidian spatial relationships between sensors, we construct a graph convolution network. In this network, sensor signal features serve as node characteristics, and the relationships between sensors are measured by cosine similarity. An attention mechanism assigns different weights to sensor nodes to improve the expressive ability of the graph convolution network. In this paper, the multi-head attention is integrated into the graph convolution network. Following the integration, node characteristics are aggregated with the assigned weights in the proposed graph attention network. Furthermore, to achieve joint extraction of the spatiotemporal relationships of sensor data, the graph attention mechanism is integrated into the transformer’s temporal-multi-attention module. This integration combines the spatial feature extraction strengths of the graph attention transformer with the temporal feature extraction abilities of the transformer model. The extracted spatiotemporal joint features are often utilized to predict the remaining useful life of the aero engine. At the same time, a Bayesian network quantifies the prediction uncertainty of the model using Gaussian mixture distribution and variational inference. Optimal approximate distribution parameters are obtained by minimizing the Kullback–Leibler divergence between the real posterior and approximate distributions. Consequently, the loss function of the proposed model network consists of two parts: minimum mean square error, which reflects the distance between the predicted remaining useful life and the actual remaining useful life, and distribution approximation error measured by Kullback–Leibler divergence. Unlike traditional point value predictions, our probabilistic prediction method yields not only an estimated remaining useful life but also a corresponding confidence interval, which provides a more reliable foundation for subsequent maintenance and decision-making. In addition, we validated the proposed method using an aero engine experimental dataset, comparing its performance against other methods through both comparative and ablation experiments. The results demonstrate the effectiveness of the proposed method and its superiority over existing methods.

【Objective】Agriculture is the main water consumer in many countries and regions, and improving agricultural water use efficiency is critical to sustainable development in these regions. A prerequisite for this is to understand the potential for water saving in the agricultural sector. This paper presents a method to evaluate agricultural water-saving potential in arid regions.【Method】The method considered the influence of desertification, soil erosion, and other environmental factors on water conservation. A total of 30 key factors, including agricultural water consumption, irrigated land area, irrigation water use efficiency, grain-to-economy ratio, and soil and water conservation rate, were considered in the evaluation. Using the Vensim PLE software, a system dynamic flow diagram model was developed to calculate agricultural water-saving potential. The model was applied to Inner Mongolia (excluding Dongsimeng City) to evaluate its agricultural water-saving potential at regional scales, in both the short term (up to 2035) and the long term (up to 2050).【Result】① Agricultural water-saving potential in Inner Mongolia was estimated to be 2.518 billion m3 in the short term (up to 2035) and 2.958 billion m3 in the long term (up to 2050). Among all areas in the province, Bayannur had the highest water-saving potential, while Wuhai had the least. ② Engineering water-saving projects contributed the most to the water-saving potential (approximately 52.83%), while technical water-saving measures contributed the least (approximately 16.91%). The contribution of engineering water-saving projects to water savings is expected to increase over time.【Conclusion】Our results demonstrate that the system dynamic model can be used to estimate agricultural water-saving potential. The results obtained using this model are reliable and provide valuable technical support for formulating agricultural water-saving policies in arid regions.

It is difficult to directly and accurately determine Hg in biological samples using inductively coupled plasma-mass spectrometry (ICP-MS) due to polyatomic interferences, such as tungsten oxide, and matrix effects. We established an ICP-MS method for the determination of Hg in biological samples based on the kinetic energy discrimination (KED) mode combined with mathematical correction and internal standard correction. In this experiment, spectral interferences of Hg in standard (STD) mode and KED mode were investigated. 202Hg was selected as the analyzed isotope in the KED mode, effectively reducing but not completely eliminating the interference. It was found that the interference amount of W with Hg was linearly related to the concentration of W (R2=0.9997). The matrix interference was eliminated with internal standard (Rh concentration of 50μg/L) and sample dilution (dilution of 100 times). The reliability of the method was tested with 9 reference materials, and the results were in agreement with certified values (or reference values). In particular, the accuracy of GBW10028 (Astragalus membranaceus), GBW10025 (spirulina) and GBW10015a (spinach) was significantly improved. The relative standard deviation (n=10) was 0.7% to 7.0%. The method is suitable for the analysis of Hg in biological samples.

This paper reviews the manufacturing difficulties of decimal quantum resistor arrays and their applications and prospects in electrical metrology standardization. By analyzing the core principles of the quantum Hall effect, the advantages and differences of gallium arsenide (GaAs) and graphene in quantum resistor arrays are discussed. This paper summarizes the key technologies for achieving decimal quantization, including the preparation of quantum Hall bars, carrier density regulation, superconducting interconnection and circuit error optimization. In addition, this paper also emphasizes the important role of quantum resistor arrays in the international metrology system, especially its contribution to the redefinition of ohms and amperes, and looks forward to the development trend of portability and intelligence of quantum resistor devices, which can not only promote the advancement of electrical measurement technology, but also provide important technical support for various high-precision measurement applications.

Aiming at the low accuracy of line selection method when the data amount of single-phase grounding fault in distribution network is small, a genetic algorithm optimized support vector machine (GA-SVM) method for single-phase grounding fault line selection in distribution network based on feature fusion is proposed, which adopts Fourier transform, the active power method and wavelet packet transform decompose the transient zero-sequence current of each line under different fault conditions, extracts four features, including fundamental wave amplitude, fifth harmonic amplitude, average active power component and wavelet energy value. The four features are fused by principal component analysis method, the principal component is extracted, and the feature database is established. 80% of the feature database is used as the training set, 20% as the test set, the samples in the feature database are trained by GA-SVM to realize fault line selection. The simulation model of distribution network with five feeders is built by MATLAB/Simulink. The results show that the proposed algorithm can realize fault line selection through small sample datawith high accuracy and strong applicability.

Objective To investigate the incidence and influencing factors of nutritional deficits during the immediate postoperative period following radical resection surgery for oral cancer and to analyze its impact on the short-term recovery of surgical patients. Methods Nutritional support data of 87 oral cancer patients early after radical resection surgery （1 to 10 d after surgery） in Guangzhou First People’s Hospital between January 2018 and March 2024 were collected. Patients were divided into the nutritional adequacy and nutritional inadequacy groups according to the average daily nutritional intake. Relevant factors were statistically compared between two groups. Logistic regression analysis was performed to identify influencing factors of nutritional deficits. The length of stay and incidence of postoperative complications， such as partial or total flap loss and surgical site infection， were also compared between two groups. Results Only 23.0% （20/87） of oral cancer patients achieved nutritional adequacy during the follow-up period. Multivariate logistic analysis revealed that nutritional inadequacy was associated with ideal body weight （OR=5.308， 95%CI： 1.103-25.551， P = 0.037） and the actual nutritional intake （OR=0.897， 95%CI： 0.809-0.994， P = 0.038）. The length of stay in the nutritional adequacy group was significantly shorter compared to that in the nutritional inadequacy group （21 d vs. 24 d， P = 0.030）. The difference in the incidence of complications between the two groups was not statistically significant（15.0% vs. 35.8%，P =0.077）. Conclusions Inadequate nutritional intake is common in oral cancer patients early after radical resection surgery. Patients with higher ideal body weight and less actual nutritional intake are prone to nutritional deficits. Adequate nutrition contributes to promoting recovery and significantly shortening the length of hospital stay. Medical staff should consider individual energy needs when planning nutritional care， and effectively improve the actual nutritional intake of patients.

Objective To analyze the current research status and trends of post-traumatic stress disorder (PTSD) in cancer patients at home and abroad, and to provide guidance for future research directions. Methods The databases of CNKI and the Web of Science Core Collection were searched for the relevant literature on PTSD in cancer patients included from 2014 to 2023. Citespace 6. 3. R1 software was used for bibliometric analysis. Results There were a total of 356 articles on PTSD in cancer patients from 2014 to 2023, including 246 in English and 110 in Chinese, and the number of published articles showed an upward trend. A relatively stable cooperation network had been formed among countries and regions in foreign literature, while no cooperation network had been formed among regions in domestic literature. Most research institutions were relatively scattered and independent. The research hotspots focused on the diversification of cancer patient groups, especially vulnerable cancer groups and primary caregivers, dynamically observing the development trend of PTSD in cancer patients, exploring the influencing factors at different stages, and exploring specific nursing intervention measures suitable for the national culture. Conclusion The analysis of the literature knowledge map shows the research patterns and trends of PTSD in cancer patients. Foreign research started earlier and covered a wider range of fields. Although the number of published articles in China has increased in recent years, there is less cooperation among institutions and authors, and it is limited to cross-sectional exploration with a single focus group. In the future, nursing researchers need to conduct in-depth exploration, diversify research groups and methods to promote the development of this field. (目的 分析国内外癌症患者创伤后应激障碍的研究现状和趋势, 为未来的研究方向提供指导。方法 检索数据库包括中国知网及Web of science核心数据库, 时间为2014年—2023年收录的关于癌症患者创伤后应激障碍相关文献, 采用Citespace 6. 3. R1软件进行文献计量学分析。结果 2014—2023年关于癌症创伤后应激障碍文献共有356篇, 其中英文246篇, 中文110篇, 发文量呈现上升趋势; 国外文献的国家地区之间已形成较为稳定的合作关系网络, 国内文献的地区之间未形成合作关系网络, 大多研究机构较为分散和独立; 研究热点是关注癌症患者群体多样化, 尤其癌症弱势群体及主要照顾者, 动态观察癌症患者创伤后应激障碍发展趋势, 探究不同阶段的影响因素, 探索适合本国文化的特异性护理干预措施等。结论 文献知识图谱分析展示了癌症创伤后应激障碍的研究规律及趋势, 国外研究起步早, 涉及领域较广, 我国虽然近年发文量升高, 但机构及作者间合作较少, 且局限于横断面探究, 关注群体单一, 未来需护理研究者进行深层次探索, 研究群体及方法多样化, 推动该领域的发展。)

Objective To investigate the effects of Chinese herbal medicine ointment and sequential six-character formula on pulmonary infection control (PIC) window opening time, exercise endurance and pulmonary function rehabilitation in patients with acute exacerbation of chronic obstructive pulmonary disease(COPD). Methods A total of 74 patients with acute exacerbation of COPD who were hospitalized from January 2022 to October 2024 were selected as the study objects by convenient sampling method. Interval randomization method was used to divide 37 cases into the experimental group and 37 cases into the control group. Both groups were given conventional Western medicine treatment and nursing care. The control group was given six-character formula after the PIC window was opened, and the experimental group was given six-character formula, followed by the sequential use of Chinese herbal medicine ointment after the PIC window was opened. The changes of PIC window opening time, Traditional Chinese Medicine syndrome score, dyspnea degree (mMRC), lung function and 6-minute walking distance (6MWD) were compared between the two groups. Results The opening time of PIC window in experimental group was earlier than that in control group (P＜0. 05). After 2 weeks of intervention, TCM syndrome score and mMRC in 2 groups were significantly improved compared with before intervention, and the experimental group was better than the control group (P＜0. 05). After 6 weeks of intervention, the lung function of 2 groups was improved compared with that when the PIC window was opened (P＜0. 05), but there was no significant difference between groups (P＞0. 05). After 6 weeks of intervention, 6MWD in the two groups was better than that in the control group when the PIC window was opened (P＜0. 05). Conclusion The clinical efficacy of Chinese herbal medicine ointment and sequential six-character formula in the treatment of patients with acute exacerbation of COPD is better than that of single use of six-character formula, which can reduce the time required for PIC window opening, alleviate dyspnea symptoms, increase exercise endurance, improve lung function, and no adverse reactions. (目的 探讨中药膏摩序贯“六字诀”对慢性阻塞性肺疾病急性加重期患者肺部感染控制(PIC)窗开启所需时间、运动耐力及肺功能康复的影响。方法 采用便利抽样法, 选取2022年1月—2024年10月在北京中医药大学东方医院呼吸热病科住院治疗的74例慢性阻塞性肺疾病急性加重期患者为研究对象。采用区间随机化方法分为试验组37例和对照组37例。两组均给予常规西医治疗护理, 对照组待PIC窗开启后给予“六字诀”, 试验组给予中药膏摩序贯“六字诀”, 均干预6周。比较两组患者PIC窗开启所需时间、中医证候积分、呼吸困难程度(mMRC)、肺功能、6分钟步行距离(6MWD)的变化。结果 试验组PIC窗开启所需时间早于对照组(P＜0. 05); 两组干预2周后中医证候积分、mMRC较干预前均有明显改善, 且试验组优于对照组(P＜0. 05); 两组干预6周后肺功能较PIC窗开启时改善(P＜0. 05), 但组间差异无统计学意义(P＞0. 05); 两组干预6周后6MWD较PIC窗开启时改善, 且试验组优于对照组(P＜0. 05)。结论 中药膏摩序贯“六字诀”治疗慢性阻塞性肺疾病急性加重期患者临床疗效优于单纯“六字诀”治疗, 可减少PIC窗开启所需时间, 减轻呼吸困难症状, 增加运动耐力, 改善肺功能, 且无不良反应。)

To summarize the experience of integrated traditional Chinese and western nursing care of an elderly patient with toxic epidermal necrolysis complicated by malignant tumors of the prostate. The patient was treated using a combination of traditional Chinese and Western nursing care methods including pain management, infection control, nutrition support, auricular acupuncture, acupoint massage, oral care by Chinese herbal medicine, acupoint application. Integrative nursing interventions effectively promoted healing of widespread skin lesions, reduced the pain and risk of complications and improved the quality of life of the patient. (本文总结1例老年前列腺恶性肿瘤合并中毒性表皮坏死松解症患者的中西医结合护理经验。患者皮损严重, 应严格加强皮肤黏膜护理, 采用中西医结合的护理方式, 包括疼痛护理、感染防控、营养支持、耳针穴位治疗、穴位按摩、中药口护、穴位贴敷等护理措施, 帮助患者顺利度过表皮剥脱期, 降低并发症风险, 减轻患者痛苦, 提高生活质量。)

[Purposes] Electrocatalytic technology for converting CO2 into high-value-added fuels and chemicals has promising applications. However, developing electrocatalysts with superior performance still faces significant challenges. [Methods] In this study, wheat bran was used as the precursor of biomass carbon and the pyrolysis method was used to prepare nitrogen-doped biomass carbon materials (NC). By further coupling with CuO via a hydrothermal method, a series of CuO@NC composite materials were costructed. The crystalline phase, microscopic morphology, structure, and elemental valence states were analyzed by multiple characterization techniques. The electrocatalytic performance was investigated towards the electrocatalytic reduction of CO2. [Findings] Results indicate that the composite catalyst synthesized at 160 ℃ (CuO@NC-160) exhibits high selectivity towards ethylene, with a maximum faradaic efficiency of 26.85% at -1.18 V vs. RHE. This study presents a feasible pathway for fabricating low-cost and efficient CuO-based electrocatalysts.

[Purposes] The separation of carbon form coal gasification slag is an important means to realize its reduction, harmlessness, and resource utilization. The airflow classification method has unique advantages because of its ability to efficiently process fine-graded particles without waste water and exhaust gas emmission. [Methods] According to CFD-DEM simulation, the gas-solid flow characteristics of horizontal turbine air classifier were investigated, and the matching relationship between the air inlet direction and turbine steering was explored. The flow mechanism of carbon and ash particles was clarified. On this basis, the air inlet direction in the turbine air classifier was optimized, and the effects of inlet air velocity and turbine speed on the efficient carbon extraction for gasification slag in air classifier were predicted. [Findings] The results show that the inlet direction of the turbine air classifier has a significant effect on the flow field distribution and the efficiency of carbon extraction for gasification slag. The tangential air inlet leads to the generation of secondary vortices in the grading zone and elution zone that interfere with each other, affecting the separation efficiency of carbon and ash particles. The optimization of tangential air inlet to vertical upward avoids the mutual interference between the elution zone and the classification zone. The secondary vortex between the turbine and the blades is eliminated. The uniform distribution of the flow field in the classification zone is improved and stabilized. The efficiency of carbon extraction is increased. In the optimized turbine airflow classifier, by matching the inlet air velocity with the turbine speed, the carbon content in the carbon-rich product can reach 80.95%, and the carbon recovery rate can reach 59.83%.

Objective The world is still in a phase of rapid industrialization and urbanization. Excessive carbon emissions has become the primary root cause of various urban or even global environmental problems, further impacting human physiological and psychological health. Cities are the largest sources of carbon emissions and are crucial regions for achieving carbon neutrality goals. Urban blue-green infrastructure (UBGI), comprising natural, semi-natural, or artificial green and blue spaces within cities, is considered as the most important carbon sink space in urban areas and has increasingly attracted widespread attention from researchers. However, there are still many unresolved issues regarding the effectiveness of UBGI in carbon sink enhancement and emission reduction: 1) How is the energy efficiency of carbon sink enhancement and emission reduction measured, and what factors influence it? 2) What are the mechanisms and pathways through which UBGI enhances carbon sink and reduces carbon emission? 3) How can UBGI be regulated to better enhance its effectiveness in carbon sink enhancement and emission reduction? 4) What are the limitations and potential directions for future research? This research aims to address these issues and propose scientifically sound planning strategies for UBGI construction to achieve urban carbon neutrality goals.Methods Through literature synthesis and deduction, this research organizes and analyzes the multi-scale measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction, identifies corresponding influencing factors at each scale, and constructs multi-scale planning strategies for UBGI based on the logical framework of “measurement methods–influencing factors – planning strategies”.ResultsThe research proposes UBGI planning strategies across three spatial scales (site, community and urban area), covering three key aspects: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. Based on current research gaps and planning needs, five major research topics are further identified. This research provides a detailed analysis of the measurement methods and influencing factors of UBGI’s efficiency in carbon sink enhancement and emission reduction from three perspectives: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. The research finds significant differences in the measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction efficiency across different scales. Contradictory results may occur at different scales, and large-scale research often lacks characterization of internal features, leading to unclear mechanisms of influencing factors and obstructing practical planning. Based on the interpretation of UBGI’s mechanisms for carbon sink enhancement and emission reduction at different scales, this research formulates UBGI planning strategies across three spatial scales (site, community, and urban area). These strategies include: 1) At the site scale, for carbon sequestration and sink enhancement – carbon sink at the source, land balance, and ecological design; for emission reduction – symbiosis with buildings and integration into daily life. 2) At the community scale, for carbon sequestration – overall balance of revenue and expenditure, precise positioning, and proper interconnection of the carbon chain; for emission reduction – incorporation of cool islands and co-construction. 3) At the urban area scale, for carbon sequestration – enhancement of ecological space management and establishment of a carbon-safe pattern; for emission reduction – demand-based layout and organic dispersion. Finally, the research proposes five major research topics for the planning of UBGI’s carbon sink enhancement and emission reduction: How to construct unified measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction across scales? How to measure UBGI’s efficiency in carbon reduction based on temperature reduction (or preservation) at the site scale? How to integrate the pathways of carbon sink enhancement and emission reduction for a life cycle assessment of UBGI? How to balance UBGI’s carbon sink enhancement and emission reduction with other functions to achieve the optimal layout for comprehensive benefits? How to achieve urban “carbon justice” through UBGI? Conclusion The carbon sink pathway of the strategy framework requires “carbon sink at the source – precise positioning – safe pattern”, and the emission reduction pathway requires “symbiotic integration – co-construction and sharing – organic dispersion”. The key trade-offs between these two pathways at three spatial scales may provide theoretical support and practical guidance for UBGI construction and management. The five major research topics mentioned above may offer valuable assistance for UBGI construction and future research.

The accelerating global energy transition and rapid expansion of renewable energy sources，presents both opportunities and challenges. This transformation has introduced new concerns related to the “safety and stability” of power grids，particularly as large-scale integration of renewable energy sources such as wind and solar power results in issues including frequency overruns and voltage instability. This study explores the impact of renewable energy output and weather conditions on equipment failures and establishes a comprehensive scenario for power grids under renewable energy integration. A novel multihead graph-attention neural network model is proposed that integrates graph neural networks with multihead attention mechanisms. By incorporating parallel training methods，the proposed model is utilized in renewable energy power systems with the aim of improving risk assessment efficiency while maintaining accuracy in grid risk assessments. The model is trained and tested using data obtained from a provincial power grid within an electrical power simulation system. Results，derived from integrating real-world data from a provincial power grid in China with that of the electrical power simulation system，demonstrate that the attention-based graph neural network method approach substantially improves the robustness and efficiency of risk assessments compared to other artificial intelligence methods. This approach shows considerable promise in renewable energy power systems for enhancing risk assessment.

Epilepsy is a common chronic neurological disorder that severely impacts the quality of life and social functioning. Approximately 1/3 of patients are diagnosed with drug⁃resistant epilepsy (DRE), for which conventional antiepileptic seizure medicine (ASM) and traditional surgery have limited efficacy. In recent years, responsive neurostimulation (RNS), as a closed⁃loop neuromodulation technique, has provided a novel treatment option for DRE. The RNS utilizes invasived electrodes to monitor brain activity in real time, detect seizure precursors, and deliver electrical stimulation, effectively reducing the frequency and severity of DRE. This paper aims to review the composition of the RNS, optimization and dyanmic adjustment of stimulation parameters, long⁃term data recording and analysis, fusion with machine learning, clinical efficacy, and comparison with vagus nerve stimulation (VNS). It also explores the technical challenges and discusses future development directions. RNS holds promise for providing personalized and precise treatment to more DRE and expanding its application to other neurological disorders.

As a mature neuromodulation technique, deep brain stimulation (DBS) has been widely used in the treatment of various neurological and psychiatric disorders. Parkinson's disease (PD) is one of the earliest indications for DBS and has received the most treatment so far. It has attracted extensive attention and in⁃depth research from the academic community for a long time, and has made remarkable progress in multiple fields. This review highlights the optimization of DBS for PD, focusing on two key directions: surgical technology innovation and neural circuit mechanism research. It explores the surgical technology innovation, equipment innovation, and programming strategy improvement of DBS, as well as the recognition and application of neural circuit markers. These studies not only significantly improve the efficacy of PD treatment, but also provide valuable ideas and scientific basis for the future development of neuromodulation technique.

The differences in the quality and antioxidant activity of Thompson seedless raisins from nine production areas in Turpan were analyzed. Their phenolic composition and content were determined by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The results showed that raisins produced in Lianmuqin had the largest mean single unit mass and shape index of 0.81 g and 2.74, respectively, while raisins produced in Gaochang had the smallest values of 0.46 g and 2.27, respectively. Raisins produced in Yuanyichang had the highest solid/acid ratio of 29.34, while raisins produced in Qiketai had the lowest value of 25.74. Lianmuqin raisins had the lowest a* value of 2.56 and a ΔE value (44.94) below the medium level, indicating the greenest color. The a* value of Yuanyichang raisins was below the medium level (2.94) and its ΔE value (44.19) was the lowest. The color of raisins from these two areas tended to be green and the most consistent with each other. A total of 518 monomeric phenolics were identified in Thompson seedless raisins from the six production areas, including 275 flavonoids (53.09%), 136 phenolic acids (26.25%), 60 lignans and coumarins (11.58%), 19 tannin (3.67%) and 28 others (5.41%). A total of 246 differential metabolites were identified in raisins from Lukeqin versus Gaochangqu (124), Qiketai versus Shengjinxiang (144), and Yuanyichang versus Lianmuqin (66), with 54, 92 and 22 differential metabolites being unique to these comparisons, respectively and 10 differential metabolites being common to all of them. The above results indicate that Lianmuqin and Yuanyichang can be considered as advantageous production areas for Thompson seedless raisins.

Microbubble air flotation cyclone technology is an innovative and efficient separation method combining flotation separation and cyclone separation. Using this technology for oil-water separation, the effects of dissolved gas water microbubbles, cyclone fields, and flocculants on separation efficiency were investigated. High-speed imaging technology was utilized to study the interaction between microbubbles and oil droplets, as well as between microbubbles and flocs. The results showed that dissolved gas water microbubbles significantly reduced oil-water separation time, cutting it by 50% compared to static settling in pure water. At an initial oil-water mixture concentration of 400 mg/L, the optimal experimental conditions for the combined flotation+cyclone+flocculant process were: Oil-water mixture to dissolved gas water volume ratio of 1∶4, cyclone velocity of 370 r/min, composite flocculant ratio (PAC∶CPAM) of 2∶1. Under these conditions, the final oil concentration in wastewater was less than 10 mg/L, meeting the requirements of the Integrated Wastewater Discharge Standard (GB 8978-1996). In static water conditions, the average projected area of microbubble-floc aggregates was approximately six times that of microbubble-oil droplet aggregates, indicating that the addition of flocculants was conducive for improving oil-water separation. Interaction experiments demonstrated that, compared to pure water static settling, oil content in wastewater decreased by 38.7%, 71.4%, and 76.5% after treatment using microbubble air flotation, flotation+cyclone, and flotation+cyclone+flocculants, respectively. The final oil-water separation effectiveness was in order of three-factor combination>dissolved gas water microbubbles +cyclone field>dissolved gas water microbubbles alone.

The difference in natural-gas enrichment significantly affects the underground medium density and thus the surface gravity. Microgravity monitoring technology monitors the morphological changes of a gas-reservoir development zone by measuring the surface gravity to obtain the change information of gas-reservoir development. The separation and extraction of gravity anomalies in microgravity monitoring is necessitated to accurately characterize the changes in gas-reservoir development intervals. The depth recursive method is the preferred method for separating residual gravity anomalies of different scales and extract reliable residual gravity anomalies. Considering the Dixi 121 well area of Xinjiang oilfield as an example and using the dynamic data of oil and gas drilling and production, the relationship between residual microgravity anomalies and reservoir characteristics is investigated in this study. The application of microgravity technology to the development of gas reservoirs in the middle and deep reservoirs is achieved, and a sand-ground ratio forward model is innovatively established for the geological conditions of the study area to analyse the response of the sand thickness in the residual gravity anomaly field. The findings of the study indicate that microgravity technology is an efficient method for developing reservoirs of middle and deep reservoirs. the higher the sand-ground ratio of the reservoir section, the lower the residual microgravity anomaly, which is in accordance with forward modelling and the distribution law of the sand-body depicted by seismic data.

Shale pore structures contribute significantly to shale gas reservoirs, with their shape, size, connectivity, and development directly affecting storage. To achieve intelligent recognition and classification of shale pores, this study proposes a shale-pore semantic segmentation network based on a pseudo-label method. A total of 251 scanning electron microscopy images of the Longmaxi Formation shale reservoir in Chongqing are used, and the Pyramid Scene Parsing Network is utilized for training. Additionally, pseudo-label generation is employed, which involves annotating only a few images and using the model’s segmentation results on unlabeled images for iterative training. Subsequently, ensemble learning is conducted to improve the model’s accuracy and generalizability. The iteratively trained model has a mean intersection-over-union (MIoU) score exceeding 0.70. Comparative experiments show that employing pseudo-labeling and ensemble learning increases the model’s MIoU by approximately 0.07. Furthermore, pseudo-labeling enhances the generalizability of neural networks while addressing the high time cost of manual annotation required in previous deep-learning segmentation methods, whereas ensemble learning stably increases the model’s accuracy.

Wound infections in elderly diabetic patients represent a severe complication of diabetes, with diabetic foot ulcers being the most common manifestation.Due to impaired immune function and the prolonged course of the disease, elderly patients often struggle to control wound infections, leading to increased medical costs, extended hospital stays, higher rates of amputation and mortality.As bacterial resistance becomes more prevalent, traditional oral or intravenous antibiotics are increasingly ineffective in treating wound infections in elderly diabetic patients.In contrast, emerging nanomaterials offer promising prospects in antibacterial therapy, owing to their superior biocompatibility, targeted action, controlled release, and low toxicity.This article reviews the latest research on the antibacterial mechanisms of nanomaterials and explores their potential as a novel strategy for treating wound infections in elderly diabetic patients.

[Objective] To investigate the preventive effect of denosumab on recurrent fractures after percutaneous vertebroplasty in patients with osteoporotic vertebral compression fractures. [Methods] A total of 72 patients diagnosed with osteoporotic vertebral compression fracture and treated by percutaneous vertebroplasty in the orthopedic department of the Second Affiliated Hospital of Guangzhou Medical University from January 2022 to December 2022 were selected as the study subjects.Patients were randomly divided into two groups, each had 36 cases.The control group received conventional anti-osteoporosis treatment, and the observation group added denosumab on the basis of control group treatment.Both groups were followed for 1 year, while the fracture rate and the levels of bone mineral density(BMD), visual analogue scale(VAS) score, oswestry disability index(ODI), beck value, sagittal cobb angle and procollagen type ⅠN-terminal propeptid(PINP) and β-carboxy-terminal cross-linked telopeptide of type Ⅰ collagen(β-CTX) were compared between the two groups. [Results] There was no significant preoperative on BMD, VAS score, ODI index,beck values, sagittal cobb angle, PINP and β-CTX levels between the two groups before the surgery(P>0.05); After postoperative follow-up of 6 months, BMD in the observation group was higher than that in the control group (P

[Objective] To investigate the effect of partially oxidized sodium alginate gel combined with intramyocardial injection of myogenic stem cells on cardiac function in aged rats with myocardial infarction. [Methods] The models of myocardial infarction in aged rats were established by ligating the coronary arteries and divided randomly into the group of saline control group, sodium alginate group, myogenic stem cells group and sodium alginate combined with myogenic stem cells group(joint group), each had 30 rats.The same amount of corresponding material was injected into the myocardial infarction area of rats in each group respectively.The cardiac structure and function of the rats were evaluated by echocardiography 8 weeks after the operation, and then the rats were executed.The hearts were removed to observe the differences in ventricular remodeling by histological analysis and the angiogenesis and collagen secretion of the ventricular slices were further analyzed. [Results] The echocardiographic indexes, histological indexes, vessel density per unit area, and the percentage of collagen-positive area in the rats of the joint group were better than those in the other groups (P0.05). [Conclusion] Sodium alginate gel combined with intramyocardial injection of myogenic stem cells can significantly improve the cardiac function in aged rats with myocardial infarction, which also shows the better effects than the injection of sodium alginate or myogenic stem cells separately.

Aiming at the problem of insufficient local feature extraction of general point cloud classification methods in fine-grained classification tasks, we propose a point cloud-oriented 3D model classification framework, HFE-Net. The Veronese mapping-based point feature enhancement module (V-PE) is used to enhance the point cloud data, so that the network learns higher-order information of the normal and the attitude; the multi-scale context-aware intra-cluster feature enhancement module (CA-IntraCE) utilizes different scales of K-nearest neighbor algorithms and cross-attention to achieve different scales of features and eliminate the loss of information caused by maximal pooling; the inter-cluster feature enhancement module (GSS-InterCE) based on grouped sparse sampling utilizes the furthest-point-sampling (FPS) algorithm to obtain sparse points and the cross-attention to achieve the enhancement of different clusters, so that the network has stronger fine-grained discriminative ability.In the experimental results on the three sub-datasets Airplane, Car, and Chair of FG3D, the overall accuracies of HFE-Net reach 97.40%, 80.53%, and 83.83%, respectively, which have ex-ceeded those of the existing SOTA methods, DC-Net and FGPNet, showcasing the superior classification performance of HFE-Net.(针对粗粒度点云分类方法在细粒度数据集中局部特征提取不足的问题，提出了一种基于层次特征增强的三维细粒度点云分类网络（HFE-Net）。基于Veronese映射的点特征增强模块（V-PE）对点云数据进行数据增强，辅助网络学习法线和姿态高阶信息；基于多尺度上下文感知的簇内特征增强模块（CA-IntraCE），利用不同尺度的K近邻（K-nearest neighbors，KNN）算法以及交叉注意力实现不同尺度特征的增强，以消除最大池化带来的信息丢失；基于分组稀疏采样的簇间特征增强模块（GSS-InterCE），利用最远点采样（FPS）算法获得稀疏点，并采用交叉注意力实验不同簇间的特征增强，从而提高网络的细粒度判别能力。在FG3D数据集Airplane、Car和Chair 3个类别上的实验结果显示，HFE-Net的总体准确率分别达97.40%，80.53%和83.83%，已超过现有最优方法DC-Net、FGPNet的分类框架，说明HFE-Net的分类性能具有一定的优越性。)

To solve the problems of poor engineering properties of clay and low utilisation of coir fiber, a green and high-performance soil was obtained by using coir fiber in synergy with lime for clay reinforcement. Compaction test and unconfined compression test were carried out to analyze the influence of fiber content and lime content on the early compressive strength, axial compression deformation characteristics, and deformation modulus parameters of clay. The microscopic mechanism of the synergistic effect of fiber-lime soil was analyzed by scanning electron microscope and X-ray diffraction, and then the synergistic mechanism was discussed. The results show that the addition of lime reduces the maximum dry density and increases the optimum moisture content of the clay. With an increase in lime content, the compressive strength of the soil initially exhibits a rise followed by a decline. The strain of the soil failure shows a decrease first and then an increase, indicating a brittle failure mode. Similarly, as the fiber content increases, the compressive strength of the soil also experiences an initial increase followed by a subsequent decrease. However, in this case, there is a gradual increase in failure strain suggesting a plastic failure mode. The relationship between deformation modulus and compressive strength of improved soil is linear. Lime fills up pores by reacting with the soil to form gelled substances, while fibers form a three-dimensional network structure providing growth areas for hydration products, thereby synergistically reinforcing the soil. This study can provide theoretical and technical guidance for roadbed improvement and slope repair.

In order to effectively control the occurrence of human accidents caused by physical fatigue of miners, in this study, grounded theory is used to construct the index system of influencing factors of miners’ physical fatigue and the questionnaire of miners’ physical fatigue is developed; based on the data of the questionnaire, entropy weighting method is used to explore the influence degree of each index on miners’ physical fatigue, and put forward corresponding safety management promotion strategies; and TOPSIS model is applied to evaluate the physical fatigue of 15 miners randomly selected. The results show that: the physical fatigue of miners is affected by their own condition, work pressure and work environment, among which work pressure is the most important factor; the TOPSIS comprehensive rating model of miners’ physical fatigue can judge the grade of miners’ physical fatigue reasonably and effectively.

Car-like robots often struggle with dynamics modeling owing to the use of nonstandardized parts and the complexity of accurately determining mechanical parameters, particularly tire characteristics like lateral deflection stiffness. Consequently, most current research and applications have relied on kinematic models for control, which frequently lead to inaccuracies and mismatches. These issues result in significant errors between actual and desired paths, causing erratic oscillations in the front wheel angle and angular velocity and adversely affecting the robot’s performance and smoothness. To address these issues, this paper introduces a novel approach: Feed-forward nonlinear model predictive control (FNMPC). This method is built on the principles of inverse kinematics and rolling optimization. Unlike other traditional methods, FNMPC incorporates feed-forward corner information into its predictive model, treating the front wheel angle as an additional dimension. This enhancement allows the model to better predict and correct deviations, thereby improving path-tracking accuracy. Extensive simulations conducted using Simulink and CarSim demonstrated the efficacy of the FNMPC approach. Results indicated that FNMPC significantly reduces the oscillations caused by model inaccuracies while maintaining high tracking accuracy. Specifically, FNMPC managed to keep displacement errors below 0.1106 m and heading errors within 0.1253 radians. When compared with other control strategies such as linear model predictive control, feed-forward linear model predictive control, pure tracking control, and Stanley control, FNMPC consistently demonstrated smaller and less dispersed errors, highlighting its superior performance in handling the complex dynamics of car-like robots. Moreover, FNMPC showed a remarkable improvement over traditional nonlinear model predictive control (NMPC), reducing the absolute cumulative control increment by 67.53% at its maximum values. Experimental validations using a wire-controlled car-like robot further validated FNMPC’s practical benefits. In these tests, the robot under FNMPC control maintained displacement errors within 0.1624 m and heading errors within 0.1138 radians, whereas traditional NMPC lost control of entering curves. In summary, FNMPC presents a substantial advancement in controlling car-like robots, offering enhanced accuracy and smoothness over existing methods. By effectively incorporating feed-forward corner information into the predictive model, FNMPC addresses the inherent challenges in car-like robot dynamics more efficiently. This approach not only improves control performance but also offers a more reliable and accurate method that could enhance the development of car-like robotic systems.