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Anther and microspore cultures are efficient methods for inducing haploids in plants. The microspore culture by chromosome-doubling method can produce double haploid lines, developing pure lines within the first or second generations. This study aimed to induce haploid plants in Platycodon grandiflorum using the shed-microspore culture method. P. grandiflorum floral buds (n = 1503) were cultured in six types of medium to induce haploids. Anthers were placed on a solid–liquid double-layer medium and cold pre-treated at 9 °C for one week, followed by incubation in the dark at 25 °C. Embryogenesis was observed after approximately 70 days of culture, producing haploid plants through regeneration. Of the 1503 floral buds, embryos developed in 120 buds, resulting in the induction of 402 individuals. Among the media used, Schenk and Hildebrandt (SH) and 1/2SH exhibited high efficiency, with embryogenesis ratios of 12% and 13.4%, respectively. Additionally, the highest embryogenesis ratio (15.3%) was observed in flower buds sized 10 mm or less. Therefore, we established shed-microspore culture conditions to induce haploids in P. grandiflorum. Using this method, haploids can be efficiently induced in P. grandiflorum, shortening the breeding period by enabling the rapid development of inbred lines.

Although deep learning techniques have potential in vehicle behavior prediction, it is difficult to integrate traffic rules and environmental information. Moreover, its black-box nature leads to an opaque and difficult-to-interpret prediction process, limiting its acceptance in practical applications. In contrast, ontology reasoning, which can utilize human domain knowledge and mimic human reasoning, can provide reliable explanations for the speculative results. To address the limitations of the above deep learning methods in the field of vehicle behavior prediction, this paper proposes a front vehicle behavior prediction method that combines deep learning techniques with ontology reasoning. Specifically, YOLOv5s is first selected as the base model for recognizing the brake light status of vehicles. In order to further enhance the performance of the model in complex scenes and small target recognition, the Convolutional Block Attention Module (CBAM) is introduced. In addition, so as to balance the feature information of different scales more efficiently, a weighted bi-directional feature pyramid network (BIFPN) is introduced to replace the original PANet structure in YOLOv5s. Next, using a four-lane intersection as an application scenario, multiple factors affecting vehicle behavior are analyzed. Based on these factors, an ontology model for predicting front vehicle behavior is constructed. Finally, for the purpose of validating the effectiveness of the proposed method, we make our own brake light detection dataset. The accuracy and mAP@0.5 of the improved model on the self-made dataset are 3.9% and 2.5% higher than that of the original model, respectively. Afterwards, representative validation scenarios were selected for inference experiments. The ontology model created in this paper accurately reasoned out the behavior that the target vehicle would slow down until stopping and turning left. The reasonableness and practicality of the front vehicle behavior prediction method constructed in this paper are verified.

Single nucleotide variant (SNV) detection is pivotal in various fields, including disease diagnosis, viral screening, genetically modified organism (GMO) identification, and genotyping. However, detecting SNVs presents significant challenges due to the fragmentation of nucleic acids caused by cellular apoptosis, molecular shearing, and physical degradation processes such as heating. Fragmented nucleic acids often exhibit variable lengths and inconsistent breakpoints, complicating the accurate detection of SNVs. This article delves into the underlying causes of nucleic acid fragmentation and synthesizes the strengths and limitations of next-generation sequencing technology, high-resolution melting curves, molecular probes, and CRISPR-based approaches for SNV detection in fragmented nucleic acids. By providing a detailed comparative analysis, it seeks to offer valuable insights for researchers working to overcome the challenges of SNV detection in fragmented samples, ultimately advancing the accurate and efficient detection of single nucleotide variants across diverse applications.

The interaction between woody plants and mycorrhizal fungi is an important biological interaction; however, the driving factors behind the diversity of mycorrhizal trees formed through the symbiosis of mycorrhizal fungi and woody plants remain unclear. In this study, we collected and compiled the woody plant data of 34 forest dynamic plots containing 3350 species from habitats around the world and divided them into AM and EcM trees. We tested the contribution of AM and EcM trees to tree diversity and its components in forest communities worldwide. Our results showed that AM trees rather than EcM trees affect the tree diversity of forest communities, and that the diversity of AM trees has a significant latitudinal gradient pattern. Climate variables, especially temperature, are strongly correlated with the diversity patterns for AM trees rather than EcM trees. Topography is the most significant factor affecting the diversity of EcM trees. Our findings highlight the importance of AM trees for the tree diversity of forest communities worldwide. Our findings have important implications for understanding the response of complex woody plant communities with different types of mycorrhizal symbiosis to climate change.

With the progress of research on ocean thermal energy conversion, the stabI have checked and revised all. le operation of ocean thermal energy conversion experiments has become a problem that cannot be ignored. The control foundation for stable operation is the accurate prediction of operational performance. In order to achieve accurate prediction and optimization of the performance of the ocean thermal energy conversion experimental platform, this article analyzes the experimental parameters of the turbine based on the basic experimental data obtained from the 50 kW OTEC experimental platform. Through the selection and training of experimental data, a GA-BP-OTE (GBO) model that can automatically select the number of hidden layer nodes was established using seven input parameters. Bayesian optimization was used to complete the optimization of hyperparameters, greatly reducing the training time of the surrogate model. Analyzing the prediction results of the GBO model, it is concluded that the GBO model has better prediction accuracy and has a very low prediction error in the prediction of small temperature changes in ocean thermal energy, proving the progressiveness of the model proposed in this article. The dual-objective optimization problem of turbine grid-connected power and isentropic efficiency is solved. The results show that the change in isentropic efficiency of the permeable device is affected by the combined influence of the seven parameters selected in this study, with the mass flow rate of the working fluid having the greatest impact. The MAPE of the GBO model turbine grid-connected power is 0.24547%, the MAPE of the turbine isentropic efficiency is 0.04%, and the MAPE of the turbine speed is 0.33%. The Pareto-optimal solution for the turbine grid-connected power is 40.1792 kW, with an isentropic efficiency of 0.837439.

Morphology plays a crucial role in defining the optical, electronic, and mechanical properties of halide perovskite microcrystals. Therefore, developing strategies that offer precise control over crystal morphology during the growth process is highly desirable. This work presents a simple scheme to simultaneously grow distinct geometries of cesium lead bromide (CsPbBr3) microcrystals, including microrods (MR), microplates (MP), and microspheres (MS), in a single chemical vapor deposition (CVD) experiment. By strategically adjusting precursor evaporation temperatures, flux density, and the substrate temperature, we surpass previous techniques by achieving simultaneous yet selective growth of multiple CsPbBr3 geometries at distinct positions on the same substrate. This fine growth control is attributed to the synergistic variation in fluid flow dynamics, precursor substrate distance, and temperature across the substrate, offering regions suitable for the growth of different morphologies. Pertinently, perovskite MR are grown at the top, while MP and MS are observed at the center and bottom regions of the substrate, respectively. Structural analysis reveals high crystallinity and an orthorhombic phase of the as-grown perovskite microcrystals, while persistent photonic lasing manifests their nonlinear optical characteristics, underpinning their potential application for next-generation photonic and optoelectronic devices.

The digital divide (DD) reflects the inequality of the digital economy, while existing research lacks a comprehensive framework for investigating the measurement of DD and its determinants. This study constructs a new framework with a five-dimensional comprehensive index system. City-level data are used to measure China’s DD index from 2010 to 2020 at the national, regional, and provincial levels. Furthermore, this study investigates the decomposition of DD at both regional and provincial levels and the determinants of DD from the perspectives of physical, human, and social capital. The key results are: (1) China’s DD has generally exhibited a fluctuating downward trend. While it remains high in the eastern and western regions, it has shown a decline year by year. However, the DD within most provinces is on the rise. (2) The intra-regional and inter-provincial are the primary drivers of changes in national DD, with both intra-regional and intra-provincial contribution rates on the rise. (3) Economic growth, infrastructure, foreign trade, education, and online interaction significantly impact DD, and these determinants may change at different periods. This study intends to provide empirical support for bridging the DD, fostering the balanced development of the digital economy, and reducing social inequality.

Phenology is a critical mirror reflecting vegetation growth and has a major impact on terrestrial ecosystems. The Loess Plateau (LP) is a paramount ecological zone in China that has experienced considerable vegetation changes. However, understanding the dynamics of vegetation phenology is limited by ambiguous vegetation interpretation and anthropogenic-induced forces. This study combined the multi-climatic and anthropogenic datasets to characterize the interactions between phenology shifts and environmental variables. The principal findings were as follows: (1) Phenological shifts exhibit spatial heterogeneity and an interannually increasing trend in greenness (R2 > 0.6, p < 0.05). Notably, SOS (the start of the growing season) advances while EOS (the end of the growing season) delays in both the southeastern and northwestern regions. (2) SOS and EOS, primarily in the range of 100–150 and 285–320 days, respectively. Phenological changes vary depending on vegetation types. The forest has an early SOS, within 80–112 days, and a delayed EOS, within 288–320 days. The SOS of shrub is mainly within 80–144 days. (3) EOS shows a strong response to the preseason of each climate variable. Precipitation (R = 0.76), soil moisture (R = −0.64), and temperature (R = 0.89) are the governing determinants in shaping vegetation phenology. In addition, agriculture and urbanization play a significant role in shaping the spatial variations of SOS. These findings provide a basis for a systematic understanding of the processes that affect vegetation growth, which is crucial for maintaining the health and sustainability of arid and semiarid ecosystems.

The direct hydrogenation of greenhouse gas CO2 to higher alcohols (C2+OH) provides a new route for the production of high-value chemicals. Due to the difficulty of C-C coupling, the formation of higher alcohols is more difficult compared to that of other compounds. In this review, we summarize recent advances in the development of multifunctional catalysts, including noble metal catalysts, Co-based catalysts, Cu-based catalysts, Fe-based catalysts, and tandem catalysts for the direct hydrogenation of CO2 to higher alcohols. Possible reaction mechanisms are discussed based on the structure–activity relationship of the catalysts. The reaction-coupling strategy holds great potential to regulate the reaction network. The effects of the reaction conditions on CO2 hydrogenation are also analyzed. Finally, we discuss the challenges and potential opportunities for the further development of direct CO2 hydrogenation to higher alcohols.

Vitamin D is an essential nutrient with important immunomodulatory properties. As a fat-soluble compound, Vitamin D (and its D3 form) is immiscible with water, which presents challenges to absorption. In an in vitro setting, the current study characterizes novel micellar formulations of Vitamin D3 designed to improve absorption. Techniques used to evaluate and compare the micellar formulations against a non-micellar formula include the following: cryo-SEM to determine morphology; laser diffraction to determine particle size and distribution; zeta potential to determine stability of the particles; solubility assays to determine solubility in water and gastrointestinal media; and Caco-2 cell monolayers to determine intestinal permeability. Results show advantageous features (particle size range in the low micrometres with an average zeta potential of −51.56 ± 2.76 mV), as well as significant improvements in intestinal permeability, in one optimized micellar formula (LipoMicel®). When introduced to Caco-2 cells, LipoMicel’s permeability was significantly better than the control (p < 0.01; ANOVA). Findings of this study suggest that the novel micellar form of Vitamin D3 (LipoMicel) has the potential to promote absorption of Vitamin D3. Thus, it can serve as a promising candidate for follow-up in vivo studies in humans.

Soil bacteria are an important part of the forest ecosystem, and they play a crucial role in driving energy flow and material circulation. Currently, many uncertainties remain about how the composition and distribution patterns of bacterial communities change along altitude gradients, especially in forest ecosystems with strong altitude gradients in climate, vegetation, and soil properties. Based on dynamic site monitoring of the Baiyun Mountain Forest National Park (33°38′–33°42′ N, 111°47′–111°51′ E), this study used Illumina technology to sequence 120 soil samples at the site and explored the spatial distribution mechanisms and ecological processes of soil bacteria under different altitude gradients. Our results showed that the composition of soil bacterial communities varied significantly between different altitude gradients, affecting soil bacterial community building by influencing the balance between deterministic and stochastic processes; in addition, bacterial communities exhibited broader ecological niche widths and a greater degree of stochasticity under low-altitude conditions, implying that, at lower altitudes, community assembly is predominantly influenced by stochastic processes. Light was the dominant environmental factor that influenced variation in the entire bacterial community as well as other taxa across different altitude gradients. Moreover, changes in the altitude gradient could cause significant differences in the diversity and community composition of bacterial taxa. Our study revealed significant differences in bacterial community composition in the soil under different altitude gradients. The bacterial communities at low elevation gradients were mainly controlled by stochasticity processes, and bacterial community assembly was strongly influenced by deterministic processes at middle altitudes. Furthermore, light was an important environmental factor that affects differences. This study revealed that the change of altitude gradient had an important effect on the development of the soil bacterial community and provided a theoretical basis for the sustainable development and management of soil bacteria.

In this work, a modified numerical algorithm that couples the quasi-static theory with the mixed thermal elastohydrodynamic lubrication (mixed-TEHL) model is proposed to examine the mechanical properties and lubrication performance of the spindle bearing that is used in a high-speed machine tool with spinning. The non-Newtonian fluid characteristics of the lubricant and the non-Gaussian surface roughness are also considered. Moreover, the mechanical properties and lubrication state of the bearing are examined in various service environments. The results indicate that the temperature reduces the lubrication efficiency, which in turn exerts a significant impact on the mechanical properties. The lubrication that either behaves in the manner of Newtonian or non-Newtonian fluid has a relatively negligible influence on the bearing working state, while the non-Gaussian surface roughness significantly alters the oil film thickness and temperature. Calculations with different operating conditions demonstrate that the operating parameters (i.e., axial load, rotation speed) will directly affect the performance of the bearings via the changes in the oil film thickness and the temperature.

This study evaluated the differences in the metabolite profile of three n-3 FA fish oil formulations in 12 healthy participants: (1) standard softgels (STD) providing 600 mg n-3 FA; (2) enteric-coated softgels (ENT) providing 600 mg n-3 FA; (3) a new micellar formulation (LMF) providing 374 mg n-3 FA. The pharmacokinetics (PKs), such as the area under the plot of plasma concentration (AUC), and the peak blood concentration (Cmax) of the different FA metabolites including HDHAs, HETEs, HEPEs, RvD1, RvD5, RvE1, and RvE2, were determined over a total period of 24 h. Blood concentrations of EPA (26,920.0 ± 10,021.0 ng/mL·h) were significantly higher with respect to AUC0-24 following LMF treatment vs STD and ENT; when measured incrementally, blood concentrations of total n-3 FAs (EPA/DHA/DPA3) up to 11 times higher were observed for LMF vs STD (iAUC 0-24: 16,150.0 ± 5454.0 vs 1498.9 ± 443.0; p ≤ 0.0001). Significant differences in n-3 metabolites including oxylipins were found between STD and LMF with respect to 12-HEPE, 9-HEPE, 12-HETE, and RvD1; 9-HEPE levels were significantly higher following the STD vs. ENT treatment. Furthermore, within the scope of this study, changes in blood lipid levels (i.e., cholesterol, triglycerides, LDL, and HDL) were monitored in participants for up to 120 h post-treatment; a significant decrease in serum triglycerides was detected in participants (~20%) following the LMF treatment; no significant deviations from the baseline were detected for all the other lipid biomarkers in any of the treatment groups. Despite a lower administered dose, LMF provided higher blood concentrations of n-3 FAs and certain anti-inflammatory n-3 metabolites in human participants—potentially leading to better health outcomes.

The application of ICESAT-2 altimetry data in river hydrology critically depends on the accuracy of the mean water surface elevation (WSE) at a virtual station (VS) where satellite observations intersect solely with water. It is acknowledged that the ATL13 product has noise elevations of the adjacent land, resulting in biased high mean WSEs at VSs. Earlier studies have relied on human intervention or water masks to resolve this. Both approaches are unsatisfactory solutions for large river basins where the issue becomes pronounced due to many tributaries and meanders. There is no automated procedure to partition the truly representative water height from the totality of the along-track ICESAT-2 photon segments (portions of photon points along a beam) for increasing precision of the mean WSE at VSs. We have developed an automated approach called “auto-segmentation”. The accuracy of our method was assessed by comparing the ATL13-derived WSEs with direct water level observations at 10 different gauging stations on 37 different dates along the Lower Murray River, Australia. The concordance between the two datasets is significantly high and without detectable bias. In addition, we evaluated the effects of four methods for calculating the mean WSEs at VSs after auto-segmentation processing. Our results reveal that all methods perform almost equally well, with the same R2 value (0.998) and only subtle variations in RMSE (0.181–0.189 m) and MAE (0.130–0.142 m). We also found that the R2, RMSE and MAE are better under the high flow condition (0.999, 0.124 and 0.111 m) than those under the normal-low flow condition (0.997, 0.208 and 0.160 m). Overall, our auto-segmentation method is an effective and efficient approach for deriving accurate mean WSEs at river VSs. It will contribute to the improvement of ICESAT-2 ATL13 altimetry data utility on rivers.

Tert-butylhydroquinone (tBHQ) has emerged as a promising candidate for mitigating the adverse effects of T-2-induced reproductive toxicity. The protective effects of tBHQ on rat sperm quality, testicular injury, apoptosis, and inflammation induced by T-2 toxin exposure were investigated. Histopathological examination of testicular tissues revealed severe damage in the T-2-treated group, characterized by disorganized germ cell arrangement, thinning of the convoluted seminiferous tubule walls, and significant cellular necrosis. However, tBHQ administration, either as a preventive or therapeutic measure, mitigated this structural damage. Image analysis confirmed an increase in the cross-sectional area and height of the convoluted seminiferous tubules in the tBHQ-treated groups compared to the T-2-treated group (p < 0.05), indicating tBHQ’s efficacy in alleviating testicular damage. Additionally, tBHQ treatment significantly inhibited T-2-induced apoptosis of testicular tissue cells, as evidenced by the results showing reduced apoptotic cell counts and downregulation of the BAX/BCL2 ratio and caspase-3 expression (p < 0.05). tBHQ significantly increased the concentrations of the antioxidant factors SOD, CAT, TAC, and GSH-PX. Furthermore, tBHQ attenuated the inflammatory response induced by T-2 exposure, as indicated by the decreased mRNA expression of the proinflammatory cytokines Tnf, Il1, and Il10 in testicular tissue (p < 0.05). Additionally, tBHQ treatment alleviated the decline in serum testosterone induced by the T-2 and promoted testosterone synthesis gene expression, including for the genes 17β-HSD and Cyp11a1, in rat testes (p < 0.05). These findings underscore tBHQ’s role as a therapeutic agent combatting T-2-induced reproductive toxicity, highlighting its antioxidative, anti-apoptotic, and anti-inflammatory properties. Further elucidation of tBHQ’s mechanisms of action may offer novel strategies for preventing and treating reproductive disorders induced by environmental toxins.

Excessive column pile heave may result in engineering disasters such as instability of retaining structures and cracking of existing engineering piles in deep excavations. However, factors such as support weight, changeable support restraint resistance, and soil disturbance at the bottom of the excavation are often ignored or simplified in existing calculation methods but have a significant impact on the calculation results. Based on field soil parameters obtained by the rebound–recompression method, a semi-analytical method is proposed for estimating column pile heaves in a deep excavation. This method considers the influence of soil disturbance, the weight of the retaining structure, and the changeable horizontal support restraint, making the calculation result more consistent with the realistic situation. This method can also be used to analyze load transfer between the pile and the surrounding soil. The rationality of this proposed calculation method is verified by measured data, where the variation in pile stress state during deep excavation is analyzed. Finally, a parametric study is conducted, and the results show that the excavation size and the excavation depth have a great influence. However, the heave is hardly affected by the value of the limit relative displacement. The use of long piles with small diameter and the method of small block excavation are effective means to control the column pile heave. When the excavation area is large or the effective pile length is short, the factor of the position of the column pile cannot be ignored.

(1) Background: Sepsis-induced muscle atrophy is characterized by a loss of muscle mass and function which leads to decreased quality of life and worsens the long-term prognosis of patients. N-acetylcysteine (NAC) has powerful antioxidant and anti-inflammatory properties, and it relieves muscle wasting caused by several diseases, whereas its effect on sepsis-induced muscle atrophy has not been reported. The present study investigated the effect of NAC on sepsis-induced muscle atrophy and its possible mechanisms. (2) Methods: The effect of NAC on sepsis-induced muscle atrophy was assessed in vivo and in vitro using cecal ligation and puncture-operated (CLP) C57BL/6 mice and LPS-treated C2C12 myotubes. We used immunofluorescence staining to analyze changes in the cross-sectional area (CSA) of myofibers in mice and the myotube diameter of C2C12. Protein expressions were analyzed by Western blotting. (3) Results: In the septic mice, the atrophic response manifested as a reduction in skeletal muscle weight and myofiber cross-sectional area, which is mediated by muscle-specific ubiquitin ligases—muscle atrophy F-box (MAFbx)/Atrogin-1 and muscle ring finger 1 (MuRF1). NAC alleviated sepsis-induced skeletal muscle wasting and LPS-induced C2C12 myotube atrophy. Meanwhile, NAC inhibited the sepsis-induced activation of the endoplasmic reticulum (ER) stress signaling pathway. Furthermore, using 4-Phenylbutyric acid (4-PBA) to inhibit ER stress in LPS-treated C2C12 myotubes could partly abrogate the anti-muscle-atrophy effect of NAC. Finally, NAC alleviated myotube atrophy induced by the ER stress agonist Thapsigargin (Thap). (4) Conclusions: NAC can attenuate sepsis-induced muscle atrophy, which may be related to downregulating ER stress.

Facility agriculture is an important initiative to adopt an all-encompassing approach to food and build a diversified food supply system. Understanding the evolution of facility agricultural land and the factors that drive it can contribute to the development of scientifically strategic agricultural planning and agricultural modernization. Therefore, this paper constructs a “situation-structure-behavior-value” theoretical framework; quantifies the relevant driving factors (physical, proximal, and socioeconomic) and their impacts on the development and layout of facility agriculture land by using a multivariate logistic regression model; and provides a strategy for optimizing land use. The results showed that the area of facility agriculture in Huzhou is rapidly expanding. Regarding drivers, facility agricultural land tends to be located in areas with higher slopes according to plot selection. Facility agriculture is more likely to develop in plots with convenient transportation and closer proximity to markets. At the economic level, economic efficiency, agricultural resource superiority, and policies significantly impact facility agriculture expansion. Finally, we propose three land use policy options to facilitate the sustainable development of facility agriculture. This study elucidates the underlying factors driving different types of facility agricultural land and offers methodological guidance for policy support, planning, control, and optimization strategies for facility agriculture.

With the rapid development of intelligent manufacturing, modern components are accelerating toward being light weight, miniaturized, and complex, which provides a broad space for the application of rare earth permanent magnet materials. As an emerging near-net-shape manufacturing process, additive manufacturing (AM) has a short process flow and significantly reduces material loss and energy consumption, which brings new possibilities and impetus to the development of rare earth permanent magnetic materials. Here, the applications of AM technology in the field of rare earth permanent magnets in recent years are reviewed and prospected, including laser powder bed fusion (LPBF), fused deposition modeling (FDM), and binder jetting (BJ) techniques. Research has found that the magnetic properties of AM Nd-Fe-B magnets can reach or even exceed the traditional bonded magnets. In addition, in situ magnetic field alignment, in situ grain boundary infiltration, and post-processing methods are effective in enhancing the magnetic properties of AM magnets. These results have laid a good foundation for the development of AM rare earth permanent magnets.

IRAK4 is a critical mediator in NF-κB-regulated inflammatory signaling and has emerged as a promising therapeutic target for the treatment of autoimmune diseases; however, none of its inhibitors have received FDA approval. In this study, we identified a novel small-molecule IRAK4 kinase inhibitor, DW18134, with an IC50 value of 11.2 nM. DW18134 dose-dependently inhibited the phosphorylation of IRAK4 and IKK in primary peritoneal macrophages and RAW264.7 cells, inhibiting the secretion of TNF-α and IL-6 in both cell lines. The in vivo study demonstrated the efficacy of DW18134, significantly attenuating behavioral scores in an LPS-induced peritonitis model. Mechanistically, DW18134 reduced serum TNF-α and IL-6 levels and attenuated inflammatory tissue injury. By directly blocking IRAK4 activation, DW18134 diminished liver macrophage infiltration and the expression of related inflammatory cytokines in peritonitis mice. Additionally, in the DSS-induced colitis model, DW18134 significantly reduced the disease activity index (DAI) and normalized food and water intake and body weight. Furthermore, DW18134 restored intestinal damage and reduced inflammatory cytokine expression in mice by blocking the IRAK4 signaling pathway. Notably, DW18134 protected DSS-threatened intestinal barrier function by upregulating tight junction gene expression. In conclusion, our findings reported a novel IRAK4 inhibitor, DW18134, as a promising candidate for treating inflammatory diseases, including peritonitis and IBD.

In recent years, clean and renewable energy sources have received much attention to balance the contradiction between resource needs and environmental sustainability. Among them, ocean thermal energy conversion (OTEC), which consists of surface warm seawater and deep cold seawater, can rely on thermal cycling to generate electricity and has great potential in alleviating the energy crisis. In this paper, the design and experiment study of a 50 kW OTEC platform is proposed. Thermodynamic modeling, calculation, optimization, and engineering calibration of the system were carried out, and the thermal efficiency reached 2.63% to meet the power generation demand. Experiments were also carried out by using a heat pump unit to simulate hot and cold seawater environments, and data on the stable operation of the system were obtained, with the grid-connected power reaching 47.5 kW and a thermal efficiency of 2.46%. The accuracy of the design scheme is verified, and the theoretical basis and data support are provided for the practical development and application of ocean thermal energy conversion.

In this study, process control factors such as dipping time, heat treatment time and curing conditions were optimized to prepare N-Si network sol–gel-based coatings on a cotton fabric. The dipping time was varied from 14 h to 30 min, the heat treatment time at ~90 °C was varied between no heating conditions to 15 h and the curing was performed at 165 °C. The microstructure of the coating was analyzed using low electron scanning microscopy (LV-SEM), while a compositional study of the coated substrate was carried out using FTIR and EDS techniques. From the thermal and combustion analysis of the coated samples using thermogravimetric and vertical flame test techniques, significant resistance to the degradation process was observed, particularly in the initial stages, in addition to the highest char residue for DI-0.5 h-15~32.93%. Similarly, for DI–5 h–RT, the peak degradation temperature was around ~372 °C, accompanied by a notable char residue of approximately 31.12%. The flame spread and burning rate profile further supported the findings; DI-0.5 h-15 and DI-5 h-RT had the lowest flame spread.

The coupled seepage–stress action has a significant deterioration effect on the structural face of the hydraulic tunnel enclosure, which intensifies the shear rupture tendency of the deteriorated structural face of the rock mass. The plastic deformation of a typical I–II composite fissure was taken as the research object, the characteristics of the tip plastic zone of the composite fissure seepage rock were explored, and the influence law of osmotic pressure and fissure rock parameters (fissure dip angle, Poisson’s ratio, and fissure length) on the radius of the tip plastic zone was analyzed. Based on the Drucker–Prager yield criterion and the stress intensity factor of the composite fracture, the theoretical analytical formula of the fracture plastic zone radius under the action of high and low osmotic pressure was established, and the fracture rock plastic zone radius was significantly correlated with the fracture parameters. The radius of the plastic zone of fracture under low osmotic pressure evolves in a trend of decreasing–increasing–decreasing with the increase in fracture dip angle, and the peak radius of the plastic zone appears at 45°. Poisson’s ratio and fracture length have less influence on the radius of the plastic zone. The radius of the plastic zone of fracture under high osmotic pressure grows in an incremental nonlinear curve, and the peak radius of the plastic zone appears at 90°, being positively correlated with the length of fracture. This study can provide theoretical reference for the analysis of the stability of the surrounding rock in hydraulic tunnels.

Vibration-assisted micro milling is a promising technique for fabricating engineered mi-cro-scaled surface textures. This paper presents a novel approach for theoretical modeling of three-dimensional (3D) surface textures produced by vibration-assisted micro milling. The proposed model considers the effects of tool edge geometry, minimum uncut chip thickness (MUCT), and material elastic recovery. The surface texture formation under different machining parameters is simulated and analyzed through mathematical modeling. Two typical surface morphologies can be generated: wave-type and fish scale-type textures, depending on the phase difference between tool paths. A 2-degrees-of-freedom (2-DOF) vibration stage is also developed to provide vibration along the feed and cross-feed directions during micro-milling process. Micro-milling experiments on copper were carried out to verify the ability to fabricate controlled surface textures using the vibration stage. The simulated and experimentally generated surfaces show good agreement in geometry and dimensions. This work provides an accurate analytical model for vibration-assisted micro-milling surface generation and demonstrates its feasibility for efficient, flexible texturing.

Urbanization induces rapid plant environmental modifications, leading to alterations in plant diversity distribution patterns and plant homogenization. However, how plant diversity is distributed along urbanization gradients in regional urban agglomerations and its relationship with environmental factors are not well defined. In three nearby Henan Province Chinese cities—Zhengzhou, Kaifeng, and Zhongmu—along an urbanization gradient, the distribution pattern of plant diversity was quantified. Both native and non-native plants found in urban green spaces were taken into consideration. A total of 176 plant quadrats were selected and separated into three urbanization gradient types using space-constrained hierarchical clustering: urban core, urban suburb, and urban outskirt. Polynomial fitting was used to characterize the spatial distribution patterns of plants along the urbanization gradient, and Pearson correlation and the Mantel test were employed to examine the effects of environmental factors, including longitude, latitude, altitude, distance from the urban center, temperature, and illumination, on plant diversity. A total of 313 vascular plant species, comprising 137 woody species and 176 herbaceous species, were examined. Along the three urbanization gradients, remarkable variations in plant diversity for woody and herbaceous species were observed. The spatial patterns of plant diversity were consistent across cities, whereas woody plants and herbaceous plants displayed the opposite behavior. Distance to the city center and temperature were the most substantial environmental effect factors for the diversity of woody plants, whereas light factors had a major impact on herbaceous plants. These findings show different life-type plants are affected differently by urbanization, and they offer managers and planners a recommendation for increasing urban plant diversity by executing various interventions throughout the urban gradient.

Combining one-dimensional parameter optimization and three-dimensional modeling optimization, a 30 kW radial inflow turbine for ocean thermal energy conversion was designed. In this paper, the effects of blade tip clearance, blade number, twist angle, and wheel–diameter ratio on the radial inflow turbine were analyzed. The results show that the model prediction method based on 3D numerical simulation data can effectively complete secondary optimization of the radial turbine rotor. The prediction model can be used to directly obtain the optimal modeling parameter of the rotor. The tip clearance, blade number, twist angle, wheel–diameter ratio, and shaft efficiency were found to be 0.273 mm, 16, 43.378°, 0.241, and 88.467%, respectively. The optimized shaft efficiency of the turbine was found to be 2.239% higher than the one-dimensional design result, which is of great significance in reducing the system’s power generation costs and promoting the application of this approach in engineering power generation using ocean thermal energy.

The deterioration of the surrounding rock at the tunnel bottom is a damage mechanics issue that occurs under disturbance load. To investigate the anisotropic characteristics of mechanical behavior and the AE response mechanism of layered sandstone, uniaxial compression tests and acoustic emission (AE) monitoring were conducted. The results show that the layer structure causes remarkable anisotropic characteristics in the wave velocities. The strain characteristics and mechanical parameters of layered sandstone exhibit obvious deterioration effects. The local strain and overall strain show a synergistic feature, with the local strain path being more complex and the deformation response being extremely sensitive. The peak stress and elastic modulus both exhibit V-type distribution rules, slowly decreasing first, then rapidly decreasing, and finally increasing rapidly, with the boundary points of the layer angle being 45° and 67.50°. The peak stress and elastic modulus show a nonlinear exponential correlation with the layer angle, and the sandstone belongs to the intermediate anisotropy level. The rupture pattern shows significant anisotropic characteristics, with the failure modes including tension failure, including tension failure I and tension failure Ⅱ, shear failure, and tension–shear composite failure. The fractal dimension shows a negative correlation with the layer deterioration effect. The AE activity exhibits a phased response characteristic to the aging deformation of layer structure. The more obvious the layer deterioration effect is, the longer the AE delay is. The AE intensity of tensile failure sandstone is generally greater than that of oblique shear failure.

Berberine is a plant-origin quaternary isoquinoline alkaloid with a vast array of biological activities, including antioxidant and blood-glucose- and blood-lipid-lowering effects. However, its therapeutic potential is largely limited by its poor oral bioavailability. The aim of this study was to investigate the in vitro solubility and Caco-2 cell permeability followed by pharmacokinetic profiling in healthy volunteers of a new food-grade berberine delivery system (i.e., Berberine LipoMicel®). X-ray diffractometry (XRD), in vitro solubility, and Caco-2 cell permeability indicated higher bioavailability of LipoMicel Berberine (LMB) compared to the standard formulation. Increased aqueous solubility (up to 1.4-fold), as well as improved Caco-2 cell permeability of LMB (7.18 × 10−5 ± 7.89 × 10−6 cm/s), were observed when compared to standard/unformulated berberine (4.93 × 10−6 ± 4.28 × 10−7 cm/s). Demonstrating better uptake, LMB achieved significant increases in AUC0–24 and Cmax compared to the standard formulation (AUC: 78.2 ± 14.4 ng h/mL vs. 13.4 ± 1.97 ng h/mL, respectively; p < 0.05; Cmax: 15.8 ± 2.6 ng/mL vs. 1.67 ± 0.41 ng/mL) in a pilot study of healthy volunteers (n = 10). No adverse reactions were reported during the study period. In conclusion, LMB presents a highly bioavailable formula with superior absorption (up to six-fold) compared to standard berberine formulation and may, therefore, have the potential to improve the therapeutic efficacy of berberine. The study has been registered on ClinicalTrials.gov with Identifier NCT05370261.

This work proposed a novel model to simultaneously reconstruct temperature distribution and soot volume fraction field for two-dimensional thin-slice flames using the knowledge of monochromatic radiation intensities at two wavelengths using a CCD camera. The deduction process and numerical analysis of the model were described. Effects of wavelength combinations and measurement errors on reconstruction accuracy were considered in detail. Numerical results have proven the model’s accuracy and showed that the temperature and soot volume fraction fields can be reconstructed well even with noisy input data from flame radiation. In addition, a series of experiments were conducted on a mesoscale combustor to obtain the real thin-slice flames for further experimental reconstruction via the model. The experimental results indicated that the proposed model can successfully reconstruct the flame temperature distribution and soot volume fraction field and the main features of thin-slice flames also can be reasonably reproduced.

Phosphorus (P) is an essential macronutrient crucial for both plant growth and crop production, playing a pivotal role in agriculture since the early 20th century. The symbiotic relationship between AMF and plants serves as a classic illustration. These fungi play a regulatory role in the growth and development of plants, especially in facilitating the absorption of P and carbon molecules by plants. While there has been a growing body of research on the community assembly of arbuscular mycorrhizal fungi (AMF) in recent decades, our knowledge of the processes governing the coexistence of these AMF communities influenced by P in agroecosystems remains limited. To investigate the impact of various P fertilizers on AMF communities in temperate agroecosystems, this study was conducted using soils sourced from wheat–maize rotation farmland at Henan Agricultural University Yuanyang Base. With the Illumina MiSeq high-throughput sequencing technique, we systematically examined the taxonomic composition of soil AMF at the Yuanyang Base of Henan Agricultural University in a wheat–maize rotation agricultural field. Our primary objective was to unravel the mechanisms behind AMF community assembly and stability under varying P gradient fertilization conditions. Nonmetric Multidimensional Scaling (NMDS) analysis revealed significant differences among AMF communities in field soil subjected to various treatments (p < 0.05). A torus translations test demonstrated positive associations with the three treatments in 36 out of the 51 examined AMF operational taxonomic units (OTUs), making up 70.59% (p < 0.05) of the results. Furthermore, 37.84% (14/37) of the OTUs displayed preferences for the low P concentration treatment, while 34.29% (12/35) and 32.26% (10/31) favored medium and high P concentrations, respectively. An analysis of the Normalized Stochasticity Ratio (NST) and Checkerboard Score (C-score) indicated that in temperate agroecosystems, deterministic processes predominantly governed AMF in all treatment groups, with high P conditions exerting a stronger influence than low or medium P conditions. This study underscores the profound impact of long-term P fertilizer application on AMF community structures within temperate agricultural systems employing wheat–maize rotation. Additionally, it highlights the dominant role played by deterministic processes in shaping the assembly of AMF communities in these temperate agricultural systems that use P fertilizers. These findings emphasize the need for balanced nutrient management, particularly concerning P, to ensure the stability of AMF communities.

Resource-exhausted cities usually face problems of environmental degradation, landscape fragmentation, and impeded ecological mobility. By clarifying the spatial heterogeneity of ecological restoration needs, efficient and coordinated ecological protection and restoration can be carried out. This study selected Jiawang District, a typical resource-exhausted city, and constructed an ecological security evaluation framework to determine the ecological source area from the three aspects of ecosystem service importance, ecological sensitivity, and landscape stability. The resistance surface was corrected with ecological sensitivity evaluation data, and ecological corridors and ecological nodes were identified using circuit theory. Finally, it explored the spatial and temporal evolution of the key areas of territorial ecological restoration in Jiawang District. This study indicates that: (1) In 2000, 2010, and 2020, the ecological source areas were 123.59 km2, 116.18 km2, and 125.25 km2, and the corresponding numbers of ecological corridors were 53, 51, and 49. The total lengths of the ecological corridors were 129.25 km, 118.57 km, and 112.25 km, mainly distributed in the northern and central areas of the study area. (2) The study area contained 17, 13, and 19 ecological pinch points in 2000, 2010, and 2020, respectively, 16, 20, and 15 ecological obstacle points, and 8, 24, and 33 ecological fracture points, respectively. Targeted rehabilitation of these key areas can significantly improve ecological connectivity. (3) The key area of territorial ecological restoration in 2020 was composed of 125.25 km2 ecological source area, 8.77 km2 of ecological pinch point, 12.70 km2 of ecological obstacle point, and 33 ecological fracture points. According to the present situation of land use, protection strategies are put forward.

The form of community established by early Confucianism, represented by Confucius and Mencius, can be called the Ren Lun (人倫) community. This community order contains two interdependent dimensions: at the ethical level, it is primarily dominated by the parent-child relationship, with filial piety as its core dimension; at the moral level, its essence lies in the consciousness of human nature centered around Ren (仁), Yi (義), Li (禮) and Zhi (智) as its core, which goes beyond a mere universal human nature. This differs from the order of the Zong Fa (宗法) community in the Western Zhou Dynasty, whose axis is the way of brotherhood, with a vertical lineage connecting ancestors and descendants, in order to achieve unity and cohesion among the horizontal brother tribes. In the Zong Fa (宗法) community, morality and ethics are undifferentiated, and there is no distinction between individual and collective virtues, as well as ruling virtues and edifying virtues. The spiritual principle of the Zong Fa (宗法) community is Qin Qin Zun Zun (親親尊尊), which is both continuous and different from Ren Yi (仁義), revered by early Confucianism. Ren Yi (仁義) is extracted from Qin Qin Zun Zun (親親尊尊), but as a value principle, it possesses a higher universality. Qin Qin Zun Zun (親親尊尊) is a systemic principle closely tied to Zhou Li (周禮), while Ren Yi transcends the system as independent moral principles.

Background and Objectives: Angioembolization has emerged as an effective therapeutic approach for pelvic hemorrhages; however, its exact effect size concerning the level of embolized artery remains uncertain. Therefore, we conducted this systematic review and meta-analysis to investigate the effect size of embolization-related pelvic complications after nonselective angioembolization compared to that after selective angioembolization in patients with pelvic injury accompanying hemorrhage. Materials and Methods: Relevant articles were collected by searching the PubMed, EMBASE, and Cochrane databases until 24 June 2023. Meta-analyses were conducted using odds ratios (ORs) for binary outcomes. Quality assessment was conducted using the risk of bias tool in non-randomized studies of interventions. Results: Five studies examining 357 patients were included in the meta-analysis. Embolization-related pelvic complications did not significantly differ between patients with nonselective and selective angioembolization (OR 1.581, 95% confidence interval [CI] 0.592 to 4.225, I2 = 0%). However, in-hospital mortality was more likely to be higher in the nonselective group (OR 2.232, 95% CI 1.014 to 4.913, I2 = 0%) than in the selective group. In the quality assessment, two studies were found to have a moderate risk of bias, whereas two studies exhibited a serious risk of bias. Conclusions: Despite the favorable outcomes observed with nonselective angioembolization concerning embolization-related pelvic complications, determining the exact effect sizes was limited owing to the significant risk of bias and heterogeneity. Nonetheless, the low incidence of ischemic pelvic complications appears to be a promising result.

The North China agro–pastoral zone is a large, ecologically fragile zone in the arid and semi-arid regions. Quantitative remote sensing inversion of soil organic carbon (SOC) in this region can facilitate understanding of the current status of degraded land restoration and provide data support for carbon cycling research in the region. Deep learning (DNN) for SOC inversion has been W.a hot topic over the past decade, but there have been few studies at the regional scale in the arid and semi-arid zones. In this study, a DNN model with five hidden layers and five skip connections was established using 644 spatially distributed SOC samples and Landsat 8 OLI imagery. The model was compared with the random forest algorithm in terms of generalization ability. The main conclusions were as follows: 1. The DNN algorithm can establish a high-precision SOC inversion model (R2 = 0.52, RMSE = 0.7), with 90% of errors concentrated in the range of −2.5 to 2.5 kg·C/m2; 2. the Boruta variable-screening algorithm can effectively improve the model accuracy of the random forest algorithm, but due to the DNN’s better ability to mine hidden information in the data, the improvement effect on the DNN model accuracy is limited; 3. the SOC samples in arid and semi-arid areas are highly positively skewed, with a significant impact on the modeling accuracy of DNN, and conversion is required to obtain a model with better generalization ability; and 4. in arid and semi-arid regions, SOC has a weak correlation with vegetation indices but a stronger correlation with temperature, elevation, and aridity. This study established a reliable deep learning model for SOC density in a large arid and semi-arid region, providing a reference and framework for the establishment of SOC inversion models in other regions.

Simultaneously polarimetric radar (SPR) realizes the rapid measurement of a target’s polarimetric scattering matrix by transmitting orthogonal radar waveforms of good ambiguity function (AF) properties and receiving their echoes via two orthogonal polarimetric channels at the same time, e.g., horizontal (H) and vertical (V) channels (antennas) sharing the same phase center. The orthogonality of the transmitted waveforms can be realized using low-correlated phase-coded sequences in the H and V channels. However, the Doppler tolerances of the waveforms composed by such coded sequences are usually quite low, and it is hard to meet the requirement of accurate measurement regarding moving targets. In this paper, a joint design approach for unimodular orthogonal complementary sequences along with the optimal receiving filter is proposed based on the majorization–minimization (MM) method via alternate iteration for obtaining simultaneously polarimetric waveforms (SPWs) of good orthogonality and of the desired AF. During design, the objective function used for minimizing the sum of the complementary integration sidelobe level (CISL) and the complementary integration isolation level (CIIL) is constructed under the mismatch constraint of signal-to-noise ratio (SNR) loss. Different SPW examples are given to show the superior performance of our design in comparison with other designs. Finally, practical experiments implemented with different SPWs are conducted to show our advantages more realistically.

In this study, three typical and most extreme precipitation events in the history of North China are analyzed and compared in terms of accumulated precipitation and synoptical circulation using surface station observations of China and the ERA5 dataset. The three events happened in August 1963 (“63.8” event, hereafter), August 1975 (“75.8” event), and July 2021 (“21.7” event), respectively, mainly in Hebei and Henan Provinces of North China. The results show that the maximum daily and 4-day accumulated precipitation of all three events exceeded 500 mm and 800 mm, with many stations’ daily precipitation ranking Top 1. The “63.8” event persisted for the longest time, affected the largest area, and rained the most in 7 days (over 1000 mm). The “75.8” event was characterized by the most extreme daily precipitation and a concentrated area. All three events characterize a normal northward subtropical high that was located in North China and Northeast China. At 500 hPa, the area from South China to the South China Sea was dominated by a uniform pressure field. In the upper levels, there were troughs and divergence anomalies in all three events. In the low levels, there were anomalous low-level jets and the associated water vapor flux anomalies, which were located at different levels and came from different directions. Stable synoptical circulation and persistent jet and water vapor flux anomalies are the key factors in these extreme events.

The bioavailability and mobility of copper (Cu) in soil play a crucial role in its toxicity and impact on soil organisms. Humic substances, with their abundant functional groups and unique pore structure, have demonstrated the ability to effectively mitigate the toxic effects of heavy metals in soil. This study explores the potential of a soluble humic substance (HS) derived from leonardite for Cu removal from contaminated soils. The effects of various washing conditions, such as concentration and washing cycles, on removal efficiency were assessed. The results showed that a single washing with HS solution achieved an optimal removal efficiency of 37.5% for Cu in soil, with a subsequent reuse achieving a removal efficiency of over 30.5%. To further enhance Cu removal efficiency, a two-step soil washing approach using a chemical reductant NH2OH·HCl coupled with an HS solution (NH2OH·HCl + HS) was employed, resulting in an increased removal efficiency to 53.0%. Furthermore, this approach significantly reduced the plant availability and bioaccessibility of Cu by 13.6% and 11.4%, respectively. Compared to a single washing with NH2OH·HCl, both HS and NH2OH·HCl + HS increased the soil pH and organic matter content. These findings suggest that the two-step soil-washing approach using NH2OH·HCl + HS effectively removed Cu from polluted soil. This study demonstrates the potential of humic substances as environmentally friendly materials for remediating heavy metal-polluted soil, promoting green and sustainable applications in soil remediation practices.

Miniature sensors are key components for applications in the Internet of Things (IoT), wireless sensor networks, autonomous vehicles, smart cities, and smart manufacturing. As a miniature and self-powered magnetic sensor, the Wiegand sensor possesses advantageous traits including changing-rate-independent output, low cost, and remarkable repeatability and reliability. A typical Wiegand sensor requires hard magnetic pole pieces that provide external fields for triggering voltage outputs that are called Wiegand pulses. However, the wire-shaped sensing element of Wiegand sensors is the critical issue that limits the design, selection, and adoption of the external triggering magnets. Currently, the widely used pole piece materials are rare-earth magnets. However, adopting rare-earth magnets brings strong stray fields, causing an electromagnetic interference (EMI) problem. In this study, patterned CoNiP hard magnets were electrodeposited on flexible substrates through microfabrication. Origami magnetization was utilized to control the resultant stray fields and thus the pole piece of CoNiP magnets can successfully trigger the output of the Wiegand pulse. In comparison, the output voltage of the triggered pulse acquired through the patterned CoNiP magnets is comparable to that acquired by using the rare-earth magnets. Furthermore, both the volume (and hence the weight) of the Wiegand sensor and the EMI issue can be significantly reduced and mitigated, respectively, by the CoNiP magnets.

The primary carbide in high carbon chromium bearing steels, which arises from solute segregation during non-equilibrium solidification, is one of the key factors affecting the mechanical properties and performance of the related components. In this work, the effects of carbide forming element diffusion, primary austenite grain size, and the cooling rate on solute segregation and carbide precipitation during the solidification of an Fe–C binary alloy were studied by the phase-field method coupled with a thermodynamic database. It was clarified that increasing the ratio of solute diffusivity in solid and liquid, refining the grain size of primary austenite to lower than a critical value, and increasing the cooling rate can reduce the solute segregation and precipitation of primary carbide at late solidification. Two characteristic parameters were introduced to quantitatively evaluate the solute segregation during solidification including the phase fraction threshold of primary austenite when the solute concentration in liquid reaches the eutectic composition, and the maximum segregation ratio. Both parameters can be well-correlated to the ratio of solute diffusivity in solid and liquid, the grain size of primary austenite, and the cooling rate, which provides potential ways to control the solute segregation and precipitation of primary carbide in bearing steels.

Asbestos has been confirmed as a major pollutant in asbestos-mining areas that are located in western China. In general, asbestos-fibre dust will is released into the environment due to the effect of intensive industrial activities and improper environmental management, such that the health of residents in and around mining areas is jeopardised. A typical asbestos mining area served as an example in this study to analyse the content and fibre morphology of asbestos in soil and air samples in the mining area. The effects of asbestos pollution in and around the mining areas on human health were also assessed based on the U.S. Superfund Risk Assessment Framework in this study. As indicated by the results, different degrees of asbestos pollutions were present in the soil and air, and they were mainly concentrated in the mining area, the ore-dressing area, and the waste pile. The concentration of asbestos in the soil ranged from 0.3% to 91.92%, and the concentration of asbestos fibres in the air reached 0.008–0.145 f·cc−1. The results of the scanning-electron microscope (SEM) energy suggested that the asbestos was primarily strip-shaped, short columnar, and granular, and the asbestos morphology of the soils with higher degrees of pollution exhibited irregular strip-shaped fibre agglomeration. The excess lifetime cancer risk (ELCR) associated with the asbestos fibres in the air of the mining area was at an acceptable level (10−4–10−6), and 40.6% of the monitoring sites were subjected to unacceptable non-carcinogenic risks (HQ > 1). Moreover, the waste pile was the area with the highest non-carcinogenic risk, followed by the ore dressing area, a residential area, and a bare-land area in descending order. In the three scenarios of adult offices or residences in the mining area, adults’ outdoor activities in the peripheral residence areas, and children’s outdoor activities, the carcinogenic-and non-carcinogenic-risk-control values in the air reached 0.1438, 0.2225 and 0.1540 f·cc−1, and 0.0084, 0.0090 and 0.0090 f·cc−1, respectively. The results of this study will lay a scientific basis for the environmental management and governance of asbestos polluted sites in China.

Net primary productivity (NPP) is a main contributor to ecosystem carbon pools. It is crucial to monitor the spatial and temporal dynamics of NPP, as well as to assess the impacts of climate change and human activities to cope with global change. The dynamic of the NPP in China’s Yellow River Basin (YRB) from 2000 to 2019 and its influencing factors were analyzed by using trend and persistence tests and the GeoDetector method. The results show that the NPP had strong spatial heterogeneity, with a low NPP in the west and north, and a high NPP in the east and south. From 2000 to 2019, the NPP showed a statistically significant increase (at a mean of 5.5 g C m−2 yr−1, for a cumulative increase of 94.5 Tg C). A Hurst analysis showed that for the NPP in 76.3% of the YRB, the time series was anti-persistent. The spatial heterogeneity of the NPP in the YRB was mainly explained by precipitation and relative humidity (q value ranged from 0.24 to 0.44). However, the strength of the precipitation explained the decreased variation over time (q value decreased from 0.40 in 2000 to 0.26 in 2019). Interactions between the climate factors and human activities affected the NPP more strongly than individual factors. The results emphasize the importance of strengthening future research on the interaction between climate change and human activities. The results reveal the risk and optimal ranges of the driving factors and provide a quantification of the impacts of those factors regarding NPP. These findings can provide a scientific basis for vegetation restoration in the YRB.

Epiphytic bryophytes are important components of forest ecosystems and play important roles in maintaining biodiversity and ecosystem function. However, the main factors driving epiphytic bryophyte diversity remain unclear. We collected the tree epiphytic bryophytes from a one-hectare plot within a temperate deciduous broadleaf forest (China). Canonical correspondence analyses and Mantel tests were used to establish linear regression models and thus dissect the effects of environmental variables (topography, light and bark physicochemical properties) on the species diversity, functional diversity, and phylogenetic diversity of epiphytic bryophytes. The relationship between environmental variables and epiphytic bryophyte diversity was analyzed using piecewise structural equation modeling. Results showed that the physicochemical properties of the bark directly influenced the species diversity and phylogenetic diversity of the epiphytic bryophytes. The physical and chemical properties of bark also indirectly affected the functional diversity of the epiphytic bryophytes. Elucidation of the factors driving epiphytic bryophyte diversity provides insights into their conservation.

The dual oil circuit centrifugal fuel nozzle is made of martensitic stainless steel, which has complex morphological characteristics. The surface roughness characteristics of the fuel nozzle directly affect the degree of fuel atomization and the spray cone angle. The surface characterization of the fuel nozzle is investigated by the fractal analysis method. A sequence of images of an unheated treatment fuel nozzle and a heated treatment fuel nozzle are captured by the super-depth digital camera. The 3-D point cloud of the fuel nozzle is acquired by the shape from focus technique, and its three-dimensional (3-D) fractal dimensions are calculated and analyzed by the 3-D sandbox counting method. The proposed method can characterize the surface morphology well, including the standard metal processing surface and the fuel nozzle surface, and the experiments show that the 3-D surface fractal dimension is positively correlated with the surface roughness parameter. The 3-D surface fractal dimensions of the unheated treatment fuel nozzle were 2.6281, 2.8697, and 2.7620, compared with the heated treatment fuel nozzles dimensions of 2.3021, 2.5322, and 2.3327. Thus, the 3-D surface fractal dimension value of the unheated treatment is larger than that of the heated treatment and is sensitive to surface defects. This study indicates that the 3-D sandbox counting fractal dimension method is an effective method to evaluate the fuel nozzle surface and other metal processing surfaces.

Most microsensors are composed of devices and covers. Due to the complicated structure of the cover and various other requirements, it difficult to use wafer-level packaging with such microsensors. In particular, for monolithic microsensors combined with read-out ICs, the available process margins are further reduced due to the thermal and mechanical effects applied to IC wafers during the packaging process. This research proposes a low-temperature, wafer-level vacuum packaging technology based on Cu-Sn bonding and nano-multilayer getter materials for use with microbolometers. In Cu-Sn bonding, the Cu/Cu3Sn/Cu microstructure required to ensure reliability can be obtained by optimizing the bonding temperature, pressure, and time. The Zr-Ti-Ru based nanomultilayer getter coating inside the cap wafer with high step height has been improved by self-aligned shadow masking. The device pad, composed of bonded wafer, was opened by wafer grinding, and the thermoelectrical properties were evaluated at the wafer-level. The bonding strength and vacuum level were characterized by a shear test and thermoelectrical test using microbolometer test pixels. The vacuum level of the packaged samples showed very narrow distribution near 50 mTorr. This wafer-level packaging platform could be very useful for sensor development whereby high reliability and excellent mechanical/optical performance are both required. Due to its reliability and the low material cost and bonding temperature, this wafer-based packaging approach is suitable for commercial applications.

We consider a cosmological model in the framework of Einstein–Cartan theory with a single scalar torsion ϕ=ϕ(t) and reconstruct the torsion model corresponding to the holographic dark energy (HDE) density. By studying the corresponding relation between the effective energy density of torsion field ρϕ and holographic dark energy density ρHDE, we naturally obtain a kind of torsion field from the interacting holographic dark energy with interaction term Q=−2ϕρm and ρm is the energy density of matter. We analyze the reconstructed torsion model and find that the torsion field behaves like the quintessence (w>−1) or quintom (exhibiting a transition from w>−1 to w<−1) dark energy, depending on the value of the model parameter c. We then perform a stability analysis according to the squared sound speed. It is shown that the model is classically stable in the current epoch for the case of c<1. We also investigate the model from the viewpoint of statefinder parameters and it turns out that the statefinder trajectories in the r−s plane behave differently for the three cases of c and also quite distinct from those of other cosmological models. From the trajectories of the statefinder pair {q,r}, we find that, for all the three cases of c, the universe has a phase transition from deceleration to acceleration, consistently with cosmological observations. In addition, we fit the reconstructed torsion model with the recent Type Ia supernovae (SNe Ia) samples, i.e., the Pantheon sample containing 1048 SNe Ia with the redshift in the range 0.01

Soybean (Glycine max (Linn.) Merr.) is a widely-cultivated crop, the yield of which is markedly affected by adverse environmental conditions. Soil salinization, in particular, has led to the degradation of agricultural land, resulting in poor plant growth and decreased crop yields. In plants, serine/threonine protein kinases (STKs) are involved in the plant response to a variety of abiotic stresses. Our previous study identified a transcription factor (GmWRKY20) involved in plant stress resistance, which can directly regulate the expression of GmSTK12. Here, we investigated the effect of the stress-responsive gene GmSTK12 (Glyma.12g198200), which encodes a serine/threonine protein kinase, on soybean salt tolerance. Overall, the overexpression of GmSTK12 (GmSTK12-OE) resulted in increased salt tolerance. Under salt stress, GmSTK12-OE soybeans exhibited significantly increased chlorophyll and proline (PRO) contents; decreased relative electrical conductivity; decreased malondialdehyde (MDA) and superoxide anion (O2−) contents; and increased activities of the antioxidant enzymes catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD). The nitroblue tetrazolium chloride (NBT) staining experiment further confirmed the reduced accumulation of reactive oxygen species (ROS) in GmSTK12-OE soybean leaves. We further determined the Na+ and K+ contents in soybean leaves and roots and found that the Na+ content and Na+/K+ ratio in GmSTK12-OE soybean leaves and roots were significantly lower than those of WT (williams82) soybeans. Furthermore, quantitative real-time PCR (qRT-PCR) analysis revealed that the expression of three SOS pathway genes (GmSOS1, GmSOS2a, and GmSOS2b) was upregulated in GmSTK12-OE soybeans under salt stress. Taken together, the results indicate that GmSTK12 is involved in the mechanism of soybean response to salt stress.

Advanced carbon materials have played an important function in the field of energy conversion and storage. The green and low-carbon synthesis of elemental carbon with controllable morphology and microstructure is the main problem for carbon materials. Herein, we develop a green and low-carbon method to synthesize porous carbon by reacting CO2 with LiAlH4 at low temperatures. The starting reaction temperatures are as low as 142, 121, and 104 °C for LiAlH4 reacting with 1, 30, and 60 bar CO2, respectively. For the elemental carbon, the porosity of elemental carbon gradually decreased, whereas its graphitization degree increased as the CO2 pressure increased from 1 bar to 60 bar. CO2 serves as one of the two reactants and the CO2 pressure can adjust the thermodynamic and kinetic properties of the formation reaction for synthesizing elemental carbon. The mechanism for CO2 pressure-dependent microstructure and morphology of carbon is discussed on the basis of the formation reaction of elemental carbon and gas blowing effect of H2 and CO2. The elemental carbon with different morphology and microstructure exhibits distinct electrochemical lithium storage performance including reversible capacity, rate capability, cycling stability, and Coulombic efficiency, owing to their different lithium storage mechanism. The elemental carbon synthesized at 30 bar CO2 delivers the highest reversible capacity of 506 mAh g−1 after 1000 cycles even at 1.0 A g−1. Advanced energy storage technology based on the green and low-carbon synthesis of carbon materials is a requisite for providing a stable and sustainable energy supply to meet the ever-growing demand for energy.

Stability condition is of critical importance for methane hydrate exploitation, transportation, and reserves. This study measured the stability conditions of methane hydrate in fine-grained sediment with different dry densities (ρd = 1.40, 1.50 and 1.60 g/cm3) and various initial water saturations by the multi-step heating method. The experimental result showed that the methane hydrate formation in fine-grained sediment required lower temperature and/or higher pressure compared to that in bulk state. At the same time, it is found that the deviation degree of P–T conditions of methane hydrate in fine-grained sediment with different dry density and initial water saturation are completely different from that in pure water. In addition, according to the nuclear magnetic resonance technique (NMR), the changes in NMR signal intensity during the formation and decomposition of methane hydrate in silt were analyzed. Regardless of formation and dissociation stages, liquid water always distributes in the small sediment pores. An empirical formula is developed to address the capillary suction of water and hydrate with respect to the unhydrated water within sediment. Furthermore, a phase equilibrium model is proposed to predict the stability conditions of hydrate-bearing fine-grained sediment.

Dihydromyricetin (DHY), the main flavonoid component in Ampelopsis grossedentata, has important benefits for health. The present study aimed to investigate the exact effects and possible mechanisms of DHY on diabetic cardiomyopathy (DCM). Male C57BL/6 mice and sirtuin 3 (SIRT3) knockout (SIRT3-KO) mice were injected with streptozotocin (STZ) to induce a diabetic model. Two weeks later, DHY (250 mg/kg) or carboxymethylcellulose (CMC) were administrated once daily by gavage for twelve weeks. We found that DHY alleviated fasting blood glucose (FBG) and triglyceride (TG) as well as glycosylated hemoglobin (HbA1c) levels; increased fasting insulin (FINS); improved cardiac dysfunction; ameliorated myocardial hypertrophy, fibrosis and injury; suppressed oxidative stress, inflammasome and necroptosis; but improved SIRT3 expression in STZ-induced mice. Neonatal rat cardiomyocytes were pre-treated with DHY (80 μM) with or without high glucose (HG) stimulation. The results showed that DHY attenuated cell damage but improved SIRT3 expression and inhibited oxidative stress, inflammasome and necroptosis in cardiomyocytes with high glucose stimulation. Moreover, the above protective effects of DHY on DCM were unavailable in SIRT3-KO mice, implying a promising medical potential of DHY for DCM treatment. In sum, DHY improved cardiac dysfunction; ameliorated myocardial hypertrophy, fibrosis and injury; and suppressed oxidative stress, inflammation and necroptosis via SIRT3 activation in STZ-induced diabetic mice, suggesting DHY may serve as a candidate for an agent to attenuate diabetic cardiomyopathy.

Improving the hazard identification ability of workers is an important way to reduce safety accidents at construction sites. Although previous studies have succeeded in improving hazard identification performance, an important gap is that they consider only two factors, the worker’s safety experience and objective environmental conditions, to analyze the impact on hazard identification performance. To fill the above gap, a visual cognitive model of hazard identification was established. Sixteen field scenes were selected to represent construction sites in each environmental condition. Eye-movement data were extracted through eye-tracking experiments, and the differences between experts’ and novices’ gazes during danger recognition in these scenes were analyzed. The results indicate the following: bright construction sites can significantly improve the correct recognition rate and information processing in hazard identification; tidy construction sites can improve the search efficiency and correct recognition rate of hazard identification; safety experience can improve workers’ correct recognition rates and information processing; and reducing distractions can effectively improve the correct identification rate of hazards. Overall, optimal site brightness needs to be further studied to improve the efficiency of hazard search and reduce the distraction effect. This study provides recommendations for the direction of safety training and safety management on site.