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The deciduous tree hickory (Carya cathayensis) holds economic significance in China due to its high oil content, particularly in unsaturated fatty acids. Oil bodies are crucial for storing triacylglycerol (TAG), with caleosin serving as a predominant oil body protein that aids in oil body formation and stability maintenance. Our study utilized bioinformatics techniques to identify caleosin genes within Carya cathayensis, Carya illinoinensis, and Juglans regia. Three caleosin genes were discovered in the genomes of Carya cathayensis, Carya illi-noinensis, and Juglans regia. These genes encode hydrophilic proteins. Additionally, all caleosin proteins feature a single Ca2+-binding EF-hand, a conserved “proline knot” motif, and a C-terminal hydrophilic region with four potential phosphorylation sites. The caleosin proteins in Carya cathayensis consist of α-helix, β-corner, extended chain, and random curl structures. Cis-acting elements related to stress response and hormone signaling were identified in Carya cathayensis, Carya illinoinensis, and Juglans regia, with distinct cis-acting elements implicated in seed-specific regulation in Carya cathayensis. Additionally, subcellular localization analysis confirmed that CcaCLO1 and CcaCLO2 were localized within oil bodies. Transcriptome analysis and quantitative real-time polymerase chain reaction (qRT-PCR) data demonstrated a significant up-regulation of CcaCLO1 expression during the developmental stages of the Carya cathayensis embryo. Furthermore, qPCR findings indicated that caleosins from Carya cathayensis were responsive to salt stress, with a significant up-regulation of CcaCLO1 following exposure to salt stress treatment. Consequently, caleosin genes in Carya cathayensis, Carya illinoinensis, and Juglans regia share similar physicochemical characteristics and conserved motifs. Specifically, CcaCLO1 in Carya cathayensis primarily responds to embryo development and salt stress. These findings offer foundational insights for future investigations into the regulatory mechanisms of oil accumulation and response to salt stress in hickory.

(1) Background: CREB-binding protein (CBP) is a key transcriptional coactivator of androgen receptors (AR). We conducted this study to investigate the effects of CBP on AR expression and proliferation in benign prostatic hyperplasia (BPH) prostate epithelial cells. (2) Methods: By analyzing a published data set, we found that CBP was closely related to the gene expression of AR in prostate cells. We enrolled 20 BPH patients who underwent transurethral resection of the prostate (TURP) in Peking University First Hospital in 2022, and analyzed the expressions of CBP and AR in BPH prostate tissues. Then, we used ICG-001 and shRNA to inhibit CBP in prostate epithelial cells (BPH-1 cells and RWPE-1 cells), and conducted immunofluorescence, cell viability assay, flow cytometry analysis, and Western blot to analyze the effects of CBP on AR expression and proliferation in prostate epithelial cells. We also studied the interaction between CBP and AR through a co-immunoprecipitation assay. (3) Results: CBP is consistent with AR in expression intensity in prostate tissues. Inhibiting CBP decreases AR expression, and induces proliferation inhibition, apoptosis, and cell cycle arrest in BPH prostate epithelial cells. The co-immunoprecipitation assay showed that CBP binds with AR to form transcription complexes in prostate epithelial cells. (4) Conclusions: Inhibiting CBP decreases AR expression and inhibits proliferation in benign prostate epithelial cells. CBP may be a potential target to affect AR expression and the proliferation of prostate epithelial cells in BPH.

MIKC-type MADS-box genes, also known as type II genes, play a crucial role in regulating the formation of floral organs and reproductive development in plants. However, the genome-wide identification and characterization of type II genes as well as a transcriptomic survey of their potential roles in Carica papaya remain unresolved. Here, we identified and characterized 24 type II genes in the C. papaya genome, and investigated their evolutional scenario and potential roles with a widespread expression profile. The type II genes were divided into thirteen subclades, and gene loss events likely occurred in papaya, as evidenced by the contracted member size of most subclades. Gene duplication mainly contributed to MIKC-type gene formation in papaya, and the duplicated gene pairs displayed prevalent expression divergence, implying the evolutionary significance of gene duplication in shaping the diversity of type II genes in papaya. A large-scale transcriptome analysis of 152 samples indicated that different subclasses of these genes showed distinct expression patterns in various tissues, biotic stress response, and abiotic stress response, reflecting their divergent functions. The hub-network of male and female flowers and qRT-PCR suggested that TT16-3 and AGL8 participated in male flower development and seed germination. Overall, this study provides valuable insights into the evolution and functions of MIKC-type genes in C. papaya.

Microneedle puncture is a standard minimally invasive treatment and surgical method, which is widely used in extracting blood, tissues, and their secretions for pathological examination, needle-puncture-directed drug therapy, local anaesthesia, microwave ablation needle therapy, radiotherapy, and other procedures. The use of robots for microneedle puncture has become a worldwide research hotspot, and medical imaging navigation technology plays an essential role in preoperative robotic puncture path planning, intraoperative assisted puncture, and surgical efficacy detection. This paper introduces medical imaging technology and minimally invasive puncture robots, reviews the current status of research on the application of medical imaging navigation technology in minimally invasive puncture robots, and points out its future development trends and challenges.

Helicobacter pylori is a gastric pathogen that infects nearly half of the global population and is recognized as a group 1 carcinogen by the Word Health Organization. The global rise in antibiotic resistance has increased clinical challenges in treating H. pylori infections. Biofilm growth has been proposed to contribute to H. pylori’s chronic colonization of the host stomach, treatment failures, and the eventual development of gastric diseases. Several components of H. pylori have been identified to promote biofilm growth, and several of these may also facilitate antibiotic tolerance, including the extracellular matrix, outer membrane proteins, shifted morphology, modulated metabolism, efflux pumps, and virulence factors. Recent developments in therapeutic approaches targeting H. pylori biofilm have shown that synthetic compounds, such as small molecule drugs and plant-derived compounds, are effective at eradicating H. pylori biofilms. These combined topics highlight the necessity for biofilm-based research in H. pylori, to improve current H. pylori-targeted therapeutic approaches and alleviate relative public health burden. In this review we discuss recent discoveries that have decoded the life cycle of H. pylori biofilms and current biofilm-targeted treatment strategies.

Temperature and humidity profiles in the atmospheric boundary layer are essential for climate studies. The ground-based infrared hyperspectral spectrometer has the advantage of measuring radiances emitted from the atmosphere at a high temporal and moderate vertical resolution. In this article, the retrieval of temperature and humidity profiles from ground-based infrared hyperspectral observations is exploited. Although existing inversion algorithms based on physical models or statistical learning have made some progress, they still suffer from high computational complexity or poor performance. Motivated by the strength of the deep learning, we present a deep retrieval architecture (DReA) by skillfully designing a light-weight one-dimensional convolution neural network (CNN) to retrieve the temperature and humidity profiles. Experiments were conducted using atmospheric emitted radiance interferometer (AERI) and radiosonde data to demonstrate the superiority of the proposed DReA. The validation of the DReA with the radiosonde, using 802 profiles with 37 layers below 3 km, presents an excellent retrieval ability with a root mean square error (RMSE) of 0.87 K for the temperature and 1.06 g/kg for the water vapor mixing ratio. Furthermore, a thorough comparison with commonly used inversion methods such as the traditional back propagation (BP) and the eigenvector (EV) regression method, shows that our proposed DReA method obtains a leading solution in retrieving temperature and humidity profiles.

Oil recovery is an essential parameter for reservoir development performance evaluation, but there is no specific research on the theoretical oil recovery prediction model of polymer microspheres (PMs)’ conformance control. This research aims to establish an oil recovery prediction model that depends on the definition of oil recovery based on stream tube theory. PMs’ enhanced oil recovery mechanism is to plug the pore throat to expand the swept area. The assumption that the stream tube between injection and production wells is trapezoidal is proposed. Based on this premise, the area sweep efficiency equation suitable for the rhombus inverse nine-spot well pattern is established based on the stream tube theory. The vertical sweep efficiency equation is optimized by introducing the equivalent mobility ratio. Additionally, the model’s adaptability and validity are studied. The analysis results show that oil recovery decreases with increasing injection rate, injection concentration, and PMs size but increases with the increasing injection period. The theoretical oil recovery is 1.37%, and the actual oil recovery of the field application is 1.22%, with an error of 0.15%. This model has good consistency with the actual physical process of the field application. The oil recovery prediction model can provide oil recovery and optimize PMs’ conformance control injection scheme. This study fills the gap in the mathematical model for oil recovery prediction of PMs’ conformance control.

The application of wearable devices for fall detection has been the focus of much research over the past few years. One of the most common problems in established fall detection systems is the large number of false positives in the recognition schemes. In this paper, to make full use of the dependence between human joints and improve the accuracy and reliability of fall detection, a fall-recognition method based on the skeleton and spatial-temporal graph convolutional networks (ST-GCN) was proposed, using the human motion data of body joints acquired by inertial measurement units (IMUs). Firstly, the motion data of five inertial sensors were extracted from the UP-Fall dataset and a human skeleton model for fall detection was established through the natural connection relationship of body joints; after that, the ST-GCN-based fall-detection model was established to extract the motion features of human falls and the activities of daily living (ADLs) at the spatial and temporal scales for fall detection; then, the influence of two hyperparameters and window size on the algorithm performance was discussed; finally, the recognition results of ST-GCN were also compared with those of MLP, CNN, RNN, LSTM, TCN, TST, and MiniRocket. The experimental results showed that the ST-GCN fall-detection model outperformed the other seven algorithms in terms of accuracy, precision, recall, and F1-score. This study provides a new method for IMU-based fall detection, which has the reference significance for improving the accuracy and robustness of fall detection.

Background and objectives: Objective, accurate, and intuitive evaluation of knee joint function in patients with knee osteoarthritis (KOA) is important. This study aimed to clarify the gait characteristics of patients with bilateral KOA and their correlation with Western Ontario and McMaster University Osteoarthritis Index (WOMAC). Materials and Methods: 20 patients with bilateral KOA and 20 conditionally matched healthy individuals were enrolled in the experimental and control groups, respectively. Footscan and CODA motion gait analysis systems were used to analyse the gait parameters. Gait spatiotemporal parameters and knee joint motion parameters were collected. Weight-bearing balance and walking stability were assessed using discrete trends of relevant gait indicators. Patients in the experimental group were evaluated using WOMAC. Pearson’s correlation analysis was performed on the gait data and WOMAC score data of the experimental group. Results: Velocity, cadence, step length, and stride length of the experimental group were significantly lower than those of the control group (p < 0.01). Step time and gait cycle were significantly greater in the experimental group than in the control group (p < 0.01). Total stance and double-stance times of the experimental group were significantly greater than those of the control group (p < 0.01), whereas the single-stance time was shorter than that of the control group (p < 0.01). The range of motion and maximum flexion angle in the experimental group were significantly lower than those in the control group (p < 0.01), and the minimum angle of knee extension was greater than that in the control group (p < 0.01). The discrete trend of weight-bearing balance and walking stability gait index in the experimental group was greater than that in the control group. The WOMAC score and gait analysis were significantly correlated (p < 0.05). Conclusions: The gait function of patients with KOA is significantly worse than that of normal people. The WOMAC scale and gait analysis can be used to assess KOA severity from different perspectives with good consistency.

The Mu Us Sandy Land is a key region of man-made desert control and farmland to forest (grass) return in China. Despite global change and the strong influence of human activities, the vegetation in this region has been significantly improved and restored. In this study, multisource remote sensing data and multiple indicators were used to quantitatively monitor and evaluate the vegetation restoration status in this area. The driving factors were also analysed. The results show that in the past 20 years, nearly the entire Mu Us Sandy Land significantly and substantively recovered. The regional fractional vegetation cover increased, with an average annual growth rate of 0.59% and obvious spatial heterogeneity. The nine most important driving factors could comprehensively account for 58.38% of the spatial distribution of the vegetation coverage. Factors such as land use and land cover, the aridity index, and gross domestic product had the most significant impact, followed by precipitation and temperature. The results confirmed that the vegetation was restored and improved in the Mu Us Sandy Land and determined the main driving factors, which is helpful for vegetation restoration and ecological improvement on sandy land similar to the Mu Us Sandy Land.

The invariant imbedding T-matrix (IIM T-matrix) model is regarded as one of the most promising models for calculating the scattering parameters of non-spherical particles. However, the IIM T-matrix model needs to be iterated along the radial direction when calculating the T-matrix, which involves complex calculations such as matrix inversion and multiplication. Therefore, how to improve its computational efficiency is an important problem to be solved. Focused on particles with N-fold symmetric geometry, this paper deduced the symmetry in the calculation process of the IIM T-matrix model, derived the block iteration scheme of the T-matrix, and contracted the IIM T-matrix program for particles with N-fold symmetric geometry. Discrete Dipole Approximation (DDA) and Geometrical Optics Approximation (IGOA) were employed to verify the accuracy of the improved IIM T-matrix model. The results show that the six phase matrix elements (P11, P12/P11, P22/P11, P33/P11, P34/P11 and P44/P11) calculated by our model are in good agreement with other models. The computational efficiency of the improved IIM T-matrix model was further investigated. As demonstrated by the results, the computational efficiency for the particles with N-fold symmetry improved by nearly 70% with the improvement of the symmetry of U matrix and T matrix. In conclusion, the improved model can remarkably reduce the calculation time while maintaining high accuracy.

Celiac disease (CD) is an autoimmune intestinal disorder caused by the ingestion of gluten in people who carry the susceptible gene. In current celiac disease research, wheat gluten is often the main target of attention, neglecting the role played by non-gluten proteins. This study aimed to describe the effects of wheat amylase trypsin inhibitors (ATI, non-gluten proteins) and gliadin in BALB/c mice while exploring the further role of relevant adjuvants (cholera toxin, polyinosinic: polycytidylic acid and dextran sulfate sodium) intervention. An ex vivo splenocyte and intestinal tissue were collected for analysis of the inflammatory profile. The consumption of gliadin and ATI caused intestinal inflammation in mice. Moreover, the histopathology staining of four intestinal sections (duodenum, jejunum, terminal ileum, and middle colon) indicated that adjuvants, especially polyinosinic: polycytidylic acid, enhanced the villi damage and crypt hyperplasia in co-stimulation with ATI and gliadin murine model. Immunohistochemical results showed that tissue transglutaminase and IL-15 expression were significantly increased in the jejunal tissue of mice treated with ATI and gliadin. Similarly, the expression of inflammatory factors (TNF-α, IL-1β, IL-4, IL-13) and Th1/Th2 balance also showed that the inflammation response was significantly increased after co-stimulation with ATI and gliadin. This study provided new evidence for the role of wheat amylase trypsin inhibitors in the pathogenesis of celiac disease.

Infrared hyperspectral remote sensing has been widely used in the field of meteorology. Many scientists have carried out research on inversion methods of meteorological elements such as thermodynamic profile, boundary layer height, cloud base height, etc. In this study, a method based on machine learning for cloud detection using ground-based infrared hyperspectral radiation data is proposed. The features of outliers, the cloudy and cloud-free data of Atmospheric Emitted Radiance Interferometer (AERI) radiation are extracted. The “reference values” of cloudy and cloud-free are determined based on the observation data of Vaisala CL31 ceilometer within the time range of 8 min before the corresponding time of AERI. A support vector machine (SVM) algorithm is used for training. The dataset comes from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site and North Slope Alaska (NSA) site from 2015 to 2017, and the ARM West Antarctic Radiation Experiment (AWARE) site in 2016 is also analyzed. The instruments used in this paper include AERI, ceilometer, etc. The experimental results reveal that the agreement of cloud detection results between the proposed algorithm and ceilometer is about 93% at each site. However, for high clouds or optically thin clouds, the agreement will decrease.

The frequent and massive use of chlorfenapyr has led to pesticide residues in crops, threatening food safety and human health. However, there is limited research on the detection of tralopyril, which is the major metabolite of chlorfenapyr with high toxicity. This study aimed to develop a novel, sensitive, and highly efficient method for the determination of chlorfenapyr and tralopyril residues in 16 crops. The optimized purification procedure provided satisfactory recovery of 76.6–110%, with relative standard deviations of 1.3–11.1%. The quantification values of pesticides in crop matrixes were all 0.01 μg kg−1. The optimal method was adopted to determine the chlorfenapyr and tralopyril residues in field trials in 12 regions in China and monitor their residues in 16 agricultural products. The results of the dissipation and terminal residue experiments show that the final residue of chlorfenapyr was less than MRL (maximum residue limit) and no tralopyril was detected in the field samples. Moreover, the qualification proportion of these residues in market samples were up to 99.5%. The RQ (risk quotient) values of chlorfenapyr and chlorfenapyr with consideration of tralopyril were both apparently lower than an RQ of 100%, indicating an acceptable level. This research provides a thorough long-term dietary risk evaluation on chlorfenapyr and tralopyril and would provide reference for their scientific and safe utilization.

This article presents a new method for retrieving the Ice Water Path (IWP), the median volume equivalent sphere diameter (Dme) of thin ice clouds (IWP < 100 g/m2, Dme < 80 μm) in the Terahertz band. The upwelling brightness temperature depressions caused by the ice clouds at 325.15, 448.0, 664.0 and 874.0 GHz channels are simulated by the Atmospheric Radiative Transfer Simulator (ARTS). The simulated forward radiative transfer models are taken as historical data for the M5 model tree algorithm to construct a set of piecewise functions which represent the relation of simulated brightness temperature depressions and IWP. The inversion results are optimized by an empirical relation of the IWP and the Dme for thin ice clouds which is summarized by previous studies. We inverse IWP and Dme with the simulated brightness temperature and analyze the inversion performance of selected channels. The 874.4 ± 6.0 GHz channel provides the most accurate results, because of the strong brightness temperature response to the change of IWP in the forward radiative transfer model. In order to improve the thin ice clouds IWP and Dme retrieval accuracy at the middle-high frequency channels in Terahertz band, a dual-channel inversion method was proposed that combines the 448.0± 3.0 GHz and 664.0 ± 4.2 GHz channel. The error analysis shows that the results of the 874.4 ± 6.0 GHz channel and the dual-channel inversion are reliable, and the IWP inversion results meet the error requirement range proposed by previous studies.

Ice clouds play a critical role in the balance of the earth–atmosphere radiation system, but there are some limitations in the existing remote sensing methods for ice clouds. Terahertz wave is expected to be the best waveband for retrieving ice clouds, with terahertz wavelengths in the order of the size of typical ice cloud particles. An inversion method for the remote sensing of ice clouds at terahertz wavelengths based on genetic algorithm is proposed in this paper. First, suitable channel sets in the terahertz band, which are mainly a combination of absorption lines and window regions, are determined. Then, to improve the efficiency of the generation of the retrieval database, based on the brightness temperature simulated by the atmospheric radiative transfer simulator (ARTS) for different cloud parameters, a fast forward operator is constructed using three-dimensional interpolation to simulate the brightness temperature difference between clear sky and a cloudy scene. Finally, an inversion model to retrieve the ice cloud base height, the effective particle diameter and the ice water path is established based on the genetic algorithm, and an analysis of the inversion errors is performed. The results show that the forward operator, constructed by the nearest interpolation, can accurately calculate the brightness temperature difference at a high speed. The proposed inversion method at terahertz wavelengths based on the genetic algorithm can achieve the expected scientific requirement. The absolute error of the cloud height is around 0.2 km, and the absolute error of the low ice water path (below 20 g/m2) is small, while the relative error of the high ice water path is generally maintained at around 10%, and the absolute error of the effective particle diameter is mostly around 4 μm.

A method for identifying hydrometeor types (rain, graupel, and wet snow) based on a microwave link is proposed in this paper. The measured hydrometeor size distribution (HSD) data from the winters of 2014 to 2019 in Nanjing, China, were used to carry out simulation experiments to verify the performance of the model. Single-, dual-, and tri-frequency models (combinations of 15 GHz, 18 GHz, 25 GHz, 38 GHz, 50 GHz, 60 GHz, 70 GHz, and 80 GHz) were established with the extreme learning machine (ELM) algorithm. The results showed that the performance of the tri-frequency models was overall better than that of the dual-frequency models, for which the performance was better than that of the single-frequency models. The mean (maximum) test set accuracies of the single-frequency, dual-frequency, and tri-frequency models reached 75.8%, 80.7%, and 83.2% (83.0%, 84.4%, and 85.6%), respectively. For the dual-frequency and tri-frequency models, it was found that the accuracy increased with the overall frequency or the frequency difference. In addition, the influences of different noise levels on the model performance were also analyzed. Finally, the effects of position and length of link relative to precipitation cell were analyzed and are also discussed.

To improve solid precipitation monitoring in the hydrology and meteorology field, 1-min precipitation data observed by the PARticle SIze VELocity (PARSIVEL) disdrometer in Nanjing, eastern China, from February 2014 to February 2019 for all days with solid precipitation, were used to study the microphysical characteristics of winter precipitation. In this study, the empirical V-D (velocity−diameter) relationships and observed surface temperature are used for matching precipitation types, and the precipitation data are divided into rain, graupel, wet snow and dry snow. The results show that dry snow and wet snow have maximum Dm (mass-weighted mean diameter) and minimum log10Nw (normalized intercept parameter), while rain shows the opposite. Additionally, the μ-Λ (shape parameter−slope parameter) curve of dry snow and wet snow is very close, and the μ value of dry snow and wet snow is higher than that of graupel and higher than that of rain for the same Λ value. Furthermore, the Ze-S (equivalent reflectivity factor−precipitation intensity) relationships among different types of precipitation are significantly different. If only the Ze-S relationship of rain is used for quantitative precipitation estimation (QPE), then, for small precipitation intensity, solid precipitation will be overestimated, while, for large precipitation intensity, it will be underestimated.

The effects of water vapor ionization on the nonlinear propagation of femtosecond laser pulses with a 248 nm wavelength are numerically investigated in this paper. It is found that ionization of H2O molecules plays a significant role in air ionization, which seriously affects the dynamic and energy deposition of filamentation. The propagation of femtosecond pulses in air with different humidity levels are compared. The total number of electrons and total deposited pulse energy increase with the humidity increases. However, they tend to be saturated in high humidity conditions. Results presented here are conducive to characterizing the long-range propagation of filaments under atmospheric conditions.

Light scattering by non-spherical particles is an important factor influencing atmospheric radiative transfer. To accurately simulate the scattering properties of non-spherical particles, the Invariant Imbedded T-matrix method (IIM T-Matrix) is developed by combining the Lorenz−Mie theory and invariant imbedding technique. In this model, the non-spherical particle is regarded as an inhomogeneous sphere and discretized into multiple spherical layers in the spherical coordinate system. The T-matrix of the inscribed sphere is firstly calculated by the Lorenz−Mie theory, and then taking it as the initial value, the T-matrix is updated layer by layer by using the invariant imbedding technique. To improve the computational efficiency, the model is further parallelized by the OpenMP technique. To verify the simulation accuracy of the IIM T-Matrix method, the results of the model are compared with those of the EBCM (Extended Boundary Condition Method) T-Matrix method, DDA (Discrete Dipole Approximation) and MRTD (Multi-Resolution Time Domain). The results show that the scattering phase matrix simulated by the IIM T-Matrix method closely agrees with that of the well-tested models, indicating that the IIM T-Matrix method is a powerful tool for the light scattering simulation of non-spherical particles. Since the IIM T-Matrix method is derived from the volume integral equation, compared to the T-Matrix method which is based on surface integral principles (i.e., “EBCM” or the “null field method”), it can be applied to the scattering calculations of particle with arbitrary shapes and inhomogeneous compositions, which can greatly expand the application scope of the T-Matrix method.

Effectively using complementary property of various renewable energy sources by an integrated generation system is a concerned study. Considering the uncertainty of PV, spot price and load, the sizing of integrated generation system with combined market operation is a difficult problem. Based on the above uncertain factors, the sizing method of hydro-PV-pumped storage integrated generation system is proposed in this paper. The output characteristic model is established by utilizing the wide range of hydropower output and flexible schedulability of pumped storage. Then, the volatility ratio of the power exchange curve and load tracking coefficient are the evaluation index of the complementary effect, which ensures the stable and smooth output curve. Further, the uncertainty models of PV, spot price and load are established, considering that, the operation of the power generation system is optimized in the day-ahead market, and the predictive deviation of PV and load is balanced in a real-time market. Based on the above factors, the sizing model of the hydro-PV-pumped storage integrated energy system was proposed based on economics and complementary index. Finally, a case study was undertaken, the sensitivity analysis of the economy and complementarity indices was carried out, as the complementarity index is improved, the economy would be down. Further, the optimal sizing of hydro-PV-pumped storage integrated generation system was obtained, hydropower was a total of 165 MW, PV was 100 MW and pumped storage was 50 MW, that could ensure the economy while meeting the complementary index, the effectiveness of the model proposed was verified.

Tall fescue (Festuca arundinacea), an accumulator that is able to accumulate and excrete cadmium (Cd), has attracted much attention for its possible use in phytoremediation of heavy metal contaminated soils. In the present study, the interaction between Cd and Zn, and their uptake, translocation and accumulation under external Cd and Zn treatment in tall fescue were investigated. The concentrations of K, Ca, Mg in xylem sap under Cd and Zn treatment were measured to determine the level of mineral nutrients and their relationship with Cd alleviation. The result showed that Cd and Zn antagonized each other in the roots, while Cd antagonized Zn and Zn synergized Cd in the shoots of tall fescue. Compared with Cd only treatment, the concentrations of Ca, Mg and K in xylem sap increased after the addition of Zn, and they increased the most in the guttation. This result indicated that the addition of Zn facilitates the level of mineral elements to alleviate Cd toxicity, which might be used to improve the phytoremediation efficiency of Cd contaminated soils by tall fescue.

Retrieval of ice cloud properties using passive terahertz wave radiometer from space has gained increasing attention currently. A multi-channel regression inversion method for passive remote sensing of ice water path (IWP) in the terahertz band is presented. The characteristics of the upward terahertz radiation in the clear-sky and cloudy-sky are first analyzed using the Atmospheric Radiative Transfer Simulator (ARTS). Nine representative center frequencies with different offsets are selected to study the changes of terahertz radiation caused by microphysical parameters of ice clouds. Then, multiple linear regression method is applied to the inversion of IWP. Combinations of different channels are selected for regression to eliminate the influence of other factors (i.e., particle size and cloud height). The optimal fitting equation are obtained by the stepwise regression method using two oxygen absorption channels (118.75 ± 1.1 GHz, 118.75 ± 3.0 GHz), two water vapor absorption channels (183.31 ± 1.0 GHz, 183.31 ± 7.0 GHz), and two window channels (243.20 ± 2.5 GHz, 874.4 ± 6.0 GHz). Finally, the errors of the proposed inversion method are evaluated. The simulation results show that the absolute errors of this method for the low IWP cases are below 7 g/m2, and the relative errors for the high IWP cases are generally ranging from 10 to 30%, indicating that the multi-channel regression inversion method can achieve satisfactory accuracy.

Centipedegrass (Eremochloa ophiuroides) is a low-maintenance turfgrass. The first extensive green roof of centipedegrass was established in TongZhou Civil Squares in 2014. However, storm-water-runoff reduction, water-retention capacity, and plant-water requirements by a centipedegrass green roof has not yet been defined. The soil moisture dynamics, rainwater-retention capacity, runoff reduction, and plant evapotranspiration were investigated by simulated centipedegrass green roof plots, which were constructed in the same manner as the green roofs in TongZhou Civil Squares in 2018. The results showed that the centipedegrass green roof retained 705.54 mm of rainwater, which consisted 47.4% of runoff reduction. The saturated soil moisture was 33.4 ± 0.6%; the excess rainfall over the saturated soil moisture resulted in runoff. The capacity of rainwater retention was negatively related to the soil moisture before rain events and was driven by plant evapotranspiration. Drought symptoms only occurred three times over the course of a year when the soil moisture dropped down to 10.97%. Our results indicate that the rainwater retained in the soil almost met the needs of plant consumption; a further increase of rainwater retention capacity might achieve an irrigation-free design in a centipedegrass green roof.

A novel and simple method to improve the corrosion resistance of copper by constructing a three-dimensional (3D) 1-dodecanethiol self-assembled monolayer (SAM) in 3.5% NaCl solution is reported in this study. Several drops of 1% H3PO4 solution are thinly and uniformly distributed on copper surface to form a 3D nanostructure constituted by Cu3(PO4)2 nanoflowers. The anticorrosion properties of 1-dodecanethiol SAM on copper surface and on copper surface that is treated with H3PO4 solution were evaluated. Results demonstrated that 1-dodecanethiol SAM on bare copper surface exhibits good protection capacity, whereas a copper surface that is pretreated with H3PO4 solution can substantially enhance the corrosion resistance of 1-dodecanethiol SAM.

Developing an efficient power system is an important way for icebreakers to respond to high maneuverability and strong fluctuation loads under icebreaking conditions. The performance of power systems under short-period, regularly fluctuating load-sea conditions has been intensively studied. However, the performance of the power system in the face of a long-period, stochastic multi-frequency fluctuation icebreaking process has not been fully explored, especially the parameter uncertainty and battery cycle life. In this study, an integrated electric propulsion system with an optimal control strategy is suggested for improving the power system’s dynamic performance and battery cycle life. First, an energy flow model with a diesel–electric unit as the main body and coupled energy storage system/hybrid energy storage system has been constructed. A comparative analysis of rule-based and optimization-based energy management strategies has been performed, and an optimized strategy with dynamic programming as global regulation at the upper level and model predictive control at the lower level is suggested to integrate the slow and fast dynamic powers and achieve adaptability to strong fluctuation loads. In this control strategy, the uncertainties of energy storage system/hybrid energy storage system parameters have been introduced to eliminate their impact on the system performance. Then, the icebreaking process with multi-frequency fluctuation has been simulated, and the hybrid energy storage system with battery and supercapacitor is recommended to reach multi-objective with the lowest power fluctuation of diesel–electric unit, highest efficiency, and the minimum battery degradation. Finally, the fuel oil consumption and emissions of the hybrid energy storage system have been discussed, and the optimized strategy can save fuel oil by up to 5.33% and reduce the CO2 emission by 22% during the icebreaking process, exhibiting great potential in the environmental friendliness and significant advantages in terms of low fuel oil consumption.

On-orbit geometric calibration is key to improving the geometric positioning accuracy of high-resolution optical remote sensing satellite data. Grouped calibration with geometric consistency (GCGC) is proposed in this paper for the Jilin1-KF01B satellite, which is the world’s first satellite capable of providing 150-km swath width and 0.5-m resolution data. To ensure the geometric accuracy of high-resolution image data, the GCGC method conducts grouped calibration of the time delay integration charge-coupled device (TDI CCD). Each group independently calibrates the exterior orientation elements to address the multi-time synchronization issues between imaging processing system (IPS). An additional inter-chip geometric positioning consistency constraint is used to enhance geometric positioning consistency in the overlapping areas between adjacent CCDs. By combining image simulation techniques associated with spectral bands, the calibrated panchromatic data are used to generate simulated multispectral reference band image as control data, thereby enhancing the geometric alignment consistency between panchromatic and multispectral data. Experimental results show that the average seamless stitching accuracy of the basic products after calibration is better than 0.6 pixels, the positioning accuracy without ground control points(GCPs) is better than 20 m, the band-to-band registration accuracy is better than 0.3 pixels, the average geometric alignment consistency between panchromatic and multispectral data are better than 0.25 multispectral pixels, the geometric accuracy with GCPs is better than 2.1 m, and the geometric alignment consistency accuracy of multi-temporal data are better than 2 m. The GCGC method significantly improves the quality of image data from the Jilin1-KF01B satellite and provide important references and practical experience for the geometric calibration of other large-swath high-resolution remote sensing satellites.

To enhance the static and dynamic performance of the grinding wheel spindle system, with the gear grinding machine (YKF2060) as the research object, a static mechanics model of the spindle system was established based on Castigliano’s theorem, taking into account the equivalent effect of the triple-point contact ball bearing at the front end of the spindle. Meanwhile, based on the overall transfer matrix method, a dynamic model of the main spindle–eccentric shaft dual-rotor system was established, taking into account the effects of shear deformation and gyroscopic moments. On this basis, the effect of the spindle span, the front and rear overhang of the eccentric shaft, and the bearing stiffness on the static stiffness and first-order critical speed of the system was analyzed. Finally, static stiffness experiments, modal tests, and finite element simulation models were conducted to verify the static and dynamic models. The results show that the stiffness of the front outer bearing has the greatest influence on the static and dynamic performance of the system, while the stiffness of the rear inner bearing has the least influence. The relative errors of the static stiffness and the first two natural frequencies between static stiffness experiments, modal tests, and finite element simulation models are less than 10%, and the mode shapes match well. The established static and dynamic model can effectively reflect both the static and dynamic characteristics of the spindle system.

In this work, a novel heterogeneous catalyst consisting of peroxophosphotungstate, microporous MOF-808, and mesoporous SBA-15 was synthesized, characterized, and used to remove sulfides from model fuel. The prepared material, PW4@MOF-808@SBA-15, exhibits excellent catalytic activity with a desulfurization efficiency of 99.8% in 60 min for multicomponent simulated fuel, and the desulfurization rate can reach more than 90% after ten consecutive cycles. The excellent catalytic activity and reusability are attributed to the hierarchically porous hybrid material MOF-808@SBA-15, which can effectively encapsulate PW4 and provide a site for the oxidation of sulfides.

Substantial proteolysis occurs and free amino acids can be degraded to biogenic amines by decarboxylation during stylo (Stylosanthes guianensis) ensiling. High biogenic amine concentrations in silage are harmful to the health of ruminant animals. The purposes of this work were to (1) analyze the biogenic amines and amino acids concentrations, bacterial composition, and fermentation profile of spontaneously fermented stylo silage, (2) explore the effect of formic acid or sugar additive on these silage parameters, and (3) further reveal the correlations between silage amines and fermentation parameters, amino acids, and bacteria. Freshly chopped stylo was treated with distilled water (control), formic acid (4 mL/kg), and sugar (20 g/kg) and fermented for 28 days. The results indicated that putrescine (321 mg/kg dry matter), cadaverine (384 mg/kg dry matter), and tyramine (127 mg/kg dry matter) rapidly increased in concentration and become predominant in the control silage after 28 days of fermentation. Applying formic acid and sugar at ensiling, especially the acidifier, significantly decreased putrescine, cadaverine, tyramine, and total biogenic amine concentrations compared with the control treatment (p < 0.0001). Clostridium pabulibutyricum, Weissella cibaria and W. paramesenteroides were the predominant bacteria in the control silage, and the application of both additives remarkably lowered their relative abundance in comparison with the control treatment (p < 0.001). Correlation analysis showed that putrescine, cadaverine, and tyramine were positively related to pH, butyric acid, non-protein nitrogen, and ammonia nitrogen (p < 0.01). These amines also had significant correlations with C. pabulibutyricum, W. cibaria and W. paramesenteroides (p < 0.001). Putrescine, cadaverine, and tyramine were the main biogenic amines and C. pabulibutyricum was the predominant undesirable bacterium in naturally fermented stylo silage. C. pabulibutyricum, W. cibaria and W. paramesenteroides were positively related to putrescine, cadaverine, and tyramine formation. The application of formic acid or sugar significantly reduced the undesirable bacterial population and improved the fermentation and hygienic quality of the stylo silage. These findings lay the foundation for further elucidating the microbial mechanism underlying the main biogenic amine formation during fermentation of stylo silage.

The China–Russia crude oil pipeline (CRCOP) operates at a temperature that continuously thaws the surrounding permafrost, leading to secondary periglacial phenomena along the route. However, the evolution and formation mechanisms of these phenomena are still largely unknown. We used multi-temporal airborne light detection and ranging (LiDAR), geophysical, and field observation data to quantify the scale of ponding and icing, capture their dynamic development process, and reveal their development mechanisms. The results show that the average depth of ponding within 5 m on both sides of the pipeline was about 31 cm. The volumes of three icings (A–C) above the pipeline were 133 m3, 440 m3, and 186 m3, respectively. Icing development can be divided into six stages: pipe trench settlement, water accumulation in the pipe trench, ponding pressure caused by water surface freezing, the formation of ice cracks, water overflow, and icing. This study revealed the advantages of airborne LiDAR in monitoring the evolution of periglacial phenomena and provided a new insight on the development mechanisms of the phenomena by combining LiDAR with geophysics and field observation. The results of our study are of great significance for developing disaster countermeasures and ensuring the safe operation of buried pipelines.

Mulberry sclerotiniose is a devastating fungal disease of mulberry fruit and has been a limitation for the utility of mulberry fruits and the diversified development of sericulture. In the present study, we presented a workflow for screening candidate sclerotiniose-resistance genes and small secreted peptides (SSPs) based on a genome-wide annotation of SSPs and comparative transcriptome analysis of different mulberry varieties. A total of 1088 SSPs with expression evidence were identified and annotated in mulberry. A comprehensive analysis of the sclerotiniose-related RNA sequencing datasets showed that photosynthesis, plant hormone signaling, and metabolic pathways were the main pathways involved in the response to sclerotiniose. Fifty-two candidate sclerotiniose-response genes (SRGs), including 15 SSPs, were identified based on comparative transcriptome analysis. These SRGs are mainly involved in the hormone signaling pathway and cell wall biogenesis. Transient overexpression in tobacco and the knock-down of five SRGs affected the resistance against Ciboria shiraiana. MaMYB29, MaMES17, and MaSSP15 were primarily determined as negative regulators of plant resistance to C. shiraiana infection. Our results provide a foundation for controlling sclerotiniose in mulberry using genetic engineering and biological approaches such as spraying antifungal peptides.

The precise editing of genes mediated by CRISPR-Cas9 necessitates the application of donor DNA with appropriate lengths of homologous arms and fragment sizes. Our previous development, SSB/CRISPR-Cas9, has demonstrated high efficiency in homologous recombination and non-homologous end joining gene editing within bacteria. In this study, we optimized the lengths and sizes of homologous arms of the donor DNA within this system. Two sets of donor DNA constructs were generated: one set comprised donors with only 10–100 bp homologous arms, while the other set included donors with homologous arms ranging from 10–100 bp, between which was a tetracycline resistance expression cassette (1439 bp). These donor constructs were transformed into Escherichia coli MG1655 cells alongside pCas-SSB/pTargetF-lacZ. Notably, when the homologous arms ranged from 10 to 70 bp, the transformation efficiency of non-selectable donors was significantly higher than that of selectable donors. However, within the range of 10–100 bp homologous arm lengths, the homologous recombination rate of selectable donors was significantly higher than that of non-selectable donors, with the gap narrowing as the homologous arm length increased. For selectable donor DNA with homologous arm lengths of 10–60 bp, the homologous recombination rate increased linearly, reaching a plateau when the homologous arm length was between 60–100 bp. Conversely, for non-selectable donor DNA, the homologous recombination rate increased linearly with homologous arm lengths of 10–90 bp, plateauing at 90–100 bp. Editing two loci simultaneously with 100 bp homologous arms, whether selectable or non-selectable, showed no difference in transformation or homologous recombination rates. Editing three loci simultaneously with 100 bp non-selectable homologous arms resulted in a 45% homologous recombination rate. These results suggest that efficient homologous recombination gene editing mediated by SSB/CRISPR-Cas9 can be achieved using donor DNA with 90–100 bp non-selectable homologous arms or 60–100 bp selectable homologous arms.

The application potential of additive manufacturing nickel-based superalloys in aeroengines and gas turbines is extensive, and evaluating their mechanical properties is crucial for promoting the engineering application in load-bearing components. In this study, Hastelloy X alloy was prepared using the laser powder bed fusion process combined with solution heat treatment. The tensile and high cycle fatigue properties were experimentally investigated at room temperature as well as two typical elevated temperatures, 650 °C and 815 °C. It was found that, during elevated-temperature tensile deformation, the alloy exhibits significant serrated flow behavior, primarily observed during the initial stage of plastic deformation at 650 °C but occurring throughout the entire plastic deformation process at 815 °C. Notably, when deformation is small, sawtooth fluctuations are significantly higher at 815 °C compared to 650 °C. Irregular subsurface lack of fusion defects serve as primary sources for fatigue crack initiation in this alloy including both single-source and multi-source initiation mechanisms; moreover, oxidation on fracture surfaces is more prone to occur at elevated temperatures, particularly at 815 °C.

The critical role of the rumen microbiota in the growth performance of livestock is recognized, yet its significance in determining the body weight of goat kids before weaning remains less understood. To bridge this gap, our study delved into the rumen microbiota, serum metabolome, rumen fermentation, and rumen development in goat kids with contrasting body weights before weaning. We selected 10 goat kids from a cohort of 100, categorized into low body weight (LBW, 5.56 ± 0.98 kg) and high body weight (HBW, 9.51 ± 1.01 kg) groups. The study involved sampling rumen contents, tissues, and serum from these animals. Our findings showed that the HBW goat kids showed significant enrichment of VFA-producing bacteria, particularly microbiota taxa within the Prevotellaceae genera (UCG-001, UCG-003, and UCG-004) and the Prevotella genus. This enrichment correlated with elevated acetate and butyrate levels, positively influencing rumen papillae development. Additionally, it was associated with elevated serum levels of glucose, total cholesterol, and triglycerides. The serum metabonomic analysis revealed marked differences in fatty acid metabolism between the LBW and HBW groups, particularly in encompassing oleic acid and both long-chain saturated and polyunsaturated fatty acids. Further correlational analysis underscored a significant positive association between Prevotellaceae_UCG-001 and specific lipids, such as phosphatidylcholine (PC) (22:5/18:3) and PC (20:3/20:1) (r > 0.60, p < 0.05). In summary, this study underscores the pivotal role of the rumen microbiota in goat kids’ weight and its correlation with specific serum metabolites. These insights could pave the way for innovative strategies aimed at improving animal body weight through targeted modulation of the rumen microbiota.

Liquefied natural gas (LNG) is widely regarded as the midterm solution toward zero-carbon transportation at sea. However, further applications of gas engines are challenging due to their weak dynamic load performance. Therefore, the comprehension of and improvements in the dynamic performance of gas-engine-based power systems are necessary and urgent. A detailed review of research on mechanisms, modeling, and optimization is indispensable to summarize current studies and solutions. Developments in engine air-path systems and power system load control have been summarized and compared. Mechanism studies and modeling methods for engine dynamic performance were investigated and concluded considering the trade-off between precision and simulation cost. Beyond existing studies, this review provides insights into the challenges and potential pathways for future applications in decarbonization and energy diversification. For further utilization of clean fuels, like ammonia and hydrogen, the need for advanced air–fuel ratio control becomes apparent. These measures should be grounded in a deep understanding of current gas engines and the combustion characteristics of new fuels. Additionally, the inherent low inertia feature of electric power systems, and consequently the weak dynamic performance when adopting renewable energies, must be considered and studied to ensure system reliability and safety during transient conditions.

Climate warming has resulted in significant changes in permafrost in Northeast China, leading to notable alterations in soil organic carbon (SOC) stocks. These changes are crucial for both the global carbon cycle and climate change, as well as directly impacting the sustainable development of ecosystems. In order to examine the SOC dynamics and the impact of permafrost changes on SOC, we investigate the changes of permafrost extent based on a regression model and TTOP (top temperature of permafrost) model and the relationship between land use and land cover (LULC), SOC stocks, and permafrost changes in Northeast China. The results showing a shrinking permafrost area from 37.43 × 104 km2 to 16.48 × 104 km2 during the period from the 1980s to the 2010s in Northeast China, and the SOC stock decreased by 24.18 Tg C from the 1980s to the 1990s and then rapidly increased by 102.84 Tg C in the 2000s. Permafrost degradation speeds up the succession of LULC, impacting about 90% of the SOC in permafrost regions. The relationship between permafrost changes and SOC in Northeast China shows that permafrost degradation significantly reduces SOC stocks in the short term but increases SOC stocks in the long term, and that LULC play a crucial role in regulating this relationship. The goals of this study are to acquire an understanding of permafrost status and deepening insights into the dynamics of SOC. Simultaneously, the study aims to furnish valuable scientific references for shaping policies on sustainable land use and management in the future, all the while advancing the cause of ecological equilibrium and sustainable development in Northeast China and other areas.

The Daxing’anling forest region represents a crucial forestry hub in China and confronts some of the nation’s most severe freezing–thawing hazards. This study delved into the temporal trends and spatial distributions of various parameters related to freezing and thawing, including air temperature, ground surface temperature, freezing index, thawing index, and freezing–thawing frequency. Furthermore, this study assessed and delineated freezing–thawing hazards within the research area. The findings revealed a rapid increase in air temperature and ground surface temperature within the Daxing’anling forest region yet a lower rate of increase in ground surface temperature compared to Northeast China. Latitude had the strongest influence on mean annual air temperature, mean annual ground surface temperature, air freezing index, air thawing index, ground surface freezing index, ground surface thawing index, air freezing–thawing frequency, and ground surface freezing–thawing frequency, followed by longitude and elevation. Overall, freezing index, and air freezing–thawing frequency increased from south to north, whereas mean annual air temperature, mean annual ground surface temperature, air thawing index, ground surface thawing index, and ground surface freezing–thawing frequency decreased from south to north. The assessment outcomes underscore the importance of closely monitoring freezing–thawing hazards in regions north of the 50th parallel.

The anisotropy of mechanical properties in SLMed alloy is very important. In order to realize the homogeneity of the microstructure and mechanical properties of GH3536 alloy prepared by selective laser melting (SLM), the as-deposited samples were treated by hot isostatic pressing and then forged at different temperatures. The microstructure, grain size, room- and high- temperature tensile properties, and endurance properties of the samples were studied. The results showed that the microstructure of the sample was mainly equiaxed austenite phase, and granular carbides were precipitated inside the grains after forging treatment, resulting in the anisotropy of the sample almost disappearing. The grain boundary phase difference distribution was most concentrated at 60°. The grain size was less than 10 μm, and a large number of twins were formed. With the increase in forging temperature, the yield strength, tensile strength, and contraction of area of the samples changed little, and the properties parallel to the z-axis (parallel samples) and vertical to the z-axis (vertical samples) were almost the same. In particular, the yield strength, tensile strength, and contraction of area in the transverse and vertical samples were almost at the same level. Judging from the elongation after fracture and the contraction of area, the properties of the samples showed characteristics of anisotropy after a high temperature endurance test.

The present study aims to investigate effects of total flavonoids from Taraxacum mongolicum Hand.-Mazz. (FT) on fermentation quality, antioxidant status, and microbial community of Caragana korshinskii Kom. (CK) silage. CK was ensiled with no additive (CON), 1% FT, and 2% FT on a fresh weight (FW) basis for 60 days. The results showed that 1% FT and 2% FT groups displayed higher DM content than CON group, and 2% FT group had the best effect on nutrient preservation. Compared with CON and 1% FT groups, 2% FT group exhibited the best silage fermentation quality and the highest antioxidant activity, including increased lactic acid, acetic acid concentrations, and the activities of antioxidant enzymes, as well as decreased pH and the ammonia nitrogen (NH3-N) concentration. Moreover, the addition of 2% FT significantly affected the microbial community, such as increased abundance of Lactobacillus and decreased abundances of Pseudomonas and unidentified Cyanobacteria. The abundances of Lactobacillus parafarraginis and Lactobacillus brevis were negatively correlated to pH, while they were positively correlated with T-AOC, GSH-Px, and CAT activities. In conclusion, 2% FT may be used as additives to promote the fermentation quality and antioxidant activity of CK silage.