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Abundance sensitivity is an important technical index of magnetic mass spectrometer, which describes the extent to which the tailing of intense ion peaks at a mass number in its neighborhood affects the weak ion peaks during isotope ratio measurement. It is particularly important in the measurement of isotope ratios containing low abundance nuclides, such as 234U/238U, 236U/238U, and 230Th/232Th. However, the abundance sensitivity of magnetic mass spectrometer is only of the order of 10−6 without taking additional technical measures. To further improve the abundance sensitivity, the techniques of tandem mass spectrometer, such as magnetic-electric, magnetic-magnetic and magnetic-electric-quadrupole tandem mass spectrometer, and retarding filter can be adopted. In fact, while various tandem mass spectrometer techniques can effectively improve the abundance sensitivity of an instrument, they also significantly increase the size, complexity, and cost of instrument, and therefore are not widely used. In contrast, due to its simple structure, small size, and excellent performance, the retarding filter has become a key component for commercial magnetic mass spectrometers to improve abundance sensitivity. Based on the basic principles of ion optics, a retarding filter consisting of five electrodes with a compact structure of only (40×50×50) mm3 was developed by utilizing the ion optics simulation software SIMION8.1. In addition to the function of energy retarding, the retarding filter also has the function of direction retarding, which greatly enhances the filtering capability to scatter ions. To test the ion transmission efficiency and the abundance sensitivity under different voltages, the retarding filter was installed on a domestic double-focusing thermal ionization mass spectrometer (TIMS). The instrument mainly consists of a thermal ionization source, a double focusing mass analyzer consisting of an electrostatic analyzer and a magnetic mass analyzer, a zoom lens, and a multi-collector detector, which can be configured with up to 16 faraday cups, 4 electron multipliers, and 2 retarding filters. The results showed that the abundance sensitivity of the mass spectrometer is successfully improved from

​​​​​​​This study compares aerosol mixing-state parameters obtained via simultaneous measurements using DMA–CCNC, H(/V)TDMA, and DMA–SP2, shedding light on the impacts of primary aerosol emissions and secondary aerosol (SA) formation. The analysis reveals significant variations in mixing-state parameters among different techniques, with VTDMA and DMA–SP2 indicating that non-volatile particles mainly stem from black carbon (BC)-containing aerosols, while a substantial proportion of nearly hydrophobic aerosols originates from fossil fuel combustion and biomass-burning emissions. Synthesizing the results, some nearly hydrophobic BC-free particles were found to be cloud condensation nuclei (CCN)-inactive under the measured supersaturated conditions, likely from fossil fuel combustion emissions, while others were CCN-active, linked to biomass-burning emissions. Moreover, BC-containing aerosols emitted from fossil fuel combustion exhibit more external mixing with other aerosol components compared to those from biomass burning. Secondary nitrate and organic aerosol formation significantly affect aerosol mixing states, enhancing aerosol hygroscopicity and volatility while reducing heterogeneity among techniques. The study also highlights distinct physical properties of two resolved secondary organic aerosol factors, hinting at their formation through different mechanisms. These findings underscore the importance of comparing aerosol mixing states from different techniques as a tool for understanding aerosol physical properties from different sources and their responses to SA formation, as well as aiding in the exploration of SA formation mechanisms.

Tropospheric ozone is a major air pollutant and greenhouse gas. It is also the primary precursor of OH, the main tropospheric oxidant. Global atmospheric chemistry models show large differences in their simulations of tropospheric ozone budgets. Here we implement the widely used GEOS-Chem atmospheric chemistry module as an alternative to CAM-chem within the Community Earth System Model version 2 (CESM2). We compare the resulting GEOS-Chem and CAM-chem simulations of tropospheric ozone and related species within CESM2 to observations from ozonesondes, surface sites, the ATom-1 aircraft campaign over the Pacific and Atlantic, and the KORUS-AQ aircraft campaign over the Seoul Metropolitan Area. We find that GEOS-Chem and CAM-chem within CESM2 have similar tropospheric ozone budgets and concentrations usually within 5 ppb but important differences in the underlying processes including (1) photolysis scheme (no aerosol effects in CAM-chem), (2) aerosol nitrate photolysis, (3) N2O5 cloud uptake, (4) tropospheric halogen chemistry, and (5) ozone deposition to the oceans. Global tropospheric OH concentrations are the same in both models, but there are large regional differences reflecting the above processes. Carbon monoxide is lower in CAM-chem (and lower than observations), at least in part because of higher OH concentrations in the Northern Hemisphere and insufficient production from isoprene oxidation in the Southern Hemisphere. CESM2 does not scavenge water-soluble gases in convective updrafts, leading to some upper-tropospheric biases. Comparison to KORUS-AQ observations shows an overestimate of ozone above 4 km altitude in both models, which at least in GEOS-Chem is due to inadequate scavenging of particulate nitrate in convective updrafts in CESM2, leading to excessive NO production from nitrate photolysis. The KORUS-AQ comparison also suggests insufficient boundary layer mixing in CESM2. This implementation and evaluation of GEOS-Chem in CESM2 contribute to the MUSICA vision of modularizing tropospheric chemistry in Earth system models.

Abstract Machine learning is becoming a preferred method for the virtual screening of organic materials due to its cost-effectiveness over traditional computationally demanding techniques. However, the scarcity of labeled data for organic materials poses a significant challenge for training advanced machine learning models. This study showcases the potential of utilizing databases of drug-like small molecules and chemical reactions to pretrain the BERT model, enhancing its performance in the virtual screening of organic materials. By fine-tuning the BERT models with data from five virtual screening tasks, the version pretrained with the USPTO–SMILES dataset achieved R2 scores exceeding 0.94 for three tasks and over 0.81 for two others. This performance surpasses that of models pretrained on the small molecule or organic materials databases and outperforms three traditional machine learning models trained directly on virtual screening data. The success of the USPTO–SMILES pretrained BERT model can be attributed to the diverse array of organic building blocks in the USPTO database, offering a broader exploration of the chemical space. The study further suggests that accessing a reaction database with a wider range of reactions than the USPTO could further enhance model performance. Overall, this research validates the feasibility of applying transfer learning across different chemical domains for the efficient virtual screening of organic materials. Scientific contribution This study verifies the feasibility of applying transfer learning to large language models in different chemical fields to help organic materials perform virtual screening. Through the comparison of transfer learning from different chemical fields to a variety of organic material molecules, the high precision virtual screening of organic materials is realized.

The chemical composition of individual particles can be revealed by single-particle mass spectrometers (SPMSs). With higher accuracy in the ratio of mass to charge (m/z), more detailed chemical information could be obtained. In SPMSs, the conventional standard-based calibration methods (internal/external) are constrained by the inhomogeneity of ionization lasers and the finite focusing ability of the inlet system, etc.; therefore, the mass accuracy is restricted. In this study, we obtained the detailed and reliable chemical composition of single particles utilizing a standard-free mass calibration algorithm. In the algorithm, the characteristic distributions of hundreds of ions were concluded and collected in a database denoted as prototype. Each single-particle mass spectrum was initially calibrated by a function with specific coefficients. The range of coefficients was constrained by the magnitude of mass deviation to a finite vector space. To find the optimal coefficient vector, the conformity of each initially calibrated spectrum to the prototype dataset was assessed. The optimum calibrated spectrum was obtained with maximum conformity. For more than 98 % ambient particles, a 20-fold improvement in mass accuracy, from ∼ 10 000 ppm (integer) to ∼ 500 ppm (two decimal places), was achieved. The improved mass accuracy validated the determination of adjacent ions with a m/z difference ∼ 0.05 Th. Furthermore, atmospheric particulate trace elements that were poorly studied before are specified. The obtained detailed single-particle-level chemical information could help explain the source apportionment, reaction mechanism, and mixing state of atmospheric particles.

Nitrogen oxide radicals (NOx≡NO+NO2) emitted by fuel combustion are important precursors of ozone and particulate matter pollution, and NO2 itself is harmful to public health. The Geostationary Environment Monitoring Spectrometer (GEMS), launched in space in 2020, now provides hourly daytime observations of NO2 columns over East Asia. This diurnal variation offers unique information on the emission and chemistry of NOx, but it needs to be carefully interpreted. Here we investigate the drivers of the diurnal variation in NO2 observed by GEMS during winter and summer over Beijing and Seoul. We place the GEMS observations in the context of ground-based column observations (Pandora instruments) and GEOS-Chem chemical transport model simulations. We find good agreement between the diurnal variations in NO2 columns in GEMS, Pandora, and GEOS-Chem, and we use GEOS-Chem to interpret these variations. NOx emissions are 4 times higher in the daytime than at night, driving an accumulation of NO2 over the course of the day, offset by losses from chemistry and transport (horizontal flux divergence). For the urban core, where the Pandora instruments are located, we find that NO2 in winter increases throughout the day due to high daytime emissions and increasing NO2/NOx ratio from entrainment of ozone, partly balanced by loss from transport and with a negligible role of chemistry. In summer, by contrast, chemical loss combined with transport drives a minimum in the NO2 column at 13:00–14:00 local time (LT). Segregation of the GEMS data by wind speed further demonstrates the effect of transport, with NO2 in winter accumulating throughout the day at low winds but flat at high winds. The effect of transport can be minimized in summer by spatially averaging observations over the broader metropolitan scale, under which conditions the diurnal variation in NO2 reflects a dynamic balance between emission and chemical loss.

Abstract Proteins play a vital role in different biological processes by forming complexes through precise folding with exclusive inter‐ and intra‐molecular interactions. Understanding the structural and regulatory mechanisms underlying protein complex formation provides insights into biophysical processes. Furthermore, the principle of protein assembly gives guidelines for new biomimetic materials with potential applications in medicine, energy, and nanotechnology. Atomic force microscopy (AFM) is a powerful tool for investigating protein assembly and interactions across spatial scales (single molecules to cells) and temporal scales (milliseconds to days). It has significantly contributed to understanding nanoscale architectures, inter‐ and intra‐molecular interactions, and regulatory elements that determine protein structures, assemblies, and functions. This review describes recent advancements in elucidating protein assemblies with in situ AFM. We discuss the structures, diffusions, interactions, and assembly dynamics of proteins captured by conventional and high‐speed AFM in near‐native environments and recent AFM developments in the multimodal high‐resolution imaging, bimodal imaging, live cell imaging, and machine‐learning‐enhanced data analysis. These approaches show the significance of broadening the horizons of AFM and enable unprecedented explorations of protein assembly for biomaterial design and biomedical research.

The electrodeposition process confronts significant challenges arising from mass transfer limitation and residual stress. To address these issues, an innovative method, combining megasonic agitation with coaxial jet electrodeposition, is introduced. This approach aims to enhance mass transfer and mitigate residual stress. First, an electrodeposition nozzle device was designed, and the liquid-phase mass transfer during electrodeposition was analyzed through finite element simulation. Simulation results indicate that the mass transfer coefficient increases with rising megasonic power density. Notably, when the megasonic power density reached 20 W/cm2, the mass transfer coefficient increased from 0.45 × 10−7 m/s to 18.63 × 10−7 m/s, compared to electrodeposition without megasonic agitation. Secondly, electrodeposition experiments were conducted both with and without megasonic assistance. X-ray diffraction (XRD) was employed to measure the residual stress values of the electrodeposited layers. The results reveal that samples processed with megasonic assistance exhibit lower residual stress values compared to those without. Specifically, at a megasonic power density of 10 W/cm2, the residual stress was 94.3 MPa, representing a 37.7 % reduction compared to the residual stress of 151.5 MPa observed in samples without megasonic agitation. Overall, the findings demonstrate that coaxial megasonic agitation can effectively enhance the liquid-phase mass transfer capability during electrodeposition and reduce the residual stress of the electroplated layer. This innovative method presents a promising avenue for improving electrodeposition processes and achieving superior material properties.

Abstract Two series of 3d‐Gd mixed‐metal phosphonate complexes with either only two gadolinium centers such as {Gd2}, {Ni2Gd2}, {Co4Gd2}, {Co8Gd2}, {Fe6Gd2}, and {Fe17Gd2} or more than two gadoliniums such as {Co8Gd4}, {Mn8Gd4}, {Co4Gd6}, {Mn4Gd6}, {Co6Gd8}, {Ni5Gd8}, {Ni6Gd6}, {Co8Gd8}, and {Mn9Gd9} have been solvothermally prepared and magnetothermally studied. The nearly identical environments of the Gd(III) dimer in the first series allow us to qualitatively analyze the effect of magnetic exchange coupling on the magnetocaloric effect (MCE). By doubling, tripling, or quadrupling of the Gd(III) centers, the second series of 3d‐Gd mixed‐metal complexes was built to further test the other effects of exchange couplings on MCE in more complicated circumstances. For the antiferromagnetic coupling cases, the results are nearly identical but diversify when topological spin frustrations are created, whose massive low‐lying excited spin states help enhance MCE. For presumably ferromagnetically coupled ones, albeit are rare in phosphonate complexes, they do exhibit excellent MCE. Meanwhile, the complexes with weakly coupled metal centers serve as excellent examples for studying the effect of molecular mass on MCE when its magnitude is expressed in the unit of Joule per kilogram, from which we can see the values are directly proportional to the percentage of the Gd(III) ions in molecular weight.

Two‐dimensional (2D) intrinsic vacancy semiconductors possess great application prospects in optoelectronics fields, originating from abundant intrinsic vacancy structures and exceptional physical properties. Understanding the structure‐activity relationship between vacancies and physical/photoelectric properties is significant for building advanced photoelectric devices. However, limited by the increasing instability of 2D structure induced by intrinsic vacancies, the precise synthesis of 2D intrinsic vacancy semiconductors faces great challenges. Here, high‐quality 2D intrinsic vacancy semiconductor α‐Ga2Se3 is synthesized via low‐pressure and space‐confined physical vapor deposition. The vacancy structures induce an intermediate energy level and a super‐bandgap photoluminescence (PL) peak, which are verified by temperature‐dependent PL spectra. Furthermore, the vacancy energy level favorably endows 2D α‐Ga2Se3‐based photodetector with a UV‐vis‐NIR super‐bandgap photoresponse, excellent ultraviolet detection ability (photoresponsivity (41.86 A W−1), epitaxial quantum efficiency (1.42 × 104%), and detectivity (6.69 × 1011 Jones) @365 nm), fast photoresponse (20 ms), and superior photocurrent‐light power‐fitting factors. In addition, 2D α‐Ga2Se3‐based phototransistor displays p‐type transport behavior with a responsivity of 105 A W−1@365 nm at a gate voltage of −40 V. This work suggests a bright future of 2D intrinsic vacancy semiconductors in tailoring physical properties and enabling sophisticated device functionality.

Electrochemical technology is frequently used to treat industrial dye wastewater. However, its degradation efficiency is restricted by pH, and the low current efficiency and high energy consumption limit its broader application. Based on this, we constructed an innovative electro-driven catalytic system by integrating nanotechnology with electric current. This system operates without pH constraints, has low energy consumption, and allows for the recycle and reuse of both electrodes and catalysts. Firstly, we synthesized palladium (Pd) cubes via a solvothermal method, and characterized their morphology, structural composition, and crystalline properties using transmission electron microscopy (TEM), energy dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD) and other methods. The prepared Pd cubes possessed dual catalytic properties of electro-driven catalysis and Fenton catalysis, achieving a synergistic degradation effect under an electric field. Subsequently, the study explored how catalysts dosage, H2O2 concentration, pH and Cl− concentration affect the catalytic rate. The optimized system was able to degrade 99.17 % of MB within 1 h and was effective against various organic pollutants. After five cycles of reuse, the recovered catalysts maintained over 90 % degradation efficiency in decomposing MB. This process realizes efficient degradation with a low concentration of catalysts, offering a novel approach for nanotechnology in wastewater treatment under electro-driven conditions.

How to precisely control and efficiently utilize the physical processes such as high temperature, high pressure, and shockwaves during the collapse of cavitation bubbles is a focal concern in the field of cavitation applications. The viscosity change of the liquid will affect the bubble dynamics in turn, and further affect the precise control of intensity of cavitation field. This study used high-speed photography technology and schlieren optical path system to observe the spatiotemporal evolution of shockwaves in liquid with different viscosities. It was found that as the viscosity of the liquid increased, the wave front of the collapse shockwave of the cavitation bubble gradually thickened. Furthermore, a high-frequency pressure testing system was used to quantitatively analyze the influence of viscosity on the intensity of the shockwave. It was found that the pressure peak of the shockwave in different viscous liquid was proportional to Lb (L represented the distance between the center of bubble and the sensor measuring point), and the larger the viscosity was, the smaller the value of b was. Through in-depth analysis, it was found that as the viscosity of the liquid increased, the proportion of the shockwave energy of first bubble collapse to the maximal mechanical energy of bubble gradually decreased. The proportion of the mechanical energy of rebounding bubble to the maximal mechanical energy of bubble gradually increased. These new findings have an important theoretical significance for the efficient utilization of ultrasonic cavitation.

Zirconium phosphate is the first artificially produced layered phosphate that can sorb a variety of nuclides from solutions. Sodium zirconium phosphate (NZP) was a type of α-zirconium phosphate (α-ZrP). The porous sodium zirconium phosphate pellets (p-NZP-P) with a diameter of more than ∼3 mm were prepared and used for uranium sorption. The p-NZP-P could be immersed in solutions for more than 5 days without dissolving and structurally collapsing. The sorption properties of U(Ⅵ) on p-NZP-P in solutions were investigated by both static and dynamic sorption tests. Synthetic p-NZP-P was analyzed in detail using various characterizations to investigate their character and structural changes. In the static sorption experiment, the equilibrium sorption capacity reached the 77.5 ± 1.5 mg·g−1 when the initial concentration of U(Ⅵ) was 100 mg/L, pHinitial = 4.5, T = 25 ℃. Uranium sorption increased by ∼69 % and ∼215 %, respectively, when the initial uranium concentration was increased from 100 to 300 mg·L−1 and the temperature was increased from 15 to 55 °C. Furthermore, uranium sorption increased by ∼541 % when the initial pH increased from 2.5 to 4.5, while it decreased by ∼39 % when the initial pH increased from 4.5 to 7.0. The sorption data corresponded to the pseudo-second-order kinetic model and the Langmuir isotherm model, as well as the theoretically predicted value of sorption capacity (∼199.9 mg·g−1). The results of the dynamic sorption experiment showed that decreasing the quality, increasing the flow rate and the initial U(Ⅵ) concentration would shorten the breakthrough time. The dynamic sorption data agreed well with the Thomas model. The characterization confirmed the porous properties, while the U(Ⅵ) sorption mechanisms relate to –OH coordination and ion exchange. A radioactive rare earth wastewater treatment test suggested that p-NZP-P could be the potential uranium sorbent due to its good stability and efficiency. This paper opened opportunities for the development of practical materials for treating radioactive wastewater in the application of actual scenarios.

In order to address the problem of poor localization in electrochemical machining (ECM), a coaxial megasonic assisted jet ECM method was proposed. Based on theoretical analysis, experiments were conducted to compare the effects of various electrolyte flow rates, electrolytic voltage and megasonic power levels on pit ECM. The results indicate that, in the range of experimental parameters, the increase of electrolyte flow rate and megasonic power can increase the machining depth, so as to improve the depth-diameter ratio of ECM pits. The use of coaxial megasonic-assisted jet ECM can enhance the depth-diameter ratio of etched pits compared to the without megasonic one. When applying a megasonic power of 22 W, the dimensions of the ECM pit were measured as 0.81 mm in depth and 5.73 mm in diameter, resulting in an depth-diameter ratio of 0.140. Under the same conditions, without megasonic assistance, the pit diameter is reduced to 0.65 mm while the pit depth increases to 6.36 mm, resulting in a depth-diameter ratio of 0.102. Additionally, The results also demonstrate that, the increase of electrolytic voltage makes the depth to diameter ratio of pit further increase on the original basis. With an electrolyte flow rate of 0.9 L/min and a megasonic power of 22 W, the use of electrolysis voltage of 50 V increased the depth-diameter ratio of etched pits to 0.173. Using the above preferred parameters, electrolytic milling of the wide groove is carried out. The depth-diameter ratio of the wide groove is increased from 0.039 to 0.059 by appending coaxial megasonic. This further verified the effectiveness of the coaxial megasonic-assisted jet ECM method.

Purpose: Early detection and diagnosis of cancer is critical for achieving positive therapeutic outcomes. Biomarkers that can provide clinicians with clues to the outcome of a given therapeutic course are highly desired. Oxygen is a small molecule that is nearly universally present in biological tissues and plays a critical role in the effectiveness of radiotherapies by reacting with DNA radicals and subsequently impairing cellular repair of double strand breaks.Techniques for measuring oxygen in biological tissues often use blood oxygen saturation to approximate the oxygen partial pressure in surrounding tissues despite the complex, nonlinear, and dynamic relationship between these two separate oxygen populations. Methods and materials: We combined a directly oxygen-sensitive, tumor-targeted, chemical contrast nanoelement with the photoacoustic lifetime-based (PALT) oxygen imaging technique to obtain image maps of oxygen in breast cancer tumors in vivo. The oxygen levels of patient-derived xenografts in a mouse model were characterized before and after a course of radiotherapy. Results: We show that, independent of tumor size, radiotherapy induced an increase in the overall oxygenation levels of the tumor. Further, this increase in the oxygenation of the tumor significantly correlated with a positive response to radiotherapy, as demonstrated by a reduction in tumor volume over the twenty-day monitoring period following therapy and histological staining. Conclusion: Our PALT imaging presented here is simple, fast, and non-invasive. Facilized by the PALT approach, imaging of tumor reoxygenation may be utilized as a simple, early indicator for evaluating cancer response to radiotherapy. Further characterization of the reoxygenation degree, temporal onset, and possible theragnostic implications are warranted.

When organic matter, especially sodium oxalate (Na2C2O4), accumulates to a certain extent, it will seriously affect the alumina production process in the refinery and therefore urgently needs to be removed. This work attempts to illuminate the benefits of ultrasonic intensification of the crystallization process of Na2C2O4, taking the alumina refinery waste liquor, i.e., flat plate washing liquor, as a case study. The effects of different operating parameters (seed crystal addition amount, caustic soda concentration, reaction time, ultrasonic power) on the crystallization behavior and yield are discussed, and it is found that ultrasonic can increase the Na2C2O4 removal rate to 70.4%. The addition of ultrasonic promotes the morphological evolution of Na2C2O4 and is of great significance to the optimization of the components of the precipitated Na2C2O4. Specifically, the proportion of Na2C2O4 in the crystallized product reaches 64% with conventional conditions, while it reaches 77% with ultrasonic conditions. Therefore, ultrasonic can greatly reduce the alkali loss caused by the crystallization process of Na2C2O4 in flat plate washing liquor, which has great economic benefits.

Recently, the plant extracts used to synthesize nanoparticles (NPs) have been considered an excellent alternative to physical and chemical ways. The applications of NPs in the fields of agriculture, industry, and medicine are so many and diverse that they cannot be counted. In recent years, silver nanoparticles (AgNPs) have attracted the consideration of several scientists because of their special characteristics and many applications in various fields, including optoelectronic catalysts, biological markers, and pharmaceutical and medical applications. In the current experiment, the cytotoxic potential of the properties of AgNPs green formulation using green tea on human colorectal cancer cells were determined. The NPs characterization was done by field emission-scanning electron microscopes, Fourier transform infrared spectroscopy, and X-ray diffraction analysis. The average diameter of the particles was about 35 nm. The presence of (111), (200), (220), and (311) peaks at the positions of 38°, 44°, 63°, and 77° indicate the presence of AgNPs, which confirms the correct synthesis of AgNPs. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay was used to measure anti-colorectal carcinoma (on HCT-8, HT-29, MDST8, HCA-7 Colony 29, HCT 116, and Ramos.2G6.4C10 cells) properties of AgNPs. The findings indicate that in 3 days, the cancer cell survival percentage in various dilations reduced as much as the NPs concentration increased. The best anticancer effect was reported at 1,000 μg/mL dilation. The IC50 was 141, 46, 149, 125, 125, and 44 µg/mL against HCT-8, HT-29, MDST8, HCA-7 Colony 29, HCT 116, and Ramos.2G6.4C10 colorectal cancer cells, respectively. The results indicated that these NPs could inhibit colorectal cancer cells more strongly than normal cells. After doing the clinical trial studies, the recent AgNPs are a suitable option for colorectal cancer treatment.

HONO is an important precursor for OH radicals that impact secondary-pollutant production. However, there are still large uncertainties about different HONO sources which hinder accurate predictions of HONO concentration and hence atmospheric oxidation capacity. Here HONO was measured during the EXPLORE-YRD campaign (EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation and their Effects in the Yangtze River Delta), along with other important parameters, enabling us to comprehensively investigate HONO variation characteristics and evaluate the relative importance of different HONO sources by using a box model. HONO showed significant variations, ranging from several tens of parts per thousand to 4.4 ppb. The average diurnal pattern of HONO / NOx showed a maximum of 0.17 around noon and resembled that of j(O1D), indicating the existence of photo-induced sources. Modeling simulations with only the default HONO source (OH + NO) largely underestimated HONO concentrations, with the modeled-averaged noontime HONO concentration an order of magnitude lower than the observed concentration. The calculated strength of the unknown HONO source (Punknown) showed a nearly symmetrical diurnal profile with a maximum of 2.5 ppb h−1 around noon. The correlation analysis and sensitivity tests showed that the photo-induced NO2 conversion on the ground was able to explain Punknown. Additional HONO sources incorporated into the box model improved the model's performance in simulating HONO concentrations. The revised box model reproduced the nighttime HONO concentration well but still underestimated the daytime HONO concentration. Further sensitivity tests indicated the underestimation of daytime HONO was not due to uncertainties of photo-induced NO2 uptake coefficients on the ground or aerosol surfaces or the enhancement factor of nitrate photolysis but was more likely due to other sources that were not considered in the model. Among the incorporated HONO sources and the default gas-phase source, photo-induced NO2 conversion on the ground dominated the modeled HONO production during the daytime, accounting for 71 % of the total, followed by NO + OH, NO2 hydrolysis on the ground surface, vehicle emissions, photo-induced NO2 conversion on the aerosol surface, nitrate photolysis and NO2 hydrolysis on the aerosol surface. NO2 hydrolysis on the ground surface was the major source of nighttime HONO, contributing 55 % of total HONO production. HONO photolysis contributed 43 % of ROx production during the daytime, followed by O3 photolysis (17 %), HCHO photolysis (14 %), ozonolysis of alkenes (12 %) and carbonyl photolysis (10 %). With observed HONO as a model constraint, the average peak of net ozone production rate increased by 88 % to 12.6 ppb h−1 compared to that without observed HONO as a model constraint, indicating HONO evidently enhanced O3 production and hence aggravated O3 pollution in summer seasons. Our study emphasized the importance of heterogeneous NO2 conversion on the ground surface in HONO production and accurate parameterization of HONO sources in predicting secondary-pollutant production.

The agricultural pest Drosophila suzukii exhibits a strong preference for feeding on fresh fruits, demonstrating high adaptability to sugary environments. Meanwhile, high sugar levels stimulate insulin secretion, thereby regulating the steady state of sugar metabolism. Understanding the mechanisms related to sugar metabolism in D. suzukii is crucial due to its adaptation to these specific environmental conditions. The insulin signaling pathway is an evolutionarily conserved phosphorylation cascade with significant roles in development and metabolism. We observed that the activation of the insulin signaling pathway inhibited FoxO activity and downregulated the expression of Pepck, thereby activating glycolysis and reducing glucose levels. By contrast, inhibiting insulin signaling increased the FoxO activity and upregulated the expression of Pepck, which activated gluconeogenesis and led to increased glucose levels. Our findings demonstrated the crucial role of the insulin signaling pathway in mediating glucose metabolism through the FoxO–Pepck axis, which supports the ecological adaptation of D. suzukii to high-sugar niches, thereby providing insights into its metabolic control and suggesting potential strategies for pest management. Elucidating these molecular processes is important for understanding metabolic regulation and ecological specialization in D. suzukii.

Alkaline water is toxic to cultured aquatic animals that frequently live in pH-neutral freshwater. Overfishing and habitat destruction have contributed to the decline in the wild sturgeon population; consequently, the domestic hybrid sturgeon has become an increasingly important commercial species in China. Hybrid sturgeons are widely cultured in alkaline water, but little is known about the effects of alkalinity stress on hybrid sturgeon liver tissues. We exposed hybrid sturgeons to four alkaline concentrations (3.14 ± 0.02 mmol/L, 7.57 ± 0.08 mmol/L, 11.78 ± 0.24 mmol/L and 15.46 ± 0.48 mmol/L). Histopathology, biochemical index assessment, gene expression level detection and metabolomics analysis were used to investigate the negative effects on liver functions following exposure to NaHCO3. Livers exposed to alkaline stress exhibited severe tissue injury and clear apoptotic characteristics. With increased exposure concentrations, the hepatic superoxide dismutase, catalase, glutathione peroxidase and alkaline phosphatase activities significantly decreased in a dose-dependent manner. NaHCO3 exposure up-regulated the transcriptional levels of apoptosis/ferroptosis-related genes in livers. Similarly, the expression trends of interleukin-1β and heat shock protein genes also increased in high-alkalinity environments. However, the expression levels of complement protein 3 significantly decreased (p < 0.05). Hepatic untargeted metabolomics revealed the alteration conditions of various metabolites associated with the antioxidant response, the ferroptosis process and amino acid metabolism (such as beta-alanine metabolism; alanine, aspartate and glutamate metabolism; and glycine, serine and threonine metabolism). These data provided evidence that NaHCO3 impaired immune functions and the integrity of hybrid sturgeon liver tissues by mediating oxidative-stress-mediated apoptosis and ferroptosis. Our results shed light on the breeding welfare of domestic hybrid sturgeons and promote the economic development of fisheries in China.

Human endogenous retroviruses (HERVs) are widely recognized as the result of exogenous retroviruses infecting the ancestral germline, stabilizing integration and vertical transmission during human genetic evolution. To date, endogenous retroviruses (ERVs) appear to have been selected for human physiological functions with the loss of retrotransposable capabilities. ERV elements were previously regarded as junk DNA for a long time. Since then, the aberrant activation and expression of ERVs have been observed in the development of many kinds of human diseases, and their role has been explored in a variety of human disorders such as cancer. The results show that specific ERV elements play respective crucial roles. Among them, long non-coding RNAs (lncRNAs) transcribed from specific long-terminal repeat regions of ERVs are often key factors. lncRNAs are over 200 nucleotides in size and typically bind to DNA, RNA, and proteins to perform biological functions. Dysregulated lncRNAs have been implicated in a variety of diseases. In particular, studies have shown that the aberrant expression of some ERV-derived lncRNAs has a tumor-suppressive or oncogenic effect, displaying significant functional bidirectionality. Therefore, theses lncRNAs have a promising future as novel biomarkers and therapeutic targets to explore the concise relationship between ERVs and cancers. In this review, we first summarize the role of ERV-derived lncRNAs in physiological regulation, mainly including immunomodulation, the maintenance of pluripotency, and erythropoiesis. In addition, pathological regulation examples of their aberrant activation and expression leading to carcinogenesis are highlighted, and specific mechanisms of occurrence are discussed.

Sirtuin 5 (SIRT5) plays an important role in the maintenance of lipid metabolism and in white adipose tissue browning. In this study, we established a mouse model for diet-induced obesity and the browning of white fat; combined with gene expression intervention, transcriptome sequencing, and cell molecular biology methods, the regulation and molecular mechanisms of SIRT5 on fat deposition and beige fat formation were studied. The results showed that the loss of SIRT5 in obese mice exacerbated white adipose tissue deposition and metabolic inflexibility. Furthermore, the deletion of SIRT5 in a white-fat-browning mouse increased the succinylation of uncoupling protein 1 (UCP1), resulting in a loss of the beiging capacity of the subcutaneous white adipose tissue and impaired cold tolerance. Mechanistically, the inhibition of SIRT5 results in impaired CCAAT/enhancer binding protein beta (C/EBPβ) expression in brown adipocytes, which in turn reduces the UCP1 transcriptional pathway. Thus, the transcription of UCP1 mediated by the SIRT5-C/EBPβ axis is critical in regulating energy balance and obesity-related metabolism.

Interaction errors are hard to avoid in the process of human–robot interaction (HRI). User emotions toward interaction errors could further affect the user’s attitudes to robots and experiences of HRI and so on. In this regard, the present study explores the effects of different factors on user emotions when interaction errors occur in HRI. There is sparse research directly studying this perspective. In so doing, three factors, including robot feedback, passive and active contexts, and previous user emotions, were considered. Two stages of online surveys with 465 participants were implemented to explore attitudes to robots and the self-reporting of emotions in active and passive HRI. Then, a Yanshee robot was selected as the experimental platform, and 61 participants were recruited for a real human–robot empirical study based on the two surveys. According to the results of statistical analysis, we conclude some design guides can cope with scenarios of interaction errors. For example, feedback and previous emotions have impacts on user emotions after encountering interaction errors, but contexts do not. There are no interactive effects between the three factors. The approach to reduce negative emotions in the cases of interaction errors in HRI, such as providing irrelevant feedback and so on, is also illustrated in the contributions.

Aiming at solving the problem of support failure caused by a large deformation of roadway surrounding rock in a deep soft coal seam, and taking the surrounding rock control of the roadway in the 11-2 coal seam in Zhujidong Coal Mine as the research background, numerical simulation and field industrial test and inspection methods were used to study the support effect of a supporting system of gob-side entry in deep soft coal seam. The deformation characteristics of various supporting systems of metal mesh, diamond mesh, metal mesh with anchor rod, steel ladder beam, M-shaped steel belt, 14#b channel steel, and 11# I-steel in the goaf supporting body of deep soft coal seam were studied under vertical load. The supporting effect of effective compressive stress zone generated by bolt and cable under different row spacings and lengths was analyzed, and the law of variation in the compressive stress field generated by supporting members with supporting parameters was explored. The length and interrow distance of bolt and cable were compared, respectively, and reasonable supporting parameters were selected. Based on the abovementioned research results and the geological conditions of the 1331 (1) track roadway, the support scheme of the 1331 (1) track roadway was designed, and the industrial test was carried out. The results show that the surrounding rock of the roadway is within the effective anchorage range of the supporting body, the active support function of the supporting components has been fully brought into play, and the overall control effect of the surrounding rock of the roadway is good, which can ensure the safety and stability of the goaf roadway. The maximum displacement of the roof and floor of the roadway is 86 mm, the maximum displacement of the solid coal side is 50 mm, the maximum displacement of the coal pillar side is 70 mm, and the maximum separation of layers is 22 mm. There is no failure phenomenon in relation to the anchor bolt and cable, and the overall deformation of the roadway surrounding the rock is good, which can provide some references for roadway-surrounding-rock control under similar conditions in deep coal seams.

The removal of cumulus cells from cumulus–oocyte complexes is a critical step in clinical in vitro fertilization. Since the oocyte is partially occluded by the surrounding cumulus cells and individual cumulus cells are small in size, it is difficult for embryologists to assess the oocyte's maturity before cumulus cell removal and to completely remove all the cumulus cells manually . Furthermore, it is easy for the oocyte to become lost inside the micropipette during aspiration due to the inaccuracy of manual control. To deal with these difficulties, a robotic system was developed to completely remove cumulus cells from mature oocytes. In this study, an EPSANet50 network was developed to accurately assess the maturity of oocytes, avoiding the removal of cumulus cells around the immature oocyte. An adaptive controller was designed to accurately position oocytes at the target position, reducing the loss of oocytes inside the micropipette. An improved Yolov5s network was proposed to quantify the number and size of cumulus cells and assess the completeness of cumulus cell removal. The experimental results on mouse cumulus–oocyte complexes showed that the robotic system had a higher success rate (98.0 ± 1.8% vs. 85.3 ± 2.4%) and lower discard rate (4.1 ± 2.7% vs. 19.6 ± 3.5%) than the manual operation. Moreover, a higher amplification rate and lower non-specific rate were also achieved by the robotic system in the subsequent genetic testing procedure, indicating reduced genetic contamination from the cumulus cells.

In the process of scratch defect detection in textured materials, there are often problems of low efficiency in traditional manual detection, large errors in machine vision, and difficulty in distinguishing defective scratches from the background texture. In order to solve these problems, we developed an enhanced scratch defect detection system for textured materials based on optimized photometric stereo vision and FFT-Gabor filtering. We designed and optimized a novel hemispherical image acquisition device that allows for selective lighting angles. This device integrates images captured under multiple light sources to obtain richer surface gradient information for textured materials, overcoming issues caused by high reflections or dark shadows under a single light source angle. At the same time, for the textured material, scratches and a textured background are difficult to distinguish; therefore, we introduced a Gabor filter-based convolution kernel, leveraging the fast Fourier transform (FFT), to perform convolution operations and spatial domain phase subtraction. This process effectively enhances the defect information while suppressing the textured background. The effectiveness and superiority of the proposed method were validated through material applicability experiments and comparative method evaluations using a variety of textured material samples. The results demonstrated a stable scratch capture success rate of 100% and a recognition detection success rate of 98.43% ± 1.0%.

As large-scale renewable energy sources are increasingly integrated into AC grids via voltage source converters (VSCs), the transient synchronization stability of phase-locked loop (PLL)-based VSCs during fault ride-through is gaining more attention. Most existing studies assume that the positive and negative sequence separation and current control dynamics are much faster than the PLL dynamics, thereby neglecting their impact on the transient synchronization stability of the system. However, when the PLL bandwidth is relatively large, ignoring the positive and negative sequence separation and current control dynamics may result in incorrect stability assessments. To address this issue, this paper first considers the multiple control loop coupling, including positive and negative sequence separation, current control, and PLL, to construct a full-order nonlinear mathematical model of the VSC grid-connected system under asymmetric fault conditions. Based on this, the phase trajectory method is employed to analyze the transient synchronization stability of the system. Additionally, this full-order mathematical model is used to determine the PLL bandwidth boundary beyond which the effects of positive and negative sequence separation and current control dynamics cannot be neglected. Finally, PSCAD/EMTDC simulation results validate the effectiveness of the theoretical analysis presented in this paper.

With the rapid development of the economy and the continuous improvement of people’s living standards, the printing and packaging industry plays an increasingly important role in people’s lives. The traditional printing industry is a discrete manufacturing industry, relying on a large amount of manpower and manual operation, low production efficiency, higher labor costs, wasting of resources, and other issues, so the realization of printing factory intelligence to improve the competitiveness of the industry is an important initiative. Automatic guided vehicles (AGVs) are an important part of an intelligent factory, serving the function of automatic transportation of materials and products. To optimize the movement paths of AGVs, enhance safety, and improve transportation efficiency and productivity, this paper proposes an alternative implementation of the A* algorithm. The proposed algorithm improves search efficiency and path smoothness by incorporating the grid obstacle rate and enhancing the heuristic function within the A* algorithm’s evaluation function. This introduces the evaluation subfunction of the nearest distance between the AGV, the known obstacle, and the unknown obstacle in the global path in the dynamic window approach (DWA algorithm), and reduces the interference of obstacles with the AGV in global path planning. Finally, the two improved algorithms are combined into a new fusion algorithm. The experimental results show that the search efficiency of the fusion algorithm significantly improved and the transportation time shortened. The path smoothness significantly improved, and the closest distance to obstacles increased, reducing the risk of collision. It can thus effectively improve the productivity of an intelligent printing factory and enhance its flexibility.

Accurate wind power prediction helps to fully utilize wind energy and improve the stability of the power grid. However, existing studies mostly analyze key wind power-related features equally without distinguishing the importance of different features. In addition, single models have limitations in fully extracting input feature information and capturing the time-dependent relationships of feature sequences, posing significant challenges to wind power prediction. To solve these problems, this paper presents a wind power forecasting approach that combines feature weighting and a combination model. Firstly, we use the attention mechanism to learn the weights of different input features, highlighting the more important features. Secondly, a Multi-Convolutional Neural Network (MCNN) with different convolutional kernels is employed to extract feature information comprehensively. Next, the extracted feature information is input into a Stacked BiLSTM (SBiLSTM) network to capture the temporal dependencies of the feature sequence. Finally, the prediction results are obtained. This article conducted four comparative experiments using measured data from wind farms. The experimental results demonstrate that the model has significant advantages; compared to the CNN-BiLSTM model, the mean absolute error, mean squared error, and root mean squared error of multi-step prediction at different prediction time resolutions are reduced by 35.59%, 59.84%, and 36.77% on average, respectively, and the coefficient of determination is increased by 1.35% on average.

Leaf angle (LA) is an important trait of plant architecture, and individuals with narrow LA can better capture canopy light under high-density planting, which is beneficial for increasing the overall yield per unit area. To study the genetic basis and molecular regulation mechanism of leaf angle in rapeseed, we carried out a series of experiments. Quantitative trait loci (QTL) mapping was performed using the RIL population, and seven QTLs were identified. Transcriptome analysis showed that the cell wall formation/biogenesis processes and biosynthesis/metabolism of cell wall components were the most enrichment classes. Most differentially expressed genes (DEGs) involved in the synthesis of lignin, xylan, and cellulose showed down-regulated expression in narrow leaf material. Microscopic analysis suggested that the cell size affected by the cell wall in the junction area of the stem and petiole was the main factor in leaf petiole angle (LPA) differences. Combining QTL mapping and RNA sequencing, five promising candidate genes BnaA01G0125600ZS, BnaA01G0135700ZS, BnaA01G0154600ZS, BnaA10G0154200ZS, and BnaC03G0294200ZS were identified in rapeseed, and most of them were involved in cell wall biogenesis and the synthesis/metabolism of cell wall components. The results of QTL, transcriptome analysis, and cytological analysis were highly consistent, collectively revealing that genes related to cell wall function played a crucial role in regulating the LA trait in rapeseed. The study provides further insights into LA traits, and the discovery of new QTLs and candidate genes is highly beneficial for genetic improvement.

Agropyron mongolicum Keng is a diploid perennial grass of triticeae in gramineae. It has strong drought resistance and developed roots that can effectively fix the soil and prevent soil erosion. GDSL lipase or esterases/lipase has a variety of functions, mainly focusing on plant abiotic stress response. In this study, a GDSL gene from A. mongolicum, designated as AmGDSL1, was successfully cloned and isolated. The subcellular localization of the AmGDSL1 gene (pCAMBIA1302-AmGDSL1-EGFP) results showed that the AmGDSL1 protein of A. mongolicum was only localized in the cytoplasm. When transferred into tobacco (Nicotiana benthamiana), the heterologous expression of AmGDSL1 led to enhanced drought tolerance. Under drought stress, AmGDSL1 overexpressing plants showed fewer wilting leaves, longer roots, and larger root surface area. These overexpression lines possessed higher superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and proline (PRO) activities. At the same time, the malondialdehyde (MDA) content was lower than that in wild-type (WT) tobacco. These findings shed light on the molecular mechanisms involved in the GDSL gene’s role in drought resistance, contributing to the discovery and utilization of drought-resistant genes in A. mongolicum for enhancing crop drought resistance.

The water jet nozzle is a penetrating drilling tool, which sends the pumped water to the nozzle through a high-pressure hose. It can work in a variety of working environments. When it dredges the blockage in the pipeline, its structural parameters will affect the jet flow field in the pipeline. Taking the self-propelled water jet nozzle as the research object, SolidWorks was used to establish the nozzle model with different parameter structures. Based on Fluent, the k-ε turbulence model was used to simulate the jet of nozzles with different nozzle sizes and arrangements in the pipeline. The distribution of the jet flow field and the change in velocity and displacement of nozzles with different parameters in the pipeline were compared, and then computational fluid dynamics (CFD) were used to process the simulation data for further research. The results show that when the inclination angle of the rear nozzle is 35°, the attenuation of the front jet velocity and the fluctuation of the wall fluid velocity are the smallest. When the nozzle aperture is increased from 2 mm to 3.5 mm, the vortex area inside the pipe is reduced, and the velocity attenuation of the front jet is also reduced, with the velocity attenuation rate decreasing by about 10%. This study provides a reference for the design and parameter optimization of self-propelled water jet nozzles.

In target-oriented multi-agent tasks, agents collaboratively achieve goals defined by specific objects, or targets, in their environment. The key to success is the effective coordination between agents and these targets, especially in dynamic environments where targets may shift. Agents must adeptly adjust to these changes and re-evaluate their target interactions. Inefficient coordination can lead to resource waste, extended task times, and lower overall performance. Addressing this challenge, we introduce the regulatory hierarchical multi-agent coordination (RHMC), a hierarchical reinforcement learning approach. RHMC divides the coordination task into two levels: a high-level policy, assigning targets based on environmental state, and a low-level policy, executing basic actions guided by individual target assignments and observations. Stabilizing RHMC’s high-level policy is crucial for effective learning. This stability is achieved by reward regularization, reducing reliance on the dynamic low-level policy. Such regularization ensures the high-level policy remains focused on broad coordination, not overly dependent on specific agent actions. By minimizing low-level policy dependence, RHMC adapts more seamlessly to environmental changes, boosting learning efficiency. Testing demonstrates RHMC’s superiority over existing methods in global reward and learning efficiency, highlighting its effectiveness in multi-agent coordination.

Ground settlement resulting from consolidation may lead to tilted buildings, cracks in the pavement, damage to underground utilities, etc. Therefore, it is crucial to understand the consolidation behaviors (including primary consolidation and secondary compression) of the soil of the subgrade. There is a large amount of soft clay deposited in Nanjing, located in the Yangtze River Basin. The consolidation behavior of Nanjing soft clay can significantly affect foundation design and the cost of construction. In this study, experimental measurements of the consolidation behavior of Nanjing soft clay were conducted, and parameters (such as pre-consolidation pressure, secondary consolidation index and secondary consolidation ratio) related to consolidation were assessed. The concept of simulated over-consolidation ratio (OCRs) was proposed, and the close relationship between primary consolidation and secondary compression settlement and the OCRs of Nanjing clay was investigated.

Connected Autonomous Vehicles (CAVs) have the potential to revolutionize traffic systems by autonomously handling complex maneuvers such as freeway ramp merging. However, the unpredictability of manual-driven vehicles (MDVs) poses a significant challenge. This study introduces a novel decision-making approach that incorporates the uncertainty of MDVs’ driving styles, aiming to enhance merging efficiency and safety. By framing the CAV-MDV interaction as an incomplete information static game, we categorize MDVs’ behaviors using a Gaussian Mixture Model–Support Vector Machine (GMM-SVM) method. The identified driving styles are then integrated into the flexible merging decision process, leveraging the concept of pure-strategy Nash equilibrium to determine optimal merging points and timing. A deep reinforcement learning algorithm is employed to refine CAVs’ control decisions, ensuring efficient right-of-way acquisition. Simulations at both micro and macro levels validate the method’s effectiveness, demonstrating improved merging success rates and overall traffic efficiency without compromising safety. The research contributes to the field by offering a sophisticated merging strategy that respects real-world driving behavior complexity, with potential for practical applications in urban traffic scenarios.

Soil nitrogen and phosphorus are directly related to soil quality and vegetation growth and are, therefore, a common research topic in studies on global climate change, material cycling, and information exchange in terrestrial ecosystems. However, collecting soil hyperspectral data under in situ conditions and predicting soil properties, which can effectively save time, manpower, material resources, and financial costs, have been generally undervalued. Recent optimization techniques have, however, addressed several of the limitations previously restricting this technique. In this study, hyperspectral data were taken from surface soils under different vegetation types in the wetlands of the Shaanxi Yellow River Wetland Provincial Nature Reserve. Through in situ original and first-order differential transformation spectral data, three prediction models for soil carbon, nitrogen, and phosphorus contents were established: partial least squares (PLSR), random forest (RF), and Gaussian process regression (GPR). The R2 and RMSR of the constructed models were then compared to select the optimal model for evaluating soil content. The soil organic carbon, total nitrogen, and total phosphorus content models established based on the first-order differential had a higher accuracy when modeling and during model validation than those of other models. Moreover, the PLSR model based on the original spectrum and the Gaussian process regression model had a superior inversion performance. These results provide solid theoretical and technical support for developing the optimal model for the quantitative inversion of wetland surface soil carbon, nitrogen, and phosphorus based on in situ hyperspectral technology.

Conductive metal–organic frameworks (c‐MOFs) have aroused extensive attention due to their excellent properties by integrating the features of both conductive and porous crystalline materials. Recent investigations in miniaturization of c‐MOFs into nanostructured conductive MOFs (nc‐MOFs) endow them with additional advantages such as reduced diffusion distance, accelerated mass/electron transfer, enhanced active site exposure, and accessibility, further widening their applications with reinforced performances compared to the conventional bulk counterparts. Herein, a timely review on the latest achievements in the field of nc‐MOFs is provided. First, we systematically introduce the synthetic strategies for producing nc‐MOFs with controllable morphologies and compositions. Second, the enhanced performance of nc‐MOFs in electrocatalysis, supercapacitors, batteries, sensors, and photocatalysis is highlighted. Finally, a discussion on the challenges and opportunities of the synthesis and applications of nc‐MOFs is presented. It is expected that this review will shed light on the future development of nc‐MOFs with promising application potential.

The phenomenon of cavitation within tubes is a common scenario in the fields of medicine and industry. This paper focuses on the effects of rigid circular tube length, diameter and the distance of bubble - tube port on the behavior of bubble in tube. The low-voltage discharge technique was utilized to induce a cavitation bubble in deionized water. The effects of rigid tube lengths, diameters, and bubble-tube port distances on the morphology of bubbles are observed using high-speed camera. It has been found that as the length of the rigid tube increases, so does the period, and this effect is more pronounced in tubes with smaller diameters. Conversely, the cavitation bubble period decreased and then stabilized as the tube diameter increased, the ratio of tube radius and the bubble radius exceeds 4.8, the period of bubble in tube is similar to that of bubble in free field. Further analysis of the influence of tube characteristics on microjets reveals that a pair of oppositely microjets were formed along the tube axis by the bubble near the midpoint of the tube axis. Moreover, when the non-dimensional tube length η

Silver ions are regarded as one of the most hazardous metal contaminants, endangering both the ecological environment and human health. Traditional silver ions detection technologies are hampered by their high cost, time-consuming nature, and labor-intensive operation. DNA aptamers play an essential part in the field of biosensors due to their ease of synthesis, ease of modification, and low cost. This paper focuses on reviewing the research progress of DNA aptamer-based biosensors in silver ions detection. According to the types of signal transduction, they are classified into four forms of signal transduction: fluorescent biosensors, colorimetric biosensors, electrochemical biosensors, and surface-enhanced Raman spectroscopy biosensors. In addition, this paper gives a perspective on the application prospects outlook and development directions of DNA aptamer-based biosensors, in order to provide theoretical ideas for the future development of more sensitive DNA aptamer biosensors for rapid detection of silver ions.

This study aimed to explore the possibility of improving the fertility of lunar soil through the reuse of resources by composting household waste and collecting composting fermentation broth. The fermentation broth was used to culture a simulated lunar soil at different concentration gradients for 30 days under aerobic and anaerobic conditions. Microbial biomass carbon and nitrogen content, typical mineral elements, and the microbial community were tested to determine whether the fertility of the lunar soil had improved. Results showed that the microorganisms in the simulated lunar soil samples successfully adhered and grew under both aerobic and anaerobic experimental conditions. The simulated lunar soil samples cultured in the anaerobic environment outperformed those in the aerobic environment regarding microbial biomass growth and water-soluble mineral elements. The study results create opportunities for the future reuse of domestic garbage on the lunar base, providing a technical basis for the in situ reuse of lunar soil resources for plant cultivation.

Futibatinib is an excellent fibroblast growth factor receptor 1–4 (FGFR 1–4) inhibitor that exhibits selective anti-tumor activeness against FGFR-deregulated tumors. A new high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) technique for the quantitative analysis of futibatinib in beagle dog plasma was developed, and the effect of Yinchenhao decoction (YCHD) on the pharmacokinetics of futibatinib was evaluated. After processing plasma samples with ethyl acetate extraction in the alkaline condition of sodium carbonate, a C18 column (4.6 mm × 150, 5 μm) was used to accomplish the separation of futibatinib and ripretinib (internal standard, ISTD), with the mobile phase consisting of methanol and 0.1% formic acid in water (60:40). The scanning method adopted a multiple reaction monitoring (MRM) mode with positive ion detection through the triple quadrupole mass spectrometer. The ion transitions for futibatinib and IS were m/z 419.20 → 296.15 and m/z 510.36 → 417.00, respectively. Futibatinib displayed excellent linearity in the range of 1–200 ng/mL. Neither inter-day nor intra-day precision exceeded 6.3%. The %RE values for accuracy ranged from −3.1% to 0.9%. The recovery, stability, and matrix effect of futibatinib also complied with the guidelines for the validation of quantitative analysis methods for biological samples in the 2020 edition of the Chinese Pharmacopoeia. In combination with YCHD, the Cmax of futibatinib increased by 40.84% compared to futibatinib dosage alone., and the AUC(0–t) and AUC(0–∞) of futibatinib increased by 78.06% and 82.71%, respectively. The Vd and CL of futibatinib were reduced by 20.05% and 40.85%, respectively. T1/2 was extended from 3.88 h to 5.26 h. The results indicated that YCHD could affect the pharmacokinetics of futibatinib and increase the plasma exposure of futibatinib. If YCHD is administered along with futibatinib, this study gives a first impression how pharmacokinetics and toxicokinetics would change.