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Rain gardens play a key role in urban non-point source pollution control. The drainage type affects the infiltration processes of runoff pollutants. The soil properties and microbial community structures were studied to reveal the stability of the ecosystem in rain gardens with different drainage types under long-term operation. The results showed that the soil water content and total organic carbon in the drained rain gardens were always higher than that of the infiltrated ones. With the increase in running time, the contents of heavy metals in rain gardens showed significant accumulation phenomena, especially the contents of Zn and Pb in drained rain gardens were higher than that in infiltrated ones. The accumulation of pollutants resulted in lower microbial diversity in drained rain gardens than in infiltrated rain gardens, but the microbial community structures were the same in all rain gardens. The effects of drainage type on microbial community evolution were not significant, only the accumulation of heavy metals led to changes in the abundance of dominant microorganisms. There were differences in the soil environment of rain gardens with different drainage types. The long-term operation of rain gardens led to fluctuations in the soil ecosystem, while the internal micro-ecosystems of the drained rain gardens were in unstable states. [ABSTRACT FROM AUTHOR]

With an increasing number of network attacks using encrypted communication, the anomaly detection of encryption traffic is of great importance to ensure reliable network operation. However, the existing feature extraction methods for encrypted traffic anomaly detection have difficulties in extracting features, resulting in their low efficiency. In this paper, we propose a framework of encrypted traffic anomaly detection based on parallel automatic feature extraction, called deep encrypted traffic detection (DETD). The proposed DETD uses a parallel small-scale multilayer stack autoencoder to extract local traffic features from encrypted traffic and then adopts an L1 regularization-based feature selection algorithm to select the most representative feature set for the final encrypted traffic anomaly detection task. The experimental results show that DETD has promising robustness in feature extraction, i.e., the feature extraction efficiency of DETD is 66% higher than that of the conventional stacked autoencoder, and the anomaly detection performance is as high as 99.998%, and thus DETD outperforms the deep full-range framework and other neural network anomaly detection algorithms. [ABSTRACT FROM AUTHOR]

Netizens all over the world can search malicious websites by malicious long-tail keywords on search engines, but malicious websites are strictly prohibited by law in most countries, so the construction of short text classification models for detecting malicious long-tail keywords has become a key research topic of Natural Language Processing (NLP). Most of the short text classification models are for English, with the widespread use of Chinese, there is an urgent need to develop Chinese short text classification models to help Chinese search engines detect malicious long-tail keywords. Considering that malicious long-tail keywords often evade detection by using homophones that have the same pinyin, pinyin is added to solve the homophonic typos problem of Chinese short text. Considering the data sparsity problem of malicious long-tail keywords, pinyin and radicals are added to obtain more abundant features. Since there is no publicly available pre-trained pinyin and radical embedding models, the embedding vectors of Chinese words, radical and pinyin are trained through Word2Vec, and 492,345 individual word embedding vectors, 207,995 individual radical embedding vectors and 402,071 individual pinyin embedding vectors are obtained. In addition, the positional encoding and part-of-speech coefficient are added to them, and the TF-IDF and MI values are added to reflect the word frequency weight and the different importance of the same word in different documents. Then, two parallel co-attention networks are used to fuse features of words, pinyin, and radicals, BIGRU is used to extract temporal features, and CNN is used to extract local features. Multi-group comparative experiment results on two short text benchmark datasets and pornographic and gambling long-tail keywords show that the proposed model outperforms the state-of-the-art text classification model. [ABSTRACT FROM AUTHOR]

Rhododendron micranthum is used traditionally as a remedy for the treatment of chronic bronchitis in China. To clarify the chemical basis and provide a reference for the rational use of this medicinal plant, a phytochemical study was carried out on the twigs and leaves of R. micranthum , which afforded eight new compounds (1 – 8) and eight known compounds (9 – 16). Their structures were rigorously determined by comprehensive HRESIMS, NMR and electronic circular dichroism (ECD) analyses. The anti-inflammatory activities of these compounds were evaluated. Compounds 3 , 13 , and 14 suppressed the transcription of the NF-κB-dependent reporter gene in LPS-induced 293T/NF-κB-luc cells at 10 μM, while no effect on cell viability was observed. Unlabelled Image [ABSTRACT FROM AUTHOR]

Rainfall runoff contained toxic pollutants such as polycyclic aromatic hydrocarbons (PAHs) and heavy metals. Bioretention systems can effectively remove PAHs and heavy metals from runoff. When PAHs and heavy metals accumulated in the media of bioretention systems, co-contamination occurred. To reveal the response processes of co-contamination in the media micro-ecosystem, bioretention systems were constructed and simulated rainfall tests were carried out to reveal the media micro-ecosystem evolution in the bioretention system under the co-contamination of PAHs and heavy metals. The simulated rainfall tests showed that the bioretention systems with different media had good purification effects with load reduction rates >90% (PAHs) and >40% (heavy metals). The microbial α-diversities in different media decreased by 6.67%–32.27%, and 9.21%–18.69% after the tests. The most dominant species of microorganisms in the media were Proteobacteria (all relative abundances >62%). As a typical PAHs-heavy metal degrading bacteria, the relative abundances of Pseudomonas increased significantly after the tests (both >9%). The co-contamination of PAHs and heavy metals inhibited all enzyme activities. The long-term operation of the bioretention system gradually increased the level of co-contamination in the media, and the stability of the media micro-ecosystem gradually deteriorated. The results of this paper can provide a theoretical basis and technical support for maintaining the operational efficiency of the bioretention system with modified-media and avoiding the risk of potential contamination. [Display omitted] • Bioretention systems showed high efficiency in load reduction of pollutants. • PAHs and heavy metals formed co-contamination in bioretention system media. • The growth of Pseudomonas was promoted in co-contamination conditions. • The co-contamination of PAHs and heavy metals inhibited the enzyme activities. • The "adsorption-adaptation-change-feedback" response processes were revealed. [ABSTRACT FROM AUTHOR]

The construction of "sponge city" made the belts on both roadsides be built in the form of bioretention tanks, resulting in runoff pollutants were accumulated in the bioretention tanks. To identify the pollution level and source of polycyclic aromatic hydrocarbons (PAHs) in the bioretention tanks, the soil samples were collected on the eight typical roads of the sponge city. The total contents of ∑PAHs in the bioretention tanks were 10,524–20,462 μg/kg (mean 15,029 μg/kg), and the pollution level of PAHs in the non-flood season was significantly higher than that in the flood season. The PAHs in bioretention tanks were dominated by 4-ring PAHs, with a proportion of 39.36%. The characteristic ratio method was proposed to identify the chemical source of PAHs, and the results indicated that PAHs in the bioretention tanks were mainly supplied by the combustion source and petroleum source. The ecological risk quotient (RQ) values showed that the accumulation of PAHs in the bioretention tank had certain potential ecological risks, and the RQ values of pyrene (PYR) were the highest. Incremental lifetime cancer risks (ILCR) indicated that PAHs in soil posed negligible cancer risks by inhalation way, but much stronger risks by dermal and ingestion ways. The roads with the highest and lowest PAHs content were selected for microbial ecology analysis, and the microbial abundances showed significant decreasing trends from the flood season to the non-flood season. The PAHs accumulated in the bioretention tanks had significant impacts on the microbial community, which made the microorganisms tend to PAHs-degrading bacteria. • PAHs showed different accumulation levels in road green infrastructures of sponge city. • The combustion source was the main source of the PAHs in bioretention tanks. • Pyrene (PYR) in the bioretention tank had higher potential ecological risks. • There were potential carcinogenic risks caused by dermal and ingestion ways. • The accumulation of PAHs made microorganisms tend to PAHs-degrading bacteria. [ABSTRACT FROM AUTHOR]

As the bioretention facilities have been extensively built in the construction of "Sponge City" in China, urban non-point source pollutants could be effectively controlled. The influences on microbial community in three bioretention facilities with different underlying types/built times at field scale were studied. The results showed that nutrient loads in road runoff were 1.1–3 times higher than of roof. Compared with the other two rain gardens, the bioretention tank (BT) was relatively stable and showed >90% nutrient load reduction rates. The nutrients brought by the stormwater runoff changed the original habitat in the soil. Nutrient removal led to the deterioration of the living environment of microorganisms, and then the number of microorganisms and diversity changed. Ten dominant bacteria species were found in the facilities, and Proteobacteria were the most dominant bacteria phyla, with the relative abundances all >30%. Suspended solids were found to be the most important factor and had a high correlation to the most dominant microorganisms. With the increased operation period, the microorganism species tended to be concentrated on Proteobacteria , resulting in decreases of other functional microorganisms. The bioretention facility with the road underlying had the lowest microbial diversity, and the built time was the factor that had the greatest impact on microbial diversity. Based on these results, the future design and construction of bioretention facilities should consider the risk after nutrients entered the bioretention facility and the changes in microbial diversity. [Display omitted] • The nutrient removal effects of bioretention facilities with different underlying types/built time were monitored. • The changes of TOC and nutrients (N and P) contents were studied. • The evolutions of the microbial communities were explored. • The relationship between soil nutrient contents and microorganisms was built. • The influences of different design types on the microbial diversity were determined. [ABSTRACT FROM AUTHOR]

Millions of new domain names are registered every day, but a large proportion of them are malicious and usually discovered and blacklisted after the crime has been committed. In order to improve the security of domain name registration, this paper proposes a lightweight detection method based on the AdaBoost to identify malicious domain names, which focuses on proactively detecting malicious domain names by exploring the abnormal WHOIS records. The domain name registries and registrars can adopt the proposed method as the first layer of defense to identify malicious domains on the domain registration stage. Extensive experiments on a large-scale database demonstrate that the proposed approach achieves satisfactory results on various malicious domain names. [ABSTRACT FROM AUTHOR]

Peri-implantitis is characterized by inflammatory cell infiltration and hyperactivation of the osteoclasts surrounding dental implants which can result in bone resorption and ultimately implant failure. Therefore, coordinating the activity of inflammatory response and bone-resorbing osteoclasts is crucial for the prevention of peri-implantitis. Asperuloside (ASP), an iridoid glycoside, has significant anti-inflammatory activities, suggesting the great potential in attenuating peri-implantitis bone resorption. A ligature-induced peri-implantitis model in the maxilla of rats was established, and the effects of ASP on preventing peri-implantitis were evaluated after four weeks of ligation using micro-CT and histological staining. RT-PCR, western blotting, tartrate-resistant acid phosphatase (TRAP), and immunofluorescent staining were conducted on osteoclasts to confirm the mechanisms of ASP on osteoclastogenesis. The results show that ASP could lead to attenuation of alveolar bone resorption in peri-implantitis by inhibiting osteoclast formation and decreasing pro-inflammatory cytokine levels in vivo. Furthermore, ASP could inhibit osteoclastogenesis by downregulating expression levels of transcription factors nuclear factor of activated T-cell (NFATc1) via restraining the activations of nuclear factor kappa beta (NF-κB) and the phosphorylation of extracellular signal-related kinase 1/2 (ERK1/2). In conclusion, ASP could significantly attenuate bone resorption in peri-implantitis via inhibition of osteoclastogenesis by suppressing NF-κB and ERK1/2 signaling pathways activations. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus (S. aureus)-induced acute lung injury (ALI) is a serious disease that has a high risk of death among infants and teenagers. Acetylharpagide, a natural compound of Ajuga decumbens Thunb. (family Labiatae), has been found to have anti-tumor, anti-inflammatory and anti-viral effects. This study investigates the therapeutic effects of acetylharpagide on S. aureus-induced ALI in mice. Here, we found that acetylharpagide alleviated S. aureus-induced lung pathological morphology damage, protected the pulmonary blood-gas barrier and improved the survival of S. aureus-infected mice. Furthermore, S. aureus-induced myeloperoxidase (MPO) activity of lung homogenate and pro-inflammatory factors in bronchoalveolar lavage (BAL) fluid were suppressed by acetylharpagide. Mechanically, acetylharpagide inhibited the interaction between polyubiquitinated receptor interacting protein 1 (RIP1) and NF-κB essential modulator (NEMO), thereby suppressing NF-κB activity. In summary, these results show that acetylharpagide protects mice from S. aureus-induced ALI by suppressing the NF-κB signaling pathway. Acetylharpagide is expected to become a potential treatment for S. aureus-induced ALI. [ABSTRACT FROM AUTHOR]

Clinical reports have found that with the improvement of treatment, most septic patients are able to survive the severe systemic inflammatory response and to enter the immunoparalysis stage. Considering that immunoparalysis leads to numerous deaths of clinical sepsis patients, alleviation of the occurrence and development of immunoparalysis has become a top priority in the treatment of sepsis. In our study, we investigate the effects of oroxylin A on sepsis in cecal ligation and puncture (CLP) mice. We find that the 60 h + 84 h (30 mg/kg) injection scheme of oroxylin A induce the production of pro-inflammatory factors, and further significantly improves the survival of CLP mice during the middle or late stages of sepsis. Mechanistically, C/EBP-homologous protein (CHOP) is upregulated and plays anti-inflammatory roles to facilitate the development of immunoparalysis in CLP mice. Oroxylin A induces the transcription of E3 ligase F-box only protein 15 gene (fbxo15), and activated FBXO15 protein binds to CHOP and further mediates the degradation of CHOP through the proteasome pathway, which eventually relieves the immunoparalysis of CLP mice. Taken together, these findings suggest oroxylin A relieves the immunoparalysis of CLP mice by degrading CHOP through interacting with FBXO15. [ABSTRACT FROM AUTHOR]

Text classification first needs to convert the text into embedding vectors. Considering that static word embedding models such as Word2vec do not consider the position information of word and the difference of its role in different documents, while dynamic word embedding models such as Bert consume a large amount of time. An improved word embedding model based on pre-trained Word2vec is proposed, which achieves better classification accuracy and much lower classification time than Bert. At first, the concept of Term Document Frequency (TDF) is proposed on the basis of TF-IDF, and the TF-IDF-TDF of each word in different documents is calculated. Then, The positional encoding is added. Finally, in order to reduce the misleading of words with low importance, a filter is designed to set the embedding vector with low importance to zero. Considering that the sequence length that the deep learning model can handle is limited, and the text sequence exceeding the Maximum Sequence Length (MSL) set by the deep learning model will be directly truncated and discarded, an adaptive segmentation model is proposed, which can set different segmentation strategies for different texts according to the length of the text and the MSL. In order to maintain the continuity of adjacent text after segmentation, an adjacent-segment-vector-attended co-attention network is designed. In addition, the multi-channel convolution and the capsule network are designed to further extract deep hidden features. Multiple comparative experiment results show that the proposed model achieves the best Accuracy and Micro-F1 on five long text baseline datasets and six short text baseline datasets. In addition, when the MSL is not set too large compared with the document length in the dataset, the classification results of the proposed model are not affected by it. • An pre-trained Word2vec based embedding model is proposed. • An adaptive segmented text classification model is proposed. • An adjacent-segment-vector-attended co-attention network is designed. • The multi-channel convolution and capsule network are used to extract deep hidden features. [ABSTRACT FROM AUTHOR]

The composition statistics of gynecological microscopic images play an important role in the diagnosis and treatment of gynecology. However, current methods mainly rely on manual analysis of microscopic images, which is time-consuming and subjective. Therefore, the purpose of this paper is to develop a gynecological microscopic image component statistics method based on optical medical equipment and medical intelligent system to improve the accuracy and efficiency of gynecological diagnosis. The method of combining optical medical equipment and medical intelligent system is used to realize the automatic analysis of gynecological microscopic images. A large number of gynecological microscopic image samples were collected, and image processing technology was used to preprocess the images. Then computer vision algorithm and machine learning method are used to extract and classify the image features. Finally, the new gynecological microscopic images were analyzed statistically according to the trained model. The experimental results show that the method presented in this paper has a good effect on the composition statistics of gynecological microscopic images. Compared with the traditional manual analysis method, this method can analyze gynecological microscopic images more quickly and accurately, and provide effective diagnostic results. [ABSTRACT FROM AUTHOR]

Novel thermoplastic polyurethane (TPU)/multi walled carbon nanotubes (MWCNTs) conductive nanocomposites were fabricated by direct solution compounding method for volatile organic compounds (VOCs) sensors applications. The results of field emission scanning electron microscopy (FESEM) and electrical conductivity test showed that MWCNTs formed ideal conductive networks in TPU matrix. The volume conductivity of TPU/MWCNTs nanocomposites increased from 10-12 to 10-4S/mm, and the percolation value was 4.76 wt%. The size parameters of MWCNTs did not show obvious effects on the formation of conductive networks based on our comparative investigation. XRD and FTIR tests showed that MWCNTs enhanced the short range ordered structure in amorphous region of TPU due to the physical entanglement. The characteristic stretching of TPU showed no obvious change because of weak chemical interaction between MWCNTs and TPU. Moreover, MWCNTs effectively enhanced the thermal stability of the nanocomposites, as verified by TG analysis. The gas sensing property tests showed that the gas sensing response of TPU/MWCNTs nanocomposites mainly came from the resistance changes due to the disconnection of conductive networks, as a result of VOCs adsorption-swelling effects. The prepared nanocomposites showed superior selectivity, especially to benzene vapor when compared with formaldehyde and other gases. The parameters and contents of MWCNTs have a certain influence on the gas sensing response speed and recovery ability of the nanocomposites. In addition, the prepared TPU/MWCNTs nanocomposites displayed excellent repeatability and fast response to the change of electrical resistance (in seconds) after cyclic exposure to VOCs and pure dry air. [ABSTRACT FROM AUTHOR]

[Display omitted] • EDTA-crosslinking-chitosan/polypyrrole composite (EDTA-CS/PPy) with multiple types of adsorption sites (carboxyl, hydroxyl, amino), successfully realizing simultaneous removal of Cr(VI) anions and metal cations. • The high adsorption affinity of numerous adsorption sites in EDTA-CS/PPy for Cr (VI) anions and metal cations. • The maximum adsorption capacities of Cr(VI), Cu(Ⅱ), Pb(Ⅱ) and Cd(Ⅱ) by EDTA-CS/PPy are 401.25, 59.03, 77.81 and 68.31 mg/g, respectively. • The adsorption capacity of EDTA-CS/PPy keeps stability after three adsorption–desorption cycles. Polypyrrole-based adsorbents have emerged in removing Cr(VI) from wastewater based on their reduction, chelation, electrostatic attraction and ion exchange. However, it is still a formidable challenge to remove metal cations simultaneously due to electrostatic repulsion. In fact, metal ions originating from industrial activities such as chemical manufacturing and metal electroplating are always complex and multifarious. Here, we report a EDTA-crosslinking-chitosan/polypyrrole composite (EDTA-CS/PPy) with multiple types of adsorption sites (carboxyl, hydroxyl, amino), successfully realizing simultaneous removal of Cr(VI) anions and other metal cations. The maximum adsorption capacities of Cr(VI), Cu(II), Pb(II) and Cd(II) reach up to 401.25, 59.03, 77.81 and 68.31 mg/g, respectively. The adsorption mechanism is attributed to coupling interactions of the reduction, chelation, electrostatic attraction and ion exchange between targeted metal ions and EDTA-CS/PPy, investigated by experiments and DFT theories. Notably, the adsorption capacity of EDTA-CS/PPy keeps stability after three adsorption–desorption cycles. These findings may promote potential applications of EDTA-CS/PPy adsorbents in highly efficient treatment of coexisting toxic metal ions from wastewater. [ABSTRACT FROM AUTHOR]

SUMMARY: Plant bacterial pathogens usually cause diseases by secreting and translocating numerous virulence effectors into host cells and suppressing various host immunity pathways. It has been demonstrated that the extensive ubiquitin systems of host cells are frequently interfered with or hijacked by numerous pathogenic bacteria, through various strategies. Some type‐III secretion system (T3SS) effectors of plant pathogens have been demonstrated to impersonate the F‐box protein (FBP) component of the SKP1/CUL1/F‐box (SCF) E3 ubiquitin system for their own benefit. Although numerous putative eukaryotic‐like F‐box effectors have been screened for different bacterial pathogens by bioinformatics analyses, the targets of most F‐box effectors in host immune systems remain unknown. Here, we show that XopI, a putative F‐box effector of African Xoo (Xanthomonas oryzae pv. oryzae) strain BAI3, strongly inhibits the host's OsNPR1‐dependent resistance to Xoo. The xopI knockout mutant displays lower virulence in Oryza sativa (rice) than BAI3. Mechanistically, we identify a thioredoxin protein, OsTrxh2, as an XopI‐interacting protein in rice. Although OsTrxh2 positively regulates rice immunity by catalyzing the dissociation of OsNPR1 into monomers in rice, the XopI effector serves as an F‐box adapter to form an OSK1–XopI–OsTrxh2 interaction complex, and further disrupts OsNPR1‐mediated resistance through proteasomal degradation of OsTrxh2. Our results indicate that XopI targets OsTrxh2 and further represses OsNPR1‐dependent signaling, thereby subverting systemic acquired resistance (SAR) immunity in rice. [ABSTRACT FROM AUTHOR]

Palmprint biometrics has a broad application prospect owing to non-intrusiveness, ease of image acquisition and stable textural pattern. Hand-crafted approaches are vulnerable to non-ideal palmprint images caused by uneven illumination, motion blur and noise contamination. Many researchers have designed excellent texture descriptors or/and advanced image pre-processing algorithms. Nevertheless, they are highly targeted at some specific data, less adaptable to the emerging data. In this paper, a semi-pretrained contactless palmprint recognition deep network is developed to achieve high accuracy and robustness. Semi-CPRN is composed of underlying network structure from ResNet-152 and the proposed assistant layers dedicated to high-performance palmprint recognition. The well-designed assistant layers enhance convolutional neural network to steadily extract the real palmprint features even from the degraded images without being deceived by the degradation factors. Besides, to better carry out the research on palmprint recognition in the open environment, we established a new contactless database HIT-NIST-V1 under natural scene. The comparative experiments on CASIA, IITD, PolyU3D/2D, Tongji and HIT-NIST-V1 illustrate that Semi-CPRN is comparable and superior to previously published state-of-the-art approaches. Simultaneously, CNN-based palmprint biometrics methods show significant robustness to motion blur, Gaussian noise, and salt and pepper noise. [ABSTRACT FROM AUTHOR]

Due to the limitations of physical resources, if a large-scale emulation network environment composed of millions of vertices and edges is constructed by virtualization technology, the whole network topology should be partitioned into a set of subnets. The topology partition is a work of graph partition. The existing topology partition methods have shortcomings, such as low efficiency and poor practicability, especially for large-scale network topology. The emulation network is a kind of complex network and has the characteristics of community structure. Therefore, we proposed LENTP (large-scale emulation network topology partition) based on the community detection with the weight of the vertex similarity for large-scale topology partition. In the first stage, the tree-structured area compression reduces the topology scales significantly to improve partition efficiency. And then, the improved Louvain algorithm is used to topology partitioning and obtain an initial set of subnets with the minimum number of subnets and remote links. Finally, after repartitioning and merging for the initial subnets, the result of subnets is the final topology partition that reaches the optimization objectives with the conditions of the virtual resources. In the experiment, the method is tested in five groups of network topology with different scales. The results demonstrate that LENTP can partition the network topology over 1 000 000 nodes and significantly improve the running-time efficiency of the network topology partition. [ABSTRACT FROM AUTHOR]

On-line gambling is the key illegal behaviour of public security department in most countries due to the potential threat to cyberspace security and social stability. Hence, the research on gambling domain names (GDN) classification is quite important and in great demand for academia and industry. Till now, there is very little research work on this topic. Most of the GDN training datasets in previous work were chosen from GDN blacklists provided by publicly available data sources, and the authors did not verify the authenticity and accuracy of these datasets, and the classification results are not particularly satisfactory. In this paper, certificated and textual analysis-based classification method CT-GDNC is proposed to get GDN training data set with an accuracy of 0.9776 and significantly improve the classification results of GDN. The exhaustive comparative experiments on 10K GDN obtained via Bert fine-tuning model and 10K benign data collected from Alex Top 1 million list show that the proposed method achieves new baseline result for GDN classification with classification accuracy 0.9936, precision 0.9936, F1 0.9936 and recall 0.9939. [ABSTRACT FROM AUTHOR]

The potential for toxic elements to contaminate soil has been extensively studied. Therefore, the development of cost-effective methods and materials to prevent toxic element residues in the soil from entering the food chain is of great significance. Industrial and agricultural wastes such as wood vinegar (WV), sodium humate (NaHA) and biochar (BC) were used as raw materials in this study. HA was obtained by acidizing NaHA with WV and then loaded onto BC, which successfully prepared a highly efficient modification agent for nickel-contaminated soil, namely biochar-humic acid material (BC-HA). The characteristics and parameters of BC-HA were obtained by FTIR, SEM, EDS, BET and XPS. The chemisorption of Ni(II) ions by BC-HA conforms to the quasi-second-order kinetic model. Ni(II) ions are distributed on the heterogeneous surface of BC-HA by multimolecular layer adsorption, which accords with the Freundlich isotherm model. WV promotes better binding of HA and BC by introducing more active sites, thus increasing the adsorption capacity of Ni(II) ions on BC-HA. Ni(II) ions in soil are anchored to BC-HA by physical and chemical adsorption, electrostatic interaction, ion exchange and synergy. [ABSTRACT FROM AUTHOR]

The potential for toxic elements to contaminate soil has been extensively studied. Therefore, the development of cost-effective methods and materials to prevent toxic element residues in the soil from entering the food chain is of great significance. Industrial and agricultural wastes such as wood vinegar (WV), sodium humate (NaHA) and biochar (BC) were used as raw materials in this study. HA was obtained by acidizing NaHA with WV and then loaded onto BC, which successfully prepared a highly efficient modification agent for nickel-contaminated soil, namely biochar-humic acid material (BC-HA). The characteristics and parameters of BC-HA were obtained by FTIR, SEM, EDS, BET and XPS. The chemisorption of Ni(II) ions by BC-HA conforms to the quasi-second-order kinetic model. Ni(II) ions are distributed on the heterogeneous surface of BC-HA by multimolecular layer adsorption, which accords with the Freundlich isotherm model. WV promotes better binding of HA and BC by introducing more active sites, thus increasing the adsorption capacity of Ni(II) ions on BC-HA. Ni(II) ions in soil are anchored to BC-HA by physical and chemical adsorption, electrostatic interaction, ion exchange and synergy. [ABSTRACT FROM AUTHOR]

Machine learning methods are widely used in Android malware detection, but carefully scrambled adversarial samples can effectively evade detection. Adversarial defence methods such as retraining and ensemble learning have high training costs and significant errors. This paper proposes a novel Android malware detection system, KFFPDet, to detect adversarial samples. It can detect adversarial samples efficiently. Firstly, this paper uses K-Nearest Neighbor (KNN) as the primary detection algorithm. In addition, this paper proposes a three-stage adversarial sample detection method, which saves the detection cost and reduces the error through prior knowledge. In the first stage, the frequency difference between benign typical features and malicious typical features is used to filter adversarial samples. In the second stage, the feature continuous values of benign typical features are used for adversarial sample filtering. The third stage filters adversarial samples by detecting isolation permissions and application programming interface (API). Experiments on various benchmark datasets verify the detection effect of KFFPDet. KFFPDet achieves 96% accuracy of adversarial sample detection on the VirusShare dataset. Compared with other advanced methods, KFFPDet 's adversarial sample detection accuracy is improved by 4.43% to 94.53%. The experimental results show that the proposed three-stage adversarial sample detection method is useful and will help design a more effective adversarial sample detection scheme. [ABSTRACT FROM AUTHOR]

[Display omitted] • Fifteen undescribed triterpene spiroketal lactones were isolated from Pseudolarix amabilis. • Six compounds exhibited significant NF-κB pathway inhibition activities (IC 50 : 0.09 to 0.49 μM). • Compound 16 showed anti-inflammatory activity against xylene-induced ear swelling and improved the disease activity index (DAI) of ulcerative colitis. Fifteen new triterpenoids (1 – 15), along with twenty known ones (16 – 35), were isolated from Pseudolarix amabilis. The triterpenoid structures include multiple skeleton types, such as 2,3-seco-cycloartane, 3,4-seco-cycloartane, 3,4:9,10-diseco-cycloartane, and 3,4:8,9:9,10-triseco-cycloartane, as elucidated by extensive spectroscopy (1D NMR, 2D NMR, HRESIMS, and IR) and single-crystal X-ray diffraction. The anti-inflammatory activities of compounds 1 – 35 were evaluated. Compounds 3 , 11 , 16 , 24 , 25 , and 26 suppressed the transcription of the NF-κB-dependent reporter gene in LPS-induced 293T/NF-κB-Luc cells with IC 50 values of 0.12, 0.10, 0.30, 0.09, 0.49, and 0.35 μ M, respectively. In addition, compound 16 showed anti-inflammatory activity against xylene-induced ear swelling in vivo with an inhibition rate of 44.7 % (30 mg/kg). Compound 16 significantly improved the disease activity index (DAI) of ulcerative colitis at a dose of 400 mg/kg in a dextran sodium sulfate (DSS)-induced mouse model of experimental ulcerative colitis (P < 0.01). [ABSTRACT FROM AUTHOR]

As the backbone of the domain name system (DNS), DNS resolvers are essential to the Internet. Nowadays, the measurement of DNS resolvers, especially open DNS resolvers, has become a research focus. Previous research works show that DNS responses returned from some open DNS resolvers are not expected for clients and the Internet. We call these DNS responses 'unexpected DNS responses'. Research on unexpected DNS responses is beneficial to the research, usage and management of open DNS resolvers. This paper explores unexpected DNS responses returned from open DNS resolvers in terms of identification and classification to better understand the behaviours of open DNS resolvers. First, an identification method is proposed to identify all kinds of DNS responses from each section of DNS messages. Second, a classification method is proposed to classify unexpected DNS responses by their influences on clients and the Internet. Furthermore, an efficient identification and classification method is proposed to simplify the above process. Among about 9 million responding open DNS resolvers in the experiments on the IPv4 address space, about 40% return unexpected DNS responses. Experimental results show that the proposed methods can identify and classify all kinds of DNS responses returned from open DNS resolvers. [ABSTRACT FROM AUTHOR]

Multi-Label Text Classification (MLTC) is one of the most import research of natural language processing. Although Deep Learning (DL) models have been widely applied to MLTC, there still exist some drawbacks. First, traditional DL models utilize all the words in the document to construct the embedding vector, while there are many words that affect the classification results. Next, the labels in MLTC have specific semantics, while traditional DL models ignore fine-grained matching signals between words and labels. Then, traditional DL models have difficulty in handling the data imbalance issue in MLTC datasets. In addition, during the training process, small errors in a certain epoch may be amplified with the increase of the number of iterations, resulting in classification errors. To address the above problems, a MLTC model integrating Label Attention and Historical Attention (i.e. LAHA) is proposed. First, a word filter is set up to select important words based on the cosine similarity between words and labels. Next, Document Self Attention (DSA) and Label Attention (LA) are obtained, and DSA-attended LA co-attention (LA-co) and LA-attended DSA co-attention (DAS-co) networks are constructed. Then, the fine-grained matching signals between words and labels are integrated through the adaptive plus of LA-co and DAS-co. At last, Historical Attention is integrated to LAHA, which not only avoids mis-classification caused by minor errors of a certain epoch, but also reduces overfitting to high-frequency labels. Multiple comparative experiments on four benchmark datasets demonstrate that LAHA outperforms the state-of-the-art baseline models and can effectively solve the data imbalance issue in MLTC datasets. Our code is available at https://github.com/sgysgywaityou/LAHA. • A word filter is introduced to select important words. • Document-Self Attention and Label Attention are used to highlight important words. • DSA-attended LA and LA-attended DSA co-attention networks are constructed. • Historical attention is taken advantage of to learn the label history information. • Our code is available at https://github.com/sgysgywaityou/LAHA. [ABSTRACT FROM AUTHOR]

[Display omitted] • The factors affecting interfacial polymerization are analyzed. • Several types of cyclodextrin membranes are discussed. • The improvement of cyclodextrin membrane performance is highlighted. • The separation applications of cyclodextrin membranes are outlined. • The challenges and opportunities of cyclodextrin membranes are summarized. Cyclodextrin has a unique hydrophobic cavity and hydrophilic outer surface. The membrane formed by cyclodextrin polymerization has high permeability to both polar and non-polar solvents. Through interfacial polymerization, cyclodextrins can be arranged in an orderly manner to form a membrane with well-defined sub-nanometre channels. In 2022, the sub-nanometre channels in cyclodextrin membranes were visualized, providing ample confidence for precise channel design and precise molecular sieving. This article reviews the development of cyclodextrin membranes in the past decade from the aspects of interfacial polymerization, classification, performance improvement, and application. The focus was on introducing methods to improve the selectivity, permeability, chemical stability, anti-fouling, and chlorine resistance of cyclodextrin membranes. Finally, some issues and development prospects in the application of cyclodextrin membranes were discussed. We hope this review can provide guidance for the development of high-performance membranes to meet the urgent need for sustainable separation. [ABSTRACT FROM AUTHOR]

Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-023-32502-x, published online 11 April 2023 The original version of this Article contained errors in Figure 7, where panel ( B a b ) was a duplication of panel ( B b b ). Graph: Figure 7EDS spectrum of (a) BC, BC-NaHA, BC-HA; (b) BC + Ni, BC-NaHA + Ni, BC-HA + Ni. [Extracted from the article]

Background and Purpose: In non-small-cell lung carcinoma (NSCLC) patients, the L858R/T790M mutation of the epithelial growth factor receptor (EGFR) is a major cause of acquired resistance to EGFR-TKIs treatment that limits their therapeutic efficacy. Identification of drugs that can preferentially kill the NSCLC harbouring L858R/T790M mutation is therefore critical. Here, we have evaluated the effects of ursolic acid, an active component isolated from herbal sources, on erlotinib-resistant H1975 cells that harbour the L858R/T790M mutation.Experimental Approach: Gene expression omnibus (GEO) profiles analyses was applied to detect differentially expressed genes in NSCLC cells harbouring EGFR mutation. AnnexinV-FITC/PI, TUNEL staining, MTT, wound healing, RT-PCR, qRT-PCR, western blots, immunostaining, dual-luciferase reporters and ChIP-PCR were utilized to investigate the effects of ursolic acid in vitro and in vivo.Key Results: The cancer/testis antigen family 45 member A2 (CT45A2) was highly expressed in H1975 cells. Ectopic expression of CT45A2 in H1975 cells increased cell proliferation and motility in vitro. Silencing the CT45A2 expression strongly attenuated H1975 cells motility and growth. The anti-cancer effect of ursolic acid was critically dependent on CT45A2 expression in H1975 cells. Ursolic acid suppressed CT45A2 gene transcription mediated by transcriptional factor TCF4 and β-catenin signalling.Conclusions and Implications: CT45A2 is a novel oncogene for NSCLC with an EGFR T790 mutation. Ursolic acid induced apoptosis and inhibited proliferation of H1975 cells by negatively regulating the β-catenin/TCF4/CT45A2 signalling pathway. Therefore, ursolic acid may be a potential candidate treatment for NSCLC harbouring the EGFR-L858R/T790M mutation. [ABSTRACT FROM AUTHOR]

Urban waterlogging and nonpoint source (NPS) pollution caused by urbanization have considerably increased, and their control effects are affected by many factors. This study established a distribution model to analyze the influences of different rainfall conditions and rain garden layouts on runoff output and NPS pollution. Simulation results showed that (a) the reduction rates of the runoff and pollution load decreased from 45% to 23% and from 57% to 23% with increasing rainfall duration (1–24 hr). The flow and concentration peaks, total discharge amount and load increased, and the reduction rates of the runoff and pollution load decreased from 47% to 32% and from 60% to 21%, respectively, with increasing recurrence period (1–50 annual). The changes in the rain peak coefficient had minimal reduction effect on water quantity and quality. (b) Under different rain garden layouts, the reduction rates of the runoff and pollution load were 37%–52% and 13%–57%, respectively. The reduction effects of the runoff and pollution load improved, whereas amplitudes decreased with increasing rain garden layouts (0%–4%). (c) Rainfall duration and rain garden proportion greatly influenced the runoff and load reductions, respectively. Practitioner points: The reduction effects of runoff and pollution load under different rainfall conditions were simulated and analyzed.The reduction effects of runoff and pollution load under different setting proportions of rain garden were simulated and analyzed.The influence degrees of different design conditions on water quantity and quality reduction rates were evaluated. [ABSTRACT FROM AUTHOR]

A new thiophene acetylene, named 2,2-dimethyl-4-[5′-(prop-1-ynyl)-2,2′-bithiophen-5-yl]-1,3-dioxolane ( 1), was isolated from the roots of Echinops spinosus, and the structure was elucidated on the basis of oneand two-dimensional NMR (including H, C NMR, DEPT, H-H COSY, HSQC, and HMBC). [ABSTRACT FROM AUTHOR]

Virtual machine placement has great potential to significantly improve the efficiency of resource utilization in a cloud center. Focusing on CPU and memory resource, this paper presents SOWO—a discrete particle swarm optimization-based workload optimization approach to minimize the number of active physical machines in virtual machine placement. The experiment results show the usability and superiority of SOWO. Compared with the OpenStack native scheduler, SOWO decreases the physical machine consumption by at least 50% and increases the memory utilization of physical machine by more than two times. [ABSTRACT FROM AUTHOR]

With the acceleration of urbanization, N pollution in rainfall runoff has become the primary cause of eutrophication. In order to control N pollution in rainfall runoff, green infrastructure (GI) has been widely implemented. However, little is known about the process through which plants, especially woody plants, affect N distribution and the microecosystem in GI. Limited information suggests that woody plants mainly affect N distribution and alter the microecosystem through the influence of their roots. Therefore, laboratory tests were conducted to investigate the roles of the taproot plant Sophora japonica and the fibrous root plant Malus baccata and the resultant changes at the microecosystem level regarding N removal in a column-scale GI. After one year of growth, analysis of the morphological traits of the roots revealed that the average root length and diameter of S. japonica were approximately 2.3 and 1.8 times greater than those of M. baccata , respectively. An investigation of microbial diversity revealed that in comparison to the control GI system without plants, the GI systems with S. japonica and M. baccata hosted 45.68% and 59.88% more Actinobacteria, respectively. Further, the soil urease (S-UE) activities in the GI systems with S. japonica and M. baccata were 13.6% and 98.8% higher than that in the control, respectively, and the soil acid protease (S-ALPT) activities were 20.5% and 25.4% higher than that in the control, respectively. Compared to the control and the S. japonica GI system, the NH 3 –N content in the soil of the M. baccata GI was 94.4% and 15.2% lower, respectively, and the NO 3 –N content was 57.3% and 12.7% lower, respectively. The M. baccata GI system had the lowest NH 3 –N and NO 3 –N contents because it was most abundant in Actinobacteria and Arthrobacter and had the highest S-UE and S-ALPT activities. The results may be useful for improving N removal in GI containing different woody plants, and by extension for improving control of N pollution from rainfall runoff. [Display omitted] • The root traits of S. japonica and M. baccata were significantly different. • A green infrastructure system with M. baccata had the highest microbial diversity. • NO 3 –N and NH 3 –N were lower in green infrastructure with trees. • Hydrolase activities were higher in green infrastructure with trees. • The abundances of Actinobacteria and Arthrobacter are greater in soil with trees. [ABSTRACT FROM AUTHOR]

A novel, metal ion-assisted drug-loading model, in which the metal ion was used to modify the microstructure of DPPC bilayers, has been developed to improve the drug-loading efficiency of cisplatin thermosensitivity liposomes. The reactions of dipalmitoyl phosphatidylcholine (DPPC) with diverse metal ions (Zn 2+ , Cu 2+ , Mn 2+ and Mg 2+ ) yield four typical liposomes, which have been characterized by FT-IR, Raman and fluorescence techniques; the mechanism for higher drug encapsulation efficiency has also been investigated. In these prepared liposomes, the conformation of DPPC is changed due to the electrostatic interaction between the metal ions and phospholipid acyl group, leading to a closer arrangement of the lipid hydrocarbon chains and higher T m of DPPC. As a result, the encapsulation efficiency of metal ion-assisted loading liposome is significantly higher than that of metal ion-free state. While for the release time, all four metal ion-assisted liposomes could be released within 10 min at 42 ± 0.5 °C, which approach to the phase transition temperature, indicating that the introduction of metal ions into the DPPC bilayer membranes has no influence on the thermosensitivity of the liposome. Furthermore, the higher cytotoxicity of metal ion-bounded liposomes than that of free cisplatin solution suggests that high encapsulation efficiency can cause cytotoxicity increase. Hence, this work highlighted that metal ion-assisted loading model increased the encapsulation efficiency and cell cytotoxicity of cisplatin in thermosensitive liposomes with no obvious effects on sustained and temperature-dependent drug release. [ABSTRACT FROM AUTHOR]

Finger-vein recognition has been widely explored for biometrics security over the past two or three decade. Its size and characteristics against presentation attacks make it suitable for various commercial, governmental and forensics applications. As with other biometric traits, finger-vein recognition approaches mainly depend on well-engineering feature descriptors and recently, more deep learning (DL) models have been designed to achieve high-performance biometrics. However, the existing DL approaches usually employ the neural networks with increasing layers and parameters, which inevitably leads to an increase in memory consumption and algorithm complexity. Besides, all the vein recognition networks use square filters, which are influenced by network designed for object detection and classification. In this paper, two network design issues for finger-vein recognition are explored: shallow network using rectangular filters and lightweight semi-pretrained network. The exhaustive experiments on three benchmark databases HKPU, FV-USM and SDUMLA demonstrate that rectangular filters outperform square filters for DL-based finger-vein recognition, and the lightweight semi-pretrained network also outperforms non-pretrained network. [ABSTRACT FROM AUTHOR]

• Field performance data were obtained for four typical LID facilities. • Exceedance probabilities of effluent concentration is reduced obviously. • The weighted annual load reduction is more than 60% and stable. • An estimation method for LID extent and cost in urban built-up areas is proposed. Field studies are valuable because of the insufficient number of field performance data in low-impact development (LID)-related research. Four typical LID facilities in northwest China were built and monitored. These facilities differ in their impervious/pervious bottom, inflow underlying surface, media types, and combinations. The water volume reduction of impervious rain garden filled with native loess decreases by approximately 20% when the total daily rainfall levels gradually increase from light to heavy. Several technical measures, such as media modification, setting internal storage area, reducing drainage area, and increasing media thickness, have been taken to improve the runoff regulation effect. The volume reduction rate in light and medium-sized rainfall (daily rainfall totals < 25 mm) is above 68.2% for two improved facilities, namely, mixed media rain garden and layered media bioswale. For impervious native loess rain garden, mixed media rain garden, and layered media bioswale, the median values of inflow total suspended solid (TSS) event mean concentrations (EMC) are reduced from 43.5 to 68.5 mg/L to 22.4–24.3 mg/L. In accordance with the Class IV limits of Surface Water Environmental Quality Standards (total nitrogen (TN) = 1.5 mg/L; total phosphorus (TP) = 0.3 mg/L), the probabilities of the effluent TN concentration exceeding the IV limit are 32.7%, 42.3%, and 19.8% for the three facilities. The exceedance probabilities for TP are 18.5%, 6.5%, and 8.9%. The weighted results indicate that the annual load reduction rate is more stable than the fluctuating concentration removal, which is above 60%. An approach to estimate the total scale of LID construction was established on the basis of rainfall level proportion, land use types, and monitored data. When native loess and mixed media rain garden are applied in building areas and layered media bioswale is applied in road area, the LID implementation cost is approximately 36.0 billion CNY until 2030 for Xi'an City. [ABSTRACT FROM AUTHOR]