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In December 2022, the United States (US) experienced an extreme cold event. Its duration was 5 days, and it ranked third in intensity (−9.16 °C) during the period from 1979 to 2022. During the Early Stage (12–16 December), the surface air temperature (SAT) anomaly peaked at 2.98 °C. In the Development Stage (17–21 December), cold air moved towards North America (NA). This event reached its peak during the Outbreak Stage (22–26 December), with a minimum SAT anomaly of −9.16 °C. Concurrently, high pressure occurred in Alaska and the Archipelago region, while low-pressure centers occurred in the US. The U-component of wind (U-wind) was in a negative anomaly in the northern part of NA. The negative anomaly of the V-component of wind (V-wind) moved southward. These atmospheric structural changes facilitated the southward movement of cold air from the Arctic to NA. Furthermore, a positive (negative) U-wind anomaly was observed to obstruct (promote) the southward progression of cold air to NA. A linear regression analysis indicated that a negative Arctic Oscillation (AO) correlated with the accumulation of cold air in the Arctic, while a positive Arctic High led to the transport of cold air to NA. In an empirical orthogonal function (EOF) analysis, EOF1 (16.3%) was characterized by a warm Arctic and cold northern part of NA pattern, reflecting the cold air from the Arctic region moving southward into NA, while EOF2 (14.4%) depicted a cold Arctic and cold NA pattern, characterizing the outbreak of cold events in the US. In January 2024, the US experienced another extreme cold event. Its maximum intensity was −9.50 °C, and its duration was 8 days. The course of the two cold events was very similar.

Global warming caused by massive carbon dioxide emissions can lead to a chain of ecological disasters. As one of the main sources of carbon emissions, transportation is of great significance, and the evaluation of its connections with carbon emissions is necessary to achieve “carbon neutrality”. Taking Beijing as an example, this study evaluated traffic efficiency (TE) by utilizing principal component analysis and fuzzy comprehensive evaluation. Using the Tapio decoupling model and coupling coordination degree model, the corresponding relationship between urban low carbon level (LCL) and TE was explored. The results showed the following: (1) The total carbon emission (CE) level exhibited fluctuating variation from increasing to decreasing. The carbon emission intensity (CEI) continued to slow down, and the rapid growth of population density played a key role in low-carbon development. (2) The traffic operations continually showed a positive trend in development. TE increased from a step-like to a slow shape, until it declined in 2020 due to the pandemic. (3) TE and LCL both developed from low coordination to an extreme level of coordination. Per capita carbon emission (CEP) and TE presented an inverted U-shaped curve; meanwhile, with increases in TE, the decline in CEI slowed. In addition, the weak decoupling of TE changed to become strong, due to CE and CEP, and maintained a strong decoupling state from CEI. (4) There is a necessity for the rational planning of land use for transportation infrastructure, the encouragement of a combination of public and private transportation, and the strengthening of the maintenance of the relative infrastructure and the management of traffic behaviors to attain a win–win situation. The results provide a reference for optimizing the traffic structure to achieve “carbon neutrality”.

Traditional radar target detectors, which are model-driven, often suffer remarkable performance degradation in complex clutter environments due to the weakness in modeling the unpredictable clutter. Deep learning (DL) methods, which are data-driven, have been introduced into the field of radar target detection (RTD) since their intrinsic non-linear feature extraction ability can enhance the separability between targets and the clutter. However, existing DL-based detectors are unattractive since they require a large amount of independent and identically distributed (i.i.d.) training samples of target tasks and fail to be generalized to the other new tasks. Given this issue, incorporating the strategy of meta-learning, we reformulate the RTD task as a few-shot classification problem and develop the Inter-frame Contrastive Learning-Based Meta Detector (IfCMD) to generalize to the new task efficiently with only a few samples. Moreover, to further separate targets from the clutter, we equip our model with Siamese architecture and introduce the supervised contrastive loss into the proposed model to explore hard negative samples, which have the targets overwhelmed by the clutter in the Doppler domain. Experimental results on simulated data demonstrate competitive detection performance for moving targets and superior generalization ability for new tasks of the proposed method.

The four-electron oxidation process of the oxygen evolution reaction (OER) highly influences the performance of many green energy storage and conversion devices due to its sluggish kinetics. The fabrication of cost-effective OER electrocatalysts via a facile and green method is, hence, highly desirable. This review summarizes and discusses the recent progress in creating carbon-based materials for alkaline OER. The contents mainly focus on the design, fabrication, and application of carbon-based materials for alkaline OER, including metal-free carbon materials, carbon-based supported composites, and carbon-based material core–shell hybrids. The work presents references and suggestions for the rational design of highly efficient carbon-based OER materials.

Panax quinquefolius L. is an important medicinal plant, and flavonoids are among its main secondary metabolites. The R2R3-MYB transcription factor plays an irreplaceable role in plant growth, development, and secondary metabolism. In our study, we identified 159 R2R3-MYBs and analyzed their physical and chemical properties in P. quinquefolius. The protein length of 159 PqMYBs varied from 107 to 1050 amino acids. The molecular weight ranged from 12.21 to 116.44 kDa. The isoelectric point was between 4.57 and 10.34. We constructed a phylogenetic tree of P. quinquefolius and Arabidopsis thaliana R2R3-MYB family members, and PqMYB members were divided into 33 subgroups. Transcriptome data analysis showed that the expression patterns of PqMYBs in root, leaf, and flower were significantly different. Following the MeJA treatment of seedlings, five candidate PqMYB genes demonstrated a response. A correlation analysis of PqMYBs and candidate flavonoid pathway genes showed that PqMYB2, PqMYB46, and PqMYB72 had correlation coefficients that were higher than 0.8 with PqCHS, PqANS4, and PqCCoAMT10, respectively. Furthermore, a transient expression assay confirmed that the three PqMYBs were localized in the nucleus. We speculated that these three PqMYBs were related to flavonoid biosynthesis in P. quinquefolius. These results provided a theoretical basis and a new perspective for further understanding the R2R3-MYB gene family and the biosynthesis mechanism of secondary metabolites in P. quinquefolius.

B0 field inhomogeneity is a long-lasting issue for Cardiac MRI (CMR) in high-field (3T and above) scanners. The inhomogeneous B0 fields can lead to corrupted image quality, prolonged scan time, and false diagnosis. B0 shimming is the most straightforward way to improve the B0 homogeneity. However, today’s standard cardiac shimming protocol requires manual selection of a shim volume, which often falsely includes regions with large B0 deviation (e.g., liver, fat, and chest wall). The flawed shim field compromises the reliability of high-field CMR protocols, which significantly reduces the scan efficiency and hinders its wider clinical adoption. This study aims to develop a dual-channel deep learning model that can reliably contour the cardiac region for B0 shim without human interaction and under variable imaging protocols. By utilizing both the magnitude and phase information, the model achieved a high segmentation accuracy in the B0 field maps compared to the conventional single-channel methods (Dice score: 2D-mag = 0.866, 3D-mag = 0.907, and 3D-mag-phase = 0.938, all p < 0.05). Furthermore, it shows better generalizability against the common variations in MRI imaging parameters and enables significantly improved B0 shim compared to the standard method (SD(B0Shim): Proposed = 15 ± 11% vs. Standard = 6 ± 12%, p < 0.05). The proposed autonomous model can boost the reliability of cardiac shimming at 3T and serve as the foundation for more reliable and efficient high-field CMR imaging in clinical routines.

We aim to improve the product quality of GABA raw Pu-erh tea during development and processing. In this study, headspace solid-phase microextraction gas chromatography–mass spectrometry technology combined with relative odor activity evaluations was used to compare the volatile compounds of GABA sun-dried green tea and GABA raw Pu-erh tea. Sensory evaluation showed a higher aroma score of GABA raw Pu-erh tea than that of GABA sun-dried green tea, with significant differences in aroma type and purity. A total of 147 volatile compounds of 13 categories were detected, which differed in composition and quantity between the two teas. 2-Buten-1-one,1-(2,6,6-trimethyl-1,3-cyclohexadien-1-yl)-,(E)- and beta.-myrcene largely contributed to the aroma formation of both teas. Five volatile compounds were screened as potential markers for tea aroma. Metabolic pathway analysis showed that monoterpenoid biosynthesis may be beneficial to the formation of flowery and fruity aromas in the teas. We suggest that the findings of this study may provide important guidance for the processing and optimization of GABA tea.

Establishing an immune balance between the mother and fetus during gestation is crucial, with the placenta acting as the epicenter of immune tolerance. The placental transfer of antibodies, mainly immunoglobulin G (IgG), is critical in protecting the developing fetus from infections. This review looks at how immunomodulation of antibody glycosylation occurs during placental transfer and how it affects fetal health. The passage of maternal IgG antibodies through the placental layers, including the syncytiotrophoblast, stroma, and fetal endothelium, is discussed. The effect of IgG subclass, glycosylation, concentration, maternal infections, and antigen specificity on antibody transfer efficiency is investigated. FcRn-mediated IgG transport, influenced by pH-dependent binding, is essential for placental transfer. Additionally, this review delves into the impact of glycosylation patterns on antibody functionality, considering both protective and pathological effects. Factors affecting the transfer of protective antibodies, such as maternal vaccination, are discussed along with reducing harmful antibodies. This in-depth examination of placental antibody transfer and glycosylation provides insights into improving neonatal immunity and mitigating the effects of maternal autoimmune and alloimmune conditions.

A new skincare application scenario for dark tea, a unique and post-fermented tea popular in the health food industry, was developed in this paper. The effects of dark tea polysaccharide (DTP) on stress-induced skin problems and its mechanism of action were investigated by modeling cortisone-induced stress injury in human HaCaT keratinocytes and SZ95 sebaceous gland cells. The results showed a reduced cortisol conversion induced by cortisone under the action of DTP with a concentration of 200 μg/mL, probably by inhibiting the expression of the HSD11B1 enzyme. DTP was also able to suppress the cortisone-induced elevation of lipid levels in SZ95 sebocytes at this concentration. In addition, the composition and structure of DTP were verified by ultrafiltration, ultraviolet-visible spectrophotometry (UV-VIS), high-performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD) and infrared spectroscopy. In brief, DTP has a unique and significant stress-relieving effect, which provides new ideas for the development of new ingredients for the skin care industry.

The development of natural antimicrobial agents offers new strategies for food preservation due to the health hazards associated with the spoilage of meat products caused by microbial contamination. In this paper, the inhibitory mechanism of protocatechualdehyde (PCA) on Listeria monocytogenes was described, and its effect on the preservation of cooked chicken breast was evaluated. The results showed that the minimal inhibitory concentration (MIC) of PCA on L. monocytogenes was 0.625 mg/mL. Secondly, PCA destroyed the integrity of the L. monocytogenes cell membrane, which was manifested as a decrease in membrane hyperpolarization, intracellular ATP level, and intracellular pH value. Field emission gun scanning electron microscopy (FEG-SEM) observed a cell membrane rupture. Transcriptome analysis showed that PCA may inhibit cell growth by affecting amino acid, nucleotide metabolism, energy metabolism, and the cell membrane of L. monocytogenes. Additionally, it was discovered that PCA enhanced the color and texture of cooked chicken breast meat while decreasing the level of thiobarbituric acid active substance (TBARS). In conclusion, PCA as a natural antibacterial agent has a certain reference value in extending the shelf life of cooked chicken breast.

In this paper, the progress of the test methods and characterization approaches of aluminum alloys hardenability was reviewed in detail. The test method mainly included the traditional end-quenching method and the modified method. While the characterization approaches of alloy hardenability consist mainly of ageing hardness curves, solid solution conductivity curves, ageing tensile curves, time temperature transformation (TTT) curves, time temperature properties (TTP) curves, continuous cooling transformation (CCT) curves, and advanced theoretical derivation method have appeared in recent years. The hardenability testing equipment for different tested samples with different material natures, engineering applications properties, and measurement sizes was introduced. Meanwhile, the improvement programmed proposed for shortcomings in the traditional hardenability testing process and the current deficiencies during the overall hardenability testing process were also presented. In addition, the influence factors from the view of composition design applied to the hardenability behaviors of Aluminum alloys were summarized. Among them, the combined addition of micro-alloying elements is considered to be a better method for improving the hardenability of high-strength aluminum alloys.

The performance of traditional direction of arrival (DOA) estimation methods always deteriorates at a low signal-to-noise ratio (SNR) or without sufficient observations. This paper investigates the Bayesian DOA estimation problem aided by the prior knowledge from the target tracker. The Bayesian Cramér–Rao lower bounds (CRLB) and the expected CRLB are first derived to evaluate the theoretical performance of Bayesian DOA estimation. Based on the maximum a posterior (MAP) estimator in the Bayesian framework, two methods are proposed. One is a two-step grid search method for a single target DOA case. The other is a gradient-based iterative solution for multiple targets DOA case, which extends the traditional Newton method by incorporating the prior knowledge. We also propose a minimum mean square error (MMSE) estimator using a Monte Carlo method, which requires trading off accuracy against computational complexity. By comparing with the maximum likelihood (ML) estimators and the MUSIC algorithm, the proposed three Bayesian estimators improve the DOA estimation performance in low SNR or with limited snapshots. Moreover, the performance is not affected by the correlation between sources.

Breast milk is tailored for optimal growth in all infants; however, in some infants, it is related to a unique phenomenon referred to as breast milk jaundice (BMJ). BMJ is a type of prolonged unconjugated hyperbilirubinemia that is often late onset in otherwise healthy-appearing newborns, and its occurrence might be related to breast milk itself. This review aims to systematically evaluate evidence regarding breast milk composition and the development of BMJ in healthy neonates. PubMed, Scopus and Embase were searched up to 13 February 2023 with key search terms, including neonates, hyperbilirubinemia, and breastfeeding. A total of 678 unique studies were identified and 12 were ultimately included in the systematic review with narrative synthesis. These included studies covered both nutritional compositions (e.g., fats and proteins) and bioactive factors (e.g., enzymes and growth factors) of breast milk and formally assessed the difference in the concentration (or presence) of various endogenous components of breast milk collected from mothers of BMJ infants and healthy infants. The results were inconsistent and inconclusive for most of the substances of interest, and there was only a single study available (e.g., total energy and mineral content, bile salts and cytokines); conflicting or even contradictory results arose when there were two or more studies on the subject matter (e.g., fats and free fatty acids contents and epidermal growth factor). The etiology of BMJ is likely multifactorial, and no single constituent of breast milk could explain all the BMJ cases observed. Further well-designed studies are warranted to investigate the complex interaction between maternal physiology, the breast milk system and infant physiology before this field could be progressed to uncover the etiology of BMJ.

We investigated the effects of CEC on the fermentation characteristics, epithelial gene expression, and bacterial community in the rumen of lambs fed a high-concentrate diet. Twenty-four 3-month-old female crossbred lambs with an initial body weight of 30.37 ± 0.57 kg were randomly allocated to consume a diet supplemented with 80 mg/kg CEC (CEC) or not (CON). The experiment consisted of a 14 d adaptation period and a 60 d data collection period. Compared with the CON group, the CEC group had higher ADG, epithelial cell thickness, ruminal butyrate proportion, and lower ammonia nitrogen concentration. Increases in the mRNA expression of Occludin and Claudin-4, as well as decreases in the mRNA expression of apoptotic protease activating factor-1 (Apaf-1), cytochrome c (Cyt-C), Caspase-8, Caspase-9, Caspase-3, Caspase-7, and toll-like receptor 4 (TLR4), were observed in the CEC group. Moreover, CEC treatment also decreased the concentration of IL-1β, IL-12, and TNF-α. Supplementation with CEC altered the structure and composition of the rumen bacterial community, which was indicated by the increased relative abundances of Firmicutes, Synergistota, Rikenellaceae_RC9_gut_group, Olsenella, Schwartzia, Erysipelotrichaceae_UCG-002, Lachnospiraceae_NK3A20_group, Acetitomaculum, [Eubacterium]_ruminantium_group, Prevotellaceae_UCG-004, Christensenellaceae_R-7_group, Sphaerochaeta, Pyramidobacter, and [Eubacterium]_eligens_group, and the decreased relative abundances of Acidobacteriota, Chloroflexi, Gemmatimonadota, and MND1. Furthermore, Spearman correlation analysis revealed that the altered rumen bacteria were closely correlated with rumen health-related indices. Dietary CEC supplementation improved growth performance, reduced inflammation and apoptosis, protected barrier function, and modulated the bacterial community of lambs fed a high-concentrate diet.

Background: An increasing number of studies have reported associations between single nucleotide polymorphisms (SNPs) and ovarian cancer (OC) risk. However, some of the findings were inconsistent. The objective of this umbrella review was to evaluate the associations comprehensively and quantitatively. Methods: The protocol of this review was registered in PROSPERO (No. CRD42022332222). We searched the PubMed, Web of Science, and Embase databases to identify related systematic reviews and meta-analyses from inception to 15 October 2021. In addition to estimating the summary effect size by using fixed and random effects models and calculating the 95% prediction interval, we evaluated the cumulative evidence for associations with nominally statistical significance based on the Venice criteria and false positive report probability (FPRP). Results: Forty articles were included in this umbrella review, which referred to a total of 54 SNPs. The median number of original studies per meta-analysis was four, while the median number of total subjects was 3455. All included articles had greater than moderate methodological quality. A total of 18 SNPs were nominally statistically associated with OC risk; 6 SNPs (8 genetic models), 5 SNPs (7 genetic models), and 16 SNPs (25 genetic models) were identified as strong, moderate, and weak cumulative evidence, respectively. Conclusion: This umbrella review revealed associations between SNPs and OC risk and suggested strong cumulative evidence of associations of six SNPs (eight genetic models) with OC risk.

Acidithiobacillus spp. are prevalent in acid mine drainage, and they have been widely used in biomining for extracting nonferrous metals from ores. The osmotic stress generated by elevated concentrations of inorganic ions is a severe challenge for the growth of Acidithiobacillus spp. in the bioleaching process; however, the adaptation mechanism of these bacteria to high osmotic pressure remains unclear. In this study, bioinformatics analysis indicated that the osmotic stress response two-component system EnvZ-OmpR is widely distributed in Acidithiobacillus spp., while OmpRs from Acidithiobacillus spp. exhibited a far more evolutionary relationship with the well-studied OmpRs in E. coli and Salmonella typhimurium. The growth measurement of an Acidithiobacillus caldus (A. caldus) ompR-knockout strain demonstrated that OmpR is essential in the adaptation of this bacterium to high osmotic stress. The overall impact of OmpR on the various metabolic and regulatory systems of A. caldus was revealed by transcriptome analysis. The OmpR binding sequences of differentially expressed genes (DEGs) were predicted, and the OmpR box motif in A. caldus was analysed. The direct and negative regulation of EnvZ-OmpR on the tetrathionate-metabolic (tetH) cluster in A. caldus was discovered for the first time, and a co-regulation mode mediated by EnvZ-OmpR and RsrS-RsrR for the tetrathionate intermediate thiosulfate-oxidizing (S4I) pathway in this microorganism was proposed. This study reveals that EnvZ-OmpR is an indispensable regulatory system for the ability of A. caldus to cope with high osmotic stress and the significance of EnvZ-OmpR on the regulation of sulfur metabolism in A. caldus adapting to the high-salt environment.

Objective: To explore if pre-diagnosis sleep status is associated with overall survival (OS) of ovarian cancer (OC). Methods: This is a prospective cohort study of 853 OC patients newly diagnosed between 2015 and 2020. Sleep status was measured by the Pittsburgh Sleep Quality Index (PSQI). Vital status of patients was obtained through active follow-up and linkage to medical records and cancer registry. The Cox proportional hazards regression model was utilized to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for aforementioned associations. Results: During the follow-up period (median: 37.57 months, interquartile: 25.00 to 50.17 months), 123 (18.39%) OC patients died. The HR (95%CI) for OS of OC was 2.13 (1.42–3.18) for sleeping after 22:00, compared with sleeping before 22:00; 2.43 (1.64–3.62) for poor sleep quality, compared to good sleep quality; 2.26 (1.37–3.72) for late bed-early rise and 1.93 (1.09–3.42) for late bed-late rise, compared with early bed-early rise; 0.40 (0.24–0.67) for night sleep duration of ≥7.5 h/day, compared with 7–7.5 h/day; 0.53 (0.29–0.98) for total sleep duration of ≥8 h/day, compared with 7.5–8 h/day. Further, the interaction effects were significant between residual lesions and wake-up time, night bedtime, sleep pattern, and between total sleep duration and menopausal status, parity. Additionally, there was a significant curvilinear association between PSQI score and OS (p nonlinear Conclusions: Pre-diagnosis longer total and night sleep duration were associated with better OS, whereas later sleeping time, poor sleep quality, and bad sleep patterns were associated with poor OS among OC survivors.

The apolipoprotein B mRNA editing enzyme catalytic subunit 3G (APOBEC3G) converts cytosine to uracil in DNA/RNA. Its role in resisting viral invasion has been well documented. However, its expression pattern and potential function in AML remain unclear. In this study, we carried out a bioinformatics analysis and revealed that the expression of APOBEC3G was significantly upregulated in AML, and high expression of APOBEC3G was significantly associated with short overall survival (OS). APOBEC3G expression was especially increased in non-M3AML, and correlated with the unfavorable cytogenetic risks. Additionally, Cox regression analyses indicated APOBEC3G is a hazard factor that cannot be ignored for OS of AML patients. In molecular docking simulations, the natural product crotonoside was found to interact well with APOBEC3G. The expression of APOBEC3G is the highest in KG-1 cells, and the treatment with crotonoside can reduce the expression of APOBEC3G. Crotonoside can inhibit the viability of different AML cells in vitro, arrest KG-1 and MV-4-11 cells in the S phase of the cell cycle and affect the expression of cycle-related proteins, and induce cell apoptosis. Therefore, APOBEC3G could be a potential drug target of crotonoside, and crotonoside can be considered as a lead compound for APOBEC3G inhibition in non-M3 AML.

We aimed to examine the associations between cord blood lipids and childhood adiposity and to investigate whether these associations vary across birth weight categories (small for gestational age (SGA), appropriate for gestational age (AGA) and large for gestational age (LGA)) in 1306 infants in the Born in Guangzhou Cohort Study, China. Adiposity outcomes at the age of three years included z-scores of weight-for-length/height (WFLZ), body mass index (BMIZ), subscapular (SSTZ) and triceps skinfold thickness (TSTZ), and the sum of skinfold thicknesses (SSFTZ). Cord blood triglycerides (TG) levels were negatively associated with WFLZ and BMIZ, whereas high density lipoprotein (HDL) levels were positively associated with WFLZ, BMIZ, TSTZ and SSFTZ. These associations were attenuated after adjustment for birth weight. Stratified analyses revealed that total cholesterol (TC) and low-density lipoprotein (LDL) levels were positively associated with childhood adiposity indicators among AGA infants but tended to be negatively associated with the adiposity indicators among LGA infants (p values for interaction p values for interaction

In this study, the compressive performance of sisal fiber-reinforced recycled aggregate concrete (SFRAC) composite, confined with jute fiber-reinforced polymer (JFRP) tube (the structure was termed as JFRP–SFRAC) was assessed. A total of 36 cylindrical specimens were tested under uniaxial compression. Three major experimental variables were investigated: (1) the compressive strength of concrete core (i.e., 25.0 MPa and 32.5 MPa), (2) jute fiber orientation angle with respect to the hoop direction of a JFRP tube (i.e., β = 0°, 30° and 45°), and (3) the reinforcement of sisal fiber (i.e., 0% and 0.3% by mass of cement). This study revealed that the prefabricated JFRP tube resulted in a significant enhancement of the compressive strength and deformation ability of RAC and SFRAC. The enhancements in strength and ultimate strain of the composite columns were more pronounced for concrete with a higher strength. The strength and ultimate strain of JFRP-confined specimens decreased with an increase in fiber orientation angle β from 0° to 45°. The sisal fiber reinforcement effectively improved the integrity of the RAC and reduced the propagation of cracks in RAC. The stress–strain behaviors of JFRP–RAC and JFRP–SFRAC were predicted by the Lam and Teng’s model with the revised ultimate condition equations.

Vehicle–road cooperative technology applies wireless communication and a new generation of internet technology to urban traffic management, providing an effective way to solve urban traffic congestion and improve traffic efficiency. This article researches the vehicle wireless positioning fusion algorithm, suitable for the actual vehicle–road collaborative environment, which is an important step of urban traffic congestion state recognition. First, based on the error correction of existing wireless positioning algorithms, a weighting indicator considering distance and positioning compound errors is designed, and a vehicle wireless positioning fusion algorithm based on error weighting to eliminate line-of-sight (LOS) and non-line-of-sight (NLOS) error is proposed. Secondly, the wireless positioning fusion algorithm is verified based on accuracy evaluation indicators such as root mean square error (RMSE), Cramer Rao lower bound (CRLB), geometric differentiation of precision (GDOP), and cumulative distribution probability (CDP), and the sensitivity of the distance propagation model parameters to the positioning error is analyzed. The verification results show that the local vehicle wireless positioning fusion algorithm proposed in this article could be useful to locate vehicles in an actual vehicle–road collaborative environment. The positioning accuracy could reach 46.31 m with 67% probability, while the positioning accuracy could reach 122.53 m with 95% probability. The average positioning accuracy could reach 39.97 m. Compared with the two types of wireless positioning methods based on ranging and non-ranging methods, the positioning accuracy is improved by 7.74% and 17.69%. The algorithm can either use the roadside base stations to carry out the individual vehicle positioning or cooperate with GPS positioning and trilateral positioning to make up for the positioning blind spots caused by the lack of signal, interference, or base station overload in the urban complex road environment and, furthermore, improves the robustness of vehicle positioning. The results could assist in all-day real-time traffic congestion state recognition and other actual scenarios.

Radiation fog episodes are characterized by aerosol radiative properties measured at Hefei in urban central China, which hopefully benefits numerical weather prediction and air quality improvement for local governments. In this study, a high mean aerosol optical depth (AOD) is seen over Hefei during the sampling period, whereas an AOD of ~3.0 at 550 nm is observed during the fog episodes. We redefine the fog scavenging coefficient based on its starting and ending points in time, and a black carbon (BC) scavenging coefficient of 30% is observed. Meanwhile, the fog process cannot reduce aerosol number concentrations at size bins between 0.5 and 0.6 μm, whereas a mean particle scavenging coefficient of 21% at sizes within 0.6–1 μm is seen. Significantly large median aerosol scattering coefficient (2690 Mm−1) and absorption coefficient (446 Mm−1) at 550 nm, and low scattering Angstrom exponent in fog are observed, while distinctive particle size distributions between fog and haze are shown. Particle mean size distribution in fog is lower than that in haze at size bins between 0.7 and 2.1 μm, whereas the reverse is true for sizes within 0.5–0.7 μm and larger than 2.1 μm. Aerosol scattering during fog episodes undergoes a bigger increase than particle absorption, and this increase of scattering in fog is even higher than in haze. Median single scattering albedos of 0.86, 0.82, and 0.76 at 550 nm and aerosol radiative forcing efficiencies of −15.0, −14.0, and −10.0 W/m2 are seen for fog, haze and clear periods, respectively, and more negative radiative forcing efficiency emphasizes the significance of fog episodes on climate forcing. Our study clearly reveals the changes of aerosol radiative properties during radiation fog, particularly a synchronous variation of fog aerosol backscattering ratio with the visibility, indicating that more large particles are formed with fog becoming thicker and are scavenged with the dissipation of fog.

Recently, the application of polymer-based composites at cryogenic conditions has become a hot topic, especially in aerospace fields. At cryogenic temperature, the polymer becomes more brittle, and the adverse effect of thermal stress induced by temperature is more remarkable. In this paper, the research development of thermoset and thermoplastic polymers for cryogenic applications are all reviewed. This review considers the literature concerning: (a) the cryogenic performance of modified thermoset polymers and the improving mechanisms of the reported modification methods; (b) the cryogenic application potential of some commercial thermoplastic polymers and the cryogenic performance of modified thermoplastic polymers; (c) the recent advance in the use of polymer for special cryogenic environment-liquid oxygen. This paper provides a comprehensive overview of the research development of the polymer for cryogenic application. Moreover, future research directions have been proposed to facilitate its practical applications in aerospace.

Yucca schidigera Roezl (Mojave), a kind of ornamental plant belonging to the Yucca genus (Agavaceae), whose extract exhibits important roles in food, beverage, cosmetic and feed additives owing to its rich spirostanol saponins. To provide a comprehensive chemical profiling of the spirostanol saponins in it, this study was performed by using a multi-phase liquid chromatography method combining a reversed phase chromatography T3 column with a normal phase chromatography silica column for the separation and an ESI-Q-Exactive-Orbitrap MS in positive ion mode as the detector. By comparing the retention time and ion fragments with standards, thirty-one spirostanol saponins were identified. In addition, according to the summary of the chromatographic retention behaviors and the MS/MS cleavage patterns and biosynthetic pathway, another seventy-nine spirostanol saponins were speculatively identified, forty ones of which were potentially new ones. Moreover, ten novel spirostanol saponins (three pairs of (25R/S)-spirostanol saponin isomer mixtures) were targeted for isolation to verify the speculation. Then, the comprehensive chemical profiling of spirostanol saponins from Y. schidigera was reported here firstly.

Advanced automatic pronunciation error detection (APED) algorithms are usually based on state-of-the-art automatic speech recognition (ASR) techniques. With the development of deep learning technology, end-to-end ASR technology has gradually matured and achieved positive practical results, which provides us with a new opportunity to update the APED algorithm. We first constructed an end-to-end ASR system based on the hybrid connectionist temporal classification and attention (CTC/attention) architecture. An adaptive parameter was used to enhance the complementarity of the connectionist temporal classification (CTC) model and the attention-based seq2seq model, further improving the performance of the ASR system. After this, the improved ASR system was used in the APED task of Mandarin, and good results were obtained. This new APED method makes force alignment and segmentation unnecessary, and it does not require multiple complex models, such as an acoustic model or a language model. It is convenient and straightforward, and will be a suitable general solution for L1-independent computer-assisted pronunciation training (CAPT). Furthermore, we find that find that in regards to accuracy metrics, our proposed system based on the improved hybrid CTC/attention architecture is close to the state-of-the-art ASR system based on the deep neural network−deep neural network (DNN−DNN) architecture, and has a stronger effect on the F-measure metrics, which are especially suitable for the requirements of the APED task.

Phenol-diaminodiphenylmethane-based benzoxazine (P-ddm)/phthalocyanine copolymer was prepared by using P-ddm resin as matrix and 3,10,17,24-tetra-aminoethoxy lead phthalocyanine (APbPc) as additive. Fourier-transform infrared (FTIR), differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), and thermogravimetric analysis (TGA) were used to investigate the curing behavior, curing kinetics, dynamic mechanical properties, thermal stability, and impact strength of the prepared copolymers. The kinetic parameters for the P-ddm/APbPc blend curing processes were examined by utilizing the iso-conversional, Flynn−Wall−Ozawa, and Málek methods. The P-ddm/APbPc blends exhibit two typical curing processes, and DSC results confirmed that the blending of APbPc monomer can effectively reduce the curing temperature of P-ddm resin. The autocatalytic models also described the non-isothermal curing reaction rate well, and the appropriate kinetic parameters of the curing process were obtained. The DMA and impact strength experiments proved that the blending of APbPc monomer can significantly improve the toughness and stiffness of P-ddm resin, the highest enhancements were observed on 25 wt.% addition of APbPc, the recorded values for the storage modulus and impact strength were 1003 MPa and 3.60 kJ/m2 higher, respectively, while a decline of 24.6 °C was observed in the glass transition temperature values. TGA curves indicated that the cured copolymers also exhibit excellent thermal stabilities.