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Soil organic matter (SOM) is a key soil component. Determining its spatial distribution is necessary for precision agriculture and to understand the ecosystem services that soil provides. However, field SOM studies are severely limited by time and costs. To obtain a spatially continuous distribution map of SOM content, it is necessary to conduct digital soil mapping (DSM). In addition, there is a vital need for both accuracy and interpretability in SOM mapping, which is difficult to achieve with conventional DSM models. To address the above issues, particularly mapping SOM content, a spatial coefficient of variation (SVC) regression model, the Geographic Gaussian Process Generalized Additive Model (GGP-GAM), was used. The root mean squared error (RMSE), mean average error (MAE), and adjusted coefficient of determination (adjusted R2) of this model for SOM mapping in Leizhou area are 7.79, 6.01, and 0.33 g kg−1, respectively. GGP-GAM is more accurate compared to the other three models (i.e., Geographical Random Forest, Geographically Weighted Regression, and Regression Kriging). Moreover, the patterns of covariates affecting SOM are interpreted by mapping coefficients of each predictor individually. The results show that GGP-GAM can be used for the high-precision mapping of SOM content with good interpretability. This DSM technique will in turn contribute to agricultural sustainability and decision making.

The effects of solution treatment and annealing temperature on the microstructure and mechanical properties of a new TWIP steel that was alloyed from aluminum (Al), silicon (Si), vanadium (V), and molybdenum (Mo) elements were investigated by a variety of techniques such as microstructural characterization and room tensile testing. The austenite grain size grew slowly with the increase in annealing temperature. The relatively weak effect of the solution treatment and annealing temperature on the austenite grain size was attributed to the precipitation of MC and M2C, which hindered the growth of the austenite grain. The plasticity of the TWIP steel in cold rolling and annealing after solution treatment was obviously higher than that in cold rolling and annealing without solution treatment. This was because the large-size precipitates redissolved in the matrix after solution treatment, which were not retained in the subsequently annealed structure. Through cold rolling and annealing at 800 °C after solution treatment, the prepared steel exhibited excellent strength and plasticity simultaneously, with a yield strength of 877 MPa, a tensile strength of 1457 MPa, and an elongation of 46.1%. The strength improvement of the designed TWIP steel was mainly attributed to the grain refinement and precipitation strengthening.

National Highway G559 is the first highway in Southeast Tibet into Motuo County, which has not only greatly improved the difficult situation of local roads, but also promoted the economic development of Tibet. However, rainfall-induced shallow landslides occur frequently along the Bomi–Motuo section, which seriously affects the safe operation and construction work of the highway. Therefore, it is urgent to carry out geological disaster assessment and zoning along the highway. Based on remote-sensing interpretation and field investigation, the distribution characteristics and sliding-prone rock mass of shallow landslides along the Bomi–Motuo Highway were identified. Three-dimensional stability analysis of regional landslides along the Bomi-Motuo Highway under different rainfall scenarios was carried out based on the TRIGRS and Scoops3D coupled model (T-S model). The temporal and spatial distribution of potential rainfall landslides in this area is effectively predicted, and the reliability of the predicted results is also evaluated. The results show that: (1) The slope structure along the highway is mainly composed of loose gravel soil on the upper part and a strong weathering layer of bedrock on the lower part. The sliding surface is mostly a circular and plane type, and the main failure types are creep–tensile failure and flexural–tensile failure. (2) Based on the T-S coupling model, it is predicted that the potential landslide along the Bomi–Motuo Highway in the natural state is scattered. The distribution area of extremely unstable and unstable areas accounts for 4.92% of the total area. In the case of extreme rainfall once in a hundred years, the proportion of instability area (Fs < 1) predicted by the T-S coupling model 1 h after rainfall is 7.74%, which is 1.57 times that of the natural instability area. The instability area (Fs < 1) accounted for 43.40% of the total area after 12 h of rainfall. The potential landslides were mainly distributed in the Bangxin–Zhamu section and the East Gedang section. (3) The TRIGRS and T-S coupling model is both suitable for predicting the temporal–spatial distribution of rainfall-induced shallow landslides, but the TRIGRS model has the problem of over-prediction. The instability area predicted by the T-S coupling model accounted for 43.30%, and 74% of the historical landslide disaster points in the area were correctly predicted. (4) In terms of rainfall response, the T-S coupling model shows higher sensitivity. The %LRclass (Fs < 1) index of the T-S coupling model is above 50% in different time periods, and its landslide-prediction effect (%LRclass = 78.80%) was significantly better than that of the one-dimensional TRIGRS model (%LRclass = 45.50%) under a 12 h rainfall scenario. The research results have important reference significance for risk identification and disaster reduction along the G559 Bomi–Motuo Highway.

Cross-view geo-localization aims to locate street-view images by matching them with a collection of GPS-tagged remote sensing (RS) images. Due to the significant viewpoint and appearance differences between street-view images and RS images, this task is highly challenging. While deep learning-based methods have shown their dominance in the cross-view geo-localization task, existing models have difficulties in extracting comprehensive meaningful features from both domains of images. This limitation results in not establishing accurate and robust dependencies between street-view images and the corresponding RS images. To address the aforementioned issues, this paper proposes a novel and lightweight neural network for cross-view geo-localization. Firstly, in order to capture more diverse information, we propose a module for extracting multi-scale features from images. Secondly, we introduce contrastive learning and design a contrastive loss to further enhance the robustness in extracting and aligning meaningful multi-scale features. Finally, we conduct comprehensive experiments on two open benchmarks. The experimental results have demonstrated the superiority of the proposed method over the state-of-the-art methods.

Proliferation, apoptosis, and steroid hormone secretion by granulosa cells (GCs) and theca cells (TCs) are essential for maintaining the fate of chicken follicles. Our previous study showed that the Wnt inhibitor factor 1 (WIF1) plays a role in follicle selection. However, the significance of WIF1 in GC- and TC-associated follicular development was not explicitly investigated. This study found that WIF1 expression was strongly downregulated during follicle selection (p < 0.05) and was significantly higher in GCs than in TCs (p < 0.05). WIF1 inhibits proliferation and promotes apoptosis in GCs. Additionally, it promotes progesterone secretion in prehierarchal GCs (pre-GCs, 1.16 ± 0.05 ng/mg vs. 1.58 ng/mg ± 0.12, p < 0.05) and hierarchal GCs (hie-GCs, 395.00 ng/mg ± 34.73 vs. 527.77 ng/mg ± 27.19, p < 0.05) with the participation of the follicle-stimulating hormone (FSH). WIF1 affected canonical Wnt pathways and phosphorylated β-catenin expression in GCs. Furthermore, 604 upregulated differentially expressed genes (DEGs) and 360 downregulated DEGs in WIF1-overexpressed GCs were found through RNA-seq analysis (criteria: |log2⁡(FoldChange)| > 1 and p_adj < 0.05). Cytokine–cytokine receptor interaction and the steroid hormone biosynthesis pathway were identified. In addition, the transcript of estrogen receptor 2 (ESR2) increased significantly (log2⁡(FoldChange) = 1.27, p_adj < 0.05). Furthermore, we found that WIF1 regulated progesterone synthesis by upregulating ESR2 expression in GCs. Additionally, WIF1 suppressed proliferation and promoted apoptosis in TCs. Taken together, these results reveal that WIF1 stimulates follicle development by promoting GC differentiation and progesterone synthesis, which provides an insight into the molecular mechanism of follicle selection and egg-laying performance in poultry.

A full understanding of bitumen fatigue cracking behavior is extremely important as this phenomenon has a considerable influence on bituminous pavement performance. The current framework for assessing this asphalt binder property is inconsistent in ranking bitumen fatigue performance in terms of the failure definition and damage characteristic curve (DCC) analysis. This study used four different types of asphalt binders: neat asphalt (NA), self-healing thermoplastic polyurethane (STP)-modified bitumen, self-healing poly (dimethyl siloxane) crosslinked with urea bond (IPA1w)-modified bitumen, and styrene–butadiene–styrene (SBS)-modified bitumen (SBSB). All the bitumens were subjected to short-term and long-term aging, and they were also tested by utilizing the linear amplitude sweep (LAS) test and the simplified viscoelastic continuum damage (S-VECD) model. LAS and S-VECD procedures were used to apply the newly proposed and current frameworks in order to analyze bitumen performance. The current framework showed that the bitumens that used a higher number of loading cycles (N) to reach their failure points (Nf) failed to exhibit greater fatigue performances in terms of DCC analysis. The developed framework (mainly based on the damage intensity [S] instead of N) was used to solve the inconsistency between the failure definition and DCC assessment in ranking bitumen performance. Additionally, the current framework (failure criterion) presented two R2 values below 0.1, but the developed framework (failure criterion) showed that all R2 values were greater than 0.9. The developed framework represents a turning point because, for the first time, this type of procedure is mainly being based on S instead of N. Although further tests are needed to confirm its efficiency, it eliminates the inconsistency between the failure definition and DCC assessment.

The scaling of agricultural land is a trend in land use transformation and is important for modernizing agriculture. Therefore, the reasons for large-scale agricultural land formation should be explored. The spatial distribution of large-scale agricultural land and the factors for its formation vary between different regions. Currently, the exploration of the formation mechanism of large-scale agricultural land from the perspective of heterogeneity is not yet sufficient. Therefore, the main objectives of this article are as follows: first, analyze the spatial pattern characteristics of large-scale agricultural land; second, explore the spatial heterogeneity characteristics of influencing factors from both global and local perspectives; third, explore the mechanism of the formation of large-scale agricultural land from the perspective of heterogeneity. The results indicate the following: (1) The large-scale agricultural land distribution pattern in the Wuling Mountains area was high in the east and low in the west. (2) Natural conditions, production factors, and location conditions all significantly impacted large-scale agricultural land, but with differences in their degree of influence. From a local perspective, the influences of various factors in different regions also exhibited spatial heterogeneity. These two types of heterogeneity can be attributed to the differences in regional development stages. (3) Natural conditions, location conditions, and production factors had negative, positive, and positive effects on the agricultural land scale, respectively, but the influence of the first two decreased with the improvement in the regional development stages. The influence of different factors on production factors was related to the regional development stage, and production factors that were suitable for the regional development stage had a greater impact. The conclusion can provide differentiated policy support for regional land use in practice.

In order to develop the biological self-cleaning anti-clogging high-permeability sand filter tube, it is very important to analyze the plugging material and plugging mechanism of crude oil sand water filter. Under laboratory conditions, based on vacuum drying, condensation reflux, chromatographic separation, and other technologies, the plugging components were preliminarily analyzed. The plugging components were analyzed via XRD, infrared analysis, 1H NMR, and 13C NMR. Through analysis and testing, XRD results showed that the solid compositions were clay and sand grains. Meanwhile, the infrared analysis, 1H NMR, and 13C NMR demonstrated that the main components of the plug are asphaltene crude oil, and the proportion of aromatic components and saturated components is close.

To address the issue of pipeline blockage caused by the formation of waxy deposits inside pipelines, hindering the flow of petroleum in the Shengli oilfield, eight new-style polyacrylic acid pour point depressants (PPD) for Shengli crude oil were prepared by maleic anhydride and ene monomers with different polar and aromatic pendant chains. The synthesized Pour Point Depressants were characterized by Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), gel permeation chromatography (GPC), and polarizing optical microscopy (POM). The results were promising and demonstrated that any type of pour point depressant exhibited excellent performance on high-pour-point crude oil. The reduction in pour-point after additive addition was largely dependent on the polymer structure. Notably, polymers containing long alkyl side chains and aromatic units displayed the most impressive performance, capable of depressing the pour point by 12 °C.

The oxidation of benzyl alcohols is an important reaction in organic synthesis. Traditional methods for benzyl alcohol oxidation have not been widely utilized due to the use of significant amounts of precious metals and environmentally unfriendly reagents. In recent years, electrocatalytic oxidation has gained significant attention, particularly electrochemical anodic oxidation, which offers a sustainable alternative for oxidation without the need for external oxidants or reducing agents. Here, a copper monosubstituted phosphotungstate-based polyacrylate resins (Cu-LPOMs@PPAR) catalyst has been fabricated with immobilization and recyclability using 3D printing technology that can be successfully applied in the electrocatalytic oxidation of benzyl alcohol to benzaldehyde, achieving atom economy and reducing pollution. In this protocol, we obtain benzaldehyde in good yields with excellent functional group toleration under metal-free and oxidant-free conditions. This strategy could provide a new avenue for heterogeneous catalysts in application for enhancing the efficiency and selectivity of electrocatalytic oxidation processes.

Soil fertility plays a crucial role in crop growth, so it is important to study the spatial distribution and variation of soil fertility for agricultural management and decision-making. However, traditional methods for assessing soil fertility are time-consuming and economically burdensome. Moreover, it is hard to capture the spatial variation of soil properties across continuous geographic space using the conventional methods. As key techniques of digital soil mapping (DSM), spatial interpolation techniques have been widely applied in soil surveys and analysis in recent years, since they can predict soil properties at unknown points in continuous space based on limited sample points. However, further research is needed on spatial interpolation models for DSM in regions with variable climates and complex terrains, which are characterized by strong spatial variation in both environmental variables and soil fertility. In this study, taking a typical hilly area in a subtropical monsoon climate, i.e., Gaozhou, Guangdong Province, China, as an example, the performances of four popular spatial interpolation models (Random Forest (RF), Ordinary Kriging, Inverse Distance Weighting, and Radial Basis Function) for digital soil mapping on available phosphorus (AP) are compared. Based on RF, the spatial variation and its driving factors of the AP of Gaozhou are then analyzed. Furthermore, by selecting three typical truncation lines from different directions, the correlations between environmental variables and AP in different spatial positions are demonstrated. The root mean square error (RMSE) results of the above four models are 32.01, 32.08, 32.74, and 33.08, respectively, which indicate that the RF has a higher interpolation accuracy. Based on the mapping results of RF, the minimum, maximum, and mean values of AP in the study area are 38.90, 95.24, and 64.96 mg/kg, respectively. The high-value areas of AP are mainly distributed in forested and orchard areas, while the low-value areas are primarily found in urban and cultivated areas in the eastern and western regions. Vegetation and topography are identified as the key factors shaping the spatial variations of AP in the study area. Furthermore, the spatial heterogeneity of the influence strength of altitude and EVI is revealed, providing a new direction for further research on DSM in the future, i.e., spatial interpolation models considering the spatial heterogeneity of the influence of environmental variables.

The composition, structure, and functionalities of prolamins from highland barley were investigated. These parameters were compared with those of the commonly applied prolamins (zein). There are more charged and hydrophilic amino acids in highland barely prolamins than zein. The molecular weight of highland barely prolamins was between 30 and 63 kDa, which was larger than that of zein (20 and 24 kDa). The main secondary structure of highland barely prolamins was β-turn helices, while α-helical structures were the main secondary structure in zein. The water holding capacity, thermal stability, emulsifying capacity, and stability of prolamins from highland barley were significantly higher than in zein, while the opposite results were observed for oil absorption capacity between the two. The diameter of fibers prepared using highland barely prolamins was almost six times that of zein, while highland barely prolamins formed ribbon structures instead of fibers. Therefore, the results provide guidance for applications of prolamins from highland barley.

The structural characteristics of an urban road network directly affect the urban road network’s overall function and service level. Because the hierarchical division and layout form of an urban road network has self-similarity and scale invariance, the urban traffic network has certain time-space fractal characteristics, and fractal theory has become a powerful tool for evaluating traffic networks. This paper calculates and compares five fractal dimensions (FD) of nine districts in Harbin. Meanwhile, each calculated FD is linearly regressed with the area, population, built-up area, building area, the total number and length of roads, and the number of buildings in the region. The results show that the fractal dimensions of the five types are between 1 and 2. In the same district, the values of the FD perimeter and FD ruler are lower compared to the FD box, FD information, and FD mass, whereas those of the FD box and FD information are higher. Compared to the FD box and FD information, the value of FD mass shows unevenly. Based on the current research results, this study discusses the feasibility of using relevant indicators in the fractal process to evaluate the layout of the urban road network and guide its optimization and adjustment.

Exposure-response (E-R) is a key aspect of pharmacometrics analysis that supports drug dose selection. Currently, there is a lack of understanding of the technical considerations necessary for drawing unbiased estimates from data. Due to recent advances in machine learning (ML) explainability methods, ML has garnered significant interest for causal inference. To this end, we used simulated datasets with known E-R “ground truth” to generate a set of good practices for the development of ML models required to avoid introducing biases when performing causal inference. These practices include the use of causal diagrams to enable the careful consideration of model variables by which to obtain desired E-R relationship insights, keeping a strict separation of data for model-training and for inference generation to avoid biases, hyperparameter tuning to improve the reliability of models, and estimating proper confidence intervals around inferences using a bootstrap sampling with replacement strategy. We computationally confirm the benefits of the proposed ML workflow by using a simulated dataset with nonlinear and non-monotonic exposure–response relationships.

We first study the error performances of the Vector Weak Rescaled Pure Greedy Algorithm for simultaneous approximation with respect to a dictionary D in a Hilbert space. We show that the convergence rate of the Vector Weak Rescaled Pure Greedy Algorithm on A1(D) and the closure of the convex hull of the dictionary D is optimal. The Vector Weak Rescaled Pure Greedy Algorithm has some advantages. It has a weaker convergence condition and a better convergence rate than the Vector Weak Pure Greedy Algorithm and is simpler than the Vector Weak Orthogonal Greedy Algorithm. Then, we design a Vector Weak Rescaled Pure Greedy Algorithm in a uniformly smooth Banach space setting. We obtain the convergence properties and error bound of the Vector Weak Rescaled Pure Greedy Algorithm in this case. The results show that the convergence rate of the VWRPGA on A1(D) is sharp. Similarly, the Vector Weak Rescaled Pure Greedy Algorithm is simpler than the Vector Weak Chebyshev Greedy Algorithm and the Vector Weak Relaxed Greedy Algorithm.

A high aluminum (Al) content β-(AlxGa1−x)2O3 film was synthesized on c-plane sapphire substrate using the gallium (Ga) diffusion method. The obtained β-(AlxGa1−x)2O3 film had an average thickness of 750 nm and a surface roughness of 2.10 nm. Secondary ion mass spectrometry results indicated the homogenous distribution of Al components in the film. The Al compositions in the β-(AlxGa1−x)2O3 film, as estimated by X-ray diffraction, were close to those estimated by X-ray photoelectron spectroscopy, at ~62% and ~61.5%, respectively. The bandgap of the β-(AlxGa1−x)2O3 film, extracted from the O 1s core-level spectra, was approximately 6.0 ± 0.1 eV. After synthesizing the β-(AlxGa1−x)2O3 film, a thick β-Ga2O3 film was further deposited on sapphire substrate using carbothermal reduction and halide vapor phase epitaxy. The β-Ga2O3 thick film, grown on a sapphire substrate with a β-(AlxGa1−x)2O3 buffer layer, exhibited improved crystal orientation along the (-201) plane. Moreover, the scanning electron microscopy revealed that the surface quality of the β-Ga2O3 thick film on sapphire substrate with a β-(AlxGa1−x)2O3 intermediate buffer layer was significantly improved, with an obvious transition from grain island-like morphology to 2D continuous growth, and a reduction in surface roughness to less than 10 nm.

Fatigue cracking is a common form of flexible pavement distress, which generally starts and spreads through bitumen. To address this issue, self-healing elastomer (SHE) modified bitumens were elaborated to assess whether these novel materials can overcome the neat asphalt (NA) fatigue performance and whether the current failure definition, failure criterion, and fatigue-restoration criteria can fit their performance. All bitumens were subjected to short-term and long-term aging. Linear amplitude sweep (LAS) test, LAS with rest period (LASH), and simplified viscoelastic-continuum-damage (S-VECD) model were utilized to appraise the behavior of the mentioned bitumens. The results showed that maximum stored pseudo-strain energy (PSE) and tau (τ) × N (number of loading cycles) failure definitions exhibited high efficiency to accommodate the fatigue life of NA and SHE-modified bitumens. Both failure criteria identified that SHE-modified bitumen (containing 1% of SHE) showed the highest increment of fatigue performance (67.1%) concerning NA. The failure criterion based on total released PSE, in terms of the area under the released PSE curve, was the only failure concept with high efficiency (R2 up to 0.999) to predict asphalt binder fatigue life. As well, the current framework to evaluate bitumen self-restoration failed to fully accommodate asphalt binder behavior, because bitumen with higher restoration could not exhibit greater fatigue performance. Consequently, a new procedure to assess this property including fatigue behavior was proposed, showing consistent results, and confirming that SHE-modified bitumen (containing 1% of SHE) exhibited the highest increment of fatigue performance (154.02%) after application of the rest period. Hence, the optimum SHE content in NA was 1%. Furthermore, it was found that a greater number of loading cycles to failure (Nf) did not ensure better fatigue performance and stored PSE influenced the bitumen fatigue behavior.

The spatial and temporal variation analysis of land cover classification is important for studying the distribution and transformation of regional land cover changes. The Qilian Mountain National Park (QMNP), an important ecological barrier in northwestern China, has lacked land cover products for long time series. The Landsat images available on the Google Earth Engine (GEE) make it possible to analyze the land cover changes over the past three decades. The purpose of this study was to generate a long time series of datasets of land cover classification based on the method of sample migration in the QMNP in Northwest China. The Landsat 5, 7, and 8 images and field sample data were combined with multiple image features and the random forest algorithm to complete the land cover classification of the QMNP from 1990 to 2020. The results indicate that (1) the method of Jeffries–Matusita (J-M) distance can reduce image feature redundancy and show that elevation and phenological features have good differentiability among land cover types that were easy to mix with feature classes; (2) the spatial distribution of land cover every 10 years between 1990 and 2020 was consistent in the QMNP, and there were obvious differences in land cover from the east to the west part of the QMNP, with a large area of vegetation distribution in Sunan county in the central part and Tianzhu county in the east part of the QMNP; (3) over the past 30 years, forests and grasslands decreased by 62.2 km2 and 794.7 km2, respectively, while shrubs increased by 442.9 km2 in the QMNP. The conversion of bare land to grassland and the interconversion between different vegetation types were the main patterns of land cover changes, and the land cover changes were mainly concentrated in pastoral areas, meaning that human activity was the main factor of land cover changes; and (4) when the samples of 2020 were migrated to 2010, 2000, and 1990, the overall classification accuracies were 89.7%, 88.0%, 86.0%, and 83.9%, respectively. The results show that the vegetation conservation process in the QMNP was closely related to human activities.

Emergencies such as machine breakdowns and rush orders greatly affect the production activities of manufacturing enterprises. How to deal with the rescheduling problem after emergencies have high practical value. Meanwhile, under the background of intelligent manufacturing, automatic guided vehicles are gradually emerging in enterprises. To deal with the disturbances in flexible job shop scheduling problem with automatic guided vehicle transportation, a mixed-integer linear programming model is established. According to the traits of this model, an improved NSGA-II is designed, aiming at minimizing makespan, energy consumption and machine workload deviation. To improve solution qualities, the local search operator based on a critical path is designed. In addition, an improved crowding distance calculation method is used to reduce the computation complexity of the algorithm. Finally, the validity of the improvement strategies is tested, and the robustness and superiority of the proposed algorithm are verified by comparing it with NSGA, NSGA-II and SPEA2.

We propose the Weak Rescaled Pure Super Greedy Algorithm (WRPSGA) for approximation with respect to a dictionary D in Hilbert space. The WRPSGA is simpler than some popular greedy algorithms. We show that the convergence rate of the RPSGA on the closure of the convex hull of the μ-coherent dictionary D is optimal. Then, we design the Rescaled Pure Super Greedy Learning Algorithm (RPSGLA) for kernel-based supervised learning. We prove that the convergence rate of the RPSGLA can be arbitrarily close to the best rate O(m−1) under some mild assumptions.

Chemokines can induce chemotactic cell migration by interacting with G protein-coupled receptors to play a significant regulatory role in the development of cancer. CXC chemokine-12 (CXCL12) can specifically bind to CXC chemokine receptor 4 (CXCR4) and is closely associated with the progression of cancer via multiple signaling pathways. Over recent years, many CXCR4 antagonists have been tested in clinical trials; however, Plerixafor (AMD3100) is the only drug that has been approved for marketing thus far. In this review, we first summarize the mechanisms that mediate the physiological effects of the CXCL12/CXCR4 axis. Then, we describe the use of CXCL12/CXCR4 antagonists. Finally, we discuss the use of nano-based drug delivery systems that exert action on the CXCL12/CXCR4 biological axis.

The main aim of this study was to identify the bZIP family members in mung bean and explore their expression patterns under several abiotic stresses, with the overarching goal of elucidating their biological functions. Results identified 75 bZIP members in mung bean, which were unevenly distributed in the chromosomes (1–11), and all had a highly conserved bZIP domain. Phylogenetic analysis divided the members into 10 subgroups, with members in the same subgroup having similar structure and motif. The cis-acting elements in the promoter region revealed that most of the bZIP members might have the connection with abscisic acid, ethylene, and stress responsive elements. The transcriptome data demonstrated that bZIP members could respond to salt stress at different degrees in leaves, but the expression patterns could vary at different time points under stress. Differentially expressed genes (DEGs), such as VrbZIP12, VrbZIP37, and VrZIP45, were annotated into the plant hormone signal transduction pathway, which might be regulated the expression of abiotic stress-related gene (ABF). Quantitative real-time polymerase chain reaction (qRT-PCR) was applied to determine the expression of bZIP members in roots and leaves under drought, alkali, and low-temperature stress. Results showed that bZIP members respond differently to diverse stresses, and their expression was tissue-specific, which suggests that they may have different regulatory mechanism in different tissues. Overall, this study will provide a reference for further research on the functions of bZIP members in mung bean.

We study the approximation capability of the orthogonal super greedy algorithm (OSGA) with respect to μ-coherent dictionaries in Hilbert spaces. We establish the Lebesgue-type inequalities for OSGA, which show that the OSGA provides an almost optimal approximation on the first [1/(18μs)] steps. Moreover, we improve the asymptotic constant in the Lebesgue-type inequality of OGA obtained by Livshitz E D.

Line-structured light three-dimensional (3D) measurement is apt for measuring the 3D profile of objects in complex industrial environments. The light-plane calibration, which is a crucial link, greatly affects the accuracy of measurement results. This paper proposes a novel calibration method for line-structured light 3D measurement based on a simple target, i.e., a single cylindrical target (SCT). First, the line-structured light intersects with the target to generate a light stripe. Meanwhile, the camera captures the calibration images, extracts the refined subpixel center points of the light stripe (RSCP) and detects the elliptic profiles of the two ends of the cylindrical target (EPCT). Second, two elliptical cones defined by the EPCT and the camera optical center are determined. Combining the two defined elliptical cones and the known radius of the SCT, we can uniquely solve the axis equation of the SCT. Finally, because the coordinates of RSCP in the camera coordinate system fulfill both the camera model and the cylindrical equation, these coordinates can be solved and used to obtain the optimal solution of the light-plane equation. The results of simulations and experiments verify that our proposed method has higher accuracy and effectiveness.

Ovarian follicle selection largely depends on the transition of granulosa cells from an undifferentiated to a fully differentiated state, which is accompanied by morphological and functional changes in follicles. The processes and transcriptional regulation of follicles during follicle selection are unclear; we thus used follicles from the prehierarchal to the hierarchal stage to investigate histology, reproductive endocrinology, and transcription. The morphology of follicles changed markedly during follicle selection. The numbers of large white, small yellow, and large yellow follicles (LWF, SYF, and LYF, respectively) were 11.83 ± 2.79, 6.83 ± 2.23, and 1.00, respectively, per ovary. LYF showed thicker granulosa cell layers than those of other prehierarchal follicles. Progesterone concentrations were significantly higher in LYF than that in LWF and SYF. In total, 16,823 genes were positively expressed in LWF, SYF, and LYF. Among follicle types, 1290 differentially expressed genes were enriched regarding cell differentiation, blood vessel morphogenesis, and response to steroid hormones. Candidate genes associated with follicle selection participated in the Wnt signaling pathway, steroid hormone biosynthesis, and the TGF-β signaling pathway. We produced insights into crucial morphological characteristics of transcriptional regulation in follicle development. Our results provide an important basis for revealing the mechanism of follicle selection and potential impact on the poultry industry.

Members of the Thaumarchaeota phylum play a key role in nitrogen cycling and are prevalent in a variety of environments including soil, sediment, and seawater. However, few studies have shown the presence of Thaumarchaeota in the terrestrial deep subsurface. Using high-throughput 16S rRNA gene sequencing, this study presents evidence for the high relative abundance of Thaumarchaeota in a biofilm sample collected from the well of Chinese Continental Scientific Drilling at a depth of 2000 m. Phylogenetic analysis showed a close relationship of these thaumarchaeotal sequences with known ammonia-oxidizing archaea (AOA) isolates, suggesting the presence of AOA in the deep metamorphic environment of eastern China which is believed to be oxic. Based on fluid geochemistry and FAProTax functional prediction, a pathway of nitrogen cycling is proposed. Firstly, heterotrophic nitrogen fixation is executed by diazotrophic bacteria coupled with methane oxidation. Then, ammonia is oxidized to nitrite by AOA, and nitrite is further oxidized to nitrate by bacteria within the phylum Nitrospirae. Denitrification and anaerobic ammonia oxidation occur slowly, leading to nitrate accumulation in the subsurface. With respect to biogeochemistry, the reaction between downward diffusing O2 and upward diffusing CH4 potentially fuels the ecosystem with a high relative abundance of Thaumarchaeota.

The optimization problem of the number of mirrors under energy efficiency (EE) maximization for vehicular visible light communication (VVLC) via mirror array-based intelligent reflecting surface (IRS) is investigated. Under considering that the formulated optimization problem is subject to the real and non-negative of the transmitted signal, the maximum power consumption satisfied luminous ability and eye safety, the minimum achievable rate, and the required bit error ratio (BER), EE is proved to be a unimodal function of the number of mirrors. Then, the binary search-conditional iteration (BSCI) algorithm is proposed for quickly finding the optimal number of mirrors with maximum EE. Numerical results demonstrate that fewer mirrors can obtain the maximum EE, and the computational complexity of the BSCI algorithm is reduced by 105 orders of magnitude, compared with the Bubble Sort method.

Tropospheric ozone is the only normal pollutant with a continuously increasing annual average concentration worldwide. In this study, data were monitored at the Nankai University Air Quality Research Supersite (NKAQRS) (38.99° N, 117.33° E) between 1 April, and 31 August from 2018 to 2020, 33 O3 episodes from 2018 to 2020 were analyzed to reveal the characteristics of O3, VOCs and OFP during O3 episodes and to evaluate the driving factors. The O3 episodes showed a decreasing trend in terms of pollution frequency, days, heavy pollution duration and peak concentration. Ethane, acetylene, cyclopentane, and methylcyclopentane were the major types in 2020, while 1-hexene was the main component in 2019. The main ozone-contributing species in 2020 were propene cyclopentane methylcyclopentane and ethylene. Alkenes were important contributors to ozone formation. Using generalized additive models (GAMs), the explanatory variables in the study are divided into environmental and meteorological factors, and 16 impact factors are selected as explanatory variables. We found that the influence of these meteorological factors on O3 pollution was nonlinear and impacted by the interaction between variables. O3 episodes were mainly driven by meteorological and precursor (NO) factors in 2018, while meteorological conditions (T), followed by precursor (NO2) were the driving factors in 2019 and 2020, suggesting that O3 episodes were mainly driven by meteorological conditions.

With the popularity of Android, malware detection and family classification have also become a research focus. Many excellent methods have been proposed by previous authors, but static and dynamic analyses inevitably require complex processes. A hybrid analysis method for detecting Android malware and classifying malware families is presented in this paper, and is partially optimized for multiple-feature data. For static analysis, we use permissions and intent as static features and use three feature selection methods to form a subset of three candidate features. Compared with various models, including k-nearest neighbors and random forest, random forest is the best, with a detection rate of 95.04%, while the chi-square test is the best feature selection method. After using feature selection to explore the critical static features contained in this dataset, we analyzed a subset of important features to gain more insight into the malware. In a dynamic analysis based on network traffic, unlike those that focus on a one-way flow of traffic and work on HTTP protocols and transport layer protocols, we focused on sessions and retained protocol layers. The Res7LSTM model is then used to further classify the malicious and partially benign samples detected in the static detection. The experimental results show that our approach can not only work with fewer static features and guarantee sufficient accuracy, but also improve the detection rate of Android malware family classification from 71.48% in previous work to 99% when cutting the traffic in terms of the sessions and protocols of all layers.

The search for a safe and effective inhibitor of ferroptosis, a recently described cell death pathway, has attracted increasing interest from scientists. Two hydrolyzable tannins, chebulagic acid and chebulinic acid, were selected for the study. Their optimized conformations were calculated using computational chemistry at the B3LYP-D3(BJ)/6-31G and B3LYP-D3(BJ)/6-311 + G(d,p) levels. The results suggested that (1) chebulagic acid presented a chair conformation, while chebulinic acid presented a skew-boat conformation; (2) the formation of chebulagic acid requires 762.1729 kcal/mol more molecular energy than chebulinic acid; and (3) the 3,6-HHDP (hexahydroxydiphenoyl) moiety was shown to be in an (R)- absolute stereoconfiguration. Subsequently, the ferroptosis inhibition of both tannins was determined using a erastin-treated bone marrow-derived mesenchymal stem cells (bmMSCs) model and compared to that of ferrostatin-1 (Fer-1). The relative inhibitory levels decreased in the following order: Fer-1 > chebulagic acid > chebulinic acid, as also revealed by the in vitro antioxidant assays. The UHPLC–ESI-Q-TOF-MS analysis suggested that, when treated with 16-(2-(14-carboxytetradecyl)-2-ethyl-4,4-dimethyl-3-oxazolidinyloxy free radicals, Fer-1 generated dimeric products, whereas the two acids did not. In conclusion, two hydrolyzable tannins, chebulagic acid and chebulinic acid, can act as natural ferroptosis inhibitors. Their ferroptosis inhibition is mediated by regular antioxidant pathways (ROS scavenging and iron chelation), rather than the redox-based catalytic recycling pathway exhibited by Fer-1. Through antioxidant pathways, the HHDP moiety in chebulagic acid enables ferroptosis-inhibitory action of hydrolyzable tannins.

Forced expression of core cardiogenic transcription factors can directly reprogram fibroblasts to induced cardiomyocyte-like cells (iCMs) in vitro and in vivo. This cardiac reprogramming approach provides a proof of concept for induced heart regeneration by converting a fibroblast fate to a cardiomyocyte fate. However, it remains elusive whether chamber-specific cardiomyocytes can be generated by cardiac reprogramming. Therefore, we assessed the ability of the cardiac reprogramming approach for chamber specification in vitro and in vivo. We found that in vivo cardiac reprogramming post-myocardial infarction exclusively induces a ventricular-like phenotype, while a major fraction of iCMs generated in vitro failed to determine their chamber identities. Our results suggest that in vivo cardiac reprogramming may have an inherent advantage of generating chamber-matched new cardiomyocytes as a potential heart regenerative approach.

The wide application of encryption technology has made traffic classification gradually become a major challenge in the field of network security. Traditional methods such as machine learning, which rely heavily on feature engineering and others, can no longer fully meet the needs of encrypted traffic classification. Therefore, we propose an Inception-LSTM(ICLSTM) traffic classification method in this paper to achieve encrypted traffic service identification. This method converts traffic data into common gray images, and then uses the constructed ICLSTM neural network to extract key features and perform effective traffic classification. To alleviate the problem of category imbalance, different weight parameters are set for each category separately in the training phase to make it more symmetrical for different categories of encrypted traffic, and the identification effect is more balanced and reasonable. The method is validated on the public ISCX 2016 dataset, and the results of five classification experiments show that the accuracy of the method exceeds 98% for both regular encrypted traffic service identification and VPN encrypted traffic service identification. At the same time, this deep learning-based classification method also greatly simplifies the difficulty of traffic feature extraction work.

With the rapid increase in the number of Android malware, the image-based analysis method has become an effective way to defend against symmetric encryption and confusing malware. At present, the existing Android malware bytecode image detection method, based on a convolution neural network (CNN), relies on a single DEX file feature and requires a large amount of computation. To solve these problems, we combine the visual features of the XML file with the data section of the DEX file for the first time, and propose a new Android malware detection model, based on a temporal convolution network (TCN). First, four gray-scale image datasets with four different combinations of texture features are created by combining XML files and DEX files. Then the image size is unified and input to the designed neural network with three different convolution methods for experimental validation. The experimental results show that adding XML files is beneficial for Android malware detection. The detection accuracy of the TCN model is 95.44%, precision is 95.45%, recall rate is 95.45%, and F1-Score is 95.44%. Compared with other methods based on the traditional CNN model or lightweight MobileNetV2 model, the method proposed in this paper, based on the TCN model, can effectively utilize bytecode image sequence features, improve the accuracy of detecting Android malware and reduce its computation.

Minerals provide physical niches and supply nutrients or serve as electron donors/acceptors for microorganism survival and growth, and thus minerals and microbes co-evolved. Yet, little is known about how sediment minerals impact microbial community assembly in hot springs and to what extent mineralogical composition influences microbial community composition and diversity. Here the influences of minerals on thermophiles in Tengchong hot springs were revealed by network analysis of field samples, as well as in-situ microcosm experiments with minerals. A molecular ecological network was constructed based on high throughput sequencing data of 16S rRNA gene, with a combination of water geochemistry and sedimentary mineralogical compositions. Six modules were identified and this highly modular network structure represents the microbial preference to different abiotic factors, consequently resulting in niche partitioning in sedimentary communities in hot springs. Diverse mineralogical compositions generated special niches for microbial species. Subsequently, the in-situ microcosm experiments with four minerals (aragonite, albite, K-feldspar, and quartz) and spring water were conducted in a silicate-hosted alkaline spring (i.e., Gmq) and a carbonate-hosted neutral hot spring (i.e., Gxs) for 70 days. Different microbial preferences were observed among different mineral types (carbonate versus silicate). Aragonite microcosms in Gmq spring enriched archaeal genera Sulfophobococcus and Aeropyrum within the order Desulfurococcales by comparison with both in-situ water and silicate microcosms. Sulfophobococcus was also accumulated in Gxs aragonite microcosms, but the contribution to overall dissimilarity is much lower than that in Gmq spring. Besides, Caldimicrobium was a bacterial genus enriched in Gxs aragonite microcosms, in contrast to in-situ water and silicate microcosms, whereas Candidatus Kryptobacter and Thermus were more abundant in silicate microcosms. The differences in microbial accumulations among different mineral types in the same spring implied that mineral chemistry may exert extra deterministic selective pressure in drawing certain species from the bulk water communities, in addition to stochastic absorption on mineral surface. Taken together, our results highlight the special niche partitioning determined by mineralogical compositions and further confirm that minerals could be used as “fishing bait” to enrich certain rare microbial species.

Mesozoic porphyritic rocks from the Zijinshan area, southwestern Fujian Province, China, are andesitic to rhyolitic in composition. The whole-rock SiO2 contents of these rocks are between 62.5% and 78.1%. Magmatic zircon from the Mesozoic porphyritic rocks was determined via secondary-ionization mass spectrometry (SIMS) for the U-Pb age and Hf and O isotopes. The zircon U-Pb ages could be mainly divided into three age groups: Group 1: ~138.8 Ma; Group 2: 109.2~107.4 Ma; and Group 3: 99.7~98.2 Ma. The εHf(t) and δ18O values of the porphyritic zircons showed that the porphyritic rocks in Group 2 were more affected by mantle-derived magma. Combined with previous research results, the medium-acidic magmatism in the southwestern Fujian Province can be divided into eight periods: Paleoproterozoic, Mesoproterozoic, Middle Neoproterozoic, Silurian to Lower Devonian, Permian to Triassic, Middle Jurassic to early Lower Cretaceous, late Lower Cretaceous, and late Lower Cretaceous to early Upper Cretaceous. The Paleoproterozoic crust was the predominant magmatic source for the subsequent Mesoproterozoic to Jurassic magmatism, but the only melts that were closely related to mineralization were derived from partial melting of the Mesoproterozoic crust and a more depleted upper mantle.

In order to study the effect of initial defects on fatigue crack propagation law, a test method to identify fatigue crack propagation rate and path based on load waveform variation was presented, and a new test device was designed to apply fatigue pulsation loads to multiple wires for bridge cables simultaneously in this paper. To simplify the corrosion defect formation process, a machine-cut notch was used to describe the initial defect on the steel wire surface. Firstly, fatigue crack propagation tests were conducted on the surface notched steel wire specimens. By using crack front marking technique, the “beach-like patterns” visible to the naked eyes on the cross sections of the steel wires were formed, and the process of fatigue crack propagation can be tracked and reproduced. Then Autodesk Computer Aided Design (AutoCAD) software was used to describe the morphology of “beach-like patterns” and accurately measure the depth and width of cracks. Finally, the influence of initial defect morphology on fatigue crack propagation rate was investigated according to the relationship between fatigue cracks depth and cyclic loading numbers. The results show that the test device designed in this paper can effectively realize the synchronous fatigue crack propagation test of multiple wires, and significantly shorten the fatigue test period. By observing and analyzing the change of load waveform, the moment of fatigue crack propagation can be directly and accurately determined. The larger the depth, the smaller the width and the sharper the morphology of initial defect, the faster the crack propagation rate and the shorter the life of notched wire specimens under the combined action of fatigue loads and corrosive medium.

The durability problem in high-strength steel wire used for bridge cable is becoming more and more severe due to chlorine salt erosion, with the primary corrosion morphology of steel wire surfaces being pit corrosion. To simplify the pitting formation process, a machine-cut notch was used to represent a corrosion pit caused by electrochemical non-uniformity, and then the fatigue performance and corrosion fatigue performance of steel wire with initial defects were studied experimentally. A new type of test device was designed to carry out synchronous pulsating fatigue loading on multiple wires. A series of S-N curves of steel wire with initial defects under various loading conditions was obtained, and the effects of the concentration and pH value of the corrosive solution, and the shape and dimension of the initial defect on the fatigue corrosion performance of steel wire for bridge cables were investigated. The results show that the test device designed in this paper can effectively perform the life test under the combined action of corrosive medium and fatigue load, and can considerably shorten the duration of the fatigue test. Under the combined action of corrosive medium and fatigue load, the life of steel wire with an initial defect is significantly lower than that without consideration of the corrosion effect. The corrosion fatigue performance of steel wire decreases with the increase of acidity of the corrosive solution, rather than the increase of solution concentration. The life of steel wire with a narrow deep notch is much lower than that with a wide shallow notch. The stress concentration leads to a sharp reduction in wire life.

Highland barley starch (HBS), as a carbohydrate shell material with excellent performance in microcapsule applications, has rarely been reported. In the present study, three different microcapsules (CEO-SWSM, CEO-PM, and CEO-UM) were synthesized successfully via saturated aqueous solution method, molecular inclusion method and ultrasonic method, respectively, using HBS as shell material coupled with cinnamon essential oil (CEO) as the core material. The potential of HBS as a new shell material and the influence of synthetic methods on the performance of microcapsules, encapsulation efficiency (EE), yield, and release rate of CEO-SWSM, CEO-PM, and CEO-UM were determined, respectively. The results confirmed that CEO-PM had the most excellent EE (88.2%), yield (79.1%), as well as lowest release rate (11.5%, after 25 days of storage). Moreover, different kinetic models were applied to fit the release process of these three kinds of microcapsules: CEO-SWSM, CEO-PM, and CEO-UM had the uppermost R-squared value in the Higuchi model, the zero-order model, and the first-level model, respectively. Over all, this work put forward a novel perspective for the improved encapsulation effect of perishable core materials (e.g., essential oil) for the food industry.

Maritime surveillance videos provide crucial on-spot kinematic traffic information (traffic volume, ship speeds, headings, etc.) for varied traffic participants (maritime regulation departments, ship crew, ship owners, etc.) which greatly benefits automated maritime situational awareness and maritime safety improvement. Conventional models heavily rely on visual ship features for the purpose of tracking ships from maritime image sequences which may contain arbitrary tracking oscillations. To address this issue, we propose an ensemble ship tracking framework with a multi-view learning algorithm and wavelet filter model. First, the proposed model samples ship candidates with a particle filter following the sequential importance sampling rule. Second, we propose a multi-view learning algorithm to obtain raw ship tracking results in two steps: extracting a group of distinct ship contour relevant features (i.e., Laplacian of Gaussian, local binary pattern, Gabor filter, histogram of oriented gradient, and canny descriptors) and learning high-level intrinsic ship features by jointly exploiting underlying relationships shared by each type of ship contour features. Third, with the help of the wavelet filter, we performed a data quality control procedure to identify abnormal oscillations in the ship positions which were further corrected to generate the final ship tracking results. We demonstrate the proposed ship tracker’s performance on typical maritime traffic scenarios through four maritime surveillance videos.

Using the ERA-Interim total column ozone data, the spatial distributions of the long-term mean of the global total ozone in summer are analyzed. The results demonstrate that there are three midlatitude ozone “valleys” on earth—they are centered over the Tibetan Plateau (TIP), the Rocky Mountains (ROM), and the Southwest Pacific (SWP), respectively. The interdecadal variations of the three ozone valleys are positively modulated by the solar radiation, and the TIP ozone’s correlation with the solar radiation gets maximized with a two-year lag. The interdecadal variation of the SWP ozone valley has a significantly negative relationship with the Pacific Decadal Oscillation (PDO) and the South Pacific quadrupole (SPQ). Warm sea surface temperature anomalies (SSTAs) associated with the SPQ strengthen the vertical ascending motion, which dilutes the high concentration ozone at high altitudes. The interdecadal variation of the ROM ozone valley is positively correlated with the PDO, leading by three years. The ROM ozone content is also modulated by SSTAs in the Indian Ocean basin (IOB) by the circumglobal teleconnection (CGT). The observed regional SSTAs can exert a significant impact on the regional and even global circulation, via which the ozone content in midlatitudes also varies.

The graphene nanosheets-based epoxy resin coating (0, 0.1, 0.4 and 0.7 wt %) was prepared by a situ-synthesis method. The effect of polyvinylpyrrolidone/reduced graphene oxide (PVP-rGO) on mechanical and thermal properties of epoxy resin coating was investigated using nanoindentation technique and thermogravimetric analysis, respectively. A significant enhancement (ca. 213% and 73 °C) in the Young modulus and thermal stability of epoxy resin coating was obtained at a loading of 0.7 wt %, respectively. Furthermore, the erosion resistance of graphene nanosheets-based epoxy resin coating was investigated by electrochemical measurement. The results showed also that the Rrcco (ca. 0.3 mm/year) of graphene nanosheets-based epoxy resin coating was far lower than neat epoxy resin (1.3 mm/year). Thus, this approach provides a novel route for improving erosion resistance and mechanical-thermal stability of polymers coating, which is expected to be used in mechanical-thermal-corrosion coupling environments.

Research Highlights: This study comprehensively revealed the carbon sequestration characteristics of secondary forests in the central Loess Plateau during vegetation succession. Background and Objectives: The secondary succession of Loess Plateau forests is of great significance in global climate change, but their carbon storage dynamics are poorly understood. The study objectives were to clarify the pattern of changes and contribution level of carbon stocks in various components of ecosystem during succession. Materials and Methods: We selected 18 plots for Pinus tabuliformis Carr. forest at the early stage of succession, 19 for pine-broadleaved mixed forest at the middle stage, and 12 for Quercus-broadleaved mixed forest at the climax stage to determine the tree, shrub, herb, fine root, litter, coarse wood debris (CWD), and soil carbon stocks. Results: Ecosystem carbon stocks increased from 160.73 to 231.14 Mg·ha−1 with the succession stages. Vegetation (including tree, shrub and herb) and soil were the two largest carbon pools, and carbon was mainly sequestrated in tree biomass and shallow soil (0–50 cm). In the early stage, soil contributed more carbon stocks to the ecosystem than vegetation, but with succession, the soil contribution decreased while vegetation contribution increased, finally reaching a balance (46.78% each) at the climax stage. Fine root, litter, and CWD contributed little (average 6.59%) to ecosystem carbon stocks and were mainly involved in the turnover of vegetation biomass to soil carbon. Conclusions: Our results provide direct evidence for carbon sequestration of secondary forests on the Loess Plateau. The dynamic results of carbon storage provide an important basis for forest restoration management under climate change.

In this paper, a three-dimensional (3D) finite element model was established by ABAQUS software to simulate the welding temperature field of a Ti-6Al-4V alloy under different welding currents based on a Gaussian heat source model. The model uses thermo-mechanical coupling analysis and takes into account the effects of convection and radiation on all weld surfaces. The microstructure evolution of the molten pool was calculated using the macro-micro coupling cellular automaton-finite different (CA-FD) method. It was found that with the increase of the welding current, the temperature in the central region of the moving heat source was improved and the weld bead became wider. Then, the dendritic morphology and solute concentration of the columnar to equiaxed transition (CET) in the weld molten pool was investigated. It is shown that fine equiaxed crystals formed around the columnar crystals tips during solidification. The coarse columnar crystals are produced with priority in the molten pool and their growth direction is in line with the direction of the negative temperature gradient. The effectiveness of the model was verified by gas tungsten arc welding experiments.

Drought causes osmotic stress and rapidly triggers abscisic acid (ABA) accumulation in plants. The roles of various ABA receptors in drought tolerance and molecular mechanisms regulating ABA receptor stability needs to be elucidated. Here, we report that Arabidopsis plants overexpressing PYL9, one of the 14 pyrabactin resistance (PYR)/pyrabactin resistance-like (PYL)/regulatory component of ABA receptors (RCAR) family ABA receptors, gained drought tolerance trait. Osmotic stress induced accumulation of the PYL9 protein, which was regulated by the 26S proteasome. PYL9 interacted with two highly homologous plant U-box E3 ubiquitin ligases PUB22 and PUB23. In the cell-free degradation assay, the degradation of GST-PYL9 was accelerated in protein extract from plants overexpressing PUB22 but slowed down in protein extract from the pub22 pub23 double mutant. The in vivo decay of Myc-PYL9 was significantly reduced in the pub22 pub23 double mutant as compared with the wild-type. Additionally, PUB22 also interacted with other ABA receptors such as PYL5, PYL7 and PYL8. Considering the improved drought tolerance in the pub22 pub23 double mutant in previous studies, our results suggest that PUB22 and PUB23 negatively regulate drought tolerance in part by facilitating ABA receptors degradation.

Most marine bacteria can produce exopolysaccharides (EPS). However, very few structures of EPS produced by marine bacteria have been determined. The characterization of EPS structure is important for the elucidation of their biological functions and ecological roles. In this study, the structure of EPS produced by a marine bacterium, Alteromonas sp. JL2810, was characterized, and the biosorption of the EPS for heavy metals Cu2+, Ni2+, and Cr6+ was also investigated. Nuclear magnetic resonance (NMR) analysis indicated that the JL2810 EPS have a novel structure consisting of the repeating unit of [-3)-α-Rhap-(1→3)-α-Manp-(1→4)-α-3OAc-GalAp-(1→]. The biosorption of the EPS for heavy metals was affected by a medium pH; the maximum biosorption capacities for Cu2+ and Ni2+ were 140.8 ± 8.2 mg/g and 226.3 ± 3.3 mg/g at pH 5.0; however, for Cr6+ it was 215.2 ± 5.1 mg/g at pH 5.5. Infrared spectrometry analysis demonstrated that the groups of O-H, C=O, and C-O-C were the main function groups for the adsorption of JL2810 EPS with the heavy metals. The adsorption equilibrium of JL2810 EPS for Ni2+ was further analyzed, and the equilibrium data could be better represented by the Langmuir isotherm model. The novel EPS could be potentially used in industrial applications as a novel bio-resource for the removal of heavy metals.

One common hypothesis is that wind can affect concentrations of nutrients (i.e., nitrogen and phosphorus) and chlorophyll-a (Chl-a) in shallow lakes. However, the tests of this hypothesis have yet to be conclusive in existing literature. The objective of this study was to use long-term data to examine how wind direction and wind speed affect the spatiotemporal variations of total nitrogen (TN), total phosphorus (TP) and Chl-a in Lake Tai, a typical shallow lake located in east China. The results indicated that the concentrations of nutrients and Chl-a tended to decrease from the northwest to the southeast of Lake Tai, with the highest concentrations in the two leeward bays (namely Meiliang Bay and Zhushan Bay) in the northwestern part of the lake. In addition to possible artificial reasons (e.g., wastewater discharge), the prevalent southeastward winds in warm seasons (i.e., spring and summer) and northwestward winds in cool seasons (i.e., fall and winter) might be the major natural factor for such a northwest-southeast decreasing spatial pattern. For the lake as a whole, the concentrations of TN, TP and Chl-a were highest for a wind speed between 2.1 and 3.2 m·s−1, which can be attributed to the idea that the wind-induced drifting and mixing effects might be dominant in the bays while the wind-induced drifting and resuspension effects could be more important in the other parts of the lake. Given that the water depth of the bays was relatively larger than that of the other parts, the drifting and mixing effects were likely dominant in the bays, as indicated by the negative relationships between the ratios of wind speed to lake depth, which can be a surrogate for the vertical distribution of wind-induced shear stress and the TN, TP and Chl-a concentration. Moreover, the decreasing temporal trend of wind speed in combination with the ongoing anthropogenic activities will likely increase the challenge for dealing with the eutrophication problem of Lake Tai.

Polydimethylsiloxane (PDMS) membranes have been widely used in the microfluidic community to achieve various functions such as control, sensing, filter, etc. In this paper, an experimental process was proposed to directly characterize the deformation of the on-chip PDMS membrane at large deformation based on the image processing method. High precision pressures were applied on the surface of the PDMS membrane with fixed edges and a series deformation of the PDMS membrane were captured by the imaging system. The Chan and Vese (CV) level set method was applied to segment the images of the deformed membrane. The volumes wrapped by the deformed membranes were obtained, and pressure-volumes relationships of the PDMS membranes with different geometry parameters were also calculated. Then the membrane capacitance can be derived by differentiating the curve of pressure-volumes. In addition, the theoretical estimation of the capacitance of the PDMS membrane at large deformation was also obtained through finite element simulation (FEM), which was in good agreement with the experimental results. These results are expected to be significant for designing and on-chip measuring of such PDMS membrane based microfluidic components in our future work.