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The reliable operation of scroll compressors is crucial for the efficiency of rotating machinery and refrigeration systems. To address the need for efficient and accurate fault diagnosis in scroll compressor technology under varying operating states, diverse failure modes, and different operating conditions, a multi-branch convolutional neural network fault diagnosis method (SSG-Net) has been developed. This method is based on the Swin Transformer, the Global Attention Mechanism (GAM), and the ResNet architecture. Initially, the one-dimensional time-series signal is converted into a two-dimensional image using the Short-Time Fourier Transform, thereby enriching the feature set for deep learning analysis. Subsequently, the method integrates the window attention mechanism of the Swin Transformer, the 2D convolution of GAM attention, and the shallow ResNet’s two-dimensional convolution feature extraction branch network. This integration further optimizes the feature extraction process, enhancing the accuracy of fault feature recognition and sensitivity to data variability. Consequently, by combining the global and local features extracted from these three branch networks, the model significantly improves feature representation capability and robustness. Finally, experimental results on scroll compressor datasets and the CWRU dataset demonstrate diagnostic accuracies of 97.44% and 99.78%, respectively. These results surpass existing comparative models and confirm the model’s superior recognition precision and rapid convergence capabilities in complex fault environments.

Jujube is a plant of the genus Ziziphus in the family Rhamnaceae; its fruit has high nutritional value, and it is rich in polyphenols, flavonoids, and other secondary metabolites. The color of its peel is an important indicator for evaluating the appearance of the fruit. However, the mechanism of the difference in color presentation between the seedling offspring of the ‘Red Fruit’ (TLHH) and the ‘Green Fruit’ (TLHL) of the fresh jujube cultivar ‘Tailihong’ is not clear. Therefore, this study used targeted metabolomics techniques to accurately and quantitatively analyze the metabolic pathways of carotenoid and anthocyanin metabolites during the ripening process of two color-presenting types of jujube fruits. Through the analysis of the dynamic changes in the pigment content of the jujube peel, it was found that 30 DAP (days after pollination), 80 DAP, and 110 DAP were the key periods for the development of the color of the peel of ‘TLHL’ and ‘TLHH’ jujube and that the substances responsible for the main differences were chlorophyll, carotenoids, and anthocyanins. Furthermore, we used an LC-MS/MS metabolic analysis to compare the differences in the carotenoids and anthocyanin metabolites between the two color-presenting types of jujube peels at the key periods of 30 DAP, 80 DAP, and 110 DAP. We detected 32 carotene metabolites and 75 anthocyanin metabolites, respectively, among which lutein had the highest content of carotenoids; it reached the maximum value (93.05 µg/g) and was higher than that of ‘TLHH’ (74.14 µg/g) at 30 DAP of ‘TLHL’. Both showed a decreasing trend with fruit ripening. The anthocyanin with the highest content was cyanidin-3-O-(tartaryl)rhamnoside-5-O-glucoside, which reached the maximum value (258.32 µg/g) at 30 DAP of ‘TLHH’ and was 51.6 times that of ‘TLHL’; similarly, both showed a decreasing trend with fruit ripening. These results elucidate the main metabolites of carotenoids and anthocyanins in the two types of jujube peel and their accumulation characteristics, suggesting that the key metabolites of the difference in color between ‘TLHL’ and ‘TLHH’ jujube fruits were lutein and cyanidin-3-O-(tartaryl)rhamnoside-5-O-glucoside, increasing the understanding of the color mechanism of jujube peel and providing a reference for targeted genetic breeding of jujube peel color.

The exploration of continental shale oil in China has made a breakthrough in many basins, but the pure shale type has only been found in the Qingshankou Formation, Gulong Sag, Songliao Basin, and the evaluation of shale oil occurrence and sweet spot faces great challenges. Using information about the total organic carbon (TOC), Rock-Eval pyrolysis, vitrinite reflectance (Ro), kerogen elemental composition, carbon isotopes, gas chromatography (GC), bitumen extraction, and component separation, this paper systematically studies the organic geochemical characteristics and shale oil occurrence at the Qingshankou Formation. The G1 well, which was cored through the entire section of the Qingshankou Formation in the Gulong Sag, was the object of this study. On this basis, the favorable sweet spots for shale oil exploration are predicted. It is concluded that the shale of the Qingshankou Formation has high organic heterogeneity in terms of organic matter features. The TOC content of the source rocks in the Qingshankou Formation is enhanced with the increase in the burial depth, and the corresponding organic matter types gradually changed from Ⅱ2 and Ⅱ1 types to the Ⅰ type. The distribution of Ro ranges from 1.09% to 1.67%, and it is the mature to high-mature evolution stage that generates a large amount of normal crude oil and gas condensate. The high-quality source rocks of good to excellent grade are mainly distributed in the Qing 1 member and the lower part of the Qing 2 member. After the recovery of light hydrocarbons and the correction of pyrolytic heavy soluble hydrocarbons, it is concluded that the occurrence state of shale oil in the Qingshankou Formation is mainly the free-state form, with an average value of 6.9 mg/g, and there is four times as much free oil as adsorbed oil. The oil saturation index (OSI), mobile hydrocarbon content, Ro, and TOC were selected to establish the geochemical evaluation criteria for shale oil sweet spots in the Qingshankou Formation. The evaluation results show that interval 3 and interval 5 of the Qingshankou Formation in the G1 well are the most favorable sections for shale oil exploration.

As a potential crop in saline-alkali land, the growth of switchgrass could also be threatened by salt stress. Promoting the growth of switchgrass under salt stress by humic acid has great significance in the utilization of saline-alkali land. In this study, a pot experiment was arranged to investigate the responses of photosynthetic and physicochemical characteristics of switchgrass to HA under salt stress. Results showed that humic acid increased the photosynthetic function of switchgrass and enhanced plant height by 41.1% and dry weight by 26.9% under salt stress. Correlation analysis showed that the membrane aquaporin gene PvPIP1, malondialdehyde, ascorbate peroxidase, abscisic acid, polyamine, and jasmonic acid were important factors affecting the photosynthetic function of switchgrass in this study. Meanwhile, HA reduced the content of malondialdehyde, indicating the alleviation of the membrane damage caused by salt stress. On the other hand, HA upregulated the relative expression of the PvPIP1 gene and activated ascorbate peroxidase, abscisic acid, polyamine, and jasmonic acid in switchgrass to resist salt stress. These improved the membrane stability and promoted the photosynthetic activity of switchgrass to enhance the plant’s tolerance against salt stress and growth. Results from this study are helpful to the efficient growing of switchgrass and the sustainable development of saline-alkali land.

As a predominant ecosystem-providing area and distinctive landscape in arid regions, an oasis plays an important role in maintaining land stability, human production, and daily activities. Studying the dynamics of oasis and its driving factors is vital to supporting arid regions’ sustainable development. As a typical mountain–desert–oasis landscape, the Turpan–Hami (Tuha) Basin, located in Xinjiang, China, includes complex interactions among different land types. For this study, we revealed the spatio-temporal patterns and transition processes of the oasis using a complex network method between 1990 and 2020 in the Tuha Basin. In the oasis transition network, the degree value, betweenness centrality, and average path length were calculated to express the transition relationship, key oasis type, and oasis structural stability, respectively. Six factors related to climate change and human actives were selected to investigate the driving forces behind oasis transitions, including the average temperature and precipitation in the growing season, the total power of agricultural machinery (TAMP), the production of raw coal (PRC), the total output value of the plantation industry (TPI), and the population (Pop). Our results show that the oasis area of the Tuha Basin, including the natural oasis and artificial oasis, all grew from 1990 to 2020, with the natural oasis expanding more than the artificial oasis. The transitions between oasis types became more frequent as the area of oasis land types increased throughout the study period. Grassland acted as the most important oasis type in the network, with the highest betweenness centrality, but its importance declined due to the increasing complexity of the oasis transition network from 1990 to 2020. The transitions between oasis types became simpler, and the oasis structural stability decreased. Through driving force analysis, the oasis changes showed a positive correlation with the temperature (p-value < 0.05, r = 0.88), and urbanization and industrialization factors prompted transitions to built-up areas and cropland from grassland and shrubland. In summary, our results suggest that to create a harmonious symbiotic relationship between the natural environment in dryland and human activities, preventing grassland degradation and excessive reclamation of land cover is an available way. Meanwhile, the protection of shrubland and water resources is also important. This study provided reference and theory support for promoting the sustainable development of oases.

Over the past several years, Shenzhen’s air quality has significantly improved despite increased ground-level ozone (O3) and the challenges in reducing fine particulate matter (PM2.5). We investigated concentration trends, concurrent pollution features, and long-term exposure health risks to enhance our understanding of the characteristics of O3 and PM2.5 pollution. From 2016 to 2022, there was a decrease in PM2.5 levels, but an increase in O3. Additionally, the premature mortality attributed to long-term air pollution exposure decreased by 20.1%. High-O3-and-PM2.5 days were defined as those when the MDA8 O3 ≥ 160 μg m–3 and PM2.5 ≥ 35 μg m–3. Significantly higher levels of O3, PM2.5, nitrogen dioxide (NO2), OX (OX = O3 + NO2), and sulfur dioxide (SO2) were observed on high-O3-and-PM2.5 days. Vehicle emissions were identified as the primary anthropogenic sources of volatile organic compounds (VOCs), contributing the most to VOCs (58.4 ± 1.3%), O3 formation (45.3 ± 0.6%), and PM2.5 formation (46.6 ± 0.4%). Cities in Guangdong Province around Shenzhen were identified as major potential source regions of O3 and PM2.5 during high-O3-and-PM2.5 days. These findings will be valuable in developing simultaneous pollution control strategies for PM2.5 and O3 in Shenzhen.

Auxin-responsive factors (ARFs) are an important class of transcription factors and are an important component of auxin signaling. This study conducted a genome-wide analysis of the ARF gene family in ginseng and presented its findings. Fifty-three ARF genes specific to ginseng (PgARF) were discovered after studying the ginseng genome. The coding sequence (CDS) has a length of 1092–4098 base pairs and codes for a protein sequence of 363–1565 amino acids. Among them, PgARF32 has the least number of exons (2), and PgARF16 has the most exons (18). These genes were then distributed into six subgroups based on the results obtained from phylogenetic analysis. In each subgroup, the majority of the PgARF genes displayed comparable intron/exon structures. PgARF genes are unevenly distributed on 20 chromosomes. Most PgARFs have B3 DNA binding, Auxin_resp, and PB1 domains. The PgARF promoter region contains various functional domains such as plant hormones, light signals, and developmental functions. Segmental duplications contribute to the expansion of the ARF gene family in ginseng, and the genes have undergone purifying selection during evolution. Transcriptomic results showed that some PgARFs had different expression patterns in different parts of ginseng; most PgARFs were affected by exogenous hormones, and a few PgARFs responded to environmental stress. It is suggested that PgARF is involved in the development of ginseng by regulating hormone-mediated genes. PgARF14, PgARF42, and PgARF53 are all situated in the nucleus, and both PgARR14 and PgARF53 noticeably enhance the growth length of roots in Arabidopsis. Our findings offer a theoretical and practical foundation for exploring PgARFs’ role in the growth of ginseng roots.

There have been numerous studies on the effects of salt stress on jujube fruit; however, only a few studies have reported the changes in fruit quality, particularly sugar content, under conditions of combined salt and alkali stress. Therefore, the present study aimed to investigate the performance of jujube fruits under Saline-Alkali stress and the changes in sugar content in fruits. To achieve this, jujube fruits were treated with varying concentrations of salt and alkali during five developmental periods. The content of relevant sugar components was determined, and metabolomics data were analyzed in combination with relevant quantitative gene data. The results indicated that 100 days after flowering, the surface color of jujube fruit gradually turned red, and the cell structure of the fruit gradually loosened with increasing salt and alkali concentration. The content of sugar components at each stage showed that glucose and fructose primarily accumulate in the early stage of development, while sucrose is the main component in the later stage of development. Metabolomic correlation network maps showed that six differentially accumulated metabolites were closely related to specific genes. Among these metabolites, sucrose was identified as the core metabolite in the metabolic pathway. Quantitative analysis of the related genes revealed that ZjvINV2 and ZjHK2 exhibited prolonged adaptability to stress. Additionally, the expression levels of ZjSS1 and ZjSPS2 under Saline-Alkali stress were consistent with the trend of sucrose content during the same period. In conclusion, the variations in sugar content in jujube fruits during different growth stages and under Saline-Alkali treatment conditions were recorded as reference data, and the primary metabolic substances and related regulatory genes produced in jujube fruits under Saline-Alkali stress were preliminarily identified.

Saline–alkali stress is an important environmental factor affecting the growth and development of plants. Plants affected by saline–alkali stress can mitigate the damage by regulating the content of osmoregulatory substances such as soluble sugars. Elucidating the regulatory mechanism of the changes in sugar fractions in jujube fruits under saline–alkali stress is crucial for the development of the jujube fruit industry in saline areas. In this study, we investigated the effects of saline–alkali stress on the development and sugar contents of jujube fruits by subjecting jujube trees to low- and high-saline–alkali stress treatments. The result showed that low saline–alkali stress increased the content of each sugar component and total sugar, whereas high saline–alkali stress suppressed their contents. In the early developmental stage, the fruit mainly accumulated fructose and glucose, whereas in the late stage, it accumulated mainly sucrose. We screened various genes, namely trehalose 6-phosphate phosphatase gene (LOC107418410), α-amylase gene (LOC107428855), α-glucosidase gene (LOC107418468), sucrose synthase gene (LOC107416188), and β-amylase gene (LOC107430415, LOC107406235), all of which were highly correlated with sucrose content in saline–alkali stress, indicating that the starch and sucrose metabolic pathways of jujube fruit are the key pathways regulating sugar accumulation in response to saline–alkali stress. To summarize, this study provides a system-level perspective on the dynamic transcriptional regulation of jujube fruits under saline–alkali stress. Additionally, the study preliminarily screened key differentially expressed genes that affect sugar accumulation in response to saline–alkali stress, providing a theoretical basis for the scientific regulation of jujube fruit quality.

The electronic mechanical brake (EMB) is considered an ideal actuator for brake-by-wire systems. We applied the negative radius roller cam mechanism as the clamping mechanism of the EMB, solving the problem of large size, poor load-bearing capacity, and the inefficiency of the existing EMBs. When designing a cam as a clamping transmission mechanism, it is necessary to take the pressure angle, contact stress, motion law, etc., as goals and constraints. Existing design methods cannot easily solve this problem. Therefore, we propose a new analysis method from the cam profile and combine it with an improved particle swarm optimization (PSO) algorithm to design the cam profiles. This method can handle various complex goals and constraints of the EMB and obtain the required negative radius roller cam profile. Finally, the logical consistency of the profile-based analysis method was verified, and the EMB design objectives and accuracy were compared using ADAMS. Under the same conditions, the result showed that the optimized cam mechanism requires only 40.52% motor power and only 65.65% clearance elimination time compared to the EMB with the lead screw mechanism.

The growth of mangroves is inhibited due to environmental degradation, and changes in the growing health of mangrove forests cause changes in internal physicochemical parameters. The canopy chlorophyll content is an important indicator to monitor the health status of mangroves. We study the effective inversion data sources and methods of mangrove health indicator parameters to monitor the health of mangrove ecosystems in typical areas of Beibu Gulf, Guangxi. In this study, we evaluated the capability of UAV, GF-6 data, and machine learning regression algorithms in estimating mangrove species-scale canopy chlorophyll content (CCC). Effective measures for mangrove pest and disease pressure, Sporobolus alterniflorus invasion, and anthropogenic risk are also explored, which are important for mangrove conservation and restoration. (1) We obtained several feature variables by constructing a combined vegetation index, and the most sensitive band of mangrove CCC was selected by the characteristic variable evaluation, and the CCC model at the mangrove species-scale was evaluated and validated. Through variable preferences, the feature variables with the highest contribution of Avicennia marina, Aegiceras corniculatum, Kandelia candel, and a collection of three categories of species in the UAV data were indices of RI35, MDATT413, RI35, and NDI35. (2) Random Forest, Gradient Boosting Regression Tree, and Extreme Gradient Boosting were evaluated using the root-mean-square error and coefficient of determination accuracy metrics. Extreme Gradient Boosting regression algorithms were evaluated for accuracy. In both UAV data and GF-6, RF achieved optimal results in inverse mangrove Aegiceras corniculatum species CCC, with higher stability and robustness in machine learning regressors. (3) Due to the sparse distribution of Kandelia candel in the study area and the low spatial resolution of the images, there is an increased possibility that individual image elements contain environmental noise, such as soil. Therefore, the level of CCC can effectively reflect the health status of mangroves and further reflect the increased possibility of the study area being exposed to risks, such as degradation. The establishment of the current protected areas and restoration of degraded ecosystems are effective measures to cope with the risks of mangrove pest and disease stress, invasion of Sporobolus alterniflorus, and anthropogenic activities, which are important for the protection and restoration of mangroves. This study provides an important data reference and risk warning for mangrove restoration and conservation.

Nature reserves are special habitats established for representative plant and animal ecosystems, and it is important to strengthen the monitoring and protection of nature reserves for ecological environmental protection. In this paper, 23 typical nature reserves of different levels and types on Hainan Island were selected as the study area. The InVEST model and LandTrendr algorithm were applied in habitat quality assessment and to anthropogenic disturbances of the study area from 2000 to 2021, respectively. Finally, an assessment mode was established, coupling the habitat quality assessment and anthropogenic disturbances, to analyze the spatial and temporal conservation effectiveness of the 23 nature reserves. The results indicate that the 23 nature reserves had good overall conservation effectiveness; 21 had an excellent effectiveness rating, and 2 had a good effectiveness rating between 2000 and 2021. Three of the nature reserves, namely, Dazhoudao, Dongzhaigang and Bangxi, have become significantly more effective. Provincial nature reserves are less effective than national nature reserves in terms of conservation, and are a key concern for follow-up. The conservation effectiveness of the four provincial nature reserves—Nanwan, Qinglangang, Dongfangheilianpilu and Qilinlai—is low, and there has been no significant trend of improvement over the past 21 years. The spatial and temporal changes in the conservation effectiveness of 23 nature reserves on Hainan Island over 21 years can provide scientific data support for the development of nature reserves and departmental supervision in Hainan Province.

Due to rising living standards, it is important to improve wheat’s quality traits by adjusting its storage protein genes. The introduction or locus deletion of high molecular weight subunits could provide new options for improving wheat quality and food safety. In this study, digenic and trigenic wheat lines were identified, in which the 1Dx5+1Dy10 subunit, and NGli-D2 and Sec-1s genes were successfully polymerized to determine the role of gene pyramiding in wheat quality. In addition, the effects of ω-rye alkaloids during 1BL/1RS translocation on quality were eliminated by introducing and utilizing 1Dx5+1Dy10 subunits through gene pyramiding. Additionally, the content of alcohol-soluble proteins was reduced, the Glu/Gli ratio was increased and high-quality wheat lines were obtained. The sedimentation values and mixograph parameters of the gene pyramids under different genetic backgrounds were significantly increased. Among all the pyramids, the trigenic lines in Zhengmai 7698, which was the genetic background, had the highest sedimentation value. The mixograph parameters of the midline peak time (MPT), midline peak value (MPV), midline peak width (MPW), curve tail value (CTV), curve tail width (CTW), midline value at 8 min (MTxV), midline width at 8 min (MTxW) and midline integral at 8 min (MTxI) of the gene pyramids were markedly enhanced, especially in the trigenic lines. Therefore, the pyramiding processes of the 1Dx5+1Dy10, Sec-1S and NGli-D2 genes improved dough elasticity. The overall protein composition of the modified gene pyramids was better than that of the wild type. The Glu/Gli ratios of the type I digenic line and trigenic lines containing the NGli-D2 locus were higher than that of the type II digenic line without the NGli-D2 locus. The trigenic lines with Hengguan 35 as the genetic background had the highest Glu/Gli ratio among the specimens. The unextractable polymeric protein (UPP%) and Glu/Gli ratios of the type II digenic line and trigenic lines were significantly higher than those of the wild type. The UPP% of the type II digenic line was higher than that of the trigenic lines, while the Glu/Gli ratio was slightly lower than that of the trigenic lines. In addition, the celiac disease (CD) epitopes’ level of the gene pyramids significantly decreased. The strategy and information reported in this study could be very useful for improving wheat processing quality and reducing wheat CD epitopes.

Patients diagnosed with thrombotic thrombocytopenic purpura (TTP) typically present with microangiopathic hemolytic anemia (MAHA) and thrombocytopenia; these two clinical manifestations were often believed to be essential indicators of TTP. However, such indicators are not always present in every case. Here, we present a patient affected by TTP but showing no distinctive schistocytes on blood smear review. TTP was diagnosed through a critically low level of a disintegrin and metalloproteinase with thrombospondin type 1 motif, member 13 (ADAMTS13) activity. Awareness of such an atypical presentation of TTP is essential for timely treatment to prevent serious and even fatal outcomes for patients.

The excessive activation of microglia cell induced by adolescent intermittent ethanol (AIE) leads to neuroinflammation in the hippocampus. The endocannabinoid system plays a key role in the modulation of microglia activation. Accumulating evidence suggests that regular exercise improves learning and memory deficits in AIE models. The purpose of this study was to explore the effects of treadmill exercise intervention on the cognitive performance, activation of microglia cells and the expression of monoacylglycerol lipase (MAGL), cannabinoid receptor type 1 (CB1R) and cannabinoid receptor type 2 (CB2R) in the hippocampus of AIE rats. Here, we show that AIE rats exhibited cognitive impairments, whereas the treadmill exercise improves the cognitive performance in AIE rats. In order to explore the possible mechanisms for the exercise-induced attenuation of cognitive disorder, we examined the neuroinflammation in the hippocampus. We found that treadmill exercise led to the decrease in the level of proinflammatory cytokines (IL-1β, IL-6 and TNF-α) and the increase in the level of anti-inflammatory cytokine (IL-10). In addition, we found that treadmill exercise reduced the excessive activation of the microglia cell in the hippocampus of AIE rats. Finally, we found that AIE led to a decrease in the expression of CB1R and CB2R in the hippocampus; however, the treadmill exercise further decreased the expression of CB2R in the hippocampus of AIE rats. Our results suggest that treadmill exercise attenuates AIE-induced neuroinflammation and the excessive activation of hippocampus microglial cells, which may contribute to the exercise-induced improvement of cognitive performance in AIE rats.

Frequent forest fires cause air pollution, threaten biodiversity and spoil forest ecosystems. Forest fire vulnerability assessment is a potential way to improve the ability of forests to resist climate disasters and help formulate appropriate forest management countermeasures. Here, we developed an automated hybrid machine learning algorithm by selecting the optimal model from 24 models to map potential forest fire vulnerability over China during the period 2001–2020. The results showed forest aboveground biomass (AGB) had a vulnerability of 26%, indicating that approximately 2.32 Gt C/year of forest AGB could be affected by fire disturbances. The spatiotemporal patterns of forest fire vulnerability were dominated by both forest characteristics and climate conditions. Hotspot regions for vulnerability were mainly located in arid areas in western China, mountainous areas in southwestern China, and edges of vegetation zones. The overall forest fire vulnerability across China was insignificant. The forest fire vulnerability of boreal and temperate coniferous forests and mixed forests showed obviously decreasing trends, and cultivated forests showed an increasing trend. The results of this study are expected to provide important support for the forest ecosystem management in China.

Bus bunching is a common phenomenon caused by irregular bus headway, which increases the passenger waiting time, makes the passenger capacity uneven, and severely reduces the reliability of bus service. This paper clarified the process of bus bunching formation, analyzed the variation characteristics of bus bunching in a single day, in different types of periods, and at different bus stops, then concluded twelve potential factors. A hybrid model integrating a genetic algorithm with elitist preservation strategy (eGA) and decision tree (DT) was proposed. The eGA part constructs the model framework and transforms the factor identification into a problem of selecting the fittest individual from the population, while the DT part evaluates the fitness. Model verification and comparison were conducted based on real automatic vehicle location (AVL) data in Shenzhen, China. The results showed that the proposed eGA–DT model outperformed other frequently used single DT and extra tree (ET) models with at least a 20% reduction in MAE under different bus routes, periods, and bus stops. Six factors, including the sequence of the bus stop, the headway and dwell time at the previous bus stop, the travel time between bus stops, etc., were identified to have a significant effect on bus bunching, which is of great value for feature selection to improve the accuracy and efficiency of bus bunching prediction and real-time bus dispatching.

It is fundamental to acquire accurate point cloud information on rock discontinuities efficiently and comprehensively when evaluating the stability of rock masses. Taking a high and steep cliff as an example, we combined 3D laser scanning and UAV photogrammetry technology to collect rock data, and proposed an intelligent identification method for rock discontinuities based on the multi-source fusion of point clouds. First, the 3D-laser-collected point cloud data were used as the basis to fuse with the UAV-photogrammetry-collected data, and the unified coordinate system and improved ICP algorithm were used to obtain the complete 3D point cloud in the study area. Secondly, we used neighborhood information entropy to achieve adaptive neighborhood-scale selection and to obtain the optimal neighborhood radius for the KNN search, to effectively calculate the point cloud normal vector and rock mass orientation information. Finally, the KDE algorithm and DBSCAN algorithm were combined for rock discontinuity clustering to achieve intelligent identification and information extraction of the rock structural plane. The clustering results were imported into the DSE program developed based on Matlab to calculate the discontinuity spacing and continuity of the rock mass structure, and to efficiently obtain the parameters of rock mass occurrence. The research results showed that this method can effectively solve the problem of incomplete-data-acquisition ground 3D laser scanning in complex geological conditions, and UAV photogrammetry prone to blurred images in depressed areas. When the extraction results were compared with the field-measured rock occurrence, the average dip angle error was about 2°, the average dip direction error was 1°, and the recognition results met the accuracy requirements. The research results provide a feasible scheme for the identification and extraction of discontinuities of high and steep rock masses.

In order to reduce the impact of global warming, forestry carbon sink trading is an effective approach to achieving carbon neutrality, while carbon storage estimation plays an important role as the basis of the whole carbon sink trading. Therefore, an accurate estimation of carbon storage is conducive to the sustainable development of carbon sink trading. In this paper, we use laser SLAM technology to model an artificial forest in three dimensions, extract the tree parameters by the point cloud processing software, and calculate the carbon storage according to the allometric growth equation of the tree species. The experimental results show that the loop path is the best among the three-path planning of ZEB-HORIZON scanner data acquisition. For large-scale plantations, the fusion data acquisition of linear and loop paths by Livox Mid-40 and ZEB-HORIZON LIDAR can be adopted with a highly precise and a complete 3D point cloud obtained. The Lidar360 software is used for single wood segmentation and parameter extraction, and the manual measurement is taken as the quasi-true value. After the measurement accuracy analysis, the carbon storage estimation is met. Using the volume source biomass method in the sample plot inventory method, the carbon storages of camphor and cypress in the experimental area were estimated through the allometric growth equation of camphor and cypress and the international conversion rate.

With the rapid development of the geographic information service industry, point cloud data are widely used in various fields, such as architecture, planning, cultural relics protection, mining engineering, etc. Despite that there are many approaches to collecting point clouds, we are facing the problem of point cloud holes caused by the inability of a 3D laser scanner to collect data completely in the narrow space of the mine access shaft. Thus, this paper uses RGB-D cameras to collect data and reconstruct the hole in the point cloud. We used a 3D laser scanner and RGB-D depth camera to collect the 3D point cloud data of the access shaft roadway. The maximum error was 2.617 cm and the minimum error was 0.031 cm by measuring the distance between the feature points, which satisfied the visualization repair of the missing parts of the 3D laser scanner data collection. We used the FPTH + ICP algorithm, ISS + ICP algorithm, SVD + ICP algorithm, and 3D-NDT algorithm to perform registration and fusion of the processed 3D point cloud and the original point cloud and finally repaired the hole. The study results show that the ISS + ICP registration algorithm had the most matching points and the lowest RMSE value of 13.8524 mm. In addition, in the closed and narrow roadway, the RGB-D camera was light and easy to operate and the point data acquired by it had relatively high precision. The three-dimensional point cloud of the repaired access shaft roadway has a good fit and can meet the repair requirements.

The bioactive lipid lysophosphatidylcholine (LPC), a major phospholipid component of oxidized low-density lipoprotein (Ox-LDL), originates from the cleavage of phosphatidylcholine by phospholipase A2 (PLA2) and is catabolized to other substances by different enzymatic pathways. LPC exerts pleiotropic effects mediated by its receptors, G protein-coupled signaling receptors, Toll-like receptors, and ion channels to activate several second messengers. Lysophosphatidylcholine (LPC) is increasingly considered a key marker/factor positively in pathological states, especially inflammation and atherosclerosis development. Current studies have indicated that the injury of nervous tissues promotes oxidative stress and lipid peroxidation, as well as excessive accumulation of LPC, enhancing the membrane hyperexcitability to induce chronic pain, which may be recognized as one of the hallmarks of chronic pain. However, findings from lipidomic studies of LPC have been lacking in the context of chronic pain. In this review, we focus in some detail on LPC sources, biochemical pathways, and the signal-transduction system. Moreover, we outline the detection methods of LPC for accurate analysis of each individual LPC species and reveal the pathophysiological implication of LPC in chronic pain, which makes it an interesting target for biomarkers and the development of medicine regarding chronic pain.

LC3-associated phagocytosis (LAP) is a noncanonical autophagy process reported in recent years and is one of the effective mechanisms of host defense against bacterial infection. During LAP, bacteria are recognized by pattern recognition receptors (PRRs), enter the body, and then recruit LC3 onto a single-membrane phagosome to form a LAPosome. LC3 conjugation can promote the fusion of the LAPosomes with lysosomes, resulting in their maturation into phagolysosomes, which can effectively kill the identified pathogens. However, to survive in host cells, bacteria have also evolved strategies to evade killing by LAP. In this review, we summarized the mechanism of LAP in resistance to bacterial infection and the ways in which bacteria escape LAP. We aim to provide new clues for developing novel therapeutic strategies for bacterial infectious diseases.

Neuro-glia antigen 2/chondroitin sulfate proteoglycan 4 (NG2/CSPG4, also called MCSP, HMW-MAA, MSK16, MCSPG, MEL-CSPG, or gp240) is a large cell-surface antigen and an unusual cell membrane integral glycoprotein frequently expressed on undifferentiated precursor cells in multiple solid organ cancers, including cancers of the liver, pancreas, lungs, and kidneys. It is a valuable molecule involved in cancer cell adhesion, invasion, spreading, angiogenesis, complement inhibition, and signaling. Although the biological significance underlying NG2/CSPG4 proteoglycan involvement in cancer progression needs to be better defined, based on the current evidence, NG2/CSPG4+ cells, such as pericytes (PCs, NG2+/CD146+/PDGFR-β+) and cancer stem cells (CSCs), are closely associated with the liver malignancy, hepatocellular carcinoma (HCC), pancreatic malignancy, and pancreatic ductal adenocarcinoma (PDAC) as well as poor prognoses. Importantly, with a unique method, we successfully purified NG2/CSPG4-expressing cells from human HCC and PDAC vasculature tissue blocks (by core needle biopsy). The cells appeared to be spheres that stably expanded in cultures. As such, these cells have the potential to be used as sources of target antigens. Herein, we provide new information on the possibilities of frequently selecting NG2/CSPG4 as a solid organ cancer biomarker or exploiting expressing cells such as CSCs, or the PG/chondroitin sulfate chain of NG2/CSPG4 on the cell membrane as specific antigens for the development of antibody- and vaccine-based immunotherapeutic approaches to treat these cancers.

Sugar, an osmoregulatory substance used by plants to adapt to abiotic stresses such as drought and salinity, is one of the most important indexes of fruit quality. In this study, 0–150 mM saline–alkali solutions (NaCl:NaHCO3 = 3:1) were used to irrigate the roots of 10-year-old “Junzao” fruit trees during the growth period to explore the regulation mechanism of different concentrations of saline–alkali stress on sugar and reactive oxygen metabolism in jujube fruit at maturity. The results showed that under low stress (0~90 mM), the contents of sucrose, glucose, and fructose in the jujube fruit and the activities of sucrose phosphate synthase (SPS), sucrose synthase decomposition direction (SS-I), and sucrose synthase synthesis direction (SS-II) increased with increases in stress concentration, results that were consistent with the relative expression trends of the SPS and SS genes; however, the results were reversed under high concentrations (120 and 150 mM). The soluble acid invertase (S-AI) activity decreased with increases in stress concentration under low stress, and the results were reversed with high stress, which was consistent with the relative expression trends of the ZjcINV3, ZjnINV1, and ZjnINV3. Research regarding the response of antioxidant enzymes in fruits under saline–alkali stress showed that only the differences in peroxidase (POD) activity under saline–alkali stress were consistent with sugar accumulation; the proline (PRO), catalase (CAT) decreased and the malondialdehyde (MDA) superoxide dismutase (SOD) increased with increases in saline–alkali stress. These results indicate that the sugar metabolism and antioxidase jointly promote and regulate sugar accumulation in jujube fruits in a low saline–alkali environment.

Geographically isolated islands are under great stress due to global climate change, as well as the social and environmental issues relating to human activities. It is necessary to monitor and analyze the spatial–temporal changes of the land surface environment in species-rich tropical islands in order to realize the sustainable development and protection of island areas. In this study, we extracted the land cover and coastline information of three tropical islands from 1990 to 2020 based on the Google Earth Engine platform and the Random Forest algorithm. The results showed that: (1) different tropical islands have similar characteristics in terms of land surface environment changes, with the amount of artificial surface and cultivated land increasing, the forest and mangrove areas decreasing, and the amount of artificial coastline increasing; (2) human disturbance plays an important role in changes in the land surface environment. Population growth, immigration policies, food security, and human activities related to achieving economic profits are likely responsible for these land cover changes; and (3) the main factors driving coastline changes include natural processes (topography, ecological ecosystems, sea-level rise, sea waves, and storms) and human activities (sand mining, tourism, port construction, aquaculture expansion, and mangrove deforestation). Understanding these changes will help tropical islands and coastal zones to make suitable policies for land management and respond to climate change and sustainable development challenges.

For intelligence brakes in the electronic pneumatic brake system of commercial vehicles, the pressure change rate is used as the key control parameter and evaluation index. This can improve the brake safety, stability, and ride comfort of the vehicle. The real-time detection of the brake pressure change rate for commercial vehicles is the premise for realizing the accurate control of brake pressure change rate. Based on Poiseuille’s law, an efficient measurement method of brake pressure change rate is proposed for commercial vehicles, and a new measuring device with an isothermal container and laminar flow resistance tube as the core components is designed. Through thermal insulation performance tests, flow resistance tests and measurement accuracy tests, combined with simulations, the effects of structural parameters and copper wire filling density on the performance of the isothermal container are analyzed, and these key parameters are optimized to improve the thermal insulation performance. A tubular laminar flow resistance tube composed of 304 stainless steel capillaries in parallel is designed. The influence mechanism of core parameters such as the number, radius, and length of laminar flow channels on its performance is studied, and the optimal parameter array is selected to optimize its performance. The experimental platform for measuring brake pressure change rate is constructed. By comparing the measurement curve of brake pressure change rate under simulation and experiment, the correctness and effectiveness of the pressure change rate measurement principle and the key components for electronically controlled pneumatic brakes of commercial vehicles are verified to meet engineering requirements.

Forest biomass change monitoring is essential for climate change. Synthetic aperture radar (SAR) and optimal remote sensing (RS) data are two very helpful data sources for forest biomass monitoring and estimation. During the procedure of biomass estimation using RS technique, optimal features selection and estimation models used are two critical steps. This paper therefore focuses on building an operational and robust method of biomass retrieval using optical and SAR RS data. First, random forest (RF) algorithms are used for reducing time-consuming and decreasing computational burden; then, an iterative procedure was embedded in K-nearest neighbor (KNN) algorithms for the best optimal feature selection and combination; last, the best feature combinations and KNN models were applied for forest biomass estimation. Moreover, forest type effects and RS feature source effects were considered. The results showed that feature combination of two optical images and the SAR image showed highest estimation accuracy by using the proposed algorithm (R2 = 0.70 for Forest-1, R2 = 0.72 for Forest-2, and R2 = 0.71 for Forest-3; RMSE = 16.18 Mg/ha for Forest-1, RMSE =17.66 Mg/ha for Forest-2, and RMSE = 18.67 Mg/ha for Forest-3, where Forest-1 is natural pure forests of Yunnan Pines, Forest-2 is natural mixed coniferous forests, and Forest-3 is the combination of Forest-1 and Forest-2). With the comparative analysis of proposed algorithm and different non-parametric algorithms, traditional nonparametric algorithms performed better in Forest-1, but worse in Forest-2 and Forest-3, while the proposed algorithm performed no obvious difference in three forest types and using five feature groups. The results revealed that the proposed algorithm was robust in biomass estimation, with almost no feature source and forest structure dependent for biomass estimation.

Substantial research indicates the effects of urbanization on vegetation cover; however, a view of this scenario from a regional scale is absent. Nowadays, coastal cities have become the new engine for the development of countries in coastal areas. To capture the effects of rapid urbanization on vegetation dynamics, 35 coastal cities along the Maritime Silk Road (MSR) were selected to study the related research using quantitative tools. We calculated spatiotemporal trends of vegetation dynamics along an urban development intensity (UDI) gradient using the MODIS-enhanced vegetation index (EVI) during the period of 2000–2015. We found a significant reduction (p < 0.05) in the EVI in the core area against that in the rural area (ΔEVI) of 14 cities and an insignificant change in vegetation in the peri-urban areas or urban outskirts. EVI decreased significantly along the UDI gradients in 12 coastal cities with a linear pattern and in seven coastal cities with a concave pattern; only Bangkok exhibited a convex pattern. The nonlinear pattern between the EVI and UDI reflected the fact that vegetation dynamics were affected by complicated factors, including climate change and human interventions, over a long period of time. In conclusion, our work provided a scientific reference for the sustainable development of coastal cities along the MSR; further work is necessary to explore the mechanic details of the positive and negative influences of urban factors and related policies on vegetation conditions.

Class III homeodomain-leucine zipper (HD-ZIP III) genes encode plant-specific transcription factors that play pivotal roles in plant growth and development. There is no systematic report on HD-ZIP III members in Brassica plants and their responses to stress are largely unknown. In this study, a total of 10, 9 and 16 HD-ZIP III genes were identified from B. rapa, B. oleracea and B. napus, respectively. The phylogenetic analysis showed that HD-ZIP III proteins were grouped into three clades: PHB/PHV, REV and CNA/HB8. Genes in the same group tended to have similar exon–intron structures. Various phytohormone-responsive elements and stress-responsive elements were detected in the promoter regions of HD-ZIP III genes. Gene expression levels in different tissues, as well as under different stress conditions, were investigated using public transcription profiling data. The HD-ZIP III genes were constitutively expressed among all the tested tissues and were highly accumulated in root and stem. In B. rapa, only one BrREV gene especially responded to heat stress, BrPHB and BrREV members were downregulated upon cold stress and most HD-ZIP III genes exhibited divergent responses to drought stress. In addition, we investigated the genetic variation at known miR165/166 complementary sites of the identified HD-ZIP III genes and found one single nucleotide polymorphism (SNP) in PHB members and two SNPs in REV members, which were further confirmed using Sanger sequencing. Taken together, these results provide information for the genome-wide characterization of HD-ZIP III genes and their stress response diversity in Brassica species.

Satellite precipitation estimation provides crucial information for those places lacking rainfall observations from ground–based sensors, especially in terrestrial or marine areas with complex climatic or topographic conditions. This is the case over much of Western China, including Upper and Middle Lancang River Basin (UMLRB), an extremely important transnational river system in Asia (the Lancang–Mekong River Basin) with complex climate and topography that has limited long–term precipitation records and high–elevation data, and no operational weather radars. In this study, we evaluated three GPM IMERG satellite precipitation estimation (IMERG E, IMERG L and IMERG F) over UMLRB in terms of multi–year average precipitation distribution, amplitude consistency, occurrence consistency, and elevation–dependence in both dry and wet seasons. Results demonstrated that monsoon and solid precipitation mainly affected amplitude consistency of precipitation, aerosol affected occurrence consistency of precipitation, and topography and wind–induced errors affected elevation dependence. The amplitude and occurrence consistency of precipitation were best in wet seasons in the Climate Transition Zone and worst in dry seasons in the same zone. Regardless of the elevation–dependence of amplitude or occurrence in dry and wet seasons, the dry season in the Alpine Canyon Area was most positively dependent and most significant. More significant elevation–dependence was correlated with worse IMERG performance. The Local Weighted Regression (LOWERG) model showed a nonlinear relationship between precipitation and elevation in both seasons. The amplitude consistency and occurrence consistency of both seasons worsened with increasing precipitation intensity and was worst for extreme precipitation cases. IMERG F had great potential for application to hydroclimatic research and water resources assessment in the study area. Further research should assess how the dependence of IMERG’s spatial performance on climate and topography could guide improvements in global precipitation assessment algorithms and the study of mountain landslides, floods, and other natural disasters during the monsoon period.

In this study, we simulated vegetation net primary productivity (NPP) using the boreal ecosystem productivity simulator (BEPS) between 2003 and 2012 over Northeast China, a region that is significantly affected by climate change. The NPP was then validated against the measurements that were calculated from tree ring data, with a determination coefficient (R2) = 0.84 and the root mean square error (RMSE) = 42.73 gC/m2·a. Overall, the NPP showed an increasing trend over Northeast China, with the average rate being 4.48 gC/m2·a. Subsequently, partial correlation and lag analysis were conducted between the NPP and climatic factors. The partial correlation analysis suggested that temperature was the predominant factor that accounted for changes in the forest NPP. Solar radiation was the main factor that affected the forest NPP, and the grass NPP was the most closely associated with precipitation. The relative humidity substantially affected the annual variability of the shrub and crop NPPs. The lag time of the NPP related to precipitation increased with the vegetation growth, and it was found that the lag period of the forest was longer than that of grass and crops, whereas the cumulative lag month of the forest was shorter. This comprehensive analysis of the response of the vegetation NPP to climate change can provide scientific references for the managing departments that oversee relevant resources.

Mangrove forests, as important ecological and economic resources, have suffered a loss in the area due to natural and human activities. Monitoring the distribution of and obtaining accurate information on mangrove species is necessary for ameliorating the damage and protecting and restoring mangrove forests. In this study, we compared the performance of UAV Rikola hyperspectral images, WorldView-2 (WV-2) satellite-based multispectral images, and a fusion of data from both in the classification of mangrove species. We first used recursive feature elimination‒random forest (RFE-RF) to select the vegetation’s spectral and texture feature variables, and then implemented random forest (RF) and support vector machine (SVM) algorithms as classifiers. The results showed that the accuracy of the combined data was higher than that of UAV and WV-2 data; the vegetation index features of UAV hyperspectral data and texture index of WV-2 data played dominant roles; the overall accuracy of the RF algorithm was 95.89% with a Kappa coefficient of 0.95, which is more accurate and efficient than SVM. The use of combined data and RF methods for the classification of mangrove species could be useful in biomass estimation and breeding cultivation.

This study was focused on extraction, radical scavenging activities, and chemical composition identification of total flavonoids in sunflower (Helianthus annuus L.) receptacles (TFSR). We investigated the optimal extract parameters of TFSR using response surface methodology. The highest yield of TFSR was 1.04% with the ethanol concentration 58%, the material-to-liquid ratio 1:20 (v/w), the extraction time 2.6 h, and the extraction temperature 67 °C. The results of radical scavenging activities showed that ethyl acetate fraction (EAF) was the strongest by using 2-diphenyl-1-picrylhydrazyl (DPPH), 2, 2’-azino-bis (3-ethylbenzo thiazoline-6-sulfonic acid) (ABTS) and iron ion reducing analysis. The EAF had the highest flavonoids contents. Four fractions A, B, C and D were enrichment from EAF by polyamide resin. Fraction B had the highest flavonoids content. Thirteen chemical components of flavonoids in fraction B were first identified by Ultimate 3000 Nano LC System coupled to a Q Exactive HF benchtop Orbitrap mass spectrometer (UHPLC-HRMS/MS). Among of the thirteen chemical components, isoquercetin and daidzein were identified accurately by comparing with standard samples. Radical scavenging analysis showed that isoquercetin and EAF had strong activities. Therefore, sunflower receptacles can be used as a source of natural flavonoids. TFSR as a natural radical scavenger has potential applications in pharmaceutical industry.

We propose a long-term parameterization scheme for two critical parameters, zero-plane displacement height (d) and aerodynamic roughness length (z0m), that we further use in the Surface Energy Balance System (SEBS). A sensitivity analysis of SEBS indicated that these two parameters largely impact the estimated sensible heat and latent heat fluxes. First, we calibrated regression relationships between measured forest vertical parameters (Lorey’s height and the frontal area index (FAI)) and forest aboveground biomass (AGB). Next, we derived the interannual Lorey’s height and FAI values from our calibrated regression models and corresponding forest AGB dynamics that were converted from interannual carbon fluxes, as simulated from two incorporated ecological models and a 2009 forest basis map These dynamic forest vertical parameters, combined with refined eight-day Global LAnd Surface Satellite (GLASS) LAI products, were applied to estimate the eight-day d, z0m, and, thus, the heat roughness length (z0h). The obtained d, z0m and z0h were then used as forcing for the SEBS model in order to simulate long-term forest evapotranspiration (ET) from 2000 to 2012 within the Qilian Mountains (QMs). As compared with MODIS, MOD16 products at the eddy covariance (EC) site, ET estimates from the SEBS agreed much better with EC measurements (R2 = 0.80 and RMSE = 0.21 mm·day−1).

In order to investigate the methane adsorption characteristics of coal seam materials in a “solid−gas” coupling physical simulation experiment, activated alumina, silica gel, the 3Å molecular sieve, 4Å molecular sieve and 5Å molecular sieve were selected as adsorption materials. According to the pore structure and adsorption characteristics, coal samples at the Aiweiergou #1890 working face were prepared as compared materials. The WY-98A methane adsorption coefficient measuring instrument was used to carry out this adsorption experiment under different temperatures, particle sizes and moisture contents. The results suggested that the adsorption principles of three kinds of molecular sieves under multiple factors do not fully fit a Langmuir adsorption model, and cannot be used as adsorption materials. The changing trend of the adsorption increment of activated alumina and silica gel are similar to that of coal samples, so they can be used as a coal-like materials. The methane adsorption coefficient a value changing trends of activated alumina and silica gel appear to be the same as the Aiweiergou #1890 coal samples, but the results from silica gel are closer to that of coal samples. Thus, silica gel is preferred as the adsorption material. The result provides an experimental basis for the selection of methane-adsorbing materials and carrying out “solid−gas” coupling physical simulation experiments in a physically similar testing model.

A new platform for triptolide (TP) delivery was prepared by conjugating TP to a carboxylmethyl chitosan (CMCS). Compared with the natural TP, the TP-conjugate (TP-CMCS) containing TP of ~5 wt% exhibited excellent aqueous solubility (> 5 mg/mL). Results of in vitro experiments showed that TP-CMCS could relieve TP-induced inhibition on RAW264.7 cells and apoptosis, respectively. Compared with the TP group, TP-CMCS could effectively alleviate the toxicity injury of TP and decreased the mortality rate of the mice (p < 0.05). TP-CMCS did not cause much damage to the liver (AST and ALT) and kidney (BUN and CRE) (p < 0.05). After administration, the levels of IL-6, IL-1β, and TNF-α decreased, and the arthritis detumescence percentages increased significantly, and the bony erosion degree was distinctly decreased in the TP-CMCS groups and TP group. Our results suggested that TP-CMCS was a useful carrier for the treatment of RA, which enhanced aqueous solubility of free TP and reduced drug toxicity in vitro and in vivo.

Difficulties are faced when formulating hydrological processes, including that of evapotranspiration (ET). Conventional empirical methods for formulating these possess some shortcomings. The artificial intelligence approach emerges as the best possible solution to map the relationships between climatic parameters and ET, even with limited knowledge of the interactions between variables. This review presents the state-of-the-art application of artificial intelligence models in ET estimation, along with different types and sources of data. This paper discovers the most significant climatic parameters for different climate patterns. The characteristics of the basic artificial intelligence models are also explored in this review. To overcome the pitfalls of the individual models, hybrid models which use techniques such as data fusion and ensemble modeling, data decomposition as well as remote sensing-based hybridization, are introduced. In particular, the principles and applications of the hybridization techniques, as well as their combinations with basic models, are explained. The review covers most of the related and excellent papers published from 2011 to 2019 to keep its relevancy in terms of time frame and field of study. Guidelines for the future prospects of ET estimation in research are advocated. It is anticipated that such work could contribute to the development of agriculture-based economy.

Ship detection in high-resolution synthetic aperture radar (SAR) imagery is a challenging problem in the case of complex environments, especially inshore and offshore scenes. Nowadays, the existing methods of SAR ship detection mainly use low-resolution representations obtained by classification networks or recover high-resolution representations from low-resolution representations in SAR images. As the representation learning is characterized by low resolution and the huge loss of resolution makes it difficult to obtain accurate prediction results in spatial accuracy; therefore, these networks are not suitable to ship detection of region-level. In this paper, a novel ship detection method based on a high-resolution ship detection network (HR-SDNet) for high-resolution SAR imagery is proposed. The HR-SDNet adopts a novel high-resolution feature pyramid network (HRFPN) to take full advantage of the feature maps of high-resolution and low-resolution convolutions for SAR image ship detection. In this scheme, the HRFPN connects high-to-low resolution subnetworks in parallel and can maintain high resolution. Next, the Soft Non-Maximum Suppression (Soft-NMS) is used to improve the performance of the NMS, thereby improving the detection performance of the dense ships. Then, we introduce the Microsoft Common Objects in Context (COCO) evaluation metrics, which provides not only the higher quality evaluation metrics average precision (AP) for more accurate bounding box regression, but also the evaluation metrics for small, medium and large targets, so as to precisely evaluate the detection performance of our method. Finally, the experimental results on the SAR ship detection dataset (SSDD) and TerraSAR-X high-resolution images reveal that (1) our approach based on the HRFPN has superior detection performance for both inshore and offshore scenes of the high-resolution SAR imagery, which achieves nearly 4.3% performance gains compared to feature pyramid network (FPN) in inshore scenes, thus proving its effectiveness; (2) compared with the existing algorithms, our approach is more accurate and robust for ship detection of high-resolution SAR imagery, especially inshore and offshore scenes; (3) with the Soft-NMS algorithm, our network performs better, which achieves nearly 1% performance gains in terms of AP; (4) the COCO evaluation metrics are effective for SAR image ship detection; (5) the displayed thresholds within a certain range have a significant impact on the robustness of ship detectors.

Biomechanics play a critical role in influencing the clinical applications of all-ceramic dental restorations. The restorative biomaterials have to demonstrate mechanical durability in the oral environment because they are always exposed to a variety of oral environments. This study was designed to evaluate the effect of soaking time, notch and saliva pH values on the impact energy of three commonly used all-ceramic materials for CAD/CAM. The leucite-reinforced glass ceramic (ProCAD), lithium disilicate glass ceramic (IPS e.max CAD) and zirconia-based ceramic materials (IPS e.max ZirCAD) were used. The experimental results indicated that the impact energy of ProCAD decreased with an increase in soaking time, but not for IPS e.max CAD and IPS e.max ZirCAD. The impact energy of the zirconia system was higher than leucite-reinforced and lithium disilicate-based ceramic systems. When subjected to preformed 0.5 mm U-shape notch on the bar specimen of 3 mm thick, the impact energy of the all-ceramic restorations revealed a markedly reduction of about 80%–90%, almost irrespective of dental compositions, which indicated the effect of flaw to a great degree. No statistically significant influence (p > 0.05) of pH values (4, 7 and 9) on impact energy was found for each group. It is concluded that the no matter which all-ceramic materials were used, it was appreciably sensitive to the presence of notches. The ceramic composition and microstructure have been shown to affect mechanical durability.

Carbon deposition considered in a solid oxide fuel cell (SOFC) model may be influenced by the operating voltage, inlet water/methane ratio, working temperature and pressure, inlet molar fraction of fuel and so on. The effects of these parameters in a planar SOFC implementing a novel bi-layer interconnector are not well understood. This paper is focused on the numerical study of carbon deposition and electrical performance of a bi-layer interconnector planar SOFC. The results illustrate that the electrical performance of the bi-layer interconnector SOFC is 11% higher than that of the conventional straight interconnector SOFC with initial state. After 120 days of operation, the electrical performance of the bi-layer interconnector SOFC has a slight decrease and more carbon deposit because of the increased electrochemical reaction rate. However, these differences minimize if higher operating voltages are involved.

Background: Coffee is a major dietary source of polyphenols. Previous research found that coffee had a protective effect on periodontal disease. In this study, we aimed to investigate whether coffee extract and its primary phenolic acid, chlorogenic acid, affect the growth and protease activity of a periodontopathogen Porphyromonas gingivalis (P. gingivalis). Methods: Coffee extract and chlorogenic acid were prepared by a two-fold serial dilution. The turbid metric test and plate count method were used to examine the inhibitory effects of chlorogenic acid on P. gingivalis. The time-kill assay was used to measure changes in the viability of P. gingivalis after exposure to chlorogenic acid for 0−24 h. The protease activity of P. gingivalis was analyzed using the optical density of a chromogenic substrate. Results: As a result, the minimum inhibitory concentration (MIC) of chlorogenic acid was 4 mg/mL, and the minimum bactericidal concentration was 16 mg/mL. Chlorogenic acid at concentrations above MIC resulted in a longer-lasting inhibitory effect on P. gingivalis viability and significantly reduced associated protease activity. The coffee extract showed antibacterial activity as observed by the disk diffusion test, whereas these inhibitory effects were not affected by different roast degrees of coffee. Conclusions: Collectively, our novel findings indicate that chlorogenic acid not only has antimicrobial activity but also reduced the protease activity of P. gingivalis. In addition, coffee extract inhibits the proliferation of P. gingivalis, which may partly be attributed to the effect of chlorogenic acid.

The Hydrologic Modeling System (HEC-HMS) and statistical analysis method were used to analyze the relationship between flood eigenvalues (i.e., flood volume and peak flow) and landscape pattern metrics. Then, the flood-landscape ecological risk index (ERI_FL) was proposed and constructed to quantitatively assess the flood-landscape ecological risk (FLER). The semivariogram method was used to spatialize the ERI_FL values. Lastly, this study analyzed the spatial−temporal change of FLER at watershed scale and at sub-basin scale, respectively. Two historical landscape distributions (i.e., 2003 and 2017) of Qinhuai River basin were used to perform this study. The results showed that there were certain relationships between landscape pattern and flood eigenvalues, and for different landscapes, the response metrics and degrees were different. FLER increased as urbanization increased. FLER change magnitude had a positive relationship with urban land percentage change magnitude. The distribution of FLER and the distribution of FLER change both showed spatial differences at watershed scale. The structural features of landscape pattern had significant effects on regional floods. In the urbanization process, avoiding forming large-scale landscape patches, improving landscape abundance, and increasing contact area between different types of landscape patches were helpful to reduce the negative effects caused by the increase of urban landscape area on flood.

Tectonic coal is a kind of soft coal that is generated during tectonic movement. Gas outbursts usually occur in seams containing both virgin coal and tectonic coal. To reveal the adsorption characteristics of this type of coal seam (containing both virgin coal and tectonic coal), both tectonic coal and virgin coal were collected from the same longwall face and a series of laboratory tests were conducted, including coal sorption tests and pore specific surface measurements. Both the tectonic coal and virgin coal were crushed into coal powder (0.18⁻0.25 mm) for the coal sorption tests. In these laboratory tests, different mass ratios between tectonic coal and virgin coal were tested. We found that with the increase of the percentage of tectonic coal, the adsorption volume showed a rising trend, reached its maximum value, and then decreased. The specific surface areas of the mixed coal samples had the same evolution trends as those of the adsorption volume. From the laboratory tests, we found that when the mass ratio of virgin coal to tectonic coal was 1:1, both the adsorption volume and the specific surface areas reached their maximum values. Due to the percentage variation of the tectonic coal in the panel with the advancement of the longwall face, when the tectonic coal accounted for 50% of the total coal, the gas content would rise. Thus, proper measures should be adopted for outburst hazards control. The mathematical model between the change of specific surface area and the stress and strain of pore expansion before and after gas adsorption was established, and the relationship between the change of pore structure and gas emission before and after gas adsorption was obtained. It provides a theoretical basis for further research on coal and gas outburst mechanisms.

Magnetic nanoparticles are used to enhance the image contrast of magnetic resonance imaging (MRI). However, the development of magnetic nanoparticles with a low dose/high image contrast and non-toxicity is currently a major challenge. In this study, cobalt-substituted hydroxyapatite nanoparticles deposited on titanium (Ti-CoHA) and cobalt-substituted hydroxyapatite nanoparticles deposited on titanium dioxide nanotubes (TNT-CoHA) were synthesized by the electrochemical deposition method. The particle sizes of Ti-CoHA and TNT-CoHA were 418.6 nm and 127.5 nm, respectively, as observed using FE-SEM. It was shown that CoHA can be obtained with a smaller particle size using a titanium dioxide nanotube (TNT) electrode plate. However, the particle size of TNT-CoHA is smaller than that of Ti-CoHA. The crystal size of the internal cobalt oxide of CoHA was calculated by using an XRD pattern. The results indicate that the crystal size of cobalt oxide in TNT-CoHA is larger than that of the cobalt oxide in Ti-CoHA. The larger crystal size of the cobalt oxide in TNT-CoHA makes the saturation magnetization (Ms) of TNT-CoHA 12.6 times higher than that of Ti-CoHA. The contrast in MRIs is related to the magnetic properties of the particles. Therefore, TNT-CoHA has good image contrast at low concentrations in T2 images. The relaxivity coefficient of the CoHA was higher for TNT-CoHA (340.3 mM−1s−1) than Ti-CoHA (211.7 mM−1s−1), and both were higher than the commercial iron nanoparticles (103.0 mM−1s−1). We showed that the TNT substrate caused an increase in the size of the cobalt oxide crystal of TNT-CoHA, thus effectively improving the magnetic field strength and MRI image recognition. It was also shown that the relaxivity coefficient rose with the Ms. Evaluation of biocompatibility of CoHA using human osteosarcoma cells (MG63) indicated no toxic effects. On the other hand, CoHA had an excellent antibacterial effect, as shown by E. coli evaluation, and the effect of TNT-CoHA powder was higher than that of Ti-CoHA powder. In summary, TNT-CoHA deposited electrochemically on the TNT substrates can be considered as a potential candidate for the application as an MRI contrast agent. This paper is a comparative study of how different electrode plates affect the magnetic and MRI image contrast of cobalt-substituted hydroxyapatite (CoHA) nanomaterials.

This paper analyzes the influence of laser linewidth on the measurement accuracy of a frequency-scanning Brillouin optical time domain reflectometer (FS-BOTDR), allowing for both the width of Brillouin gain spectrum and the signal-to-noise ratio (SNR) of the BOTDR system. The measurement accuracy of the Brillouin frequency shift (BFS) is theoretically investigated versus the duration of the probe pulse and the linewidth of the laser source, by numerically simulating how a FS-BOTDR works and evaluating the Brillouin gain spectrum (BGS) width and the system SNR. The simulation results show that the BFS accuracy is improved as the laser linewidth becomes narrower when the probe pulse width is fixed. We utilize five types of lasers with respective linewidths of 1.05 MHz, 101 kHz, 10.2 kHz, 3.1 kHz, and 98 Hz to compare the BFS measurement accuracy over a ~10 km optical sensing fiber. The experimental results demonstrate that the root-mean-square error (RMSE) of BFS decreases with the laser linewidth narrowing from 1.05 MHz to 3.1 kHz, which is in good agreement with the numerical simulation. However, the RMSE of BFS increases when the laser linewidth is less than 3.1 kHz, which may arise from the coherent Rayleigh noise due to a too narrow laser linewidth. The results can provide a theoretical basis and experimental guidance for choosing the appropriate laser linewidth in BOTDR.

This study focuses on the association between the ABO blood group system and the risk of gastric cancer or Helicobacter pylori infection. The data for the ABO blood group was collected from 1045 cases of gastric cancer, whereby the patient underwent a gastrectomy in Ruijin Hospital, Shanghai. The information on the ABO blood group from 53,026 healthy blood donors was enrolled as control. We searched the Pubmed database on the relationship between ABO blood groups and gastric cancer risk for meta-analysis. In our case-control study, the risk of gastric cancer in blood group A was significantly higher than that in non-A groups (O, B and AB) (odd ratio, OR1.34; 95% confidential interval, CI 1.25–1.44). Compared with non-O groups (A, B and AB), individuals with blood group O demonstrated a reduced risk of gastric cancer (OR = 0.80; 95% CI 0.72–0.88). The proportion of H. pylori infection in blood group A individuals was significantly higher than that in non-A blood groups (OR = 1.42; 95% CI 1.05–1.93). We further combined our data with the published data of others, and crossreferenced the risk of gastric cancer with the blood type, finding consistent evidence that gastric cancer risk in the blood A group was higher than that in the non-A groups (OR = 1.11; 95% CI 1.07–1.15), and that blood type O individuals were consistently shown gastric cancer risk reduction (OR = 0.91; 95% CI 0.89–0.94). Our study concluded that there was a slightly increased risk of gastric cancer in blood group A individuals, and people with blood type A are more prone to be infected by H. pylori than other ABO blood type individuals, whereas, a slightly decreased risk of gastric cancer was identified in blood type O individuals.

Echinococcus granulosus is the causative agent of cystic echinococcosis (CE), a widespread parasitic zoonosis. Leucine aminopeptidases (LAPs) of the M17 peptidase family have important functions in regulating the balance of catabolism and anabolism, cell maintenance, growth and defense. In this study, we presented a bioinformatic characterization and experimentally determined the tissue distribution characteristics of E. granulosus LAP (Eg-LAP), and explored its potential value for diagnosis of CE in sheep based on indirect ELISA. Through fluorescence immunohistochemistry, we found that Eg-LAP was present in the tegument and hooks of PSCs, the whole germinal layer and adult worm parenchymatous tissue. Western blotting results revealed that the recombinant protein could be identified using E. granulosus-infected sheep serum. The diagnostic value of this recombinant protein was assessed by indirect ELISA, and compared with indirect ELISA based on hydatid fluid antigen. The sensitivity and specificity rEgLAP-ELISA were 95.8% (23/24) and 79.09% (87/110), respectively, while using hydatid fluid as antigen showed the values 41.7% (10/24) and 65.45% (72/110). This is the first report concerning leucine aminopeptidase from E. granulosus, and the results showed that Eg-LAP belong to M17 peptidase families, and that it is involved in important biological function of E. granulosus. Furthermore, rEg-LAP is appropriate for diagnosing and monitoring CE in sheep in field. Development of a rapid test using rEg-LAP to diagnose sheep CE deserves further study.

This study improved simulation of forest carbon fluxes in the Changbai Mountains with a process-based model (Biome-BGC) using incorporation and data assimilation. Firstly, the original remote sensing-based MODIS MOD_17 GPP (MOD_17) model was optimized using refined input data and biome-specific parameters. The key ecophysiological parameters of the Biome-BGC model were determined through the Extended Fourier Amplitude Sensitivity Test (EFAST) sensitivity analysis. Then the optimized MOD_17 model was used to calibrate the Biome-BGC model by adjusting the sensitive ecophysiological parameters. Once the best match was found for the 10 selected forest plots for the 8-day GPP estimates from the optimized MOD_17 and from the Biome-BGC, the values of sensitive ecophysiological parameters were determined. The calibrated Biome-BGC model agreed better with the eddy covariance (EC) measurements (R2 = 0.87, RMSE = 1.583 gC·m−2·d−1) than the original model did (R2 = 0.72, RMSE = 2.419 gC·m−2·d−1). To provide a best estimate of the true state of the model, the Ensemble Kalman Filter (EnKF) was used to assimilate five years (of eight-day periods between 2003 and 2007) of Global LAnd Surface Satellite (GLASS) LAI products into the calibrated Biome-BGC model. The results indicated that LAI simulated through the assimilated Biome-BGC agreed well with GLASS LAI. GPP performances obtained from the assimilated Biome-BGC were further improved and verified by EC measurements at the Changbai Mountains forest flux site (R2 = 0.92, RMSE = 1.261 gC·m−2·d−1).