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Bioremediation is a promising strategy to remove crude oil contaminants. However, limited studies explored the potential of bacterial consortia on crude oil biodegradation in high salinity soil. In this study, four halotolerant strains (Pseudoxanthomonas sp. S1-2, Bacillus sp. S2-A, Dietzia sp. CN-3, and Acinetobacter sp. HC8-3S), with strong environmental tolerance (temperature, pH, and salinity), distinctive crude oil degradation, and beneficial biosurfactant production, were combined to construct a bacterial consortium. The inoculation of the consortium successfully degraded 97.1% of total petroleum hydrocarbons in 10 days, with notable removal of alkanes, cycloalkanes, branched alkanes, and aromatic hydrocarbons. Functional optimization showed that this consortium degraded crude oil effectively in a broad range of temperature (20–37 °C), pH (6–9), and salinity (0–100 g/L). In salt-enriched crude-oil-contaminated soil microcosms, the simultaneous treatment of bioaugmentation and biostimulation achieved the highest crude oil degradation rate of 568.6 mg/kg/d, compared to treatments involving abiotic factors, natural attenuation, biostimulation, and bioaugmentation after 60 days. Real-time PCR targeting the 16S rRNA and alkB genes showed the good adaptability and stability of this consortium. The degradation property of the constructed bacterial consortium and the engineered consortium strategy may have potential use in the bioremediation of crude oil pollution in high-salinity soil.

In view of the high-sensitivity vibration effect of precision instrument laboratory buildings under the influence of surrounding traffic loads, field micro-vibration tests under various working conditions were carried out based on actual projects. Combined with numerical simulation, measured data served as input loads to simulate the vibration effect of various traffic loads on the floor of a building structure, and the structural vibration laws under the comprehensive action of various loads were analyzed. The vibration isolation effect of the isolation ditch on the oblique orthogonal load was investigated according to the corresponding safety index. The results show that the main frequency components of the site vibration frequency caused by various traffic loads are approximately 25 Hz and that the root-mean-square speed value is stable below VC-E, which meets the design requirements. Under the comprehensive action of multiple loads, the site structure will produce a vibration amplification effect, which is obvious when all types of loads are distributed symmetrically and the curve distribution is controlled by load factors with large amplitudes. The isolation effect of a small isolation ditch is best when it is located close to the source and the building. The depth of the isolation ditch must be greater than the maximum depth of the source to achieve better results, and the width has little influence. The effect of a small isolation trench on vertical vibration is poor, and the oblique orthogonal triaxial load has a counteracting effect on the vertical component. Thus, additional structural vibration isolation measures are needed. The research results provide a reference for engineering vibration isolation, damping measures, and structural design.

Arundo donax (family: Poaceae) is a perennial rhizomatous plant with considerable economic and ecological benefits. The plant is characterized by its fast growth, high yield, wide adaptability, and strong disease resistance. However, widespread cultivation is difficult because A. donax can only be asexually propagated. This study tested the efficacy of an aqua-based culture method with short duration and high rooting rate. The aqua-based culture protocol involved treating cane fragments with the commercial broad-spectrum rooting powder ABT-1 (No. 1 of the ABT series) at 100 mg/L for 24 h, followed by culturing in tap water for 19 days. We found that plant materials sampled from September to February of the following year were more suitable for aqua-based culturing than materials sampled from other months. Nodes on different parts of the cane did not vary significantly in the ability to form seedlings. The rooting percentage reached >95% after only 20 days, while the sprouting percentage was >93%. The seedlings obtained were strong, with high survival rates during cultivation and acclimation. No strict requirements for the growing media were necessary to achieve these results. In conclusion, this study provides an empirical foundation for a technique that could facilitate the factory production of high-quality A. donax seedlings.

A coverage prediction model helps network operators find coverage gaps, plan base station locations, evaluate quality of service, and build radio maps for spectrum sharing, interference management, localization, etc. Existing coverage prediction models rely on the height and transmission power of the base station, or the assistance of a path loss model. All of these increase the complexity of large-scale coverage predictions. In this paper, we propose a multi-modal model, DNN-SS, which combines a DNN (deep neural network) and SS (semantic segmentation) to perform coverage prediction for mobile networks. Firstly, DNN-SS filters the samples with a geospatial-temporal moving average filter algorithm, and then uses a DNN to extract numerical features. Secondly, a pre-trained model is used to perform semantic segmentation of satellite images of the measurement area. Thirdly, a DNN is used to extract features from the results after semantic segmentation to form environmental features. Finally, the prediction model is trained on the dataset consisting of numerical features and environmental features. The experimental results on campus show that for random location prediction, the model achieves a RMSE (Root Mean Square Error) of 1.97 dB and a MAE (Mean Absolute Error) of 1.41 dB, which is an improvement of 10.86% and 10.2%, respectively, compared with existing models. For the prediction of a test area, the RMSE and MAE of the model are 4.32 dB and 3.45 dB, respectively, and the RMSE is only 0.22 dB lower than that of existing models. However, the DNN-SS model does not need the height, transmission power, and antenna gain of the base station, or a path loss model, which makes it more suitable for large-scale coverage prediction.

Arundo donax is widely used as an ornamental plant in landscape gardening because of its adaptability to varying degrees of waterlogged conditions. However, to date, little information is available about the adaptive mechanism of A. donax under waterlogging stress. The results showed that long-term mild waterlogging efficiently induced the formation of adventitious roots (ARs) and further promoted root aerenchyma development, and that the activity of antioxidant enzymes (SOD, POD, and CAT) in Ars also was greatly enhanced after waterlogging. At the transcriptomic level, the expression of genes related to apoptosis, the regulation of cell division, ethylene biosynthesis, alginate synthesis, auxin signaling pathways, and anaerobic respiration was mostly up-regulated after the occurrence of waterlogging stress but genes involved in the abscisic acid signaling pathways were partly down-regulated, which indicated a preferential and favorable transcriptional response in regulating adventitious root development. Taken together, this study definitely advances our knowledge of the morphological, physiological, and transcriptomic responses of A. donax under waterlogging stress and sheds new lights on its adaptive mechanisms.

Ambrosia trifida is an invasive alien plant species, which has very high reproductive and environmental adaptability. Through strong resource acquisition ability and allelopathy, it could inhibit the growth and reproduction of surrounding plants and destroy the stability of an invasive ecosystem. It is very important to predict the change of suitable distribution area of A. trifida with climate change before implementing scientific control measures. Based on 106 A. trifida distribution data and 14 points of environmental data, the optimal parameter combination (RM = 0.1, FC = LQ) was obtained using the MaxEnt (version 3.4.1) model optimized by Kuenm package, and thus the potential suitable areas of A. trifida in Northeast China under three different climate scenarios (RCP2.6, RCP4.5, RCP8.5) with different emission intensities in the future (2050, 2070) were predicted. The changes of A. trifida suitable area in Northeast China under three climate scenarios were compared, and the relationship between the change of suitable area and emission intensity was analyzed. In general, the suitable area of A. trifida in Northeast China will expand gradually in the future, and the area of its highly suitable area will also increase with the increasing emission intensity, which is unfavorable to the control of A. trifida.

The remaining useful life (RUL) of bearings is vital for the manipulation and maintenance of industrial machines. The existing domain adaptive methods have achieved major achievements in predicting RUL to tackle the problem of data distribution discrepancy between training and testing sets. However, they are powerless when the target bearing data are not available or unknown for model training. To address this issue, we propose a single-source domain generalization method for RUL prediction of unknown bearings, termed as the adaptive stage division and parallel reversible instance normalization model. First, we develop the instance normalization of the vibration data from bearings to increase data distribution diversity. Then, we propose an adaptive threshold-based degradation point identification method to divide the healthy and degradation stages of the run-to-failure vibration data. Next, the data from degradation stages are selected as training sets to facilitate the RUL prediction of the model. Finally, we combine instance normalization and instance denormalization of the bearing data into a unified GRU-based RUL prediction network for the purpose of leveraging the distribution bias in instance normalization and improving the generalization performance of the model. We use two public datasets to verify the proposed method. The experimental results demonstrate that, in the IEEE PHM Challenge 2012 dataset experiments, the prediction accuracy of our model with the average RMSE value is 1.44, which is 11% superior to that of the suboptimal comparison model (Transformer model). It proves that our model trained on one-bearing data achieves state-of-the-art performance in terms of prediction accuracy on multiple bearings.

Although great progress has been made in the development of hybrid rice with increased yield, challenges for the improvement of grain quality still remain. In this study, the textural properties of cooked rice and physicochemical characteristics of starch were investigated for 29 new hybrid rice derived from 5 sterile and 11 restorer rice lines. Except for one sterile line Te A (P1) with high apparent amylose content (AAC) (26.9%), all other parents exhibited a low AAC. Gui 263 demonstrated the highest AAC (20.6%) among the restorer lines, so the Te A/Gui 263 hybrid displayed the highest AAC (23.1%) among all the hybrid rice. The mean AAC was similar between sterile, restorer lines and hybrid rice. However, the mean hardness of cooked rice and gels of sterile lines were significantly higher than that of restorer lines and hybrid rice (p < 0.05). Pasting temperature and gelatinization temperatures were significantly higher in the hybrids than in the restorer lines (p < 0.05). Cluster analysis based on the physicochemical properties divided the parents and hybrid rice into two major groups. One group included P1 (Te A), P12 and P14 and three hybrid rice derived from P1, while the other group, including 39 rice varieties, could be further divided into three subgroups. AAC showed significant correlation with many parameters, including peak viscosity, hot peak viscosity, cold peak viscosity, breakdown, setback, onset temperature, peak temperature, conclusion temperature, enthalpy of gelatinization, gel hardness and cooked rice hardness (p < 0.05). Principal component analysis revealed that the first component, comprised of the AAC, peak viscosity, breakdown, setback, onset temperature, peak temperature, conclusion temperature and gel hardness, explained 44.1% of variance, suggesting AAC is the most important factor affecting the grain quality of hybrid rice. Overall, this study enables targeted improvements to key rice grain quality attributes, particularly AAC and textural properties, that will help to develop superior rice varieties.

Microbial dysbiosis has an increasingly appreciated impact on carcinogenesis, and the cervicovaginal microbiome plays a critical role in microenvironmental inflammation. Here, we investigated the involvement of the female genital tract Peptostreptococcus species in gynecological cancer via indoleacrylic acid (IAA). IAA production from Peptostreptococcus species and the effect of bacterial culture on tumor growth in vivo were examined. The impact of IAA on cytokine production and indoleamine-2,3-dioxygenase 1 (IDO1) expression in an endometrial cancer (EC) cell line, as well as their effect on Treg and Teff cells, and M1 and M2 macrophage populations were examined in EC patients and tumor-grafted mice. Clinically, Peptostreptococcus species abundance, IAA, and IDO1 expression were verified in EC patients. The results showed that IAA production was induced in the uteri of BALB/c nude mice by Peptostreptococcus species transplantation, and the intratumoral injection of a conditioned medium from Peptostreptococcus cultures into tumor-grafted mice promoted tumor growth. IL-10 expression was upregulated by IAA; IFN-γ expression was increased by IL-10. IFN-γ induced IDO1 expression in the EC cell line. The co-culture of IDO1-expressing EC cells with peripheral blood mononuclear cells upregulated the Treg proportion and decreased the M1/M2 ratio. Clinically, P. anaerobius was more abundant amongst the uterine microbiota of EC patients than the control. The IAA, IDO1, and kynurenine/tryptophan ratios were all higher in EC tissue, and the M1/M2 ratio was lower. Our study sheds light on the link between IDO1 induction and uterine Peptostreptococcus dysbiosis and provides a potential rationale for the role of Peptostreptococcus species in immune tolerance induction in type I endometrial cancer.

Despite the long-term implementation of air pollution control policies in northeast China, severe haze pollution continues to occur frequently. With the adoption of a megacity (Changchun) in northeast China, we analysed the vertical characteristics of aerosols and the causes of aerosol pollution throughout the year using multisource data for providing recommendations for controlling pollution events (i.e., straw burning and fireworks). Based on a ground-based LiDAR, it was found that the extinction coefficient (EC) of aerosols at a height of 300 m in Changchun was highest in winter (0.44 km−1), followed by summer (0.28 km−1), with significant differences from those in warmer regions, such as the Yangtze River Delta. Therefore, it is recommended that air pollution control policies be differentiated between winter and summer. On Chinese New Year’s Eve in Changchun, the ignition of firecrackers during the day and night caused increases in the EC at a height of 500 m to 0.37 and 0.88 km−1, respectively. It is suggested that the regulation of firecracker ignition should be reduced during the day and strengthened at night. Based on the CALIPSO and backward trajectory analysis results, two events of dust–biomass-burning composite pollution were observed in March and April. In March, the primary aerosol component was dust from western Changchun, whereas in April, the main aerosol component was biomass-burning aerosols originating from northern and eastern Changchun. Hence, reducing the intensity of spring biomass burning can mitigate the occurrence of dust–biomass-burning composite pollution. These findings can provide emission policy suggestions for areas facing similar issues regarding biomass-burning transmission pollution and firework emissions.

The stability of contemporary ice shelves is under threat due to global warming, and the geological records in the Ross Sea offer such an opportunity to test the linkage between them. However, the absence of calcareous microfossils in the sediments of the Ross Sea results in uncertainties in establishing a precise chronology for studies. Hence, three sediment cores were collected and studied in terms of radiocarbon dating, magnetic susceptibility, and sediment grain size to reconstruct the environmental processes in the Ross Sea since the last glacial period. The main results are as follows: (1) two grain-size components were identified for the studied cores, which can be correlated to ice-shelf and sea-ice transport, respectively; (2) due to old-carbon contamination and an inconsistent carbon reservoir, the radiocarbon dates were generally underestimated, and as an alternative, changes in magnetic susceptibility of the studied cores can be tuned to the ice-core records to establish a reliable age–depth model and; (3) integrating sediment grain-size changes and comparisons with other paleoenvironmental proxies in the Antarctic, a process from a sub-ice sheet in the last glacial period to a sub-ice shelf in the glacial maximum, and, finally, to a glaciomarine state since the last deglacial period was identified in the western Ross Sea. Integrating these findings, the warming processes in the Antarctic were highlighted in the retreat processes of the Ross Ice Shelf in the past.

As global climate change and human activities increasingly influence our world, forest fires have become more frequent, inflicting significant damage to ecosystems. This study conducted measurements of combustible materials (moisture content ratio, ignition point, and calorific value) across 14 representative sites. We employed Pearson correlation analysis to ascertain the significant differences in combustible properties and utilized entropy methods to evaluate the fire resistance of materials at these sites. Cluster analysis led to the development of four combustible models. Using BehavePlus software, we simulated their fire behaviors and investigated the effects of wind speed and slope on these behaviors through sensitivity analysis. The results revealed notable differences in the moisture content ratios among different types of combustibles, especially in sites 2, 3, 8, 9, and 13, indicating higher fire risks. It was also found that while humus has a higher ignition point and lower calorific value, making it less prone to ignite, the resultant fires could be highly damaging. The Pearson analysis underscored significant variations in the moisture content ratios among different combustibles, while the differences in ignition points and calorific values were not significant. Sites 5 and 6 demonstrated stronger fire resistance. The simulations indicated that fire-spread speed, fireline intensity, and flame length correlate with, and increase with, wind speed and slope. Sensitivity analysis confirmed the significant influence of these two environmental factors on fire behavior. This study provides critical insights into forest fire behavior, enhancing the capability to predict and manage forest fires. Our findings offer theoretical support for forest fire prediction and a scientific basis for fire management decision-making.

The fast and accurate solution of integer ambiguity is the key to achieve GNSS high-precision positioning. Based on the lattice theory of high-dimensional ambiguity solving, the reduction time consumption is much larger than the search time consumption, and it is especially important to improve the efficiency of the lattice basis reduction algorithm. The Householder QR decomposition with minimal column pivoting is utilized to pre-sort the basis vectors and reduce the number of basis vector exchanges during the reduction process by partial size reduction and relaxing the basis vector exchange condition to improve the reduction efficiency of the LLL algorithm. The improved algorithm is validated using simulated and measured data, respectively, and the performance advantages and disadvantages of the improved algorithm are evaluated from the perspectives of the extent of reduction basis orthogonality and the quality of reduction basis size reduction. The results show that the improved LLL algorithm can significantly reduce the number of basis vector exchanges and the reduction time consumption. The HSLLL and PSLLL algorithms with the Siegel condition as the basis vector exchange condition have a better reduction effect, but are slightly less stable. The PLLLR algorithm significantly improves the search ambiguity resolution efficiency, which is conducive to the rapid realization of ambiguity resolution.

A high-quality canopy architecture is central to obtaining high crop yields. A field experiment was carried out at the Wuqiao Experimental Station from 2015 to 2019 under four irrigation schemes (W0, no irrigation after sowing; W1, 75 mm irrigation at jointing stage; W2, 75 mm irrigation at jointing and anthesis stages, respectively; W3, 75 mm irrigation at tillering, jointing and anthesis stages, respectively) to investigate the canopy structure, canopy apparent photosynthesis (CAP), canopy temperature (CT), yield and water use efficiency (WUE). The results showed that increasing irrigation times improved the leaf area index (LAI), non-leaf area index (NLAI) and light interception (LI) of the spike and total canopy but decreased the canopy temperature (CT) after anthesis. The CAP in the W3 treatment was consistently lower than that in the W1 treatment, suggesting lower effective utilization of light energy under the W3 treatment. Increasing irrigation times improved wheat yield, but the W2 treatment had no significant difference in yield compared to the W3 treatment. In addition, the W1 and W2 treatments had higher WUEs. The CT, organ temperature and LI were closely positively associated with each other, but they were all strongly negatively related to the yield. Overall, the W2 treatment was the best irrigation scheme for constructing a reasonable canopy architecture for winter wheat, obtaining more efficient water use and yield in the North China Plain (NCP). CT and organ temperature can be used as proxy parameters to estimate the canopy structure.

The content of magnesium ions (Mg2+) in drinking water is relatively high and the excessive Mg2+ ingestion may lead to pathological lesions in the human body system. At present, the detection of Mg2+ still relies on costly devices or/and complex organic fluorescence probes. To solve this problem, this work proposed a NaBH4-mediated co-reduction strategy for the synthesis of glutathione-stabilized bimetallic AuAg nanoclusters (GSH@AuAg NCs) with performance recognition to Mg2+. The preparation of GSH@AuAg NCs was simple and rapid and could be performed at mild conditions. The reaction parameters and sampling orders were optimized to understand the formation mechanism of GSH@AuAg NCs. The GSH@AuAg NCs exhibited a sensitive “light on” fluorescence response to Mg2+ due to the re-molding of the interfacial physicochemical environment following the Mg2+ coordination, which affected the surface charge transfer process, and thus led to a novel method for fluorescence detection of Mg2+ with admirable selectivity for Mg2+. The proposed method showed a detection limit of 0.2 μM, and its practical utility for the detection of Mg2+ in a real sample of purified drinking water was also demonstrated, confirming its practicability in monitoring the Mg2+ concentration in drinking water.

Multipath error is an important factor restricting the relative positioning accuracy of the Beidou Navigation Satellite System (BDS). Because of the complexity of the reflection environment, the mathematical modeling of multipath errors is quite difficult. The sidereal filtering algorithm corrects multipath errors by using the feature of period repetition, which can greatly reduce its influence and improve the accuracy of positioning and attitude measurement. In view of the constellation heterogeneity of BDS, it is more complicated to apply sideral filtering. Based on the reconstructed single-difference residual of the carrier phase, the multipath repetition time of the Beidou satellite is estimated using the idea of segmentation. The Tikhonov regularization method and the classical wavelet method are used to extract the multipath of the single-difference residual of the carrier phase, and the “clean” sequence of the single-difference residual is obtained. The experimental results show that it is feasible to extract the multipath error correctly by Tikhonov regularization, and the multipath error is smoother than the original residual measurement. Furthermore, the estimation method of the regularization parameter is further optimized. After using the optimized Tikhonov regularization method with sidereal filtering, the mean RMS improvements of GEO, IGSO, and MEO satellites are 45.9%, 38.2%, and 37.5%, respectively. The positioning accuracy on E, N, and U components is improved by 24.8%, 26.3%, and 42.7%, respectively. The attitude resolution accuracy is improved by 22.9% in the yaw angle and 12.6% in the pitch angle. The proposed method can be an alternative BDS multipath error modeling and mitigation approach.

Reconstructing changes in deep/bottom-water redox conditions are critical for understanding the role of the deep ocean in global carbon and metals cycling; nevertheless, the quantitative relationships between redox proxies and abyssal dissolved oxygen are poorly investigated. In this work, we studied the rock magnetic properties of surficial sediments in the western Pacific to investigate their relationship with regional redox conditions. Our results reveal a consistent sedimentary magnetic mineral assemblage in the western Pacific, dominated by pseudo-single-domain magnetite (Fe3O4), while the ratio of detrital and biogenic magnetite particles in different sites varies substantially. Detailed analyses identified two major magnetic-coercivity components, with modal coercivity values of 13.1 ± 1.6 mT and 54.7 ± 5.3 mT, respectively. All the magnetic parameters we measured, including both concentration-dependent and grainsize-dependent parameters, and the magnetic coercivities, are generally correlated to sedimentary redox conditions; however, the coercivities obtained by mathematical unmixing exhibit a stronger linkage, explaining about a quarter of variance of redox changes. Our findings confirm the potential of magnetic properties for tracing abyssal redox changes in the western Pacific, while the observed magnetic-redox relationships are complex and need further investigation.

The Swarm mission aims to study the principle and change regularities of the Earth’s magnetic field. Precise orbit determination is essential to the successful implementation of the mission and relevant scientific research. This article focuses on using two different double-difference methods to improve the accuracy of Swarm kinematic orbit determination. The accuracy of the kinematic orbit determination relies entirely on the space-borne observation data, independent of any dynamic parameters. The article analyzes the data quality of the Swarm space-borne global positioning system (GPS) receiver and presents a detailed introduction to the data pre-processing algorithms. The double-difference observation gathering and the applied orbit determination strategy using two different double-difference methods are discussed. The results of the kinematic orbits under different solar cycle conditions are presented, along with an evaluation based on analysis of GPS carrier phase residuals, subtracting from the post-processed orbits, and assessment with satellite laser ranging (SLR) measurements. The results show that the accuracy of the kinematic orbit determination is at the centimeter level for the three Swarm satellites’ orbit solutions. The daily root mean square (RMS) values of the three satellites’ phase residuals remain at around the 6 mm level. The RMS values of the position residuals between the kinematic orbits and the reduced dynamic orbits released by the European Space Agency (ESA) are at about the 2–3 cm level. The external evaluation with SLR measurements shows a good agreement with the ESA level, with the RMS values of the SLR residuals for kinematic orbits around 2 cm.

Porous structures with light weight and high mechanical performance exist widely in the tissues of animals and plants. Biomimetic materials with those porous structures have been well-developed, and their highly specific surfaces can be further used in functional integration. However, most porous structures in those tissues can hardly be entirely duplicated, and their complex structure-performance relationship may still be not fully understood. The key challenges in promoting the applications of biomimetic porous materials are to figure out the essential factors in hierarchical porous structures and to develop matched preparation methods to control those factors precisely. Hence, this article reviews the existing methods to prepare biomimetic porous structures. Then, the well-proved effects of micropores, mesopores, and macropores on their various properties are introduced, including mechanical, electric, magnetic, thermotics, acoustic, and chemical properties. The advantages and disadvantages of hierarchical porous structures and their preparation methods are deeply evaluated. Focusing on those disadvantages and aiming to improve the performance and functions, we summarize several modification strategies and discuss the possibility of replacing biomimetic porous structures with meta-structures.

The SHPRH (SNF2, histone linker, PHD, RING, helicase) subfamily belonging to ATP-dependent chromatin remodeling factor is the effective tumor-suppressor, which can polyubiquitinate PCNA (proliferating cell nuclear antigen) and participate in post-replication repair in human. However, little is known about the functions of SHPRH proteins in plants. In this study, we identified a novel SHPRH member BrCHR39 and obtained BrCHR39-silenced transgenic Brassica rapa. In contrast to wild-type plants, transgenic Brassica plants exhibited a released apical dominance phenotype with semi-dwarfism and multiple lateral branches. Furthermore, a global alteration of DNA methylation in the main stem and bud appeared after silencing of BrCHR39. Based on the GO (gene ontology) functional annotation and KEGG (Kyoto encyclopedia of genes and genomes) pathway analysis, the plant hormone signal transduction pathway was clearly enriched. In particular, we found a significant increase in the methylation level of auxin-related genes in the stem, whereas auxin- and cytokinin-related genes were hypomethylated in the bud of transgenic plants. In addition, further qRT-PCR (quantitative real-time PCR) analysis revealed that DNA methylation level always had an opposite trend with gene expression level. Considered together, our findings indicated that suppression of BrCHR39 expression triggered the methylation divergence of hormone-related genes and subsequently affected transcription levels to regulate the apical dominance in Brassica rapa.

Recombinases are in part responsible for homologous recombination and genome integrity during DNA repair. DMC1 has a typical RecA domain, and belongs to the recombinase superfamily. The reactive oxygen species (ROS) as a potent DNA damage agent is produced during seed germination under stress conditions. DNA repair should be initiated immediately to allow for subsequent seedling development. In this study, we attempted to characterize the underlying mechanism of BrDMC1 responsiveness to salinity stress using the RNA interference approach in Brassica rapa (B. rapa). Bioinformatics and expression pattern analysis revealed that BrDMC1 only retained BrDMC1.A01 after the whole genome triplication (WGT) event and was primarily transcribed in flowers and seeds. BrDMC1 had high activity in the promoter region during germination, according to histochemical GUS staining. The data showed that salt treatment reduced the germination rate, weakened seed vigor and decreased antioxidant enzyme activity, but increased oxidative damage in BrDMC1-RNAi seeds. Furthermore, the expression of stress-responsive genes and damage repair genes was significantly different in transgenic lines exposed to salt stress. Therefore, BrDMC1 may respond to salt stress by controlling seed germination and the expression of stress-related and damage repair genes in B. rapa.

NiCr alloys with different components were obtained by pack chromation and homogenization heat treatment of octet Ni lattice. The microstructure, alloy composition, microhardness and quasi-static compression properties of the NiCr lattice were tested. The results showed that after homogenization heat treatment, the NiCr alloy lattice had an austenitic structure with uniform composition. Compared with the pure nickel lattice, the microhardness, compressive strength, elastic modulus and energy absorption of the NiCr lattice increased with the increase of chromium content. The microhardness, specific strength, specific modulus and specific energy absorption of the Ni-45Cr alloy were 363 HV, 11.1 MP/(g/cm3), 1169.1 MP/(g/cm3) and 10 J/g, respectively, which were attributed to the solid solution strengthening provided by chromium and the increase in density. NiCr alloy lattices have high strength and toughness and may have potential applications in high-temperature filters or heat exchangers.

Multi-view 3D reconstruction technology based on deep learning is developing rapidly. Unsupervised learning has become a research hotspot because it does not need ground truth labels. The current unsupervised method mainly uses 3DCNN to regularize the cost volume to regression image depth. This approach results in high memory requirements and long computing time. In this paper, we propose an end-to-end unsupervised multi-view 3D reconstruction network framework based on PatchMatch, Unsup_patchmatchnet. It dramatically reduces memory requirements and computing time. We propose a feature point consistency loss function. We incorporate various self-supervised signals such as photometric consistency loss and semantic consistency loss into the loss function. At the same time, we propose a high-resolution loss method. This improves the reconstruction of high-resolution images. The experiment proves that the memory usage of the network is reduced by 80% and the running time is reduced by more than 50% compared with the network using 3DCNN method. The overall error of reconstructed 3D point cloud is only 0.501 mm. It is superior to most current unsupervised multi-view 3D reconstruction networks. Then, we test on different data sets and verify that the network has good generalization.

The soft robot is a new type of robot with strong adaptability, good pliability, and high flexibility. Today, it is widely used in the fields of bioengineering, disaster rescue, industrial production, medical services, exploration, and surveying. In this paper, the typical driven methods, 3D printing technologies, applications, the existed problems, and the development prospects for soft robots are summarized comprehensively. Firstly, the driven methods and materials of the soft robot are introduced, including fluid driven, smart materials driven, chemical reaction driven, a twisted and coiled polymer actuator, and so on. Secondly, the basic principles and characteristics of mainstream 3D printing technologies for soft materials are introduced, including FDM, DIW, IP, SLA, SLS, and so on. Then, current applications of soft robots, such as bionic structures, gripping operations, and medical rehabilitation are described. Finally, the problems existing in the development of soft robots, such as the shortage of 3D printable soft materials, efficient and effective manufacturing of soft robots, shortage of smart soft materials, efficient use of energy, the realization of complex motion forms of soft robot, control action accuracy and actual kinematic modeling are summarized. Based on the above, some suggestions are put forward pertinently, and the future development and applications of the soft robot are prospected.

In order to mitigate the negative effects of global climate change, the Chinese government has committed to achieving peak carbon emissions by 2030 and carbon neutrality by 2060. Since municipal cities are the bottom administrative level for drawing up development plans, it is necessary and important to conduct decarbonization pathway research on municipal energy systems (MESs). However, there is little research on decarbonization at the municipal level, and the impact of development paths in each forecast scenario is mostly based on expert evaluation and qualitative assessment. Therefore, this study established a complete decarbonization framework for MESs, including general research procedures, models, and a sustainable evaluation method. The models of energy consumption and carbon emission were adapted and improved for MESs. In order to quantitatively evaluate the energy system development for each scenario, we proposed an energy–economy–environment–security (3E–S) evaluation method, in which principal component analysis (PCA) was adopted for multi-criterion decision making. According to the analysis results of the case city in Guangdong, this evaluation method was proved to be an effective way to identify the factors that may influence coordinated development. By adjusting the relevant parameters and factors in the model, the optimal decarbonization pathway can be found to promote sustainable and coordinated development, thus helping government decision makers to quantitatively evaluate planning paths.

This study presents a GIS-based method integrating hourly transport pathways and wind-field grid reconstruction, straw open burning (SOB) source identification, and a two-stage spatiotemporal multi-box modeling approach to quantify the contribution of external sources of SOB to elevated urban PM2.5 concentrations during a specific pollution episode (PE) at a high temporal resolution of 1 h. Taking Jilin Province as an empirical study, the contribution of SOB in province-wide farmlands to urban haze episodes in Changchun during the SOB season of 2020–2021 was evaluated quantitatively using a combination of multi-source datasets. The results showed that Changchun experienced three severe PEs and one heavy PE during the study period, and the total PM2.5 contributions from SOB sources were 352 μg m−3, 872 μg m−3, and 1224 μg m−3 during the three severe PEs, respectively; these accounted for 7%, 27%, and 23% of the urban cumulative PM2.5 levels, which were more obvious than the contribution during the PE. The total PM2.5 contribution from SOB sources (4.9 μg m−3) was only 0.31% of the urban cumulative PM2.5 level during the heavy PE. According to the analysis of the impact of individual factors, some policy suggestions are put forward for refined SOB management, including control spatial scope, burning time interval, as well as burning area limit under different urban and transport pathways’ meteorological conditions and different transport distances.

Harbin is a northmost megacity in the cold regions of China and experiences severe PM2.5 pollution. However, comprehensive investigations for severe haze formation are few. In this study, we simultaneously measured aerosol composition in real time to assess the sources apportionment, regional transport and its interaction with meteorology from 1 October 2018 to 1 May 2019 by using the single particle aerosol mass spectrometer (SPAMS). The daily average PM2.5 concentration was 51.21 µg/m3 with the hourly maximum of 900.45 µg/m3. Winter coal combustion was the largest source of PM2.5 aerosols during this period. Open straw burning from surrounding and adjacent areas by short-distance transport could aggravate air quality deterioration in Harbin. Three extreme haze events (i.e., Ep1, Ep2 and Ep3) were observed in this study, showing the typical characteristics of local winter pollution. The pollutants of PM2.5 and SO2 emitted from coal combustion played an important role in haze episode during Ep1, whereas Ep2 was caused by the joint effect of coal combustion and straw burning. Ep3 was characterized by long-distance transport of windblown dust from southeast Inner Mongolia and northwest Harbin. Real-time source apportionment of fine particulate matter highlights the importance of joint control of coal and straw burning from the surrounding cities of Harbin.

Drought can seriously hinder the growth of plants, resulting in reduced crop yield and quality. At present, the tolerance of DEAD-box helicases (DHC) to abiotic stresses, such as drought, high salinity, low temperature, and high temperature, has been confirmed in a variety of plants; therefore, using DEAD-box helicases to develop stress-resistant plants has great application prospects. In this study, Brassica rapa was used as a model to explore the response of the BrDHC1 gene to drought stress by creating RNA interference and overexpressing lines in B. rapa. The mechanism of BrDHC1 involved in drought resistance was revealed by the analysis of morphological characteristics, physiological indicators, and expression analysis of related stress response genes. The results showed that the overexpression of the BrDHC1 gene was more conducive to enhancing the resilience of plants under drought stress in B. rapa. Taken together, these results confirmed BrDHC1 as a newly identified DEAD-box helicase gene that could actively regulate plant growth and development under drought stress in B. rapa.

The difficulty of genetic transformation has restricted research on functional genomics in cotton. Thus, a rapid and efficient method for gene overexpression that does not rely on genetic transformation is needed. Virus-based vectors offer a reasonable alternative for protein expression, as viruses can infect the host systemically to achieve expression and replication without transgene integration. Previously, a novel four-component barley stripe mosaic virus (BSMV) was reported to overexpress large fragments of target genes in plants over a long period of time, which greatly simplified the study of gene overexpression. However, whether this system can infect cotton and stably overexpress target genes has not yet been studied. In this study, we verified that this new BSMV system can infect cotton through seed imbibition and systemically overexpress large fragments of genes (up to 2340 bp) in cotton. The target gene that was fused with GFP was expressed at a high level in the roots, stems, and cotyledons of cotton seedlings, and stable fluorescence signals were detected in the cotton roots and leaves even after 4 weeks. Based on the BSMV overexpression system, the subcellular localization marker line of endogenous proteins localized in the nucleus, endoplasmic reticulum, plasma membrane, Golgi body, mitochondria, peroxisomes, tonoplast, and plastids were quickly established. The overexpression of a cotton Bile Acid Sodium Symporter GhBASS5 using the BSMV system indicated that GhBASS5 negatively regulated salt tolerance in cotton by transporting Na+ from underground to the shoots. Furthermore, multiple proteins were co-delivered, enabling co-localization and the study of protein–protein interactions through co-transformation. We also confirmed that the BSMV system can be used to conduct DNA-free gene editing in cotton by delivering split-SpCas9/sgRNA. Ultimately, the present work demonstrated that this BSMV system could be used as an efficient overexpression system for future cotton gene function research.

With rapid development of modern agriculture, a multitude and a large amount of air pollutants were generated by agricultural activities, which are becoming more and more serious issues with regards to air pollution [...]

Polyploidy plays a crucial role in plant evolution and speciation. The development of male and female gametes is essential to the reproductive capacity of polyploids, but their gene expression pattern has not been fully explored in newly established polyploids. The present study aimed to reveal a detailed atlas of gene expression for gamete development in newly synthetic Brassica allohexaploids that are not naturally existing species. Comparative transcriptome profiling between developing anthers (staged from meiosis to mature pollen) and ovules (staged from meiosis to mature embryo sac) was performed using RNA-Seq analysis. A total of 8676, 9775 and 4553 upregulated differentially expressed genes (DEGs) were identified for the development of both gametes, for male-only, and for female-only gamete development, respectively, in the synthetic Brassica allohexaploids. By combining gene ontology (GO) biological process analysis and data from the published literature, we identified 37 candidate genes for DNA double-strand break formation, synapsis and the crossover of homologous recombination during male and female meiosis and 51 candidate genes for tapetum development, sporopollenin biosynthesis and pollen wall development in male gamete development. Furthermore, 23 candidate genes for mitotic progression, nuclear positioning and cell specification and development were enriched in female gamete development. This study lays a good foundation for revealing the molecular regulation of genes related to male and female gamete development in Brassica allohexaploids and provides more resourceful genetic information on the reproductive biology of Brassica polyploid breeding.

Newly synthetic autotetraploid rice shows lower pollen fertility and seed setting rate relative to diploid rice, which hinders its domestication and breeding. In this study, cytological analysis showed that at meiosis I stage, an unbalanced segregation of homologous chromosomes, occurred as well as an early degeneration of tapetal cells in autotetraploid rice. We identified 941 differentially expressed proteins (DEPs) in anthers (meiosis I), including 489 upregulated and 452 downregulated proteins. The DEPs identified were related to post-translational modifications such as protein ubiquitination. These modifications are related to chromatin remodeling and homologous recombination abnormalities during meiosis. In addition, proteins related to the pentose phosphate pathway (BGIOSGA016558, BGIOSGA022166, and BGIOSGA028743) were downregulated. This may be related to the failure of autotetraploid rice to provide the energy needed for cell development after polyploidization, which then ultimately leads to the early degradation of the tapetum. Moreover, we also found that proteins (BGIOSGA017346 and BGIOSGA027368) related to glutenin degradation were upregulated, indicating that a large loss of glutenin cannot provide nutrition for the development of tapetum, resulting in early degradation of tapetum. Taken together, these evidences may help to understand the differences in anther development between diploid and autotetraploid rice during meiosis.

Carbonate compensation depth (CCD) is an important factor in the global deep ocean and in global carbon cycling; however, its variabilities have not been well documented in previous studies. In this study, we investigate two deep-sea cores collected from the Philippine Sea in terms of geochronology and geochemical properties over the past ~900 kyr. The principle results are as follows: (1) Two magnetozones are determined from the sediment’s magnetic records, which can be correlated with the Brunhes and Matuyama chrons in the geomagnetic polarity timescale. (2) The age models can be refined by tuning the Ba and Sm intensities of the two studied cores to the global ice volume, and the estimated sediment accumulation rate is ~4 mm/kyr. (3) Chalky mud and the bulk carbon δ13C record vary abruptly at ~430 ka and imply 200 m shoaling of the CCD. Based on these results, a close link is inferred between marine productivity, aeolian dust, and CCD changes, which can be correlated with a major change that occurred during the Mid-Brunhes Event. Therefore, we propose that the sedimentary processes in the Philippine Sea are evidence of global climate change, providing a unique window to observe interactions between various environmental systems.

Large-scale open burning of straw residues causes seasonal and severe atmospheric pollution in Northeast China. Previous studies focused on the causes or assessment of atmospheric pollution in a single city. However, studies conducted on the interaction range, degree and policy control of pollutant transport on a large scale are still to be performed. In this study, we propose combined control of straw burning by dividing region the straw burning in Northeast China in recent 20 years, determining the transport routes between main cities, and analyzing the interaction characteristics of straw burning under different scenarios. The fire point data suggest that the most intense straw burning years in Northeast China in the past 20 years occurred in the range from 2014 to 2017, mainly after the autumn harvest (October–November) and before spring cultivation (March–April). The burning areas were concentrated in the belt of Shenyang-Changchun-Harbin, the border of the three provinces and Eastern-Inner Mongolia, and the surrounding area of Hegang and Jiamusi City. The lower number of fire points before 2013 indicates that high-intensity burning has not always been the case, while the sharp decline after 2018 is mainly due to scientific control of straw burning and increased comprehensive utilization of straw. Compared with S2, the PM2.5 concentrations increased by 6.2% in S3 and 18.7% in S4, indicating that burning in three or four provinces at the same time will significantly increase air pollution and exert a regional transmission effect. Straw burning in Northeast China is divided into six main regions based on correlation analysis and satellite fire monitoring. Under typical S3, the case analysis results indicate that there is regional transmission interaction between different cities and provinces, focusing on multi-province border cities, and it is affected by Northwest long airflow, and Southeast and Northeast short airflow. These results provide scientific and technological support for implementing the joint prevention and control plan for straw incineration in Northeast China.

In recent years, deep learning has become prevalent in Remaining Useful-Life (RUL) prediction of bearings. The current deep-learning-based RUL methods tend to extract high dimensional features from the original vibration data to construct the Health Indicators (HIs), and then use the HIs to predict the remaining life of the bearings. These approaches ignore the sequential relationship of the original vibration data and seriously affect the prediction accuracy. In order to tackle this problem, we propose a hard negative sample contrastive learning prediction model (HNCPM) with encoder module, GRU regression module and decoder module, used for feature embedding, regression RUL prediction and vibration data reconstruction, respectively. We introduce self-supervised contrast learning by constructing positive and negative samples of vibration data rather than constructing any health indicators. Furthermore, to avoid the subtle variability of vibration data in the health stage to aggravate the degradation features learning of the model, we propose the hard negative samples by cosine similarity, which are most similar to the positive sample. Meanwhile, a novel infoNCE and MSE-based loss function is derived and applied to the HNCPM to simultaneously optimize a lower bound on mutual information of the positive and negative sample over life cycle, as well as the discrepancy between true and predicted values of the vibration data, such that the model can learn the fine-grained degradation representations by predicting the future without any HIs as labels. The HNCPM is validated on the IEEE PHM Challenge 2012 dataset. The results demonstrate that the prediction performance of our model is superior to the state-of-the-art methods.

The fast development of large-scale intensive animal husbandry has led to an increased proportion of atmospheric pollution arising from livestock and poultry housing. Atmospheric pollutants, including particulate matter (PM), ammonia (NH3), hydrogen sulfide (H2S), and greenhouse gases (GHG), as well as other hazardous materials (e.g., gases, bacteria, fungi and viruses), have significant influences upon the local atmospheric environment and the health of animals and nearby residents. Therefore, it is imperative to develop livestock and poultry housing mitigation strategies targeting atmospheric pollution, to reduce its negative effects on the ambient atmosphere and to promote sustainable agricultural production. In this paper, we summarize the various strategies applied for reducing outlet air pollutants and purifying inlet air from mechanical ventilated livestock and poultry housing. This review highlights the current state of knowledge on the removal of various atmospheric pollutants and their relative performance. The potential optimization of processes and operational design, material selection, and other technologies, such as electrostatic spinning, are discussed in detail. The study provides a timely critical analysis to fill the main research gaps or needs in this domain by using practical and stakeholder-oriented evaluation criteria.

In recent years, the development of deep learning-based remaining useful life (RUL) prediction methods of bearings has flourished because of their high accuracy, easy implementation, and lack of reliance on a priori knowledge. However, there are two challenging issues concerning the prediction accuracy of existing methods. The run-to-failure sequential data and its RUL labels are almost inaccessible in real-world scenarios. Meanwhile, the existing models usually capture the general degradation trend of bearings while ignoring the local information, which restricts the model performance. To tackle the aforementioned problems, we propose a novel health indicator derived from the original vibration signals by combining principal components analysis with Euclidean distance metric, which was motivated by the desire to resolve the dependency on RUL labels. Then, we design a novel self-attention augmented convolution GRU network (SACGNet) to predict the RUL. Combining a self-attention mechanism with a convolution framework can both adaptively assign greater weights to more important information and focus on local information. Furthermore, Gated Recurrent Units are used to parse the long-term dependencies in weighted features such that SACGNet can utilize the important weighted features and focus on local features to improve the prognostic accuracy. The experimental results on the PHM 2012 Challenge dataset and the XJTU-SY bearing dataset have demonstrated that our proposed method is superior to the state of the art.

PARP proteins are highly conserved homologs among the eukaryotic poly (ADP-ribose) polymerases. After activation, ADP-ribose polymers are synthesized on a series of ribozymes that use NAD+ as a substrate. PARPs participate in the regulation of various important biological processes, such as plant growth, development, and stress response. In this study, we characterized the homologue of PARP1 in B. rapa using RNA interference (RNAi) to reveal the underlying mechanism responding to drought stress. Bioinformatics and expression pattern analyses demonstrated that two copy numbers of PARP1 genes (BrPARP1.A03 and BrPARP1.A05) in B. rapa following a whole-genome triplication (WGT) event were retained compared with Arabidopsis, but only BrPARP1.A03 was predominantly transcribed in plant roots. Silencing of BrPARP1 could markedly promote root growth and development, probably via regulating cell division, and the transgenic Brassica lines showed more tolerance under drought treatment, accompanied with substantial alterations including accumulated proline contents, significantly reduced malondialdehyde, and increased antioxidative enzyme activity. In addition, the findings showed that the expression of stress-responsive genes, as well as reactive oxygen species (ROS)-scavenging related genes, was largely reinforced in the transgenic lines under drought stress. In general, these results indicated that BrPARP1 likely responds to drought stress by regulating root growth and the expression of stress-related genes to cope with adverse conditions in B. rapa.

Biogenic reefs and carbonate platforms are valuable natural resources, playing an important role in modulating the global climate and in carbon cycles through biological processes. Biogenic reefs in the Xisha (Paracel) Islands began in the late Oligocene and covaried with the deep-sea basin of the South China Sea and with the aeolian deposit in the Chinese Loess Plateau. Core XK-1 was drilled into the Xisha Islands to their granitic base and well dated by magnetostratigraphy, offering an opportunity to reveal the details of how the Xisha reefs initiated. In this report, the lower section of the biogenic reefs (23.0–24.5 Ma) was sampled for studying magnetic properties. The main results are as follows: (1) magnetic minerals in the XK-1 biogenic reefs are dominated by low-coercivity and relatively coarse-grained magnetite; (2) the variabilities of magnetic parameters can be clustered into two sections around 23.6 Ma, and the differences between the two units are evident both in the amplitudes and the means; and (3) changes in the concentration-dependent magnetic parameters can be well correlated with the records of global deep-sea oxygen and carbon isotopes, and the sea level during the Oligo–Miocene boundary. Based on these results, a close link was inferred between biogenic reef evolution in the Xisha Islands and global climate change. This link likely highlights the covariation or the dominant role of the Asian monsoon in biogenic reefs and involves different responses to global temperature, CO2, and sea-level changes on various timescales. Therefore, we proposed that the origin of biogenic reefs in the Xisha Islands was likely paced by orbital obliquity from a long-term perspective.

Fengyun-3C (FY-3C) is a Global Navigation Satellite Systems (GNSS) Radio Occultation (RO) mission founded which was by China on 23 September 2013. In this study, under a specific temporal and spatial domain, we systematically compare FY-3C refractivity profiles with Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) refractivity profiles for the year 2015. The COSMIC profiles used in this study contain reflections, as identified in the Radio Occultation Meteorology Satellite Application Facility (ROM SAF) flag database. From 0 to 25 km altitude, the mean biases and relative standard deviations of the comparisons between FY-3C and COSMIC are less than 1% and 2% when COSMIC profiles present reflected signals. Radio holographic analysis is used to visualize and identify the spectra of FY-3C-reflected signals in the time-frequency domain. It is confirmed that the reflected signals in the lower troposphere and near the surface can be tracked by an FY-3C receiver. Further, most of the FY-3C events that matched with COSMIC reflected events show reflection patterns at a lower height, especially above the ocean’s surface. Under Bouguer’s rule and spherical symmetry assumptions, we reconstructed the reflected bending angle models by Abel transformation, which are valuable for reducing N-bias in the ducting layer. Three examples of FY-3C events show that the reflected bending branch is near the surface. Overall, the reflected signal of FY-3C could be used as a supplementary data portion for FY-3C atmospheric products.

Carbonaceous aerosol, one of the major components of atmospheric aerosols, significantly affects haze episodes, climate change, and human health. Northeastern China suffers severe air pollution, especially in some periods (e.g., the Spring Festival). However, studies on carbonaceous aerosols in typical northeast industrial cities (i.e., Changchun) are rare, limiting further comprehension of the atmospheric haze formation. In this study, we monitored the concentrations of carbonaceous aerosols (i.e., OC and EC) in Changchun during the Lunar New Year of 2018 (i.e., from Lunar 20 December to Lunar 20 January), and analyzed the temporal variation and source contributions via the HYbrid-Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model with the potential source contribution factor weights (PSCF) method. The daily concentrations of OC and EC were 9.00 ± 2.81 and 1.57 ± 0.46 µg m−3, respectively, and were significantly lower at nighttime than at the day during the Spring Festival. The concentrations during the major period (i.e., OC: 8.13 ± 2.93 µg m−3; EC: 1.47 ± 0.47 µg m−3 in festival days), including the Lunar Little New Year; the Lunar New Year’s Eve; New Year’s Day; Lunar 5 January, and the Spring Lantern Festival, were mainly from the northwestward with the wind speed of 4–6 m/s being lower than that of normal period (OC: 9.87 ± 2.46 µg m−3; EC: 1.67 ± 0.44 µg m−3) from the southeastward with a wind speed of 6–7 m/s. The direction of the airflow trajectory was mainly in local, northwestward, and northward, carrying particulate matter and gaseous pollutants. In major period, the daily concentration of atmospheric pollutants presented a bimodal trend, with peaks appearing regularly from 11:00 a.m. to 12:00 p.m. and 5:00 p.m. 10:00 p.m., which might be related to traffic, cooking, and firecrackers. The OC/EC was greater than 2 during the whole period, indicating the generation of secondary organic aerosols (i.e., SOC). This study was essential to understand the formation mechanisms of severe pollution episodes and develop control measures for the industrial cities of Northeast China during the Spring Festival.

This manuscript reported the synthesis of Al2O3 coating onto quartz fiber fabric by plasma electrolysis spray for enhanced thermal conductivity and stability. The nano- and micro-sized clusters were partially observed on the coating, while most coating was relatively smooth. It was suggested that the formation of a ceramic coating was followed as the nucleation-growth raw, that is, the formation of the coating clusters was dependent on the fast grow-up partially, implying the inhomogeneous energy distribution in the electrolysis plasma. The deposition of the Al2O3 coating increased the tensile strength from 19.2 to 58.1 MPa. The thermal conductivity of the coated quartz fiber was measured to be 1.17 W m−1 K−1, increased by ~45% compared to the bare fiber. The formation mechanism of the Al2O3 coating was preliminarily discussed. The thermally conductive quartz fiber with high thermal stability by plasma electrolysis spray will be widely used in flexible thermal shielding and insulation materials.

Agricultural emissions are crucial to regional air quality in the autumn and spring due to the intense agricultural activities in Northeast China. However, information on rural ambient particulate matter (PM) in Northeast China is rare, limiting the accurate estimation of agricultural atmospheric particulate matter emissions. In this study, we monitored hourly ambient PM2.5 (PM with a diameter of less than 2.5 μm) concentrations and analyzed daily chemical components (i.e., water-soluble ions, trace elements, organic carbon, and element carbon) at a rural site in Northeast China during the autumn and spring and assessed the impact of agricultural activities on atmospheric PM2.5 concentrations. The results showed that the daily average concentrations of PM2.5 were 143 ± 109 (range: 39−539) μg m−3 from 19 October to 23 November 2017 (i.e., typical harvesting month) and 241 ± 189 (range: 97−976) μg m−3 from 1 April to 13 May 2018 (i.e., typical tilling month). In autumn, the ambient PM2.5 concentrations were high with a Southwest wind, while a Southeast wind caused high PM2.5 concentrations during spring in the rural site. The concentrations of selected water-soluble ions, trace elements, and carbonaceous fractions accounted for 33%, 4%, and 26% of PM2.5 mass concentrations, respectively, in autumn and for 10%, 5%, and 3% of PM2.5 mass concentrations, respectively, in spring. On the basis of the component analysis, straw burning, agricultural machinery, and soil dust driven by wind and tilling were the main contributors to high rural PM2.5 concentrations. In addition, the increasing coal combustion around the rural site was another important source of PM2.5.

Generally, the period (i.e., October and November) was seriously affected by frequent atmospheric pollution under concentrative seasonal crop residue burning and coal burning in Jilin Province, Northeast China. A strict straw open burning ban policy was implemented in Jilin Province during October and November 2018. However, the quantitative effect of straw fire control and its effect on air quality are still unclear. In this study, using multisource data, we evaluated the status of straw-burning control and its contribution to air quality improvement in late autumn and early winter (i.e., October and November) of 2018 at a provincial level. The results showed that the open burning of straw was effectively controlled in October and November 2018 by comparing farmland fire point data to those collected in 2015−2017. There were significant positive correlations among the fire points, aerosol optical depth (AOD), and ground-monitored air quality index (AQI) on a spatial scale. The concentration values of AQI, PM2.5, and PM10 were significantly lower than for the other three years of 2015, 2016, and 2017. Based on meteorological analysis, similar conditions were found in 2018 and 2017, which were worse than that in 2016. Combined with emissions, meteorological conditions, and source apportionment information, if the straw-burning control of 2018 had been performed in 2016 and 2017, the PM2.5 concentrations could have been reduced by at least 30.6%. These results suggest the necessity of straw burning control in the improvement of air quality during the period of late autumn and early winter. Nevertheless, the comprehensive impact of straw-burning control on air quality should be further evaluated for the whole post-harvest period (i.e., October to April of the following year) as the straw-burning period can be postponed in some cities. Furthermore, the establishment of a scientific and reasonable planned burning of straw is also crucial in gradually reducing atmospheric pollution and the actual operation of local governments in those areas where straw can be burned under certain conditions.

Limbs originated from paired fish fins are an important innovation in Gnathostomata. Many studies have focused on limb development-related genes, of which the T-box transcription factor 4 gene (tbx4) has been considered as one of the most essential factors in the regulation of the hindlimb development. We previously confirmed pelvic fin loss in tbx4-knockout zebrafish. Here, we report a high-quality genome assembly of the Japanese eel (Anguilla japonica), which is an economically important fish without pelvic fins. The assembled genome is 1.13 Gb in size, with a scaffold N50 of 1.03 Mb. In addition, we collected 24 tbx4 sequences from 22 teleost fishes to explore the correlation between tbx4 and pelvic fin evolution. However, we observed complete exon structures of tbx4 in several pelvic-fin-loss species such as Ocean sunfish (Mola mola) and ricefield eel (Monopterus albus). More interestingly, an inversion of a special tbx4 gene cluster (brip1-tbx4-tbx2b- bcas3) occurred twice independently, which coincides with the presence of fin spines. A nonsynonymous mutation (M82L) was identified in the nuclear localization sequence (NLS) of the Japanese eel tbx4. We also examined variation and loss of hindlimb enhancer B (HLEB), which may account for pelvic fin loss in Tetraodontidae and Diodontidae. In summary, we generated a genome assembly of the Japanese eel, which provides a valuable genomic resource to study the evolution of fish tbx4 and helps elucidate the mechanism of pelvic fin loss in teleost fishes. Our comparative genomic studies, revealed for the first time a potential correlation between the tbx4 gene cluster and the evolutionary development of toxic fin spines. Because fin spines in teleosts are usually venoms, this tbx4 gene cluster may facilitate the genetic engineering of toxin-related marine drugs.

Catalytic degradation of organic pollutants by nanomaterials is an effective way for environmental remediation. The Fenton reaction involving H2O2 oxidation catalysed by Fe3+ is an advisable way for wastewater degradation. Herein, Fe3O4/SiO2 core-shell nanoparticles were prepared as catalyst by coprecipitation and sol-gel methods, and this catalyst is used for degradation of fuchsin in wastewater by H2O2. The Fenton reaction between H2O2 and Fe3O4 is proposed to explain the catalytic performance. The coating of SiO2 on Fe3O4 nanoparticles could dramatically stabilize the Fe3O4 in aqueous solution and prevent their oxidation. More importantly, the magnetic property of Fe3O4 nanoparticles endows them with good recyclability. Thus, due to the outstanding catalytic results, almost 100% removal degradation was achieved within 5 min over a wide pH value range at room temperature, which is better than that without catalysts. Temperature is a positive factor for improving the degradation rate, but room temperature is selected as the best temperature for economic and energy savings reasons, because more than 98% of fuchsins can still be degraded at room temperature. Moreover, these Fe3O4/SiO2 core-shell nanoparticles exhibit excellent magnetic recyclability and stable properties after repeated utilization. Therefore, these as-presented Fe3O4/SiO2 core-shell nanoparticles with low-cost and high performance are expected to be applied in practical industry wastewater degradation.

Satellite-based monitoring can retrieve ground-level PM2.5 concentrations with higher-resolution and continuous spatial coverage to assist in making management strategies and estimating health exposures. The Sichuan Basin has a complex terrain and several city clusters that differ from other regions in China: it has an enclosed air basin with a unique planetary boundary layer dynamic which accumulates air pollution. The spatiotemporal distribution of 1-km resolution Aerosol Optical Depth (AOD) in the Sichuan Basin was retrieved using the improved dark pixel method and Moderate Resolution Imaging Spectroradiometer (MODIS) data in this study. The retrieved seasonal AOD reached its highest values in spring and had the lowest values in autumn. The higher correlation (r = 0.84, N = 171) between the ground-based Lidar AOD and 1-km resolution MODIS AOD indicated that the high-resolution MODIS AOD could be used to retrieve the ground-level PM2.5 concentration. The Lidar-measured annual average extinction coefficient increased linearly with the Planetary Boundary Layer Height (PBLH) in the range of 100~670 m, but exponentially decreased between the heights of 670~1800 m. Both the correlation and the variation tendency of simulated PBLH from the Weather Research and Forecasting (WRF) model & Shin-Hong (SHIN)/California Meteorological (CALMET) model (WRF_SHIN/CALMET) were closer to the Lidar observation than that of three other Planetary Boundary Layer (PBL) schemes (the Grenier-Bretherton-McCaa (GBM) scheme, the Total Energy-Mass Flux (TEMF) scheme and the University of Washington (UW) scheme), which suggested that the simulated the Planetary Boundary Layer Height (PBLH) could be used in the vertical correction of retrieval PM2.5. Four seasonal fitting functions were also obtained for further humidity correction. The correlation coefficient between the aerosol extinction coefficient and the fitted surface-level PM2.5 concentration at the benchmark station of Southwest Jiao-tong University was enhanced significantly from 0.62 to 0.76 after vertical and humidity corrections during a whole year. During the evaluation of the retrieved ground-level PM2.5 with observed values from three cities, Yibin (YB), Dazhou (DZ), and Deyang (DY), our algorithm performed well, resulting in higher correlation coefficients of 0.78 (N = 177), 0.77 (N = 178), and 0.81 (N = 181), respectively.