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Jatropha curcas L. (J. curcas), a shrub plant of the Euphorbiaceae family, has received enormous attention as a promising biofuel plant for the production of biodiesel and medical potential in ethnopharmacology. However, the tumor-promoter toxin phorbol esters present in J. curcas raise concerns for health and environmental risk as its large-scale cultivation limits the use of meal obtained after oil extraction for animal feed. Here, we determined the variation of phorbol ester profiles and contents in eight J. curcas tissues by high-performance liquid chromatography (HPLC) and found phorbol esters present in all parts of the plant except the seed shell. We showed tissue-specific patterns of accumulation of phorbol esters and associated terpenoids at the transcriptional level with high transcript levels in reproductive and young tissues. Genes involved in the same module of terpenoids biosynthesis were positively correlated. We further present diverse abiotic and biotic stresses that had different effects on the accumulation of transcripts in terpenoids shared and branched terpenoid pathways in plant seedlings. The fine-tuning of terpenoids biosynthesis may link with ecological functions in plants under extreme environments and defense against pathogens.

In recent years, live streaming has become the mainstream way of online shopping in China. As the dominant player and performer in live streaming, streamers play a crucial role in consumers’ purchase decisions. Therefore, this study focuses on the self-presentation behavior of streamers in the context of e-commerce live streaming and explores the mechanism of its influence on consumers’ purchase intention from the perspective of persuasion knowledge. A total of 538 consumers from China participated in this anonymous survey. The results indicate that helpful and empathetic behaviors of streamers can significantly enhance consumers’ purchase intention, while derogatory, exaggerated, and flattering behaviors of streamers can significantly diminish consumers’ purchase intention. Persuasion knowledge played a mediating role and had a significant negative impact on purchase intention, while anticipated inaction regret weakened its effect on purchase intention.

Exploring the effect of the magnesium alloy aging process on dynamic impact performance could plays an important role in the application of magnesium alloy in automotive lightweighting. In this work, the effects of single-stage, two-stage, and reverse two-stage aging processes on the dynamic mechanical properties of Mg-8.5 Gd-3 Y-0.5 Zr alloy were studied by means of SEM analysis, hardness testing, a quasi-static compression experiment, and SHPB. The results show that the compressive strength of the materials after single-stage, two-stage, and reverse two-stage aging treatments is improved to different degrees compared with that of the alloys in the extruded state. Due to the generation of dynamic precipitation with semi-annular distribution during SHPB, the compressive strength of the reverse two-stage aging alloys reached an excellent 761 MPa, while the two-stage aging alloys had more dynamic precipitation phases at the strain rate of 3500 s−1, resulting in a compressive strength of 730 MPa, which is superior to that of the aluminum alloys used in a wide range of automotive applications. The results of this study can provide a reference for the application of Mg-Gd magnesium alloys under dynamic loading.

The Xuanwei Formation’s claystones in the Dian-Qian District of Southwest China are rich in rare-earth elements (REEs), suggesting their potential as a source of medium and heavy rare earths. However, the REE content in these rocks is lower than other types of rare-earth deposits, and the interrelationship among clay minerals is intricate. There is no direct evidence indicating the mineralization of REEs, limiting their beneficiation and extraction. The objective of this study is the characterization of REE distribution in the Dian-Qian District. The sedimentary rocks in this district are mainly composed of kaolinite, boehmite, quartz, rutile, and pyrite. The results of continuous chemical extraction of REE-rich claystone and transmission electron microscope (TEM) observations have confirmed that REEs occurred as florencite in the rocks, and that the ion-absorption state makes only a negligible contribution to the REE content. A close relationship between florencite and kaolinite makes traditional mineral processing operations very difficult. Combined with the properties of kaolinite, roasting-acid leaching was the efficacious approach for rare-earth resources extracted from the rare earth-rich clay rocks of the Xuanwei Formation.

The genetic diversity and structure of 17 populations of J. curcas, including 92 accessions from different provenances (tropical and subtropical), were investigated and effectively evaluated using twelve inter-simple sequence repeats (ISSRs) and seven pairs of florescence-amplified fragment-length polymorphism (AFLP) primers. Genetic diversity, at the overall level among populations of J. curcas based on the ISSR markers, showed that the observed number of alleles (Na) was 1.593, the effective number of alleles (Ne) was 1.330, Nei’s gene diversity (H) was 0.200, Shannon’s information index (I) was 0.303, and the percentage of polymorphic loci was 59.29%, indicating moderate genetic diversity between and within the different populations of J. curcas. Based on the genetic diversity analysis of AFLP markers, there were 1.464 (Na) and 1.216 (Ne) alleles, Nei’s gene diversity (H) was 0.132, Shannon’s information index (I) was 0.204, and the percentage of polymorphic loci was 46.40%. The AMOVA analysis showed that this large variance was due to differences within the populations, with genetic distinctions and limited gene flow among those from varied regions. The 17 populations were clustered into five main groups via UPGMA clustering analysis based on Nei’s genetic distance, and the genetic relationships among the populations exhibited no significant correlations with geographical provenances. The genetic variation among Chinese populations of J. curcas distributed in dry-hot valley areas was remarkable, and the American germplasm presented with distinct genetic differentiation.

Genetic transformation of forest trees is essential for validating gene functions and breeding new varieties through molecular means. Appropriate selective pressure is critical for creating an effective screening system. ‘Beilinxiongzhu 1’ sensitivity testing showed that the critical tolerance concentrations for hygromycin (Hyg), kanamycin (Kan), and glyphosate (PPT) in leaf explants were 2.0 mg/L, 20 mg/L, and 1.0 mg/L, respectively. Among the physiological indicators, soluble sugar content, soluble protein content, and endogenous hormone levels were identified as key markers of the effects of the different antibiotic treatments. Transcriptome analysis showed that Hyg treatment resulted in a large number of differentially expressed genes (DEGs) involved in leaf cell wall synthesis and glucose metabolism. Under Kan treatment, the DEGs were associated with pathways such as ribosome biosynthesis and histone packaging in eukaryotes. Under PPT treatment, significant DEGs were related to ABC transporters. DEGs common to all three antibiotics were involved in glutathione metabolism pathways. A weighted gene co-expression network analysis identified TRXH2, H3.2, H2B, GST, U71K1, and CHS as key genes in response to antibiotic stress. By elucidating the physiological and molecular mechanisms by which different antibiotics affect leaf sprouting, our study serves as a reference for research into the genetic transformation of poplar leaves.

Sweet potato (Ipomoea batatas L.) is an important food, feed, and industrial raw material and new energy crop. Its rich nutritional value and health effects are increasingly being recognized by consumers, and the demand is increasing. However, due to the continuous cultivation of sweet potato over many years, the degeneration of seedlings and the accumulation of viral diseases are important factors affecting the yield and quality of sweet potatoes. This article provides an overview and analysis of the types and hazards of sweet potato virus diseases, the advantages of virus-free sweet potatoes, the scale of virus-free sweet potato cultivation, sweet potato stem tip virus-free production technology, its development status, and the existing problems. Combined with the development of the sweet potato industry across China, relevant development suggestions are proposed to provide a reference for promoting the healthy, stable, sustainable, high-quality, and efficient development of the sweet potato industry.

A new green water treatment agent, a poly(aspartic acid)-modified polymer (PASP/5–AVA), was synthesized using polysuccinimide and 5-aminovaleric acid (5-AVA) in a hybrid system. The structure was characterized, and the scale and corrosion inhibition performance were carried out with standard static scale inhibition and electrochemical methods, respectively. The mechanism was explored using XRD, XPS, SEM, and quantum chemistry calculations. The results indicated that PASP/5–AVA exhibited better scale and corrosion inhibition performance than PASP and maintained efficacy and thermal stability of the scale inhibition effect for a long time. Mechanistic studies indicated that PASP/5–AVA interferes with the normal generation of CaCO3 and CaSO4 scales through lattice distortion and dispersion, respectively; the combined effect of an alkaline environment and terminal electron-withdrawing -COOH groups can induce the stable C- ionic state formation in -CH2- of the extended side chain, thus enhancing its chelating ability for Ca2+ ions. At the same time, the extension of the side chain length also enhances the adsorption ability of the agent on the metal surface, forming a thick film and delaying the corrosion of the metal surface. This study provides the necessary theoretical reference for the design of green scale and corrosion agents.

Local ice pressure refers to the ice pressure exerted on a very small area of a structure during ice failure. The existence of high-pressure zones may lead to local deformation and damage to ice-resistant structures, posing a serious threat to the overall structural stability. This study simulates the interaction between sea ice and structures through model tests, analyzing the timing of extreme local ice pressures. The results show that at low loading speeds, there is a 50% probability that the extreme local ice pressure occurs at the peak of the global ice force, while at high loading speeds, this probability drops to around 25%. Further investigation into the relationship between the global ice force peak, ice thickness, loading speed, and local area with local ice pressure amplitude reveals that the local ice pressure amplitude decreases with increasing loading speed and increases with ice thickness. Based on the area averaging method for square regions, the relationship between local ice pressure amplitude and local area is studied, showing that ice thickness, local width, and loading speed all influence the pressure–area relationship. Based on the square area averaging method, the relationship between the local ice pressure amplitude and the local area was studied. It was found that a linear relationship exists between the power function coefficient of local ice pressure–area and the thickness-to-width ratio. Compared to brittle failure, the local ice pressure amplitude under ductile failure of the ice sheet is more significantly affected by ice thickness. This study provides a foundation and reference for the analysis of ice-resistant performance and structural design of polar marine engineering structures.

To meet the demands for high-temperature performance and lightweight materials in aerospace engineering, the Au-Ni solder is often utilized for joining dissimilar materials, such as Ti3Al-based alloys and Ni-based high-temperature alloys. However, the interaction between Ti and Ni can lead to the formation of brittle phases, like Ti2Ni, TiNi, and TiNi3, which diminish the mechanical properties of the joint and increase the risk of crack formation during the welding process. Cu doping has been shown to enhance the mechanical properties and high-temperature stability of the Au-Ni brazed joint’s central area. Due to the difficulty in accurately controlling the solid solution content of Cu in the Au-Ni alloy, along with the high cost of Au, traditional experimental trial-and-error methods are insufficient for the development of Au-based solders. In this study, first principles calculations based on density functional theory were employed to analyze the effect of Cu content on the stability of the Au-2.0Ni-xCu (x = 0, 0.25, 0.5, 0.75, 1.0, 1.25 wt%) alloy phase structure. The thermal properties of the alloy were determined using Gibbs software fitting. The results indicate that the Au-2.0Ni-0.25Cu alloy exhibits the highest plastic toughness (B/G = 5.601, ν = 0.416, Cauchy pressure = 73.676 GPa) and a hardness of 1.17 GPa, which is 80% higher than that of Au-2.0Ni. This alloy balances excellent strength and plastic toughness, meeting the mechanical performance requirements of brazed joints. The constant pressure specific heat capacity (Cp) of the Au-2.0Ni-xCu alloy is higher than that of Au-2.0Ni and increases with Cu content. At 1000 K, the Cp of the Au-2.0Ni-0.25Cu alloy is 35.606 J·mol−1·K−1, which is 5.88% higher than that of Au-2.0Ni. The higher Cp contributes to enhanced high-temperature stability. Moreover, the linear expansion coefficient (CTE) of the Au-2.0Ni-0.25Cu alloy at 1000 K is 8.76 × 10−5·K−1, only 0.68% higher than Au-2.0Ni. The lower CTE helps to reduce the risk of solder damage caused by thermal stress. Therefore, the Au-2.0Ni-0.25Cu alloy is more suitable for brazing applications in high-temperature environments due to its excellent mechanical properties and thermal stability. This study provides a theoretical basis for the performance optimization and engineering application of the Au-2.0Ni-xCu alloy as a gold-based solder.

Heyndrickxia coagulans (formerly Bacillus coagulans) has been increasingly utilized as an immunomodulatory probiotics. Oral administration of H. coagulans HOM5301 significantly boosted both innate and adaptive immunity in mice, particularly by increasing the phagocytic capacity of monocytes/macrophages. Lipoteichoic acid (LTA), a major microbe-associated molecular pattern (MAMP) in Gram-positive bacteria, exhibits differential immunomodulatory effects due to its structural heterogeneity. We extracted, purified, and characterized LTA from H. coagulans HOM5301. The results showed that HOM5301 LTA consists of a glycerophosphate backbone. Its molecular weight is in the range of 10–16 kDa. HOM5301 LTA induced greater productions of nitric oxide, TNFα, and IL-6 in RAW 264.7 macrophages compared to Staphylococcus aureus LTA. Comparative transcriptome and proteome analyses identified the differentially expressed genes and proteins triggered by HOM5301 LTA. KEGG analyses revealed that HOM5301 LTA transcriptionally and translationally activated macrophages through two immune-related pathways: cytokine–cytokine receptor interaction and phagosome formation. Protein–protein interaction network analysis indicated that the pro-inflammatory response elicited by HOM5301 LTA was TLR2-dependent, possibly requiring the coreceptor CD14, and is mediated via the MAPK and NF-kappaB pathways. Our results demonstrate that LTA is an important MAMP of H. coagulans HOM5301 that boosts immune responses, suggesting that HOM5301 LTA may be a promising immunoadjuvant.

Fructilactobacillus sanfranciscensis, the dominant species of lactic acid bacteria in sourdoughs, impacts the microstructure and flavor of steamed bread through exopolysaccharide production, acidification, proteolysis, and volatile compound generation. The aim of this study is to investigate the phenotypic diversity and technological traits of 28 F. sanfranciscensis strains of different genotypes isolated from Chinese traditional sourdoughs. The results showed that F. sanfranciscensis strains exhibited substantial variation in proteinase and peptidase activities and the amount of acidification and volatiles in fermented sourdoughs. However, we observed no significant differences in exopolysaccharide production among the strains. The strains Sx14 and Ts1 were further chosen for transcriptomics to gain a deep insight into their intraspecies diversity in sourdough fermentation. Significant transcriptome differentiations between these two strains after 12 h fermentation in sourdoughs were revealed. According to the results, the strain Sx14 possessed higher dipeptidase and aminopeptidase activities, galactose utilization, and lactic and acetic acid production abilities, whereas Ts1 showed higher transmembrane transport of substrates and fructose utilization.

Alzheimer’s disease (AD) is a multifaceted neurodegenerative disorder characterized by cognitive decline and neuronal loss, representing a most challenging health issue. We present a computational analysis of transcriptomic data of AD tissues vs. healthy controls, focused on the elucidation of functional roles played by long non-coding RNAs (lncRNAs) throughout the AD progression. We first assembled our own lncRNA transcripts from the raw RNA-Seq data generated from 527 samples of the dorsolateral prefrontal cortex, resulting in the identification of 31,574 novel lncRNA genes. Based on co-expression analyses between mRNAs and lncRNAs, a co-expression network was constructed. Maximal subnetworks with dense connections were identified as functional clusters. Pathway enrichment analyses were conducted over mRNAs and lncRNAs in each cluster, which served as the basis for the inference of functional roles played by lncRNAs involved in each of the key steps in an AD development model that we have previously built based on transcriptomic data of protein-encoding genes. Detailed information is presented about the functional roles of lncRNAs in activities related to stress response, reprogrammed metabolism, cell polarity, and development. Our analyses also revealed that lncRNAs have the discerning power to distinguish between AD samples of each stage and healthy controls. This study represents the first of its kind.

The discharge and flashover phenomenon of post insulators in rainy weather has not been given sufficient consideration; however, with the construction of ultra-high voltage power grids, the performance of the external insulation and the ability to withstand special climate conditions need to be guaranteed. Therefore, it is meaningful to conduct studies on the discharge characteristics of contaminated post insulators under rainfall conditions. Moreover, the conventional perception tends to confuse the flashover of polluted insulators in the rain with the pollution flashover that occurs in the fog; however, in fact, the discharge of contaminated insulators that occurs during rainfall has characteristics that can be distinguished from the pollution flashover. In this study, firstly, the current status of research on the external insulation characteristics of post insulators was analyzed through an examination of the available literature. Secondly, the concept of a ‘pollution rain flashover’ of insulators was established and clarified, to distinguish it from the traditional meaning of ‘pollution flashover’ or ‘contamination flashover’. Thirdly, research results on the pollution rain flashover of post insulators used in power stations in recent years were summarized, which included the characteristics and mechanism of the discharge, parameters and factors influencing the flashover voltage, and their influence laws. Particularly, the gap discharge between insulator sheds triggered by raindrops, which is the most significant feature of the pollution rain flashover, and the profile optimization of sheds, which is an effective way to improve the performance, were emphasized in this work. Fourthly, the prevention methods were studied, which mainly include the application of rainproof sheds and the shed optimization for pollution rain flashover of post insulators. Finally, a brief prospect is given for future research.

Infusion systems are widely used in clinical medicine. Intravenous infusion therapy must be monitored to ensure patient safety. We proposed a compact flow rate sensor device based on the time-of-flight method. This device included one ceramic heater and two infrared sensors. Practical sensor prototypes were fabricated and characterized. The response time was 30 s. The sensor range was estimated to be 33 dB from μL/min to tens of mL/min, covering almost the entire usage range This flow rate sensor can be applied to common infusion tubes. Through the use of a mobile phone app, detailed information can be presented in real time.

The Surface Waves Investigation and Monitoring instrument (SWIM) provides the directional wave spectrum within the wavelength range of 23–500 m, corresponding to a frequency range of 0.056–0.26 Hz in deep water. This frequency range is narrower than the 0.02–0.485 Hz frequency range of buoys used to validate the SWIM nadir Significant Wave Height (SWH). The modulation transfer function used in the current version of the SWIM data product normalizes the energy of the wave spectrum using the nadir SWH. A discrepancy in the cut-off frequency/wavelength ranges between the nadir and off-nadir beams can lead to an overestimation of off-nadir cut-off SWHs and, consequently, the spectral densities of SWIM wave spectra. This study investigates such errors in SWHs due to the wavelength cut-off effect using buoy data. Results show that this wavelength cut-off error of SWH is small in general thanks to the high-frequency extension of the resolved frequency range. The corresponding high-frequency cut-off errors are systematic errors amenable to statistical correction, and the low-frequency cut-off error can be significant under swell-dominated conditions. By leveraging the properties of these errors, we successfully corrected the high-frequency cut-off SWH error using an artificial neural network and mitigated the low-frequency cut-off SWH error with the help of a numerical wave hindcast. These corrections significantly reduced the error in the estimated cut-off SWH, improving the bias, root-mean-square error, and correlation coefficient from 0.086 m, 0.111 m, and 0.9976 to 0 m, 0.039 m, and 0.9994, respectively.

High-resolution and thermal infrared hyperspectral data acquired from the Thermal Infrared Airborne Spectrographic Imager (TASI) have been recognized as efficient tools in geology, demonstrating significant potential for rock discernment. Deep learning (DL), as an advanced technology, has driven substantial advancements in lithological mapping by automatically extracting high-level semantic features from images to enhance recognition accuracy. However, gathering sufficient high-quality lithological samples for model training is challenging in many scenarios, posing limitations for data-driven DL approaches. Moreover, existing sample collection approaches are plagued by limited verifiability, subjective bias, and variation in the spectra of the same class at different locations. To tackle these challenges, a novel sample generation method called multi-lithology spectra sample selection (MLS3) is first employed. This method involves multiple steps: multiple spectra extraction, spectra combination and optimization, lithological type identification, and sample selection. In this study, the TASI hyperspectral data collected from the Liuyuan area in Gansu Province, China, were used as experimental data. Samples generated based on MLS3 were fed into five typical DL models, including two-dimensional convolutional neural network (2D-CNN), hybrid spectral CNN (HybridSN), multiscale residual network (MSRN), spectral-spatial residual network (SSRN), and spectral partitioning residual network (SPRN) for lithological mapping. Among these models, the accuracy of the SPRN reaches 84.03%, outperforming the other algorithms. Furthermore, MLS3 demonstrates superior performance, achieving an overall accuracy of 2.25–6.96% higher than other sample collection methods when SPRN is used as the DL framework. In general, MLS3 enables both the quantity and quality of samples, providing inspiration for the application of DL to hyperspectral lithological mapping.

Accurate monitoring of steel plate coating thickness is crucial in construction quality control and durability assessments. To address this challenge, this study introduces a terahertz time-domain reflection spectroscopy based on a BP neural network model to achieve a quantitative visualization characterization of coating thickness. The BP neural network eliminates the inherent dependence of terahertz reflection spectroscopy on the refractive index value in thickness calculation. This trained BP neural network model effectively establishes a functional relationship between signal feature parameters and the corresponding thickness values. Additionally, the proposed model can innovatively measure different coating materials’ refractive indexes, revealing the corresponding values for the black paint, white paint, epoxy resin, and rubber as 2.212, 1.967, 1.924, and 2.185, respectively. The experimental results demonstrate the trained BP neural network model possesses remarkable accuracy in predicting coating thickness within the scanning area, achieving a precision level exceeding 96%. This method enables the visualization of coating thickness and the extraction of thickness characterization values. Furthermore, using the thickness imaging results as a reference, the method can accurately identify the thickness abnormalities across the scanning area, locating the position and size of potential defects such as internal scratches and foreign object defects. This innovative approach offers a superior means of monitoring and assessing the thickness distribution quality of the steel plate coating layer materials.

Compared to conventional support methods, the close-fitting pile–wall integration technique features a minimized construction spacing between the retaining pile and the basement retaining wall. This approach leverages the pile stiffness to minimize the wall thickness and enhance underground space utilization. However, it currently lacks significant discussions and measured data about the interaction laws between the pile and the wall. The model test and finite element method (FEM) are employed to study the deformation and internal force interaction laws of two typical close-fitting pile–wall integrated structures, and a comparison with conventional design is conducted. Furthermore, this study separately investigates the impact of sensitivity factors, specifically the pile–wall stiffness ratio and floor plate stiffness, on both structures during the basement construction and serviceability stages. The test results can closely match the numerical simulation. The study results reveal that the wall impacts the bending moment of the pile to some extent. The internal force in the wall is significantly influenced by the lateral deformation of the pile and the floor plate. Compared to conventional designs, this structure significantly reduces the bending moment of the wall, particularly in the composite structure. Additionally, the analysis of sensitivity factors reveals their considerable influence on the pile–wall interaction.

Cation exchange resin (CER) has been reported to promote sludge fermentation. However, previous studies have typically focused on the effects of CER on sludge properties to enhance fermentation, and the role of CER as a biocarrier for anaerobic consortia during fermentation has been overlooked. Thus, in this study, the potential of gel-type and macro-reticular type CERs to serve as biocarriers in fermentation was investigated. A significant number of anaerobes appeared to be attached to the surfaces of CER during 2-day fermentation. However, an extended fermentation time negatively affected the attachment of anaerobic consortia, suggesting that CER may be a suitable carrier for short-term fermentation processes, such as biohydrogen fermentation. Electrochemical analyses revealed that the electron transfer capacities of CER with attached anaerobes were enhanced after both 2-day and 28-day fermentation periods, with the macro-reticular type CER exhibiting higher electron transfer capacity than the gel-type CER. Fermentation experiments using mixing model substrates with macro-reticular and gel-type CERs with attached anaerobes showed that the macro-reticular type CER was more beneficial for biohydrogen fermentation than the gel-type CER. Further analyses of microbial communities revealed that hydrogen-producing bacteria (i.e., Caloramator, unclassified_f_Caloramatoraceace, and Sporanaerobacter) were more likely to adhere to the macro-reticular type CERs. This outcome confirmed that macro-reticular type CERs have significant potential as a carrier for anaerobic consortia to promote the generation of hydrogen and volatile fatty acids. These findings are expected to provide a reference for using materials as biocarriers to enhance the biohydrogen fermentation of sludge.

Excessive use of chemical fertilizer is a global concern. Arbuscular mycorrhizal fungi (AMF) are considered a potential solution due to their symbiotic association with crops. This study assessed AMF’s effects on maize yield, fertilizer efficiency, plant traits, and soil nutrients under different reduced-fertilizer regimes in medium–low fertility fields. We found that phosphorus supplementation after a 30% fertilizer reduction enhanced AMF’s positive impact on grain yield, increasing it by 3.47% with pure chemical fertilizers and 6.65% with mixed fertilizers. The AMF inoculation did not significantly affect the nitrogen and phosphorus fertilizer use efficiency, but significantly increased root colonization and soil mycelium density. Mixed fertilizer treatments with phosphorus supplementation after fertilizer reduction showed greater mycorrhizal effects on plant traits and soil nutrient contents compared to chemical fertilizer treatments. This study highlights that AMF inoculation, closely linked to fertilization regimes, can effectively reduce fertilizer use while sustaining or enhancing maize yields.

A liquid–liquid extraction pretreatment method using n-hexane as the extractant was developed for the analysis of volatile aroma substances in three flavors (six cola samples, six lemon samples, and six orange samples) of carbonated beverages by gas chromatography–mass spectrometry (GC-MS). Quantitative analysis was conducted using the external standard method. The spiked recovery rate of α-terpineol was used as the evaluation criterion. Single-factor and response surface experiments were conducted to investigate the effects of extraction temperature, extraction time, and solvent-to-sample ratio. The results indicated that the maximum spiked recovery rate of α-terpineol, 81.00%, was achieved at an extraction temperature of 45 °C, extraction time of 30 min, and a solvent-to-sample ratio of 1 mL:15 mL. Thirty-four components were identified by GC-MS on the pretreated samples via the internal standard method. 1,4-Cineole, fenchyl alcohol, borneol, and α-terpineol are covered aroma substances in cola beverages. Two aromatic substances, D-limonene and α-terpineol, were detected in orange juices. α-Terpineol was detected in each lemon-flavor carbonated beverage sample. Going a step further, α-terpineol was detected in all 18 carbonated beverage samples and had high response values. The principal component analysis by functional group classification led to the conclusion that acids, phenols, hydrocarbons, alcohols, and ethers played a major contribution to the aroma of these 18 beverages. Increased separation of target compounds was found using the new pre-treatment methods, resulting in improved analytical resolution and selectivity.

In China, a substantial portion of highway asphalt pavements are no longer capable of accommodating increasing traffic volumes and necessitate renovation and expansion. Prior to commencing such activities, it is crucial to evaluate the performance of the existing asphalt pavements. This study developed a novel normal cloud framework integrating a comprehensive weighted indicator system for existing asphalt pavement. Five key performance indicators including riding quality index (RQI), rutting area ratio (Rr), cracking area ratio (Cr), patching area ratio (Pr), and pavement structural strength index (PSSI) were selected to holistically represent the pavement condition in highway renovation and expansion projects. Subsequently, a method was proposed to determine the weights of these indicators by integrating the analytic hierarchy process (AHP) and entropy. A normal cloud model was constructed to address data characteristics and representation of indicator fuzziness/randomness through digital cloud modeling. The model was applied to 12 sections of the Jingjintang Expressway (Tianjin section). The results revealed only one section where the normal cloud model differed from the pavement maintenance quality assessment (PQI) model. The 3D ground-penetrating radar detection results of this different section indicated that the normal cloud model more closely aligned with the road structure condition. Compared to absolute pass/fail criteria of the traditional PQI model, the cloud model offered enhanced sensitivity to define graded condition assessments essential for reconstruction planning and decision analysis. Therefore, the normal cloud model is more suitable for assessing the performance of existing asphalt pavements in highway reconstruction and extension projects compared to the PQI model.

This paper aims to investigate the strengthening mechanism of laser shock peening on the interfacial bonding properties between TiN coatings and TC4 titanium alloy substrates. The different surface textures were induced by LSP on a TC4 titanium alloy substrate. Subsequently, titanium nitride (TiN) coatings were deposited on the surface texture. A scratch test and reciprocating sliding wear assessment were conducted to evaluate the impact of LSP on the interfacial bonding properties and wear performance of the coatings. The experimental results demonstrated that the adhesion of TiN coatings deposited on the surface texture formed by laser shock peening was significantly enhanced. The efficacy of laser shock treatment in reducing wear rates was found to be significantly enhanced in cases of both increased spot overlapping rate and increased laser power density. The surface texture created using laser parameters of 6.43 GW/cm2 and a 50% overlapping rate was found to have the most significant effect on improving the adhesion and anti-wear properties of the coating. The laser shock texture was identified as the main contributor to this improvement, providing a large interfacial contact area and a mechanical bond between the coating and the substrate. This bond inhibited the initiation and propagation of micro-cracks caused by the concentration of internal stress and interfacial stress of the coating.

Coral reef bleaching events have become more frequent all over the world and pose a serious threat to coral reef ecosystems. Therefore, there is an urgent need for better detection of coral reef bleaching in a time- and cost-saving manner. In recent years, remote sensing technology has often been utilized and gained recognition for coral reef bleaching detection. However, bleaching corals in the water always have weak spectral change signals, causing difficulties in using remote sensing data. Additionally, uneven change samples make it challenging to adequately capture the details of coral reef bleaching detection and produce thematic maps. To resolve these problems, a novel method named coral reef bleaching detection by positive-unlabeled bagging (CBD-PUB) is proposed in this paper. To test the capacity of the method, a series of multi-temporal Sentinel-2 remote sensing images are utilized, and Lizard Island in Australia is taken as a case study area. The pseudo-invariant feature atmospheric correction (PIF) algorithm is adopted to improve coral reef bleaching spectral signals. After that, CBD-PUB is employed to effectively explore coral reef bleaching variation and its corresponding influence relations. The experimental results show that the overall accuracy of bleaching detection by the proposed algorithm reaches 92.1% and outperforms the traditional method. It fully demonstrates the feasibility of the model for the field of coral reef bleaching detection and provides assistance in the monitoring and protection of coral environments.

Intelligent Traditional Chinese Medicine can provide people with a convenient way to participate in daily health care. The ease of acceptance of Traditional Chinese Medicine is also a major advantage in promoting health management. In Traditional Chinese Medicine, tongue imaging is an important step in the examination process. The segmentation and processing of the tongue image directly affects the results of intelligent Traditional Chinese Medicine diagnosis. As intelligent Traditional Chinese Medicine continues to develop, remote diagnosis and patient participation will play important roles. Smartphone sensor cameras can provide irreplaceable data collection capabilities in enhancing interaction in smart Traditional Chinese Medicine. However, these factors lead to differences in the size and quality of the captured images due to factors such as differences in shooting equipment, professionalism of the photographer, and the subject’s cooperation. Most current tongue image segmentation algorithms are based on data collected by professional tongue diagnosis instruments in standard environments, and are not able to demonstrate the tongue image segmentation effect in complex environments. Therefore, we propose a segmentation algorithm for tongue images collected in complex multi-device and multi-user environments. We use convolutional attention and extend state space models to the 2D environment in the encoder. Then, cross-layer connection fusion is used in the decoder part to fuse shallow texture and deep semantic features. Through segmentation experiments on tongue image datasets collected by patients and doctors in real-world settings, our algorithm significantly improves segmentation performance and accuracy.

The retina, a tissue of the central nervous system, is vital for vision as its photoreceptors capture light and transform it into electrical signals, which are further processed before they are sent to the brain to be interpreted as images. The retina is unique in that it is continuously exposed to light and has the highest metabolic rate and demand for energy amongst all the tissues in the body. Consequently, the retina is very susceptible to oxidative stress. VDAC, a pore in the outer membrane of mitochondria, shuttles metabolites between mitochondria and the cytosol and normally protects cells from oxidative damage, but when a cell’s integrity is greatly compromised it initiates cell death. There are three isoforms of VDAC, and existing evidence indicates that all three are expressed in the retina. However, their precise localization and function in each cell type is unknown. It appears that most retinal cells express substantial amounts of VDAC2 and VDAC3, presumably to protect them from oxidative stress. Photoreceptors express VDAC2, HK2, and PKM2—key proteins in the Warburg pathway that also protect these cells. Consistent with its role in initiating cell death, VDAC is overexpressed in the retinal degenerative diseases retinitis pigmentosa, age related macular degeneration (AMD), and glaucoma. Treatment with antioxidants or inhibiting VDAC oligomerization reduced its expression and improved cell survival. Thus, VDAC may be a promising therapeutic candidate for the treatment of these diseases.

In this research, with an aim to develop novel pyrazole oxime ether derivatives possessing potential biological activity, thirty-two pyrazole oxime ethers, including a substituted pyridine ring, have been synthesized and structurally identified through 1H NMR, 13C NMR, and HRMS. Bioassay data indicated that most of these compounds owned strong insecticidal properties against Mythimna separata, Tetranychus cinnabarinus, Plutella xylostella, and Aphis medicaginis at a dosage of 500 μg/mL, and some title compounds were active towards Nilaparvata lugens at 500 μg/mL. Furthermore, some of the designed compounds had potent insecticidal effects against M. separata, T. cinnabarinus, or A. medicaginis at 100 μg/mL, with the mortalities of compounds 8a, 8c, 8d, 8e, 8f, 8g, 8o, 8s, 8v, 8x, and 8z against A. medicaginis, in particular, all reaching 100%. Even when the dosage was lowered to 20 μg/mL, compound 8s also expressed 50% insecticidal activity against M. separata, and compounds 8a, 8e, 8f, 8o, 8v, and 8x displayed more than 60% inhibition rates against A. medicaginis. The current results provided a significant basis for the rational design of biologically active pyrazole oxime ethers in future.

Climate data derived from long-term, multisource altimeter significant wave height (SWH) measurements are more valuable than those obtained from a single altimeter source. Such data facilitate exploration of long-term air–sea momentum transfer and more comprehensive investigation of weather system dynamics processes over the ocean. Despite the deployment of the first satellite in the Chinese Haiyang-2 (HY-2) series more than 12 years ago, validation and integration of SWH data from China’s offshore waters, derived using Chinese altimeters, have been limited. This study constructed a high-resolution, long-term, multisource gridded SWH climate dataset using along-track data from the HY-2 series, CFOSAT, Jason-2, Jason-3, and Cryosat-2 altimeters. Validation against observations from 31 buoys covering China’s offshore waters indicated that the SWH variances from HY-2A, HY-2B, HY-2C, CFOSAT, and Jason-3 altimeters correlated well with observations, with a temporal correlation coefficient of approximately 0.95 (except HY-2A, correlation: 0.89). These SWH measurements generally showed a robust linear relationship with the buoy data. Additionally, cross-calibration between Jason-3 and the HY-2A, HY-2B, HY-2C, and CFOSAT altimeters also demonstrated a typically linear relationship for SWH > 6.0 m. Using this relationship, the SWH data were linearly corrected and integrated into a 10 d mean, long-term, multisource altimeter gridded SWH dataset. Compared with in situ observations, the merged 10 d mean SWHs are more accurate and closely match the observations, with temporal correlation coefficients improving from 0.87 to 0.90 and bias decreasing from 0.28 to 0.03 m. The merged gridded SWHs effectively represent the local spatial distribution of SWH. This study revealed the importance of observational data in the process of merging and recalibrating long-term multisource altimeter SWH datasets, particularly before their application in specific ocean regions.

Tuberculosis (TB) is a major global health threat despite its virtual elimination in developed countries. Issues such as drug accessibility, emergence of multidrug-resistant strains, and limitations of the current BCG vaccine highlight the urgent need for more effective TB control measures. This study constructed BCG strains overexpressing Rv1002c and found that the rBCG-Rv1002c strain secreted more glycosylated proteins, significantly enhancing macrophage activation and immune protection against Mycobacterium tuberculosis (M. tb). These results indicate that Rv1002c overexpression promotes elevated levels of O-glycosylation in BCG bacteriophages, enhancing their phagocytic and antigenic presentation functions. Moreover, rBCG-Rv1002c significantly upregulated immune regulatory molecules on the macrophage surface, activated the NF-κB pathway, and facilitated the release of large amounts of NO and H2O2, thereby enhancing bacterial control. In mice, rBCG-Rv1002c immunization induced greater innate and adaptive immune responses, including increased production of multifunctional and long-term memory T cells. Furthermore, rBCG-Rv1002c-immunized mice exhibited reduced lung bacterial load and histological damage upon M. tb infection. This result shows that it has the potential to be an excellent candidate for a preventive vaccine against TB.

Incorporating carbon footprints into the production efficiency framework to construct a standardized technology model for cleaner production in black soil regions is of great significance for improving the soil environment and the sustainable development of agriculture. This study used an orthogonal experimental design and the DEA–Malmquist method to calculate the carbon footprint and total factor productivity of orthogonal experimental groups of cleaner production technologies for maize cultivation in China’s black soil region and then identified integrated models of cleaner production technology in the black soil region. The results showed that the carbon footprint of maize cultivation and total factor productivity were generally higher in the experimental group using cleaner production techniques than in the control group. Still, none of them reached the optimum. In the future, the synergistic effect of technological progress and technological efficiency enhancement should be brought into play, and the integrated models of “Soil testing and formulation + Full mobile sprinkler irrigation + Straw tilling and field return” and “No tillage in spring + Soil testing and formulation + Straw tilling and field return” should be promoted in semi-arid and semi-humid black soil regions, which can improve the low carbon productivity of maize by 20.3% and 15.4%, respectively.

cAMP-dependent protein kinase (PKA) activity regulates protein phosphorylation, with Na+ playing a crucial role in PKA activity. The aim of this study was to investigate the effects of different Na+ concentrations on PKA activity and protein phosphorylation level in postmortem muscle. The study consisted of two experiments: (1) NaCl of 0, 20, 100, 200 and 400 mM was added to a muscle homogenate incubation model to analyze the effect of Na+ concentration on PKA activity, and (2) the same concentrations were added to pure PKA in vitro incubation models at 4 °C to verify the effect of Na+ on PKA activity. The PKA activity of the muscle homogenate model increased with storage time in groups with different Na+ concentrations. High concentrations of Na+ inhibited sarcoplasmic protein phosphorylation. The PKA activity at 24 h of storage and the sarcoplasmic protein phosphorylation level at 12 h of storage in the group with 200 mM Na+ was lower than that of the other groups. After 1 h incubation, the PKA activity of samples in the 200 mM Na+ group was inhibited and lower than that in the other Na+ groups in the in vitro incubation model. These results suggest that the Na+ concentration at 200 mM could better inhibit PKA activity. This study provided valuable insights for enhancing curing efficiency and improving meat quality.

The ratoon rice cropping pattern is an alternative to the double-season rice cropping pattern in central China due to its comparable annual yield and relatively lower cost and labor requirements. However, the impact of the ratoon rice cropping pattern on greenhouse gas (GHG) emissions and yields in the double-season rice region requires further investigation. Here, we compared two cropping patterns, fallow-double season rice (DR) and fallow-ratoon rice (RR), by using two early-season rice varieties (ZJZ17, LY287) and two late-season rice varieties (WY103, TY390) for DR, and two ratoon rice varieties (YLY911, LY6326) for RR. The six varieties constituted four treatments, including DR1 (ZJZ17 + WY103), DR2 (LY287 + TY390), RR1 (YLY911), and RR2 (LY6326). The experimental results showed that conversion from DR to RR cropping pattern significantly altered the GHG emissions, global warming potential (GWP), and GWP per unit yield (yield-scaled GWP). Compared with DR, the RR cropping pattern significantly increased cumulative methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2) emissions by 65.73%, 30.56%, and 47.13%, respectively, in the first cropping season. Conversely, in the second cropping season, the RR cropping pattern effectively reduced cumulative CH4, N2O, and CO2 emissions by 79.86%, 27.18%, and 30.31%, respectively. RR led to significantly lower annual cumulative CH4 emissions, but no significant difference in cumulative annual N2O and CO2 emissions compared with DR. In total, the RR cropping pattern reduced the annual GWP by 7.38% and the annual yield-scaled GWP by 2.48% when compared to the DR cropping pattern. Rice variety also showed certain effects on the yields and GHG emissions in different RR cropping patterns. Compared with RR1, RR2 significantly increased annual yield while decreasing annual GWP and annual yield-scaled GWP. In conclusion, the LY6326 RR cropping pattern may be a highly promising strategy to simultaneously reduce GWP and maintain high grain yield in double-season rice regions in central China.

The term “viscoelastic pipe” refers to high polymer pipes that exhibit both elastic and viscoelastic properties. Owing to their widespread use in water transport systems, it is important to understand the transient flow characteristics of these materials for pipeline safety. Despite extensive research, these characteristics have not been sufficiently explored. This study evaluates the impact of friction models on the transient flow of viscoelastic pipes across various Reynolds numbers by employing an energy analysis approach. Given the complexity and computational demands of two-dimensional models, this paper compares the accuracy of one-dimensional and quasi-two-dimensional models. Notably, the superiority of the quasi-two-dimensional model in simulating viscoelastic pipelines is demonstrated. Owing to the interaction between pressure waves and fluid within viscoelastic pipes, fluid–structure coupling significantly attenuates pressure waves during transmission. These findings shed light on the constitutive properties of viscoelastic pipes and the influence of pipe wall friction models on transient hydraulic characteristics, building upon prior studies focused on elastic pipes. Nevertheless, numerous factors affecting transient flow in viscoelastic pipes remain unexplored. This paper suggests further analysis of strain effects, starting with temperature and pipe dynamics, to enhance the understanding of the coupling laws and flow mechanisms in viscoelastic pipelines.

In recent years, the development of hydrogen energy has been widely discussed, particularly in combination with renewable energy sources, enabling the production of “green” hydrogen. With the significant increase in wind power generation, a promising solution for obtaining green hydrogen is the development of wind-to-hydrogen (W2H) systems. However, the high proportion of wind power and electrolyzers in a large-scale W2H system will bring about the problem of renewable energy consumption and frequency stability reduction. This paper analyzes the operational characteristics and economic feasibility of mainstream electrolyzers, leading to the proposal of a coordinated hydrogen production scheme involving both a proton exchange membrane (PEM) electrolyzer and an alkaline (ALK) electrolyzer. Subsequently, a coordinated control based on Model Predictive Control (MPC) is proposed for system frequency regulation in a large-scale W2H islanded microgrid. Finally, simulation results demonstrate that the system under PEM/ALK electrolyzers coordinated control not only flexibly accommodates fluctuating wind power but also maintains frequency stability in the face of large disturbances. Compared with the traditional system with all ALK electrolyzers, the frequency deviation of this system is reduced by 25%, the regulation time is shortened by 80%, and the demand for an energy storage system (ESS) is reduced. The result validates the effectiveness of MPC and the benefits of the PEM/ALK electrolyzers coordinated hydrogen production scheme.

Using shallow-water buoy observations, reanalysis data, and numerical models, this study analyzes the variations in sea temperature and significant wave height (SWH) caused by two sequential tropical cyclones (TCs) ‘Lionrock’ and ‘Kompasu’ in October 2021 in the northeast Beibu Gulf, South China Sea. The results show that the sea surface temperature (SST) cooling of the nearshore waters was larger than the offshore water in the basin of the gulf, with the cooling amplitude and rate decreasing and the cooling time lagging behind wind increasing from coast to offshore. The near-surface temperature at the buoy station had a maximum decrease of 2.8 °C after ‘Lionrock’, and the decrease increased slightly to 3 °C after the stronger wind of ‘Kompasu’. The total decrease of 4.6 °C indicates that the sequential TCs had a superimposed effect on the cooling of the Beibu Gulf. The heat budget analysis revealed that the sea surface heat loss and the Ekman pumping rate in the nearshore waters during ‘Kompasu’ (−535 W/m2 and 5.8 × 10−4 m/s, respectively) were significantly higher than that (−418 W/m2 and 4 × 10−4 m/s) during ‘Lionrock’. On the other hand, the SST cooling (−1.2 °C) during the second TC is smaller than (−1.6 °C) the first weaker TC in the gulf basin, probably due to the deepening of the mixed layer. During the observation period, the waves in the Beibu Gulf were predominantly wind-driven. The maximum SWHs reached 1.58 m and 2.3 m at the bouy station near shore during the two TCs, and the SWH variation was highly correlated to the wind variation with a correlation of 0.95. The SWH increases from the nearshore to offshore waters during the TCs. The SAWN and ARCIRC coupled model results suggest that wave variations in the Beibu Gulf are primarily influenced by water depth, bottom friction, and whitecapping. Two days after the TCs, sea surface cooling and high waves appeared again due to a cold air event.

Previous meta-analyses of multiple studies have suggested that dietary intake and blood concentrations of carotenoids, as well as dietary supplement of certain carotenoids, play a role in reducing the risk of cancer. However, the conclusions of these studies have been subject to controversy. We conducted an umbrella review of meta-analyses to comprehensively analyze and evaluate the evidence pertaining the association between carotenoids and cancer outcomes. We searched PubMed, Web of Science, Embase, and Cochrane Library databases of meta-analyses and systematic reviews up to June 2023. Our selection criteria encompassed meta-analyses of cohort and case-control studies, as well as randomized controlled clinical trials, which investigated the associations between carotenoids and cancer risk. We also determined the levels of evidence for these associations with AMSTAR 2 criteria. We included 51 eligible articles, including 198 meta-analyses for qualitative synthesis in the umbrella review. Despite the presence of moderate to high heterogeneity among the studies, dietary intake, supplementation, and blood concentrations of carotenoids were inversely associated with the risk of total cancer, and certain specific cancers of lung, digestive system, prostate, breast, head and neck, and others. Subgroup analysis also showed that individual carotenoids (α-carotene, β-carotene, β-cryptoxanthin, lutein, zeaxanthin, and lycopene) offer certain protection against specific types of cancers. However, high doses of carotenoid supplements, especially β-carotene, significantly increased the risk of total cancer, lung cancer, and bladder cancer. Our umbrella meta-analysis supported that high intake of dietary carotenoids as a whole food approach could be more beneficial in reducing cancer risk. Concurrently, the findings suggest that the efficacy of single-carotenoid supplementation in cancer prevention remains a subject of controversy.

Optimized fertilizer use improves crop yield and mitigates environmental pollution associated with crop production. Fertilizer and plant density are core strategies to ensure food security and cope with climate change. However, little is known about the long-term interactive effect of reduced nitrogen (N) and increased density on yield and C (Carbon) balance. In this study, field experiments were conducted in a double-cropping rice region to evaluate long-term effects on yield and carbon footprint (CF) by crop-based and soil-based methods. Treatments were set for 10% reduction in N coupling with conventional density (N1D1), 20% higher density (N1D2), 40% higher density (N1D3), and 20% reduction in N coupling with conventional density (N2D1), 20% higher density (N2D2), and 40% higher density (N2D3), with the prevailing practices as control, conventional plant density, and fertilizer dose. Results showed that the yield continued to increase with increasing density; under the same density, reducing N by 10% is more beneficial for yield improvement and for CH4 emission reduction. Compared with CK, reducing N application by 10% generally increased the annual yields by 7.34–23.25% on average, and reduced CH4 emissions by 16.19–22.11%, resulting in a reduced crop-based carbon footprint of 22.24–26.82%, and a reduced soil-based carbon footprint of 22.08–32.85%. While reducing N application by 20% increased the annual yields by 5.00–20.19% and reduced the CH4 emission by 1.66–4.93%, it reduced crop-based carbon footprints by 1.81–10.05% and reduced soil-based carbon footprints by 7.22–19.86%. As density increased, the crop-based CF decreased, whereas the soil-based CF increased. Overall, the highest yield and the lowest soil-based CF and unit yield CF (CFy) were observed in N1D3. Regarding sustainability, a 10% reduction in N, along with an increase in density to 40%, can be recommended for double-cropping rice production.

There is a growing interest in the similarities and differences in reading processes in L1 and L2. Some researchers propose that reading shares commonalities across languages, while others state that each language has particularities that would affect reading processes. One way to better understand the reading processes is by using eye-tracking methodologies to explore reading processes online. This review focuses on the research done about reading processes in bilinguals to understand the effect of L1 in L2 processing. We found that most of the studies followed two methods of comparison: Bilinguals vs. monolinguals and L1 vs. L2. In general, bilinguals presented longer times in all reading measures; however, the results are discussed based on different characteristics of the studies and the type of comparison.

The environmental/economic dispatch (EED) of power systems addresses the environmental pollution problems caused by power generation at the operational level, offering macroscopic control without requiring additional construction and remediation costs, garnering widespread attention in recent years. This paper undertakes a comprehensive review of existing EED models, categorizing them according to the control of atmospheric pollutants into total air pollutant control (TAPC) and control considering the spatial and temporal diffusion (STD) of atmospheric pollutants. In addition, various methods employed to address the EED problems, as well as the current state of research on multi-area EED models, are presented. Finally, this paper analyzes and summarizes the literature on existing EED models, highlighting the deficiencies of the current work and future research directions. Through these explorations, the authors find that controlling the EED model by considering TAPC is more suitable for general macro planning, whereas the EED model considering the STD of air pollutant emissions enables more precise and effective control. Summarizing such models and techniques is conducive to developing dispatch plans adapted to local conditions, which is significantly beneficial for public welfare and government management, promoting sustainable and environmentally friendly power system dispatch methods.

The lattice Boltzmann method is employed in the current study to simulate the heat transfer characteristics of sinusoidal-temperature-distributed heat sources at the bottom of a square cavity under various conditions, including different amplitudes, phase angles, initial positions, and angular velocities. Additionally, a machine learning-based model is developed to accurately predict the Nusselt number in such a sinusoidal temperature distribution of heat source at the bottom of a square cavity. The results indicate that (1) in the phase angle range from 0 to π, Nu basically shows a decreasing trend with an increase in phase angle. The decline in Nu at an accelerated rate is consistently observed when the phase angle reaches 4π/16. The corresponding Nu decreases as the amplitude increases at the same phase angle. (2) The initial position of the sinusoidal-temperature-distributed heat source Lc significantly impacts the convective heat transfer in the cavity. Moreover, the decline in Nu was further exacerbated when Lc reached 7/16. (3) The optimal overall heat transfer effect was achieved when the angular velocity of the non-uniform heat source reached π. As the angular velocity increases, the local Nu in the square cavity exhibits a gradual and oscillatory decline. Notably, it is observed that Nu at odd multiples of π surpasses that at even multiples of π. Furthermore, the current work integrates LBM with machine learning, enabling the development of a precise and efficient prediction model for simulating Nu under specific operational conditions. This research provides valuable insights into the application of machine learning in the field of heat transfer.

Solutes segregating at the grain boundary (GB) have a significant influence on the mechanical and chemical properties of steel. In this study, the segregation effects of Si, P, and S on γ-Fe ∑5 (210)[001] GB were systematically analyzed with solution energy, segregation energy, and tensile tests by using a first principles calculation. Si, P, and S are preferred to segregate at substitutional sites in the first layer near the GB. The variation in atomic configuration and electron distribution were investigated by the analysis of bond lengths, charge density, charge density difference, and density of states (DOS), which is caused by the atomic size and electronegativity of solute atoms. Through tensile tests, it was found that Si has a strengthening effect on GB, while P and S exhibit embrittlement effects at low concentration. As the concentration of solutes increase, the segregation sites of P are different from the others owing to the tendency to form Fe3P. The exhibited embrittlement effect is mitigated at first and then aggravated. However, in both cases Si and S show aggravating embrittlement effects on GB cohesion, while the effect of Si changes from strengthening to embrittlement. This work provides comprehensive insights into the effects of Si, P, and S, which will be a useful guidance in steel design.

Vaccines typically work by eliciting an immune response against larger antigens like polysaccharides or proteins. Small molecules like nicotine, on their own, usually cannot elicit a strong immune response. To overcome this, anti-nicotine vaccines often conjugate nicotine molecules to a carrier protein by carbodiimide crosslinking chemistry to make them polymeric and more immunogenic. The reaction is sensitive to conditions such as pH, temperature, and the concentration of reactants. Scaling up the reaction from laboratory to industrial scales while maintaining consistency and yield can be challenging. Despite various approaches, no licensed anti-nicotine vaccine has been approved so far due to the susboptimal antibody titers. Here, we report a novel approach to conjugate maleimide-modified nicotine hapten with a disulfide bond-reduced carrier protein in an organic solvent. It has two advantages compared with other approaches: (1) The protein was unfolded to make the peptide conformation more flexible and expose more conjugation sites; (2) thiol–maleimide “click” chemistry was utilized to conjugate the disulfide bond-reduced protein and maleimide-modified nicotine due to its availability, fast kinetics, and bio-orthogonality. Various nicotine conjugate vaccines were prepared via this strategy, and their immunology effects were investigated by using MPL and QS-21 as adjuvants. The in vivo study in mice showed that the nicotine–BSA conjugate vaccines induced high anti-nicotine IgG antibody titers, compared with vaccines prepared by using traditional condensation methods, indicating the success of the current strategy for further anti-nicotine or other small-molecule vaccine studies. The enhancement was more significant by using MPL and QS-21 than that of traditional aluminum adjuvants.

Distribution network scheduling (DNS) is the basis for distribution network management, which is computed in a periodical way via solving the formulated mixed-integer programming (MIP). To achieve the online scheduling, a provably robust learn-to-optimize approach for online DNS is proposed in this paper, whose key lies in the transformation of the MIP-based DNS into the simple linear program problem with a much faster solving time. It formulates the parametric DNS model to construct the offline training dataset and then proposes the provably robust learning approach to learn the integer variables of MIP. The proposed learning approach is adversarial to minor perturbation of input scenario. After training, the learning model can predict the integer variables to achieve online scheduling. Case study verifies the acceleration effectiveness for online DNS.

Artificial intelligence-generated content (AIGC) technology has had disruptive results in AI, representing a new trend in research and application and promoting a new era of AI. The potential benefits of this technology are both profound and diverse. However, the benefits of generative tools are accompanied by a series of significant challenges, the most critical of which is that it may cause AI information pollution on social media and mislead the public. Traditional network security models have shown their limitations in dealing with today’s complex network threats, so ensuring that generated content published on social media accurately reflects the true intentions of content creators has become particularly important. This paper proposes a security framework called “secToken”. The framework adopts multi-level security and privacy protection measures. It combines deep learning and network security technology to ensure users’ data integrity and confidentiality while ensuring credibility of the published content. In addition, the framework introduces the concept of zero trust security, integrates OAuth2.0 ideas, and provides advanced identity authentication, fine-grained access control, continuous identity verification, and other functions, to comprehensively guarantee the published content’s reliability on social media. This paper considers the main issues of generative content management in social media and offers some feasible solutions. Applying the security framework proposed in this paper, the credibility of generated content published on social media can be effectively ensured and can help detect and audit published content on social media. At the operational level, when extracting key information summaries from user-generated multimodal artificial intelligence-generated content and binding them to user identity information as a new token to identify user uniqueness, it can effectively associate user identity information with the current network status and the generated content to be published on the platform. This method significantly enhances system security and effectively prevents information pollution caused by generative artificial intelligence on social media platforms. This innovative method provides a powerful solution for addressing social and ethical challenges and network security issues.

Nowadays, it is highly desired to develop highly active and humidity-resistive ozone decomposition catalysts to eliminate the ozone contaminant, one of the primary pollutants in the air. In this work, a series of Cu2S hollow structured materials were rapidly synthesized using different structured Cu2O templates. The Cu2S from porous Cu2O showed the highest ozone catalytic decomposition efficiency of >95% to 400 ppm ozone with a weight hourly space velocity of 480,000 cm3·g−1·h−1 in dry air. Importantly, the conversion remained >85% in a high relative humidity of 90%. The mechanism was explored by diffusive reflectance infrared spectroscopy which showed the decomposition intermediate of O22−, and X-ray photoelectron spectroscopy revealed the dual active site of both Cu and S. The EPR and UPS characterization results also explained the superiority of porous Cu2S catalysts from the material itself. All these results show the effective decomposition of ozone by Cu2S, especially in harsh environments, promising for active ozone elimination.

Breast cancer (BC) has become the fifth most prevalent cause of cancer-related morbidity, attracting significant attention from researchers due to its heightened malignancy and drug resistance. Conventional chemotherapy approaches have proven inadequate in addressing all BC subtypes, highlighting the urgent need for novel therapeutic approaches or drugs. Curcumin (CUR), a phytochemical derived from Curcuma longa (turmeric), has shown substantial potential in inhibiting BC cell migration, metastasis, and proliferation. However, the use of CUR in this context comes with challenges due to its dynamic and easily degradable nature, poor aqueous solubility, low bioavailability, rapid metabolism, and swift systemic elimination, collectively limiting its clinical applications. As such, we provide an overview of the properties, synthesis, and characterization of the hybridization of CUR and its analogue with chemo-drug building blocks. We reviewed research from the last five years on CUR’s biogenesis with respect to the regulation of BC, revealing that CUR participates in arresting BC cells in the cell cycle and significantly induces apoptosis in BC cells. Information on the chemotherapeutic and antitumor mechanisms of CUR in BC, including regulation of the cell cycle, increased cell apoptosis, and inhibition of multidrug resistance (MDR), was compiled. Additionally, we provide an overview of CUR loaded into nanomaterials that are cotreated with other chemotherapeutic drugs, such as paclitaxel, thymoquinone, and tamoxifen. In this review, we discuss different types of nanoparticles that can be used for CUR delivery, such as polymeric nanoparticles, carbon nanotubes, and liposomes. By comparing the size, entrapment efficiency, drug-loading capacity, release time, biocompatibility, pharmaceutical scale, and reproducibility of various nanomaterials, we aimed to determine which formulations are better suited for loading CUR or its analogue. Ultimately, this review is expected to offer inspiring ideas, promising strategies, and potential pathways for developing advanced anti-BC strategy nanosystems in clinical practice.

Crop removal of cations and anions is one of the main factors causing soil acidification. Mollisols, also known as black soils, which are inherently neutral soils, have been acidified due to irrational land use. However, the magnitude of acidification of black soils in relation to crop removal under crop rotation and field management remains unclear. In this study, we collect soil samples from 9- and 10-year long-term trials with seven treatments of soybean and corn monoculture, and corn–soybean rotation under different fertilization or straw return in the Mollisol region of Northeast China. Total removal of cations and anions is 371–508 and 92–125 kg ha−1 in corn but 166–250 and 56–82 kg ha−1 in soybean, which leads to the production of 7.06–10.2 kmol ha−1 H+ for corn and 4.43–5.77 kmol ha−1 H+ for soybean. Among the four cations (K+, Ca2+, Na+, and Mg2+) analyzed in different tissues of crops, K+ contributes more to the total H+ production, where K+ in corn stem contributes more than 55% H+, while K+ in soybean seed contributes more than 64% H+. The sum of Ca2+ and Mg2+ removal for soybean is 37.6–66.9 kg ha−1, 1.26–2.07 times (p < 0.05) greater than for corn. Net H+ produced by corn and soybean removal may potentially lead to a soil acidification of 0.053–0.074 and 0.032–0.045 year−1 units pH, respectively. The greater the corn or soybean biomass, the higher the net H+ production. Continuous soybean and combination of chemical fertilizer for corn but no chemical fertilizer for soybean reduce the soil pH buffering capacity (pHBC), while other treatments increase the soil pHBC, but there is no effect for continuous corn. Compared to normal corn–soybean rotation, soil pH in 9-year continuous corn declines from 5.76 to 5.63, while 10-year continuous soybean declines from 5.68 to 5.43 (p < 0.05). However, soil pH with chemical fertilizer for corn and dairy manure for soybean increases by 0.60 and 0.89 units (p < 0.05). Changes in pH might not be fully related to crop ion removal. Manure application with crop rotation is an effective approach to alleviate soil acidification.

There is a need for monitoring air pollution associated with black carbon (BC) using a passive monitor is required in remote areas where the measurements are absent. In this pilot study, we developed a quantitative method to determine dry deposition submicron BC using dual-wavelength ultraviolet–visible spectroscopy. Furthermore, we measured the levels of dry deposition BC on plant leaves from 30 plant species located in urban Nanjing using the established method. The oxidative potential of BC on plant leaves as passive bio-monitoring samplers was assessed. The concentrations of black carbon (BC) on tree leaves varied from 0.01 to 1.6 mg m−2. Significant differences in levels of BC across leaves from different tree types were observed. The values of oxidative potential in deposited particles of leaf samples were observed to be in the range of 33–46 nmol min−1 mg−1 using the dithiothreitol (DTT) assay and 18–32 nmol min−1 mg−1 using the ascorbic acid (AA) assay, respectively. In comparison, the oxidative potential of BC-dominated mass in water extracts of leaf samples was in the range of 5–35 nmol min−1 mg−1 measured using the DTT assay and 2 to 12 nmol min−1 mg−1 using the AA assay, respectively. We found variations in the levels of OP across the leaves of different tree types were not large, while the levels of OP in terms of BC-dominated mass varied greatly. These results indicate that the established method with dual-wavelength ultraviolet–visible spectroscopy could provide a simple tool to determine submicron BC in plant leaves of the passive monitor.

Influenza is a potentially fatal acute respiratory viral disease caused by the influenza virus. Influenza viruses vary in antigenicity and spread rapidly, resulting in seasonal epidemics. Vaccination is the most effective strategy for lowering the incidence and fatality rates of influenza-related disorders, and it is also an important method for reducing seasonal influenza infections. Mammalian Madin–Darby canine kidney (MDCK) cell lines are recommended for influenza virus growth, and such cell lines have been utilized in several commercial influenza vaccine productions. The limit dilution approach was used to screen ATCC-MDCK cell line subcellular strains that are especially sensitive to H1N1, H3N2, BV, and BY influenza viruses to increase virus production, and research on influenza virus culture media was performed to support influenza virus vaccine development. We also used RNA sequencing to identify differentially expressed genes and a GSEA analysis to determine the biological mechanisms underlying the various levels of susceptibility of cells to influenza viruses. MDCK cell subline 2B6 can be cultured to increase titer and the production of the H1N1, H3N2, BV, and BY influenza viruses. MDCK-2B6 has a significantly enriched and activated in ECM receptor interaction, JAK-STAT signaling, and cytokine receptor interaction signaling pathways, which may result in increased cellular susceptibility and cell proliferation activity to influenza viruses, promote viral adsorption and replication, and elevate viral production, ultimately. The study revealed that MDCK-2B6 can increase the influenza virus titer and yield in vaccine production by increasing cell sensitivity and enhancing proliferative activity.