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In recent years, the application of free-form surface spatial grid structures in large public buildings has become increasingly common. The layouts of grids are important factors that affect both the mechanical performance and aesthetic appeal of such structures. To achieve a triangular grid with good mechanical performance and uniformity on free-form surfaces, this study proposes a new method called the “strain energy gradient optimization method”. The grid topology is optimized to maximize the overall stiffness, by analyzing the sensitivity of nodal coordinates to the overall strain energy. The results indicate that the overall strain energy of the optimized grid has decreased, indicating an improvement in the structural stiffness. Specifically, compared to the initial grid, the optimized grid has a 30% decrease in strain energy and a 43.3% decrease in maximum nodal displacement. To optimize the smoothness of the grid, the study further applies the Laplacian grid smoothing method. Compared to the mechanically adjusted grid, the structural mechanical performance does not significantly change after smoothing, while the geometric indicators are noticeably improved, with smoother lines and regular shapes. On the other hand, compared to the initial grid, the smoothed grid has a 21.4% decrease in strain energy and a 28.3% decrease in maximum nodal displacement.

Ferroptosis is a recently identified iron-dependent programmed cell death with lipid peroxide accumulation and condensation and compaction of mitochondria. A recent study indicated that ferroptosis plays a pivotal role in ischemic cardiac injury with the mechanisms remain largely unknown. This study demonstrates that when an iron overload occurs in the ischemia/reperfusion cardiac tissues, which initiates myocardial ferroptosis, the expression levels of mitochondrial inner membrane protein MPV17 are reduced. Overexpression of MPV17 delivered via adenovirus significantly reduced ferroptosis in both cardiomyocytes with high levels of iron and cardiac I/R tissues. Mitochondrial glutathione (mtGSH), crucial for reactive oxygen species scavenging and mitochondrial homeostasis maintenance, is depleted in myocardial ferroptosis caused by iron overload. This mechanistic study shows that MPV17 can increase mitochondrial glutathione levels through maintaining the protein homeostasis of SLC25A10, which is a mitochondrial inner-membrane glutathione transporter. The absence of MPV17 in iron overload resulted in the ubiquitination-dependent degradation of SLC25A10, leading to impaired mitochondrial glutathione import. Moreover, we found that MPV17 was the targeted gene of Nrf2, which plays a pivotal role in preventing lipid peroxide accumulation and ferroptosis. The decreased expression levels of Nrf2 led to the inactivation of MPV17 in iron overload-induced myocardial ferroptosis. In summary, this study demonstrates the critical role of MPV17 in protecting cardiomyocytes from ferroptosis and elucidates the Nrf2-MPV17-SLC25A10/mitochondrial glutathione signaling pathway in the regulation of myocardial ferroptosis.

Lead (Pb) and cadmium (Cd) are toxic pollutants that are prevalent in wastewater and pose a serious threat to the natural environment. In this study, a new immobilized bacterial microsphere (CYB-SA) was prepared from corn stalk biochar and Klebsiella grimontii by sodium alginate encapsulation and vacuum freeze-drying technology. The removal effect of CYB-SA on Pb(II) and Cd(II) in a monometallic contaminated solution was studied. The results showed that the removal of Pb(II) and Cd(II) by CYB-SA was 99.14% and 83.35% at a dosage of 2.0 g/L and pH = 7, respectively, which was 10.77% and 18.58% higher than that of biochar alone. According to the Langmuir isotherm model, the maximum adsorption capacities of Pb(II) and Cd(II) by CYB-SA at 40 °C were 278.69 mg/g and 71.75 mg/g, respectively. A combination of the kinetic model, the isothermal adsorption model, scanning electron microscopy–energy dispersive X-ray spectroscopy (SEM-EDS), X-ray photoelectron spectroscopy (XPS) and Fourier-transform infrared spectroscopy (FTIR) analyses showed that the main adsorption mechanisms of CYB-SA encompass functional group complexation, ion exchange, electrostatic attraction and physical adsorption. The findings of this study offer practical and theoretical insights into the development of highly efficient adsorbents for heavy metals.

Natural gas hydrates are a clean and efficient new energy source with the potential to replace conventional energy, holding significant production value. Studying hydrate accumulation systems is fundamental for hydrate resource evaluation and target reservoir selection. The Shenhu area of the South China Sea has abundant hydrate resources, and drilling data show that the hydrate distribution in this area exhibits noticeable heterogeneity. Aiming at this phenomenon, we used a novel thermo-flow/chemical coupled simulator to simulate the hydrate accumulation system based on the actual geological strata and provide a detailed depiction of the evolution of components in the process. The results indicate that favorable migration conditions can accelerate hydrate formation. However, to achieve the rapid formation of thick, high-saturation hydrate layers, the fluid migration conditions must be complemented by effective fluid aggregation conditions. Furthermore, a sensitivity analysis of the fault morphology was conducted, revealing that larger-scale faults are more conducive to rapid hydrate accumulation. In summary, this study provides a quantitative analysis of the hydrate accumulation process and its key influence factors using a novel simulator, offering theoretical support for resource evaluation and an exploration of hydrate distribution.

Background/Objectives: Osteoarthritis (OA) is a prevalent degenerative disease globally, characterized by cartilage degradation and joint dysfunction. Current treatments are insufficient for halting OA progression. Irigenin (IRI), a flavonoid extracted from natural plants with anti-inflammatory and antioxidant properties, has demonstrated potential in mitigating inflammation and oxidative stress in various diseases; however, its effects on OA remain unexplored. This study aims to evaluate the therapeutic effects of IRI on OA through in vivo and in vitro experiments and to elucidate the underlying molecular mechanisms. Methods: In vitro, chondrocytes were exposed to hydrogen peroxide (H2O2) to induce an oxidative stress environment and were then treated with IRI. Western blotting, RT-qPCR, immunofluorescence staining assays, flow cytometry, and apoptosis assays were employed to assess the effects of IRI on chondrocyte matrix homeostasis, inflammatory response, and apoptosis. In vivo, an OA rat model was treated with regular IRI injections, and therapeutic effects were evaluated using micro-CT, histological staining, and immunohistochemistry assays. Results: IRI treatment restored matrix homeostasis in chondrocytes and effectively suppressed H2O2-induced inflammation and apoptosis. Subsequent studies further revealed that IRI exerts its therapeutic effects by activating the Nrf2/HO-1 pathway. Inhibition of Nrf2 expression in chondrocytes partially blocked the anti-inflammatory and antioxidant effects of IRI. In the OA rat model, regular IRI injections effectively ameliorated cartilage degeneration. Conclusions: This study identifies IRI as a promising strategy for OA treatment by modulating inflammation and apoptosis through the Nrf2/HO-1 pathway.

MXenes nanosheets with high conductivity, hydrophilicity, and excellent reactive oxygen species (ROS) scavenging ability have shown promise in treating various degenerative diseases correlated with abnormal ROS accumulation. Herein, the therapeutic potential of Ti3C2Tx nanosheets, which is the most widely investigated MXene material, in delaying osteoarthritis (OA) progression is demonstrated. In vitro experiments indicate the strong ROS scavenging capacity of Ti3C2Tx nanosheets and their acceptable biocompatibility. Ti3C2Tx nanosheets effectively protect chondrocytes from cell death induced by oxidative stress. In addition, Ti3C2Tx nanosheets demonstrate a prominent anti-inflammatory effect and the ability to restore homeostasis between anabolic activities and catabolic activities in chondrocytes. Furthermore, RNA sequencing reveals the potential mechanism underlying the Ti3C2Tx nanosheet-mediated therapeutic effect. Finally, the in vivo curative effect of Ti3C2Tx nanosheets is verified using a rat OA model. Histological staining and immunohistochemical analyses indicate that Ti3C2Tx nanosheets effectively ameliorate OA progression. Conclusively, the in vitro and in vivo experiments suggest that Ti3C2Tx nanosheets could be a promising and effective option for OA treatment.

Some natural rubber farmers mistakenly equate the ecological functions of rubber plantations with those of primary forests. This cognitive bias can hinder pesticide reduction efforts. Meanwhile, natural rubber farmers gain security through price insurance, which helps them adopt a long-term perspective on environmental protection, mitigating the negative impact of cognitive biases on pesticide use decisions. However, existing research often overlooks the influence of ecological cognitive bias on pesticide reduction and the moderating role of price insurance satisfaction. This study utilizes field survey data from Hainan and employs logit models and double machine learning models to empirically analyze the impact of ecological cognitive bias on pesticide reduction among natural rubber farmers. It further tests the underlying mechanisms using moderation models. The results indicate that (1) ecological cognitive bias negatively affects pesticide reduction among natural rubber farmers, and (2) price insurance satisfaction mitigates the impact of ecological cognitive bias on pesticide reduction. Based on these findings, the government should enhance education and training to raise ecological awareness among natural rubber farmers and reduce ecological cognitive biases. Disseminating knowledge about price insurance and establishing a comprehensive insurance system can secure farmers’ income and promote the rational use of pesticides.

Two-stage harvesting is the main method used for the mechanized harvesting of peanuts in China, in which the pickup device is a core part of the combine harvester. In order to solve the problem of pod loss caused by “stack” and “loss picking” from peanut plants when using a traditional spring-finger cylinder pickup device, an optimal spring-finger cylinder peanut pickup mechanism was designed and its picking properties were tested. Based on the picking characteristics and picking force analysis when considering a peanut plant windrow, the ideal picking attitude and swing rule of the spring-finger were determined, and the cam slide, as the core element of the spring-finger cylinder peanut pickup device, was optimized. A mathematical model of the cam cylinder center line was established according to the swing law of the four picking stations utilizing the spring-finger. MATLAB and ADAMS were used to establish a simulation of the pickup mechanism, and kinematics and dynamics simulation analyses of the pickup mechanism were carried out. According to the design results, a prototype was constructed and a running pickup test was carried out. The peanut plant picking experiments indicated that the phenomenon of peanut plant stacking had significantly disappeared. Furthermore, through response surface analysis, the optimal working parameters of the picking device were obtained as follows: the forward speed Vm was 48.0 m/min, the rotational speed N was 50 r/min, and the ground height H was −16.8 mm. The picking rate of peanut plants was 99.21% and the pod loss rate was 1.79% under two harvesting conditions, with a peanut plant moisture content of 15% to 17%. This study provides technical support for the future design of picking devices for two-stage peanut pickup harvesters.

Structural monitoring is crucial for assessing structural health, and high-precision deformation prediction can provide early warnings for safety monitoring. To address the issue of low prediction accuracy caused by the non-stationary and nonlinear characteristics of deformation sequences, this paper proposes a similarity clustering (SC) deformation prediction model based on GNSS/accelerometer time-frequency analysis. First, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm is used to decompose the original monitoring data, and the time-frequency characteristic correlations of the deformation data are established. Then, similarity clustering is conducted for the monitoring sub-sequences based on their frequency domain characteristics, and clustered sequences are combined subsequently. Finally, the Long Short-Term Memory (LSTM) model is used to separately predict GNSS displacement and acceleration with clustered time series, and the overall deformation displacement is reconstructed based on the predicted GNSS displacement and acceleration-derived displacement. A shake table simulation experiment was conducted to validate the feasibility and performance of the proposed CEEMDAN-SC-LSTM model. A duration of 5 s displacement prediction is analyzed after 153 s of monitoring data training. The results demonstrate that the root mean square error (RMSE) of predicted displacement is 0.011 m with the proposed model, which achieves an improvement of 64.45% and 61.51% in comparison to the CEEMDAN-LSTM and LSTM models, respectively. The acceleration predictions also show an improvement of 96.49% and 95.58%, respectively, the RMSE of the predicted acceleration-reconstructed displacement is less than 1 mm, with a reconstruction similarity of over 99%. The overall displacement reconstruction similarity can reach over 95%.

Sulfonamides are not only widely applied in clinics but also highly valued in animal husbandry. Recently, it has become common for sulfonamide residues to exceed the standard limits in food, which can affect human health. Current regulations limit these residues. Therefore, we constructed a new limit test method to rapidly determine the levels of sulfonamide residues. Six sulfonamides were detected using the latest method called TLC-SERS, namely, sulfamethasone (A), sulfamethazine (B), sulfadoxine (C), sulfamethoxydiazine (D), sulfamethoxazole (E), and sulfathiazole (F). The optimal conditions for SERS detection were investigated for these six drugs, and the separation effects of different TLC spreaders on them were compared. Then, we successfully established a separation system using dichloromethane–methanol–ammonia in a ratio of 5:1:0.25 (v/v/v), which provided good separation effects on the six drugs. The residues were preliminarily separated via TLC. A silver sol solution was added to the spot on the silica gel G plate at the corresponding specific shift values, and SERS detection was performed. The sample solution was placed on the spot under a 532 nm laser, and the SERS spectrum was collected and analyzed for the six sulfonamides. The results showed obvious variations in the SERS spectrum among the six sulfonamides, with the LODs being 12.5, 6.4, 6.3, 7.1, 18.8, and 6.2 ng/mL from A to F, respectively, and an RSD of

Biotic and abiotic stresses have already seriously restricted the growth and development of Pinus massoniana, thereby influencing the quality and yield of its wood and turpentine. Recent studies have shown that C2H2 zinc finger protein transcription factors play an important role in biotic and abiotic stress response. However, the members and expression patterns of C2H2 TFs in response to stresses in P. massoniana have not been performed. In this paper, 57 C2H2 zinc finger proteins of P. massoniana were identified and divided into five subgroups according to a phylogenetic analysis. In addition, six Q-type PmC2H2-ZFPs containing the plant-specific motif ‘QALGGH’ were selected for further study under different stresses. The findings demonstrated that PmC2H2-ZFPs exhibit responsiveness towards various abiotic stresses, including drought, NaCl, ABA, PEG, H2O2, etc., as well as biotic stress caused by the pine wood nematode. In addition, PmC2H2-4 and PmC2H2-20 were nuclear localization proteins, and PmC2H2-20 was a transcriptional activator. PmC2H2-20 was selected as a potential transcriptional regulator in response to various stresses in P. massoniana. These findings laid a foundation for further study on the role of PmC2H2-ZFPs in stress tolerance.

The ability to make informed decisions in complex scenarios is crucial for intelligent automotive systems. Traditional expert rules and other methods often fall short in complex contexts. Recently, reinforcement learning has garnered significant attention due to its superior decision-making capabilities. However, there exists the phenomenon of inaccurate target network estimation, which limits its decision-making ability in complex scenarios. This paper mainly focuses on the study of the underestimation phenomenon, and proposes an end-to-end autonomous driving decision-making method based on an improved TD3 algorithm. This method employs a forward camera to capture data. By introducing a new critic network to form a triple-critic structure and combining it with the target maximization operation, the underestimation problem in the TD3 algorithm is solved. Subsequently, the multi-timestep averaging method is used to address the policy instability caused by the new single critic. In addition, this paper uses Carla platform to construct multi-vehicle unprotected left turn and congested lane-center driving scenarios and verifies the algorithm. The results demonstrate that our method surpasses baseline DDPG and TD3 algorithms in aspects such as convergence speed, estimation accuracy, and policy stability.

Flower endophytic fungi play a major role in plant reproduction, stress resistance, and growth and development. However, little is known about how artificial cultivation affects the endophytic fungal community found in the tepals of rare horticultural plants. In this research, we used high-throughput sequencing technology combined with bioinformatics analysis to reveal the endophytic fungal community of tepals in Lirianthe delavayi and the effects of artificial cultivation on the community composition and function of these plants, using tepals of L. delavayi from wild habitat, cultivated campus habitat, and cultivated field habitat as research objects. The results showed that the variety of endophytic fungi in the tepals of L. delavayi was abundant, with a total of 907 Amplicon sequencing variants (ASVs) obtained from all the samples, which were further classified into 4 phyla, 23 classes, 51 orders, 97 families, 156 genera, and 214 species. We also found that artificial cultivation had a significant impact on the community composition of endophytic fungi. Although there was no significant difference at the phylum level, with Ascomycota and Basidiomycota being the main phyla, there were significant differences in dominant and unique genera. Artificial cultivation has led to the addition of new pathogenic fungal genera, such as Phaeosphaeria, Botryosphaeria, and Paraconiothyrium, increasing the risk of disease in L. delavayi. In addition, the abundance of the endophytic fungus Rhodotorula, which is typical in plant reproductive organs, decreased. Artificial cultivation also altered the metabolic pathways of endophytic fungi, decreasing their ability to resist pests and diseases and reducing their ability to reproduce. A comparison of endophytic fungi in tepals and leaves revealed significant differences in community composition and changes in the endophytic diversity caused by artificial cultivation. To summarize, our results indicate that endophytic fungi in the tepals of L. delavayi mainly consist of pathogenic and saprophytic fungi. Simultaneously, artificial cultivation introduces a great number of pathogenic fungi that alter the metabolic pathways associated with plant resistance to disease and pests, as well as reproduction, which can increase the risk of plant disease and reduce plant reproductive capacity. Our study provides an important reference for the conservation and breeding of rare horticultural plants.

In order to scientifically and rationally evaluate the susceptibility to landslide hazards in Tekes County, Yili State. This paper takes Tekes County in Xinjiang as an example, on the basis of a comprehensive analysis of the regional geological environment conditions and the distribution pattern and formation conditions of geological disasters, using the data of geological disaster points (landslide center points), and through the correlation matrix calculation of the evaluation factors, the nine evaluation factors with larger absolute values of correlation coefficients were determined to construct the evaluation system of the susceptibility to landslide geological hazards in Tekesi County. Combining the information quantity method and the entropy value method, using the weights determined by the entropy value method, the information quantity method is used to calculate the information quantity value of each factor within the factor, calculate the susceptibility index of landslide geological disasters within the territory of Tekes County, and then carry out the landslide susceptibility evaluation. The susceptibility of landslide disasters was evaluated by ArcGIS. The results show that the landslide disaster susceptibility level in Tekes County can be divided into four levels: high susceptibility, medium susceptibility, low susceptibility, and not susceptible, with areas of 491.3276 km2, 1181.5171 km2, 1674.7609 km2 and 5295.2976 km2 accounting for 5.68%, 13.67%, 19.38% and 61.27% of the total area of Tex County, respectively. The AUC number obtained by the success curve method (ROC) is 0.8736, reflecting the evaluation accuracy of 87.36%, indicating that the model method used in this paper is effective. The results are expected to provide practical data support for landslide disaster control in Tekes County and provide a reference for geological disaster monitoring, early warning and engineering prevention and control deployment in Yili Valley.

To address the challenges of indoor mold in southern China, this study designed and constructed an innovative experimental system to investigate mold growth in buildings under the combined influence of multiple factors. Using Fluent simulation (Ansys Fluent 19.0), we designed a suitably sized experimental chamber to realistically replicate the effects of factors such as temperature, humidity, and air velocity on mold growth. After establishing and fine-tuning the experimental system, we conducted two preliminary experiments, successfully validating the feasibility of our setup. Additionally, we observed that in a high-temperature, high-humidity environment of 28 °C and 80% relative humidity, the mold growth rate in the experimental chamber increased with the rise in inlet air velocity. This experimental system will serve as the foundation for future studies on indoor mold growth in building spaces in southern China.

Soybean is an important source of high-quality vegetable protein with various health-improving properties, and its main bioactive substances are small peptides produced by in vitro enzymatic hydrolytic processes. In traditional layer breeding, the nutritional health of roosters is frequently neglected, ultimately affecting the quality and quantity of offspring. This study investigated the effects of various quantities (0%, 0.15%, 0.30%, 0.45%, and 0.60%) of soybean bioactive peptide (SBP) feed additives on immunological and antioxidant functions, gut health, and reproductive performance of roosters. SBP supplementation significantly improved male growth and reproductive performance, including growth rate, feed conversion ratio, reproductive organ development, and semen quality. SBP also increased immune and antioxidant levels, boosted the integrity of the small intestinal physiological structure and barrier function, and diversity of cecal microbes, and decreased the apoptotic ratio of small intestinal epithelial cells. The effects of SBP on various functions of males showed a quadratic trend, with the optimal concentration determined to be 0.45%.

This paper addresses the issue of the frequent collision and grinding of rolling elements in cageless bearings during operation by proposing a method to calculate the total circumferential clearance. The calculation is based on the maximum orbital speed difference in the bearing rolling elements to determine the minimum clearance needed to prevent collision. The study analyzes the impact of the rolling element diameter, bearing pitch diameter, contact angle, and number of rolling elements on the total circumferential clearance. The discussion then focuses on optimizing the number of rolling elements in cageless bearings. The optimization results demonstrate that the proposed calculation reduces collisions between rolling elements and bearing stress. Additionally, a total circumferential clearance test was conducted on a logarithmic spiral bearing, showing significant improvements in wear, average temperature, and temperature rise when designed according to the method presented in this article. These findings offer valuable insights into the design of cageless bearings.

This paper proposes a novel censored autoregressive conditional Fréchet (CAcF) model with a flexible evolution scheme for the time-varying parameters, which allows deciphering tail risk dynamics constrained by price limits from the viewpoints of different risk preferences. The proposed model can well accommodate many important empirical characteristics of financial data, such as heavy-tailedness, volatility clustering, extreme event clustering, and price limits. We then investigate tail risk dynamics via the CAcF model in the price-limited stock markets, taking entropic value at risk (EVaR) as a risk measurement. Our findings suggest that tail risk will be seriously underestimated in price-limited stock markets when the censored property of limit prices is ignored. Additionally, the evidence from the Chinese Taiwan stock market shows that widening price limits would lead to a decrease in the incidence of extreme events (hitting limit-down) but a significant increase in tail risk. Moreover, we find that investors with different risk preferences may make opposing decisions about an extreme event. In summary, the empirical results reveal the effectiveness of our model in interpreting and predicting time-varying tail behaviors in price-limited stock markets, providing a new tool for financial risk management.

Changzhou is a city situated in the eastern region of China and serves as a pivotal juncture of the UNESCO World Cultural Heritage site, the Grand Canal of China. The study employed spatial syntax foreground and background network analysis to examine the cultural landscape characteristics and determinants of the urban spatial context in Changzhou, influenced by the Grand Canal, with a focus on rivers, streets, and social networks. The findings revealed that: (1) Foreground network construction: serving as the fundamental framework of urban space, street and river networks exhibited distinct functionalities in terms of structural configuration, functional organization, and potential impact. (2) Background network construction: social networks identified through spatial structure recognition demonstrated sustainable characteristics, as their layout was not directly correlated to the foreground network but contributed to the identification of the identity and the traits of social networks. (3) Dual network adaptability to contemporary urban space: it was imperative to redefine the role of river networks to augment their potential impact in shaping scenic leisure systems. This study provides novel insights into preserving and acknowledging the urban spatial context while offering valuable references for safeguarding regional cultural landscapes.

The contact resistance formed between MoS2 and metal electrodes plays a key role in MoS2-based electronic devices. The Schottky barrier height (SBH) is a crucial parameter for determining the contact resistance. However, the SBH is difficult to modulate because of the strong Fermi-level pinning (FLP) at MoS2-metal interfaces. Here, we investigate the FLP effect and the contact types of monolayer and multilayer MoS2-metal van der Waals (vdW) interfaces using density functional theory (DFT) calculations based on Perdew–Burke–Ernzerhof (PBE) level. It has been demonstrated that, compared with monolayer MoS2-metal close interfaces, the FLP effect can be significantly reduced in monolayer MoS2-metal vdW interfaces. Furthermore, as the layer number of MoS2 increases from 1L to 4L, the FLP effect is first weakened and then increased, which can be attributed to the charge redistribution at the MoS2-metal and MoS2-MoS2 interfaces. In addition, the p-type Schottky contact can be achieved in 1L–4L MoS2-Pt, 3L MoS2-Au, and 2L–3L MoS2-Pd vdW interfaces, which is useful for realizing complementary metal oxide semiconductor (CMOS) logic circuits. These findings indicated that the FLP and contact types can be effectively modulated at MoS2-metal vdW interfaces by selecting the layer number of MoS2.

A highly sensitive, selective and recyclable histidine detection method based on magnetic Fe3O4@mTiO2 (M-TiO2) nanocomposites with SERRS was developed. Mesoporous M-TiO2 nanoparticles were functionalized with 4-aminothiophenol and then coupled with histidine through an azo coupling reaction in 5 min, producing the corresponding azo compound. The strong and specific SERRS response of the azo product allowed for ultrasensitive and selective detection for histidine with an M-TiO2 device loaded with Ag NPs due to the molecular resonance effect and plasmonic effect of Ag NPs under a 532 nm excitation laser. The sensitivity was further enhanced with the magnetic enrichment of M-TiO2. The limit of detection (LOD) was as low as 8.00 × 10−12 mol/L. The M-TiO2 demonstrated applicability towards histidine determination in human urine without any sample pretreatment. Additionally, the M-TiO2 device can be recycled for 3 cycles with the photodegradation of the azo product under UV irradiation due to TiO2-assisted and plasmon-enhanced photocatalysis. In summary, a multifunctional and recyclable M-TiO2 device was synthesized based on azo coupling and SERRS spectroscopy for ultra-sensitive and specific histidine sensing. In addition, the proposed system demonstrated the potential for the multiplex determination of toxic compounds in the fields of food safety, industrial production and environmental protection, which benefit from the fingerprint property and universality of SERRS.

Cement-based cementitious materials occupy a central position in the construction industry, but the problem of high carbon dioxide(CO2) emissions from cement production has attracted global attention. To meet this challenge, finding low-carbon alternative materials has become a top priority in the research of new building materials. At the same time, the problem of large amounts of lithium slag piling up needs to be solved, and resource utilization has become its potential way out. In this study, the volcanic ash activity of lithium slag was activated by composite activation means of high-temperature calcination and sodium silicate, and it was used as an alternative mix to cement. The Box–Behnken design and response surface method (BBD-RSM) was utilized to optimize the ratio of activated lithium slag composite cement-based cementitious materials, and high-performance new solid waste cementitious materials were prepared. The results show that activated lithium slag composite cementitious materials activated lithium slag exhibit excellent performance when activated lithium slag mass fraction is 7.3%, the sodium silicate dosage is 8.8%, and water–solid ratio is 0.6:1. The composite cementitious material under this ratio shows excellent performance, with fluidity 235.69 mm, gelation time 73.54 s, water evolution rate 1.123%, 3d and 28d compressive strengths, respectively, are 11.54 MPa and 22.9 MPa. Compared with ordinary Portland-cement-based cementing materials, the uniaxial compressive strength, modulus of elasticity, and tensile strength at break of activated lithium slag cementitious material solidified body were increased by 34.33%, 36.43%, and 34.98%, and the compressive deformation and tensile deformation were enhanced by 37.78% and 40%. This study not only provides a theoretical basis and experimental foundation for the preparation of new solid waste cementitious materials, but also provides a new solution for the reinforcement of crushed rock bodies in engineering practice, which is of great significance for promoting the low-carbon development of the construction industry.

The bond–slip behavior of the steel–concrete interface is critical in reinforced concrete (RC) structures since the bond action is the mechanism that ensures the two materials work in co-operation. However, there is little research considering the bond–slip behavior in massive ring-type reinforced concrete (MRRC) structure bearing analyses due to the complexity of modeling the interfacial behavior. Hence, the influence of the bond–slip behavior on the bearing characteristics of MRRC structures remains unclear. Steel-lined reinforced concrete penstock is such an MRRC structure, composed of steel liner and reinforced concrete and commonly used in diversion pipelines. This paper aims to explore the bearing characteristics considering the bond–slip behavior in the composite penstock by using a promising numerical method, the cohesive zone model. Three interface models were proposed to represent the different interaction conditions at the steel–concrete interface. Moreover, a sensitivity analysis was performed to study the impact of the bond strength on the bond performance and structural behavior. The simulation results showed that the prediction results (steel stress and crack process) considering the bond–slip behavior were in good agreement with the experimental results. The steel stresses near the cracks were smaller and more uniform after considering the bond–slip behavior, since the stresses were no longer concentrated on the crack but distributed in an area near the crack. However, the steel stress differences in these models were within 10%, which means that the bond performance had a limited effect on the structural safety design. The crack widths were greatly influenced by the bond conditions, and the maximum crack width (0.461 mm) in poor conditions was beyond the limiting value (0.3 mm). Consequently, bond–slip behavior must be paid more attention in durability design.

Half-grouted sleeve connectors are a primary method for connecting rebar in prefabricated concrete structures. However, due to limitations in the construction environment, all kinds of grouting defects are inevitable, especially grouting voids. Additionally, fire disasters, among the most common types of disasters, significantly threaten the structural performance and safety of these prefabricated structures. Therefore, it is imperative to determine the mechanical properties of half-grouted sleeve connectors with grouting voids after high temperatures. This study designed and prepared 48 groups of half-grouted sleeve specimens with different grouting voids and defect locations. These specimens were heated to the specified temperature (25 °C, 200 °C, 300 °C, 400 °C, 500 °C, 600 °C), followed by unidirectional tensile testing after natural cooling. The experimental results showed that rebar fracture failure and rebar pulled-out failure were the failure modes of specimens. With the increase in temperature, bearing capacity, safety factor and ductility coefficient of specimens all decreased. When the temperature was lower than 400 °C, the specimen with void length less than twice the diameter of the rebar (i.e., 2d) had sufficient connection performance. For specimens with the same total void lengths, the bearing capacity of discrete voids is lower than concentrate voids at the same temperature. The load-displacement curve, safety coefficient, ductility coefficient and grey correlation degree of half-grouted sleeve specimens with grouting voids at different temperatures are analyzed and discussed, and the bond stress slip constitutive model is given. Grouting defects have greater influence on specimens after grey correlation analysis. Findings from this study provide valuable references for the safety performance evaluation of prefabricated structures with half-grouted sleeve connectors after exposure to fire.

Information on long-term effects of postovulatory oocyte aging (POA) on offspring is limited. Whether POA affects offspring by causing oxidative stress (OS) and mitochondrial damage is unknown. Here, in vivo-aged (IVA) mouse oocytes were collected 9 h after ovulation, while in vitro-aged (ITA) oocytes were obtained by culturing freshly ovulated oocytes for 9 h in media with low, moderate, or high antioxidant potential. Oocytes were fertilized in vitro and blastocysts transferred to produce F1 offspring. F1 mice were mated with naturally bred mice to generate F2 offspring. Both IVA and the ITA groups in low antioxidant medium showed significantly increased anxiety-like behavior and impaired spatial and fear learning/memory and hippocampal expression of anxiolytic and learning/memory-beneficial genes in both male and female F1 offspring. Furthermore, the aging in both groups increased OS and impaired mitochondrial function in oocytes, blastocysts, and hippocampus of F1 offspring; however, it did not affect the behavior of F2 offspring. It is concluded that POA caused OS and damaged mitochondria in aged oocytes, leading to defects in anxiety-like behavior and learning/memory of F1 offspring. Thus, POA is a crucial factor that causes psychological problems in offspring, and antioxidant measures may be taken to ameliorate the detrimental effects of POA on offspring.

The advancement of an intelligent automobile sound switching system has the potential to elevate the market standing of automotive products, with the pivotal prerequisite being the selection of automobile sounds based on the driver’s subjective perception. The subjective responses of diverse individuals to sounds can be objectively manifested through EEG signals. Therefore, EEG signals are employed herein to attain the recognition of automobile sounds. A subjective evaluation and EEG signal acquisition experiment are designed involving the stimulation of three distinct types of automobile sounds, namely comfort, power, and technology sounds, and a comprehensive database of EEG signals corresponding to these three sound qualities is established. Then, a specific transfer learning model based on a convolutional neural network (STL-CNN) is formulated, where the method of training the upper layer parameters with the fixed bottom weights is proposed to adaptively extract the EEG features related to automobile sounds. These improvements contribute to improving the generalization ability of the model and realizing the recognition of automobile sounds fused with EEG signals. The results of the comparison with traditional support vector machine (SVM) and convolutional neural network (CNN) models demonstrate that the accuracy of the test set of the STL-CNN model reaches 91.5%. Moreover, its comprehensive performance, coupled with the ability to adapt to individual differences, surpasses that of both SVM and CNN models. The demonstrated method in the recognition of automobile sounds based on EEG signals is of significance for the future implementation of switching driving sound modes fused with EEG signals.

As an alternative for perfluorooctane sulfonic acid (PFOS), sodium p-perfluorononyloxybenzene sulfonate (OBS) has been widely used in petroleum, fire-fighting materials, and other industries. In order to efficiently and economically remove OBS contaminations from water bodies, in this study, a ternary heterojunction was constructed by coupling BiOBr and BiOI@Bi5O7I for improving the redox capacity and carrier separation ability of the material and investigating the effect of the doping ratios of BiOBr and BiOI@ Bi5O7I on the performance of the catalysts. Furthermore, the effects on the degradation of OBS were also explored by adjusting different catalyst doping ratios, OBS concentrations, catalyst amounts, and pH values. It was observed that when the concentration of OBS was 50 mg/L, the amount of catalyst used was 0.5 g/L, and the pH was not changed. The application of BiOBr/BiOI@ Bi5O7I consisting of 25% BiOBr and 75% BiOI@ Bi5O7I showed excellent stability and adsorption degradation performance for OBS, and almost all of the OBS in the aqueous solution could be removed. The removal rate of OBS by BiOBr/BiOI@ Bi5O7I was more than 20% higher than that of OBS by BiOI@Bi5O7I and BiOBr when the OBS concentration was 100 mg/L. In addition, the reaction rate constants of BiOBr/BiOI@ Bi5O7I were 2.4 and 10.8 times higher than those of BiOI@ Bi5O7I and BiOBr, respectively. Therefore, the BiOBr/BiOI@ Bi5O7I ternary heterojunction can be a novel type of heterojunction for the efficient degradation of OBS in water bodies.

Oil shale, as a vast potential resource, is considered an important alternative energy source, and its effective development and economic utilization are of significant importance in alleviating the contradiction between energy supply and demand. Presently, the in situ conversion technology for oil shale has gained significant global attention, with numerous extraction methods undergoing active research and development. One of these methods is the in situ conversion of oil shale based on the hydration reaction of calcium-oxide-based composite material (CaO-CM). This approach harnesses the heat produced by the reaction between CaO-CM and water as a heat source for the pyrolysis of oil shale. This paper conducted experiments to assess the feasibility of temperature associated with this method. The feasibility study mainly includes two aspects: First, it is necessary to investigate whether the temperature generated by the hydration reaction of CaO-CM can meet the temperature requirements for the pyrolysis of oil shale. Through pyrolysis experiments of Xinjiang oil shale, the minimum temperature required for oil shale pyrolysis was determined to be 330 °C. High-temperature and high-pressure reaction vessels were employed to explore the temperature generated by the hydration reaction of CaO-CM. The results show that with the increase in environment pressure, environment temperature, and reaction mass, the maximum temperature generated by the hydration reaction of CaO-CM also increases (reach 455.5 °C), meeting the temperature requirements for the pyrolysis of oil shale. Second, the study evaluates whether the hydration reaction of CaO-CM can induce pyrolysis hydrocarbons of the oil shale. Through the pyrolysis experiments of oil shale based on the hydration reaction of CaO-CM, the changes in the content of pyrolysis hydrocarbons (S2) in oil shale before and after pyrolysis are measured. The results show that under 10 MPa pressure, the content of pyrolysis hydrocarbons in the oil shale decreased from 40.96 mg/g to 0.08 mg/g after pyrolysis. This confirms the feasibility of the temperature conditions for the in situ conversion of oil shale based on the hydration reaction of CaO-CM.

Enhancing the total factor productivity in forestry is an important part of deepening the reform of the collective forest rights system. Based on the survey data of 295 forest plots in 12 towns of Liuyang City, Hunan Province, China, the study utilized a three-stage DEA model to assess the total factor productivity of forestry at the plot level. The empirical study employs Tobit and fractional regression models to investigate the effects and differences of forestry subsidies and forestry regulatory policies on the heterogeneous total factor productivity of different types of forests. The study found that: (1) the mean value of plot-scale forestry total factor productivity is 0.127, and there are obvious differences in total factor productivity among timber forests, economic forests, and mixed forests; and (2) afforestation subsidies and nurturing subsidies significantly positively influence high-level TFP. Ecological benefit compensation positively affects high-level TFP, but is not significant at any level of TFP. Forestry regulatory policies negatively impact high-level TFP, but are not significant at any level of TFP. This paper puts forward countermeasure suggestions to improve forestry subsidy policies, optimize forestry regulatory policies, and improve forestry total factor productivity from the perspective of heterogeneous forest types.

This study explores the influence of micelles on the evolution of MCM−41’s pore structure via 24 h hydrothermal treatments in a range of temperatures from 100 °C to 200 °C. MCM−41 was characterized using BET, SAXD, FTIR, TEM, and TG-DSC. The findings demonstrate that with temperature elevation from 100 °C to 160 °C, the micelles undergo expansion, leading to an enhanced lattice constant from 4.50 nm to 4.96 nm and an increase in pore diameter from 3.17 nm to 3.45 nm, while maintaining the structural orderliness of the pore channels. Upon cooling, the reversible contraction of micelles and the strategic addition of water glass contribute to a reduction in pore size. However, at a threshold of 180 °C, the SAXD (100) peak’s half-peak width surges by approximately 40% relative to that at 160 °C, illustrating a progressive disruption of the hexagonal configuration of MCM−41. Coupled with elevated silica dissolution at higher temperatures in an alkaline solution, a total disintegration of the ordered pore structure at 200 °C results in a drastic reduction in the specific surface area to 307 m2/g. These results are beneficial to developing structural transformation mechanisms of MCM−41 materials and designing mesoporous materials via temperature modulation innovatively.

Muscle regeneration, representing an essential homeostatic process, relies mainly on the myogenic progress of resident satellite cells, and it is modulated by multiple physical and nutritional factors. Here, we investigated how myogenic differentiation-related factors and pathways respond to the first limiting amino acid lysine (Lys) in the fast and slow muscles, and their satellite cells (SCs), of swine. Thirty 28-day-old weaned piglets with similar body weights were subjected to three diet regimens: control group (d 0–28: 1.31% Lys, n = 12), Lys-deficient group (d 0–28: 0.83% Lys, n = 12), and Lys rescue group (d 0–14: 0.83% Lys; d 15–28: 1.31% Lys, n = 6). Pigs on d 15 and 29 were selectively slaughtered for muscular parameters evaluation. Satellite cells isolated from fast (semimembranosus) and slow (semitendinosus) muscles were also selected to investigate differentiation ability variations. We found Lys deficiency significantly hindered muscle development in both fast and slow muscles via the distinct manipulation of myogenic regulatory factors and the Wnt/Ca2+ pathway. In the SC model, Lys deficiency suppressed the Wnt/Ca2+ pathways and myosin heavy chain, myogenin, and myogenic regulatory factor 4 in slow muscle SCs but stimulated them in fast muscle SCs. When sufficient Lys was attained, the fast muscle-derived SCs Wnt/Ca2+ pathway (protein kinase C, calcineurin, calcium/calmodulin-dependent protein kinase II, and nuclear factor of activated T cells 1) was repressed, while the Wnt/Ca2+ pathway of its counterpart was stimulated to further the myogenic differentiation. Lys potentially manipulates the differentiation of porcine slow and fast muscle myofibers via the Wnt/Ca2+ pathway in opposite trends.

Microalgae can convert carbon dioxide into organic matter through photosynthesis. Thus, they are considered as an environment-friendly and efficient cell chassis for biologically active metabolites. Microalgal lipids are a class of organic compounds that can be used as raw materials for food, feed, cosmetics, healthcare products, bioenergy, etc., with tremendous potential for commercialization. In this review, we summarized the commercial lipid products from eukaryotic microalgae, and updated the mechanisms of lipid synthesis in microalgae. Moreover, we reviewed the enhancement of lipids, triglycerides, polyunsaturated fatty acids, pigments, and terpenes in microalgae via environmental induction and/or metabolic engineering in the past five years. Collectively, we provided a comprehensive overview of the products, biosynthesis, induced strategies and genetic engineering in microalgal lipids. Meanwhile, the outlook has been presented for the development of microalgal lipids industries, emphasizing the significance of the accurate analysis of lipid bioactivity, as well as the high-throughput screening of microalgae with specific lipids.

The frequency of forest fires has increased dramatically due to climate change. The occurrence of forest fires affects the carbon and nitrogen cycles and react to climate change to form a positive feedback mechanism. These effects further impact the distribution of microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) and the soil microbial community structure. In addition, permafrost degradation can significantly affect the microorganisms in the soil. Based on these findings, this review examines the effects of fire intensity and post-fire recovery time on permafrost, the soil microbial community, MBC, MBN, and their interrelationships. This review demonstrated that (1) fires alter the condition of surface vegetation, reduce the organic layer thickness, redistribute snow, accelerate permafrost degradation, and even lead to permanent changes, where the restoration of the pre-fire state would require several decades or even centuries; (2) soil microbial community structure, soil MBC, and MBN negatively correlate with fire intensity, and the effects become more pronounced with increasing fire intensity; and (3) the structural diversity and stability of the soil microbial community were improved with time, and the amount of MBC and MBN increases as the years after a fire go by; it would still take more than ten years to recover to the pre-fire level. However, the relationship between permafrost degradation and soil microbes after forest fires is still unclear due to a lack of quantitative research on the mechanisms underlying the changes in soil microorganisms resulting from fire-induced permafrost degradation. Therefore, expanding quantitative studies and analyses of the mechanisms of interactions between forest fires, permafrost, and soil microorganisms can provide a scientific basis for understanding ecosystem carbon pools and dual-carbon targets in Arctic–boreal permafrost regions.

The acoustic tomography (AT) velocity field reconstruction technique has become a research hotspot in recent years due to its noninvasive nature, high accuracy, and real-time measurement advantages. However, most of the existing studies are limited to the reconstruction of the velocity field in a rectangular area, and there are very few studies on a circular area, mainly because the layout of acoustic transducers, selection of acoustic paths, and division of measured regions are more difficult in a circular area than in a rectangular area. Therefore, based on AT and using the reconstruction algorithm of the Markov function and singular value decomposition (MK-SVD), this paper proposes a measured regional division optimization algorithm for velocity field reconstruction in a circular area. First, an acoustic path distribution based on the multipath effect is designed to solve the problem of the limited emission angle of the acoustic transducer. On this basis, this paper proposes an adaptive optimization algorithm for measurement area division based on multiple sub-objectives. The steps are as follows: first, two optimization objectives, the condition number of coefficient matrix and the uniformity of acoustic path distribution, were designed. Then, the weights of each sub-objective are calculated using the coefficient of variation (CV). Finally, the measured regional division is optimized based on particle swarm optimization (PSO). The reconstruction effect of the algorithm and the anti-interference ability are verified through the reconstruction experiments of the model velocity field and the simulated velocity field.

Current image feature extraction methods fail to adapt to the fine features of apple image texture, resulting in image matching errors and degraded image processing accuracy. A multi-view orthogonal image acquisition system was constructed with apples as the research object. The system consists of four industrial cameras placed around the apple at different angles and one camera placed on top. Following the image acquisition through the system, synthetic image pairs—both before and after transformation—were generated as the input dataset. This generation process involved each image being subjected to random transformations. Through learning to extract more distinctive and descriptive features, the deep learning-based keypoint detection method surpasses traditional techniques by broadening the application range and enhancing detection accuracy. Therefore, a lightweight network called ALIKE-APPLE was proposed for surface feature point detection. The baseline model for ALIKE-APPLE is ALIKE, upon which improvements have been made to the image feature encoder and feature aggregation modules. It comprises an Improved Convolutional Attention Module (ICBAM) and a Boosting Resolution Sampling Module (BRSM). The proposed ICBAM replaced max pooling in the original image feature encoder for downsampling. It enhanced the feature fusion capability of the model by utilizing spatial contextual information and learning region associations in the image. The proposed BRSM replaced the bilinear interpolation in the original feature aggregator for upsampling, overcoming the apple side image’s geometric distortion and effectively preserving the texture details and edge information. The model size was shrunk by optimizing the number of downsampling operations from the image encoder of the original model. The experimental results showed that the average number of observed keypoints and the average matching accuracy were improved by 166.41% and 37.07%, respectively, compared with the baseline model. The feature detection model of ALIKE-APPLE was found to perform better than the optimal SuperPoint. The feature point distribution of ALIKE-APPLE showed an improvement of 10.29% in average standard deviation (Std), 8.62% in average coefficient of variation (CV), and 156.12% in average feature point density (AFPD). Moreover, the mean matching accuracy (MMA) of ALIKE-APPLE improved by 125.97%. Thus, ALIKE-APPLE boasts a more consistent allocation of feature points and greater precision in matching.

The Hibiscus manihot L. (HML) Medic, an edible hibiscus of the Malvaceae family, is abundant with flavonoids. The study investigated how Rhizopus-arrhizus-31-assisted pretreatment affects the extraction and bioactivity of flavonoids from HML. The fiber structure of the fermented flavonoid sample (RFF) appears looser, more porous, and more disordered than the unfermented flavonoid sample (RUF). RFF demonstrates milder conditions and yields higher extraction rates. According to the Box–Behnken response surface optimization experiment, the optimal conditions for RFF include a material–liquid ratio of 1:41 g/mL, a 2 h extraction time, a 57% ethanol concentration, and an extraction temperature of 800 °C, resulting in a 3.69% extraction yield, which is 39.25% higher than that of RUF. Additionally, RFF exhibits greater activity than RUF in the radical-scavenging system. The IC50 values for DPPH, OH, and ABTS radicals are 83.43 μg/mL and 82.62 μg/mL, 208.38 μg/mL and 175.99 μg/mL, and 108.59 μg/mL and 75.39 μg/mL for RUF and RFF, respectively. UPLC-QTOF-MS analysis of the active components in the HML flavonoid sample revealed significant differences in the chromatograms of RUF and RFF, indicating that biofermentation led to substantial changes in composition and content from HML.

The aim of this study is to better understand diffusive convection (DC) and its role in the upper ocean dynamic environment and sea ice melting in the Canada Basin. Based on a moored dataset with 6737 profiles collected from August 2003 to August 2011 in the upper layer of the Canada Basin, DC between the warm and salty Atlantic Water (AW) and the colder and less salty Lower Halocline Water (LHW) were investigated. The moorings were designated at four stations: A, B, C, and D, located at the southwestern, southeastern, northeastern, and northwestern parts of the basin, respectively. During the observation period, the temperature, salinity, and depth of the AW and LHW exhibited unique temporal variations. The temperature and salinity of the AW varied among stations, with a decreasing trend from northwest to southeast, consistent with the propagation path of the AW in the Canada Basin. The temperature and salinity of the LHW were similar at all stations. The AW and LHW cores were located between depths of 320–500 m and 160–300 m, respectively, and both gradually deepened over time. Distinct DC staircase structures were observed between the AW and LHW, more pronounced at stations C and D than at stations A and B, which is speculated to be related to eddies at stations A and B during the observation period. The vertical heat fluxes through the DC staircase layer at stations C and D (FHc_C and FHc_D) were estimated using an empirical formula. FHc_C ranged from 0.05 to 0.94 W/m2, and FHc_D ranged from 0.05 to 0.6 W/m2, with the maximum probability value for both at approximately 0.2 W/m2. The effective diffusivities at these two stations (KT_C and KT_D) are similar, ranging from 2 × 10−6 to 3 × 10−5 m2/s, with the highest probability occurring at 6 × 10−6 m2/s. Both the probability density function of the heat flux and the effective diffusivity skewed towards larger values and obey a lognormal distribution, indicating turbulence intermittency of the DC staircase in the Canada Basin. These finding offers new insights into the heat transport and turbulence in the DC staircase, and then bring a deeper understanding of sea ice melting in the Canada Basin.

This study successfully fabricated the quaternary topological insulator thin films of Bi1.2Sb0.8Te0.4Se2.6 (BSTS) with a thickness of 25 nm, improving the intrinsic defects in binary topological materials through doping methods and achieving the separation of transport characteristics between the bulk and surface of topological insulator materials by utilizing a comprehensive Physical Properties Measurement System (PPMS) and Terahertz Time-Domain Spectroscopy (THz-TDS) to extract electronic transport information for both bulk and surface states. Additionally, the dielectric polarization behavior of BSTS in the low-frequency (10–107 Hz) and high-frequency (0.5–2.0 THz) ranges was investigated. These research findings provide crucial experimental groundwork and theoretical guidance for the development of novel low-energy electronic devices, spintronic devices, and quantum computing technology based on topological insulators.

The study of apple damage mechanisms is key to improving post-harvest apple treatment techniques, and the evolution pattern of damaged tissue is fundamental to the study of apple damage mechanisms. In the study, ‘Red Delicious’ apples were used to explore the relationship between damage and time. A cell death zone was found in the pulp of the damaged tissue after the apple had been bruised. The tissue damage was centered in the cell death zone and developed laterally, with the width of the damage increasing with injury time. The extent of tissue damage in the core and pericarpal directions varied. About 60% of the damaged tissue developed in the core direction and 40% in the pericarpal direction, and the damage ratios in both directions remained consistent throughout the injury. The depth of damage and the rate of damage were influenced by the impact force size and the difference in the size of the damaged part of the apple, but the damage development pattern was independent of the impact force size and the difference in the damaged part. The maximum damage rate was reached at about 30 min, and the depth of damage was stabilized at about 72 min. By studying the evolution pattern of the damaged tissue of the bruised ‘Red Delicious’ apple, it provides the research idea and theoretical basis for enhancing the prediction accuracy and robustness of early stage damage in apples.

WUSCHEL-related homeobox (WOX) transcription factors (TFs) play a crucial role in regulating plant development and responding to various abiotic stresses. However, the members and functions of WOX proteins in Pinus massoniana remain unclear. In this study, a total of 11 WOX genes were identified, and bioinformatics methods were used for preliminary identification and analysis. The phylogenetic tree revealed that most PmWOXs were distributed in ancient and WUS clades, with only one member found in the intermediate clade. We selected four highly conserved WOX genes within plants for further expression analysis. These genes exhibited expressions across almost all tissues, while PmWOX2, PmWOX3, and PmWOX4 showed high expression levels in the callus, suggesting their potential involvement in specific functions during callus development. Expression patterns under different abiotic stresses indicated that PmWOXs could participate in resisting multiple stresses in P. massoniana. The identification and preliminary analysis of PmWOXs lay the foundation for further research on analyzing the resistance molecular mechanism of P. massoniana to abiotic stresses.

In order to safeguard the ecological health of Changxinggang River’s water environment, conducting research on ecological discharge, including establishing reasonable ecological discharge control values, is of great importance. This study utilized monthly hydro-ecological data from the Xintang section of the Changxinggang River that spanned the years 2016 to 2020. It defined the water quality control indicators for both non-flood and flood periods in the Changxinggang River and utilized the MIKE 11 software to construct the MIKE 11 one-dimensional hydrodynamic–water quality coupling model. A comparison between simulated values and measured values showed that the model exhibits a relative error of less than 17%, indicating its suitability for practical use. The results indicate that the water quality control indicators for the non-flood period in the Changxinggang River encompass ammonium nitrogen (NH3-N), chemical oxygen demand (manganese) (CODMn), and biochemical oxygen demand (BOD), while those for the flood period include NH3-N, total phosphorus (TP), and CODMn. Reasonable ecological discharge control values for both non-flood and flood periods in the Changxinggang River are calculated to be 2.59 m3/s and 2.63 m3/s, respectively. The model developed in this study is applicable for ecological discharge calculations in the Changxinggang River, and the proposed ecological discharge control values are achievable.

Hypsizygus marmoreus has become one of the most popular edible mushrooms due to its high nutritional and economic value. Previous researchers found that Serratia odorifera could promote the growth of H. marmoreus by producing and secreting some of its inducers. However, the specific mechanism of action was still unclear. In this study, we found that the exogenous addition of sterile fermentation filtrate (HZSO-1), quorum sensing (QS) signaling molecules, 3-oxo-C6-HSL, cyclo(Pro-Leu), and cyclo(Tyr-Leu) could significantly promote the growth of H. marmoreus, increase the number of clamp junctions, and the diameter of mycelium (p < 0.05). In addition, non-targeted metabolomic analysis revealed that 706 metabolites were detected in the treated group. Of these, 307 metabolites were significantly different (p < 0.05). Compared with the control, 54 and 86 metabolites were significantly increased and decreased in the HZSO-1 group, respectively (p < 0.05). We speculate that the sterile fermentation filtrate of S. odorifera could mediate the carbohydrate and amino acid metabolism of H. marmoreus by influencing the pentose phosphate pathway (PPP) to increase the energy supply for the growth and development of the mycelium. The above results will further reveal the growth-promoting mechanism of S. odorifera on H. marmoreus.

Flavone glycosides, their aglycones, and metabolites are the major phytochemicals in dietary intake. However, there are still many unknowns about the cellular utilization and active sites of these natural products. Uridine diphosphate glucuronosyltransferases (UGTs) in the endoplasmic reticulum have gene polymorphism distribution in the population and widely mediate the absorption and metabolism of endogenous and exogenous compounds by catalyzing the covalent addition of glucuronic acid and various lipophilic chemicals. Firstly, we found that rutin, a typical flavone O-glycoside, has a stronger UGT2B7 binding effect than its metabolites. After testing a larger number of flavonoids with different aglycones, their aglycones, and metabolites, we demonstrated that typical dietary flavone O-glycosides generally have high binding affinities towards UGT2B7 protein, but the flavone C-glycosides and the phenolic acid metabolites of flavones had no significant effect on this. With the disposition of 4-methylumbelliferone examined by HPLC assay, we determined that 10 μM rutin and nicotifiorin could significantly inhibit the activity of recombinant UGT2B7 protein, which is stronger than isovitexin, vitexin, 3-hydroxyphenylacetic acid and 3,4-dihydroxyphenylacetic acid. In addition, in vitro experiments showed that in normal and doxorubicin-induced lipid composition, both flavone O-glycosides rutin and flavone C-glycosides isovitexin at 10 μM had no significant effect on the expression of UGT1A1, UGT2B4, UGT2B7, and UGT2B15 genes for 24 h exposure. The obtained results enrich the regulatory properties of dietary flavone glycosides, aglycones, and metabolites towards the catalysis of UGTs and will contribute to the establishment of a precise nutritional intervention system based on lipid bilayers and theories of nutrients on endoplasmic reticulum and mitochondria communication.

Predicting the remaining time before the next earthquake based on seismic signals generated in a laboratory setting is a challenging research task that is of significant importance for earthquake hazard assessment. In this study, we employed a mel spectrogram and the mel frequency cepstral coefficient (MFCC) to extract relevant features from seismic signals. Furthermore, we proposed a deep learning model with a hierarchical structure. This model combines the characteristics of long short-term memory (LSTM), one-dimensional convolutional neural networks (1D-CNN), and two-dimensional convolutional neural networks (2D-CNN). Additionally, we applied a stacking model fusion strategy, combining gradient boosting trees with deep learning models to achieve optimal performance. We compared the performance of the aforementioned feature extraction methods and related models for earthquake prediction. The results revealed a significant improvement in predictive performance when the mel spectrogram and stacking were introduced. Additionally, we found that the combination of 1D-CNN and 2D-CNN has unique advantages in handling time-series problems.

Pathogens cause infections and millions of deaths globally, while antipathogens are drugs or treatments designed to combat them. To date, multifunctional nanomaterials (NMs), such as organic, inorganic, and nanocomposites, have attracted significant attention by transforming antipathogen livelihoods. They are very small in size so can quickly pass through the walls of bacterial, fungal, or parasitic cells and viral particles to perform their antipathogenic activity. They are more reactive and have a high band gap, making them more effective than traditional medications. Moreover, due to some pathogen’s resistance to currently available medications, the antipathogen performance of NMs is becoming crucial. Additionally, due to their prospective properties and administration methods, NMs are eventually chosen for cutting-edge applications and therapies, including drug administration and diagnostic tools for antipathogens. Herein, NMs have significant characteristics that can facilitate identifying and eliminating pathogens in real-time. This mini-review analyzes multifunctional NMs as antimicrobial tools and investigates their mode of action. We also discussed the challenges that need to be solved for the utilization of NMs as antipathogens.

Photodynamic therapy (PDT) has emerged as a powerful tumor treatment tool due to its advantages including minimal invasiveness, high selectivity and thus dampened side effects. On the other side, the efficacy of PDT is severely frustrated by the limited oxygen level in tumors, thus promoting its combination with other therapies, particularly photothermal therapy (PTT) for bolstered tumor treatment outcomes. Meanwhile, nanomedicines that could respond to various stimuli in the tumor microenvironment (TME) provide tremendous benefits for combined phototherapy with efficient hypoxia relief, tailorable drug release and activation, improved cellular uptake and intratumoral penetration of nanocarriers, etc. In this review, we will introduce the merits of combining PTT with PDT, summarize the recent important progress of combined phototherapies and their combinations with the dominant tumor treatment regimen, chemotherapy based on smart nanomedicines sensitive to various TME stimuli with a focus on their sophisticated designs, and discuss the challenges and future developments of nanomedicine-mediated combined phototherapies.

A large body of research has explored various factors influencing volunteer participation, particularly revealing the association between religious beliefs and volunteer engagement. However, there was relatively limited research on volunteer participation among international immigrants in China, a newly emerging immigrant country. Further investigation was needed to identify the factors influencing the volunteer engagement of international immigrants in China and the underlying mechanisms. This study analyzed data from international immigrants in Yiwu, China and found that their volunteer behavior was significantly influenced by their religious beliefs. Additionally, social resources were closely related to their volunteer participation. Furthermore, although perceived discrimination among international immigrants in China was not directly associated with volunteer participation, it promoted their religious participation and frequency, consequently encouraging their volunteer engagement. Further analysis also revealed two mechanisms through which religion impacted volunteer participation. On the one hand, religious beliefs influenced volunteer participation through the mechanism of religious indoctrination. On the other hand, though perceived discrimination among international immigrants did not directly influence volunteer participation, it did encourage them to engage in religious meetings to establish social networks for support, thereby enriching their social resources and subsequently promoting volunteer engagement. We discussed the implications of our findings for encouraging volunteer participation and for promoting the social integration of international immigrants.

The urban water environment is seriously affected by human activities. Rivers in highly industrialized areas, which often carry various types of industrial pollutants, such as metals and nutrients, are especially affected. In this study, the water quality of the Pi River, an industrial base that flows through Chengdu, a large city in Southwest China, was tested for one year. Heavy metal concentrations in the water, sediment, and macrobenthic and algal communities in the river were examined. The water pollution index (WPI) and trophic level index (TLI) were employed to measure the water pollution degree and eutrophication status, respectively. The Shannon—Wiener index (H’) and Margalef’s index (dM) were determined to represent the diversity and richness of macroinvertebrates. The principal component analysis (PCA) was employed to define the main heavy metal influencing factors in the Pi River. Our study showed that the eutrophication status increased with spatial change, and the eutrophication status was the most serious in the downstream reach, which was moderately eutrophic. The water body of the Pi River was seriously polluted by heavy metals, and the content of chromium (Cr) in the sediment and cadmium (Cd) in the water/sediment was far beyond the prescribed limit. In addition, we found that Cd had a serious impact on both the benthic and algal communities, and the benthic community structure was completely changed, destroying the original aquatic environment. We explored the mechanisms of the influence of Cd on aquatic fauna, and this information is of great significance for the future conservation of industrial urban rivers. In this study, the spatial–temporal variations in water quality and aquatic communities revealed the pollution status of a river flowing through industrial areas, which provided a basis for future river conservation and restoration.

Remote sensing scene classification (RSSC) is a very crucial subtask of remote sensing image understanding. With the rapid development of convolutional neural networks (CNNs) in the field of natural images, great progress has been made in RSSC. Compared with natural images, labeled remote sensing images are more difficult to acquire, and typical RSSC datasets are consequently smaller than natural image datasets. Due to the small scale of these labeled datasets, training a network using only remote sensing scene datasets is very difficult. Most current approaches rely on a paradigm consisting of ImageNet pretraining followed by model fine-tuning on RSSC datasets. However, there are considerable dissimilarities between remote sensing images and natural images, and as a result, the current paradigm may present some problems for new studies. In this paper, to break free of this paradigm, we propose a general framework for scene classification (GFSC) that can help to train various network architectures on limited labeled remote sensing scene images. Extensive experiments show that ImageNet pretraining is not only unnecessary but may be one of the causes of the limited performance of RSSC models. Our study provides a solution that not only replaces the ImageNet pretraining paradigm but also further improves the baseline for RSSC. Our proposed framework can help various CNNs achieve state-of-the-art performance using only remote sensing images and endow the trained models with a stronger ability to extract discriminative features from complex remote sensing images.

Takotsubo syndrome (TTS) is a stress-induced cardiomyopathy that presents with sudden onset of chest pain and dyspneic and cardiac dysfunction as a result of extreme physical or emotional stress. The sigma-1 receptor (Sigmar1) is a ligand-dependent molecular chaperone that is postulated to be involved in various processes related to cardiovascular disease. However, the role of Sigmar1 in TTS remains unresolved. In this study, we established a mouse model of TTS using wild-type and Sigmar1 knockout mice to investigate the involvement of Sigmar1 in TTS development. Our results revealed that Sigmar1 knockout exacerbated cardiac dysfunction, with a noticeable decrease in ejection fraction (EF) and fractional shortening (FS) compared to the wild-type model. In terms of the gut microbiome, we observed regulation of Firmicutes and Bacteroidetes ratios; suppression of probiotic Lactobacillus growth; and a rise in pathogenic bacterial species, such as Colidextribacter. Metabolomic and transcriptomic analyses further suggested that Sigmar1 plays a role in regulating tryptophan metabolism and several signaling pathways, including MAPK, HIF-1, calcium signaling, and apoptosis pathways, which may be crucial in TTS pathogenesis. These findings offer valuable insight into the function of Sigmar1 in TTS, and this receptor may represent a promising therapeutic target for TTS.