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Cooking quality is the main factor determining the market value of rice. Although several major genes and a certain number of QTLs controlling cooking quality have been identified, the genetic complexity and environmental susceptibility limit the further improvement for cooking quality by molecular breeding. This research conducted a genome-wide association study to elucidate the QTLs related to cooking quality including amylose content (AC), gel consistency (GC) and alkali spreading value (ASV) by using 450 rice accessions consisting of 300 indica and 150 japonica accessions in two distinct environments. A total of 54 QTLs were identified, including 25 QTLs for AC, 12 QTLs for GC and 17 QTLs for ASV. Among them, 10 QTLs were consistently observed by the same population in both environments. Six QTLs were co-localized with the reported QTLs or cloned genes. The Wx gene for AC and GC, and the ALK gene for ASV were identified in every population across the two environments. The qAC9-2 for AC and the qGC9-2 for GC were defined to the same interval. The OsRING315 gene, encoding an E3 ubiquitin ligase, was considered as the candidate gene for both qAC9-2 and qGC9-2. The higher expression of OsRING315 corresponded to the lower AC and higher GC. Three haplotypes of OsRING315 were identified. The Hap 1 mainly existed in the japonica accessions and had lower AC. The Hap 2 and Hap 3 were predominantly present in the indica accessions, associated with higher AC. Meanwhile, the GC of accessions harboring Hap 1 was higher than that of accessions harboring Hap 3. In addition, the distribution of the three haplotypes in several rice-growing regions was unbalanced. The three traits of cooking quality are controlled by both major and minor genes and susceptible to environmental factors. The expression level of OsRING315 is related to both AC and GC, and this gene can be a promising target in quality improvement by using the gene editing method. Moreover, the haplotypes of OsRING315 differentiate between indica and japonica, and reveal the differences in GC and AC between indica and japonica rice. [ABSTRACT FROM AUTHOR]

Transformer is widely used in natural language processing (NLP) tasks due to the parallel and modeling of long texts. However, its performance in Chinese named entity recognition (NER) is not effective. While distance, direction, and information on global and local perspectives of sequence are all important for NER tasks, the traditional transformer structure only focus on distance and partial global information by fully connected self-attention mechanism. In this paper, we propose a multi-view and sliding attention (MVSA) model to enhance transformer's ability to model Chinese character-word features in NER task. MVSA combines directional information to extract character-word features from multiple views, proposes a weighted ternary fusion method for feature fusion and uses slider attention mechanisms to enhance the local representation ability of the model. Experiments on five Chinese NER datasets show that MVSA achieves superior performance than CNN-based, LSTM-based and traditional transformer-based models. [ABSTRACT FROM AUTHOR]

Abstract Aberrant localization of proteins to mitochondria disturbs mitochondrial function and contributes to the pathogenesis of Huntington’s disease (HD). However, the crucial factors and the molecular mechanisms remain elusive. Here, we found that heat shock transcription factor 1 (HSF1) accumulates in the mitochondria of HD cell models, a YAC128 mouse model, and human striatal organoids derived from HD induced pluripotent stem cells (iPSCs). Overexpression of mitochondria‐targeting HSF1 (mtHSF1) in the striatum causes neurodegeneration and HD‐like behavior in mice. Mechanistically, mtHSF1 facilitates mitochondrial fission by activating dynamin‐related protein 1 (Drp1) phosphorylation at S616. Moreover, mtHSF1 suppresses single‐stranded DNA‐binding protein 1 (SSBP1) oligomer formation, which results in mitochondrial DNA (mtDNA) deletion. The suppression of HSF1 mitochondrial localization by DH1, a unique peptide inhibitor, abolishes HSF1‐induced mitochondrial abnormalities and ameliorates deficits in an HD animal model and human striatal organoids. Altogether, our findings describe an unsuspected role of HSF1 in contributing to mitochondrial dysfunction, which may provide a promising therapeutic target for HD.

Cultivating rice varieties with robust blast resistance is the most effective and economical way to manage the rice blast disease. However, rice blast disease comprises leaf and panicle blast, which are different in terms of resistance mechanisms. While many blast resistant rice cultivars were bred using genes conferring resistance to only leaf or panicle blast, mining durable and effective quantitative trait loci (QTLs) for both panicle and leaf blast resistance is of paramount importance. In this study, we conducted a pangenome-wide association study (panGWAS) on 9 blast resistance related phenotypes using 414 international diverse rice accessions from an international rice panel. This approach led to the identification of 74 QTLs associated with rice blast resistance. One notable locus, qPBR1, validated in a F4:5 population and fine-mapped in a Heterogeneous Inbred Family (HIF), exhibited broad-spectrum, major and durable blast resistance throughout the growth period. Furthermore, we performed transcriptomic analysis of 3 resistant and 3 sensitive accessions at different time points after infection, revealing 3,311 differentially expressed genes (DEGs) potentially involved in blast resistance. Integration of the above results identified 6 candidate genes within the qPBR1 locus, with no significant negative effect on yield. The results of this study provide valuable germplasm resources, QTLs, blast response genes and candidate functional genes for developing rice varieties with enduring and broad-spectrum blast resistance. The qPBR1, in particular, holds significant potential for breeding new rice varieties with comprehensive and durable resistance throughout their growth period. [ABSTRACT FROM AUTHOR]

Strong seedling vigor is imperative to achieve stable seedling establishment and enhance the competitiveness against weeds in rice direct seeding. Shoot length (SL) is one of the important traits associated with seedling vigor in rice, but few genes for SL have been cloned so far. In the previous study, we identified two tightly linked and stably expressed QTLs for SL, qSL-1f and qSL-1d by genome-wide association study, and cloned the causal gene (LOC_Os01g68500) underlying qSL-1f. In the present study, we identify LOC_Os01g66100 (i.e. the semidwarf gene SD1), a well-known gene controlling plant height (PH) at the adult-plant stage, as the causal gene underlying qSL-1d through gene-based haplotype analysis and knockout transgenic verification. By measuring the phenotypes (SL and PH) of various haplotypes of the two genes and their knockout lines, we found SD1 and LOC_ Os01g68500 controlled both SL and PH, and worked in the same direction, which provided the directly genetic evidence for a positive correlation between SL and PH combined with the analysis of SL and PH in the diverse natural population. Moreover, the knockout transgenic experiments suggested that SD1 had a greater effect on PH compared with LOC_ Os01g68500, but no significant difference in the effect on SL. Further investigation of the pyramiding effects of SD1 and LOC_Os01g68500 based on their haplotype combinations suggested that SD1 may play a dominant role in controlling SL and PH when the two genes coexist. In this study, the effect of SD1 on SL at the seedling stage is validated. In total, two causal genes, SD1 and LOC_ Os01g68500, for SL are cloned in our studies, which controlled both SL and PH, and the suitable haplotypes of SD1 and LOC_ Os01g68500 are beneficial to achieve the desired SL and PH in different rice breeding objectives. These results provide a new clue to develop rice varieties for direct seeding and provide new genetic resources for molecular breeding of rice with suitable PH and strong seedling vigor. [ABSTRACT FROM AUTHOR]

Social network rumor harm metric is a task to score the harm caused by a rumor by analyzing the spreading range of the rumor, the users affected, the repercussions caused, etc., and then the harm caused by the rumor. Rumor hazard metric models can help rumor detection digital twins to understand and analyze user behaviors and assist social network network managers to make more informed decisions. However, there is a lack of models that can quantify the harm of rumors and automated harm metric models in rumor detection digital twins. To address this issue, this paper proposes an innovative social network rumor harm metric based on rumor propagation knowledge and a large language model (LLM), RSK-T5. The method first completes the joint task of rumor comment stance detection and sentiment analysis to capture critical features of rumor propagation. Then, this knowledge is used in the pre-training process of LLM to improve the model's understanding of rumor propagation patterns. Finally, the fine-tuning phase focuses on the hazard metrics task to improve the generalization energy. We compare with some existing variants of rumor detection methods, and experimental results demonstrate that RSK-T5 achieves the lowest MSE scores on three well-known rumor detection datasets. The ablative learning work demonstrates the effectiveness of RSK-T5's knowledge of two rumor spreads. [ABSTRACT FROM AUTHOR]

This article explores the chemical constituents of Salvia cavaleriei var. simplicifolia, a plant used for medicinal purposes by the Miao and Dong nations in Guizhou Province, China. The researchers isolated seven compounds from the plant, including dehydrodiisoeugenol and 14-formyl-2,7-dihydroxycadalene, which were isolated from the Salvia genus for the first time. The article provides detailed information about the extraction and purification processes used to obtain these compounds. The compounds were analyzed using nuclear magnetic resonance spectroscopy, and their structures and characteristics were determined. Some of the compounds showed potential hemostatic activity. The research was supported by various funding sources. [Extracted from the article]

Triclosan (TCS) has been regarded as an emerging contaminant in aquatic systems, making its efficient removal of great significance. In this study, NPVMo@iPAF-1, with a specific surface area of 665 m2/g, was prepared by incorporating (NH4)5H6PV8Mo4O40 into porous aromatic frameworks (PAF). The maximum adsorption capacity of TCS on NPVMo@iPAF-1 reached 917.1 mg/g, as calculated from the Langmuir model. Fixed-bed columns packed with NPVMo@iPAF-1 were employed for TCS removal; the experiment data strongly correlated with the Thomas and Yoon-Nelson models under different operational conditions. Pore preservation, electrostatic effects, and the synergistic effect of π-π interactions contributed to the effective adsorption of TCS onto NPVMo@iPAF-1. The NPVMo@iPAF-1 fixed-bed column could be effectively regenerated through in-situ ozonation for more than 10 regeneration cycles. NPVMo@iPAF-1 turned out to be a promising adsorbent for removing TCS not only from pure water but also from reclaimed water and surface water samples. [ABSTRACT FROM AUTHOR]

Key message: Genome-wide association mapping revealed a novel QTL for shoot length across multiple environments. Its causal gene, LOC_Os01g68500, was identified firstly through gene-based haplotype analysis, gene expression and knockout transgenic verification. Strong seedling vigor is an important breeding target for rice varieties used in direct seeding. Shoot length (SL) is one of the important traits associated with seedling vigor characterized by rapid growth of seedling, which enhance seedling emergence. Therefore, mining genes for SL and conducting molecular breeding help to develop varieties for direct seeding. However, few QTLs for SL have been fine mapped or cloned so far. In this study, a genome-wide association study of SL was performed in a diverse rice collection consisting of 391 accessions in two years, using phenotypes generated by different cultivation methods according to the production practice, and a total of twenty-four QTLs for SL were identified. Among them, the novel QTL qSL-1f on chromosome 1 could be stably detected across all three cultivation methods in the whole population and indica subpopulation. Through gene-based haplotype analysis of the annotated genes within the putative region of qSL-1f, and validated by gene expression and knockout transgenic experiments, LOC_Os01g68500 (i.e., Os01g0913100 in RAP-DB) was identified as the causal gene for SL, which has a single-base variation (C-to-A transversion) in its CDS region, resulting in the significant difference in SL of rice. LOC_Os01g68500 encodes a DUF538 (Domain of unknown function) containing protein, and the function of DUF538 protein gene on rice seedling growth is firstly reported in this study. These results provide a new clue for exploring the molecular mechanism regulating SL, and promising gene source for the molecular breeding in rice. [ABSTRACT FROM AUTHOR]

Efficient exploration technology leads to the rapid growth of seismic acquisition data; how to improve the big shot I/O efficiency has a direct impact on field acquisition speed. Considering the construction environment and actual requirements of the field acquisition operation site, this study proposes a two-level index method for a big shot to improve its I/O speed by thoroughly studying the storage structure of the shot file. This method instantly locates the boundary location of any full shot, arrangement, and any trace of massive shot files through the two-level index and eliminates the time to find a shot or trace in order, to realize the rapid reading of shot, arrangement, or trace data. The practical application shows that this method greatly improves the efficiency of searching the starting position of a shot in the file, thereby improving the I/O speed of the big shot and laying the groundwork for comprehensively improving the field quality control efficiency and data processing efficiency of field seismic acquisition. [ABSTRACT FROM AUTHOR]

Fine particulate matter ( P M 2.5 ) poses a significant threat to human life and health, and therefore, accurately predicting P M 2.5 concentration is critical for controlling air pollution. Two improved types of recurrent neural networks (RNNs), the long short-term memory (LSTM) and gated recurrent unit (GRU), have been widely used in time series data prediction due to their ability to capture temporal features. However, both degrade into random guessing as the time length increases. In order to enhance the accuracy of P M 2.5 concentration prediction and address the issue of random guessing in RNNs neural networks, this study introduces a TCN-biGRU neural network model. This model is a hybrid prediction approach based on combining temporal convolutional networks (TCN) and bidirectional gated recurrent units (bi-GRU). TCN extracts higher-level feature information from longer time series data of P M 2.5 concentrations, while bi-GRU captures features from past and future data to achieve more accurate predictive outcomes. This case study utilizes data from monitoring stations in Beijing in 2021 for conducting P M 2.5 prediction experiments. The TCN-biGRU model achieves an average absolute error, root mean square error, and R 2 of 4.20, 7.71, and 0.961 in its predictive outcomes. When compared to the predictive outcomes of individual LSTM, GRU, and bi-GRU models, it is evident that the TCN-biGRU model exhibits smaller errors and superior predictive performance. [ABSTRACT FROM AUTHOR]

The development of a simple and sensitive electrochemical sensing platform for levofloxacin (LVF) analysis is of great significance to human health. In this work, a covalent organic framework (TP-COF) was in situ grown on the surface of Sn-MoC nanospheres with nanoflower-like morphology through a one-pot method to obtain the TP-COF@Sn-MoC composite. The prepared composite was used to modify a glassy carbon electrode (GCE) to realize the sensitive detection of levofloxacin. TP-COF was formed by polycondensation of 2,4,6-tris(4-aminophenyl)-1,3,5-triazine (TAPT) and pyromellitic dianhydride (PMDA), in which C = O and C = N groups served as double active centers for the recognition and electrocatalytic oxidation of the target molecule. Meanwhile, the introduction of Sn-MoC improved the conductivity of the electrode. The TP-COF@Sn-MoC composite produced a strong synergistic effect and showed a high electrocatalytic ability toward levofloxacin oxidation. The linear range of LVF was 0.6–1000 μM and the limit of detection (LOD) was 0.029 μM (S/N = 3). In addition, the sensor has been successfully applied for the analysis of LVF in human urine and blood serum samples with acceptable recovery rates, demonstrating that the sensor was promising in practical applications. [ABSTRACT FROM AUTHOR]

Azide polymers are currently a major research hotspot in the field of energetic materials, with the advantages of high energy, low sensitivity and good thermal stability. A series of new azide polymer-modified nitrocellulose (NC) spherical powder were prepared by the internal solution method with introducing different azide polymers (GAP, GAPA, GAPE, and GAP-ETPE) into NC. The effect of different azide polymers on the performance of NC spherical powder was investigated. The addition of azide polymers led to a decrease in the average particle size of the spherical powder. The addition of azide polymer substantially reduced the mechanical sensitivities of NC spherical powder and improved their thermal stability. The critical temperature of thermal explosion (Tb) and self-accelerated decomposition temperature (TSADT) of the modified spherical powder were 5~10 °C higher than those of the NC spherical powder. Meanwhile, the mechanical sensitivities of the azide polymer-modified spherical powder were significantly reduced, in which the impact sensitivity was reduced by about 30.3%~65.3%, and the friction sensitivity was reduced by about 23.3%~41.1%. Therefore, the azide polymer-modified spherical powder have more excellent thermal stability and safety performance, and probably have a broader application prospect. [ABSTRACT FROM AUTHOR]

Anchor link prediction across social networks is highly important for multiple social network analysis. Traditional methods rely heavily on user-generated information or the quality of network topology information and are not suitable for real-life multiple social networks. Deep learning methods based on graph embedding are limited by the latent similarity of the associated nodes in a single network and the overlap between different networks used for projections of multiple network feature spaces. In this paper, we propose a novel method which eliminates overlapping restriction. The proposed method consists of two phases. First, graph embedding with reconciliation of similarity and distinction is used to obtain an effective embedding vector space. Second, cross-network features for supervised learning are constructed via cross-network feature mining based on collisions between the features of nodes belonging to different networks. The combination of similarity reduction and cross-network feature collisions alleviates the restriction on overlapping parts. Extensive experiments on large-scale real-life social networks demonstrate that the proposed method significantly outperforms the state-of-the-art methods in terms of both precision and robustness. [ABSTRACT FROM AUTHOR]

Long time exposure to indoor air pollution environments can increase the risk of cardiovascular and respiratory system damage. Most previous studies focus on outdoor air quality, while few studies on indoor air quality. Current neural network-based methods for indoor air quality prediction ignore the optimization of input variables, process input features serially, and still suffer from loss of information during model training, which may lead to the problems of memory-intensive, time-consuming and low-precision. We present a novel concurrent indoor PM prediction model based on the fusion model of Least Absolute Shrinkage and Selection Operator (LASSO) and an Attention Temporal Convolutional Network (ATCN), together called LATCN. First, a LASSO regression algorithm is used to select features from PM1, PM2.5, PM10 and PM (>10) datasets and environmental factors to optimize the inputs for indoor PM prediction model. Then an Attention Mechanism (AM) is applied to reduce the redundant temporal information to extract key features in inputs. Finally, a TCN is used to forecast indoor particulate concentration in parallel with inputting the extracted features, and it reduces information loss by residual connections. The results show that the main environmental factors affecting indoor PM concentration are the indoor heat index, indoor wind chill, wet bulb temperature and relative humidity. Comparing with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) approaches, LATCN systematically reduced the prediction error rate (19.7% ~ 28.1% for the NAE, and 16.4% ~ 21.5% for the RMSE) and improved the model running speed (30.4% ~ 81.2%) over these classical sequence prediction models. Our study can inform the active prevention of indoor air pollution, and provides a theoretical basis for indoor environmental standards, while laying the foundations for developing novel air pollution prevention equipment in the future. [ABSTRACT FROM AUTHOR]

A novel electrochemical biosensor with excellent performance was fabricated for levofloxacin (LEV) detection, which adopted triangular Ag nanoplates (Tri-AgNP) confined in a poly-L-cysteine (poly-L-Cys) film and a semiconducting covalent organic framework (COF) as the electrochemical sensing material. The developed electrochemical sensor revealed excellent analytical properties because of its good electrical conductivity, fast electron transfer, and abundant bioactive site. Based on this, a linear relationship between the LEV concentration and the peak current response at 0.92 V was obtained under the optimal experimental conditions by differential pulse voltammetry (DPV), with a wide linear range of 0.05 to 600 μM and a low limit of detection (LOD) of 0.0061 μM. The prepared sensor also realized sensitive and accurate determination of LEV in human serum and urine samples by standard addition method, with satisfactory recoveries (97.1 to 104%) and a low relative standard deviation of less than 4.6%. These results indicated that the novel ternary system has a promising application in the development of electrochemical signal probe and electrochemical biosensing platform. [ABSTRACT FROM AUTHOR]

Epilepsy is a chronic brain disease and often occurs suddenly for no reason. Eucommiae folium (EF), an edible herb, can be used in the treatment of various kinds of brain diseases in clinic. From the perspective of safety and efficacy, EF is especially suitable for the treatment of chronic brain diseases. With the help of biolabels, this study was aimed to explore the value and feasibility of EF in the treatment of epilepsy. Proteomics and metabolomics were used to explore the biolabels of EF intervention in brain tissues. Bioinformatics was then applied to topologically analyze its neuroprotective effects and mechanisms and material basis based on biolabels, which were validated in an animal model. The biolabel-led research revealed that EF may exert the therapeutic potential to treat brain diseases through the interaction between multiple compounds and multiple targets, among which its therapeutic potential for epilepsy is particularly prominent. In the pentylenetetrazole-induction model, EF and four active compounds (oleamide, catechol, chlorogenic acid, and kaempferol) protected epileptic hippocampal neurons (Nissl and FJB staining) against mitochondrial dysfunction (MYH6, MYL3, and MYBPC3, etc.) and calcium overload (TNNI3, TNNC1, and TNNT2, etc.) through the hypertrophic cardiomyopathy pathway. This study provides new evidence and insights for the neuroprotective effects of EF, in which four active compounds may be potential drug candidates for the treatment of epilepsy. [ABSTRACT FROM AUTHOR]

Erythritol is a novelty 4-carbon sugar polyol and has great potential to be used as the precursor of some platform chemicals. The increasing cost of glucose poses researchers shifting insights to the cheaper biodiesel raw materials. Herein, we engineered a non-degradation, non-byproducts Yarrowia lipolytica for the erythritol production with high-titer from glycerol. Initially, the degradation and competition modules were blocked by URA3 counter-selection marker. Subsequently, a shortened biosynthetic pathway was explored to elevate its synthetic flux by multi-modules combination expression of functional genes. Furthermore, a screened glycerol transporter ScFPS1 was integrated into ERY6 genome to promote the glycerol uptake. The constructed strain ERY8 produced 176.66 g/L erythritol in the 5-L bioreactor with a yield and productivity of 0.631 g/g and 1.23 g/L/h, respectively, which achieved the highest fermentation production efficiency till date. This study proposed a novel multi-modules combination strategy for effectively engineering Y. lipolytica to produce erythritol using glycerol. [ABSTRACT FROM AUTHOR]

Low-cost and high-performance bifunctional electrocatalysts for efficient oxygen reduction reaction (ORR)/oxygen evolution reaction (OER) are vital for the applications of rechargeable Zn-air batteries (ZABs). Herein, a porous carbon material is fabricated by traditional pulp and papermaking and carbonization process from bamboo. The resultant carbon paper catalyst possesses a high surface area, porous structure, and high content of nitrogen. Benefiting from these characteristics, this material exhibits remarkable ORR and OER catalytic performances. The aqueous rechargeable Zn-air batteries assembled with this catalyst exhibit a high power density of 279.5 mW cm−2. This work paves an encouraging way for the industrial production of cost-effective catalysts in a sustainable manner. [ABSTRACT FROM AUTHOR]

The track random irregularity not only worsens the running stability and smoothness of the rack vehicle, but increases the vibration and impact of the gear-rack system. To reduce the influence of track random irregularity on the dynamic characteristics of rack vehicle, the sensitivity of rack vehicle to track irregularity is studied based on the rack vehicle-track(rack)-coupled dynamic model (RVTM). Firstly, the effectiveness and accuracy of RVTM are verified through engineering tests. Then, according to the generation principle of track irregularity, the influence mechanism of irregularity on the dynamic meshing behavior of gear-rack system is analyzed. The results show that the track random irregularity has a great influence on the vibration of the rack vehicle. The vibration of the rack vehicle mainly comes from the track random irregularity. The vertical and longitudinal vibration of the gear-rack system is less affected by the irregularity excitation, while the lateral vibration is significantly affected. The gear-rack system is less sensitive to irregularity I (vertical irregularity and roll irregularity) and has a strong response to irregularity II (lateral irregularity and gauge irregularity). Therefore, it is suggested to improve the stability of the gear-rack system by reducing the track irregularity II to ensure the safe and smooth operation of the rack vehicle. RVTM is validated in this paper, which can be effectively used in the dynamics research of rack railway and optimizes the running performance of rack vehicle. The research on the dynamic response of the rack vehicle to the track irregularity provides an important theoretical basis for improving the stability of the rack vehicle and can provide a reference for the design and evaluation of the rack railway. [ABSTRACT FROM AUTHOR]

This paper investigates fixed-time stabilization of linear two-time-scale systems. The existing fixed-time control techniques are no longer applicable due to the inherent ill-conditioned numerical issues, which is induced by the time-scale separation of two-time-scale systems when carrying out stability analysis. Alternative challenge is that the considered systems are not fully actuated, such that some full rank conditions regarded to the control matrix do not hold anymore. All of these pose difficulties to the fixed-time controller design and stability analysis. To handle these issues, appropriate state transformations are proposed to decouple the system into slow and fast subsystems with approximate strict feedback structure. Then, by the backstepping method, a continuous-time controller is designed to achieve fixed-time stabilization. Furthermore, a Zeno-free event-triggered strategy is proposed to reduce the control updates and then a practical stability result of two-time-scale systems is obtained. A numerical simulation is presented to illustrate the effectiveness of the results. [ABSTRACT FROM AUTHOR]

A substrate is one critical factor for the wide application of flexible displays and electronic packaging materials in the future. Polyimides with high optical transparency, good thermal stability, dielectric properties, and nice mechanical properties are significant in substrates. A simple and feasible method to modify transparent polyimide films is to blend them with inorganic fillers. In this work, we successfully modified the transparent films by using phenyltriethoxysilane to synthesize trisilanol phenyl polyhedral silsesquioxane and adding it to the films. The introduction of trisilanol phenyl polyhedral silsesquioxane into the copolymer films resulted in the increase of high-temperature dimensional stability, optical performance, and mechanical properties of the films. The sample containing 5% of trisilanol phenyl polyhedral silsesquioxane exhibited a glass transition temperature of 322°C, coefficient of thermal expansion of 41.4 ppm/K, and tensile strength of 127 MPa, and the transmittance at 450 nm has reached 83.5%. [ABSTRACT FROM AUTHOR]

Transparent polyimide films with excellent comprehensive properties may be indispensable to next-generation optoelectronic and flexible display applications. To date, the most studied transparent polyimide films are mainly prepared with alicyclic dianhydride as monomer, but the related properties of such films are not satisfactory. In this work, two series of highly optically transparent copolyimide films were prepared by the polycondensation of dicyclohexyl-3,4,3',4'-tetracarboxylic dianhydride, 1,2,4,5-cyclohexane-tetracarboxylic dianhydride, 4,4'-(hexafluoroisopropylidene) diphthalic anhydride with 4,4'-oxydianiline via a facile one-step method. Through the optimization of structure and composition, the relationship between structure and properties of copolymerized semi-alicyclic polyimide was studied. The prepared copolyimide films show good thermal stability: glass transition temperatures in the range of 264–315°C and 5% weight loss temperature of 463–527°C, superior optical transparency up to 90%. Specifically, these copolyimide films have tensile strength greater than 90.3 MPa. [ABSTRACT FROM AUTHOR]

Given the poor mechanical properties of traditional adhesive hydrogels, many pieces of research have been focused on the preparation of adhesive hydrogels with good mechanical properties and expanded their application. In this study, a novel multifunctional adhesive hydrogel acrylated adenine/chitosan/polyacrylamide/ Fe(III)(Aa/CS/PAM/Fe(III)) hydrogels were prepared by a chemical and physical hybrid crosslinking strategy. The hydrogels can adhere to various solid substrate surfaces and show good mechanical properties. The highest adhesion strength of the hydrogel to wood reached 11.17 kPa with the fracture stress being 0.11 MPa and the toughness 0.84 MJ/m3. The hydrogels can be stretched to more than 1400% of their original length without breaking. Additionally, the hydrogels also have good repetitive adhesion and fatigue resistance. Due to the presence of Fe3+ and Cl−, hydrogels also have certain electrical conductivity, which can be used in human motion detection. [ABSTRACT FROM AUTHOR]

Through the introduction of green finance policies, governments hope to improve the guiding role of institutional investors in green investment and provide financial support for green enterprises. Using the data in China, the difference-in-difference (DID) analysis explores whether the implementation of policies could change institutional investors' attitude to environmental factors when making investment decisions. Considering the effect of investment horizons, we find that long-term institutional investors have shown symmetric preferences on green investment, while short-term institutions are more affected by green finance policies. Additionally, the mechanism analysis shows that green finance policies can influence the green investment of institutional investors not only by affecting stock price returns but also by increasing the innovation capabilities of green companies and thus improving corporate performance. Besides, heterogeneity and moderating effect analyses find that green finance policies can achieve better policy effects when financial institutions invest in non-state-owned enterprises, enterprises with higher quality of information disclosure and poor external supervision. The finding would extend the studies of green investment in emerging markets and present new evidence about the policy effect on institutions' preferences for green investment. [ABSTRACT FROM AUTHOR]

Background: Grain shape is a key trait in rice breeding. Although many QTLs and genes of grain shape have been identified, how different combinations of alleles of these genes affect grain shape is largely unknown. It is important to understand the effects of grain shape gene combinations for breeding by design. In the present study, we performed genetic dissection of the grain shapes in Guangdong Simiao varieties, a popular kind of rice in South China, to identify the effective alleles and their combination for breeding. Results: We selected two hundred nineteen indica accessions with diverse grain shapes and fifty-two Guangdong Simiao varieties with long and slender grain shapes for genome-wide selection analysis. The results showed that four (GS3, GS5, GW5 and GL7) of the twenty grain shape genes fall into the regions selected for in Guangdong Simiao varieties. Allele analysis and frequency distribution of these four genes showed that GS3allele3 and GW5allele2 accounted for 96.2%, and GL7allele2 and GS5allele2 accounted for 76.9% and 74.5% of the Simiao varieties, respectively. Further analysis of the allelic combinations showed that 30 allelic combinations were identified in the whole panel, with 28 allelic combinations found in the international indica accessions and 6 allelic combinations found in Guangdong Simiao varieties. There were mainly three combinations (combinations 17, 18 and 19) in the Guangdong Simiao varieties, with combination 19 (GS3allele3 + GW5allele2 + GL7allele2 + GS5allele2) having the highest percentage (51.9%). All three combinations carried GS3allele3 + GW5allele2, while combinations 17 (GL7allele1) and 19 (GL7allele2) showed significant differences in both grain length and length/width ratio due to differences in GL7 alleles. Pedigree analysis of Guang8B, the maintainer of the first released Simiao male sterile line Guang8A, showed that the parent lines and Guang8B carried GS3allele3 + GW5allele2 + GS5allele2, while the GL7 allele differed, resulting in significant differences in grain size. Conclusion: The results suggest that specific alleles of GS3, GS5, GW5 and GL7 are the key grain shape genes used in the Guangdong Simiao varieties and selected for grain shape improvement. Combination 19 is the predominant allelic combination in the Guangdong Simiao varieties. Our current study is the first to dissect the genetics of grain shape in Guangdong Simiao varieties, and the results will facilitate molecular breeding of Guangdong Simiao varieties. [ABSTRACT FROM AUTHOR]

Fraction 9 (3.4 g) was purified with Sephadex LH-20 (CH SB 2 sb Cl SB 2 sb -MeOH, 1:1) and silica gel column chromatography (CH SB 2 sb Cl SB 2 sb -EtOAc, 11:1-0:1) to afford compounds B 6 b (20 mg) [[14]] and B 7 b (30 mg) [[15]]. The CH SB 2 sb Cl SB 2 sb fraction was subjected to silica gel column chromatography (CH SB 2 sb Cl SB 2 sb -MeOH, 90:1-0:1) to afford twelve fractions. The PE fraction was subjected to silica gel column chromatography (PE-EtOAc, 20:1-0:1) to afford twelve fractions. Fraction 9 (10 g) was subjected to Sephadex LH-20 (CH SB 2 sb Cl SB 2 sb -MeOH, 1:1) and silica gel column chromatography (CH SB 2 sb Cl SB 2 sb -MeOH, 40:1-1:1) to afford compounds B 3 b (44 mg) [[11]], B 4 b (16 mg) [[12]], and B 5 b (4 mg) [[13]]. [Extracted from the article]

The removal of dye pollutants from dyeing and printing industrial wastewater is a very important issue, and different methods have developed for this purpose. Here, a hydrogel adsorbent gelatin/chitosan/β-cyclodextrin/sodium humate (GEL/CS/β-CD/SH) was developed by a simple method for removal of the reactive dyes in aqueous solutions. The hydrogel used as an adsorbent had a good adsorption to different kinds of organic dyes. In this work, we focused on the adsorption process of GEL/CS/β-CD/SH hydrogels to the cationic dyes methylene blue (MB) and anionic dyes acid fuchsin (AF), which are commonly used in the printing and dyeing industry. The effects of dye solution pH, ionic strength, temperature, and contact time were investigated in a batch system. The adsorption thermodynamic and dynamic behaviors towards AF and MB were investigated in detail. The adsorption process could occur spontaneously at environmental temperature. The results indicated that the maximum adsorption capacity of AF and MB reached 1666.7 mg/g and 714.3 mg/g, respectively. Moreover, the GEL/CS/β-CD/SH hydrogel could be degraded completely by microorganisms in the soil. Therefore, GEL/CS/β-CD/SH hydrogel has a potential application as an effective adsorbent for the treatment of dyeing wastewater. [ABSTRACT FROM AUTHOR]

Aims: Human activities have more than doubled the input of atmospheric reactive nitrogen into terrestrial ecosystems, affecting plant and soil microbial communities. This study aimed to investigate the effect of atmospheric N deposition on the rhizosphere soil microbial community composition of the main plant species with different niches in grassland.An N addition experiment was performed in a semi-arid grassland on the Loess Plateau, China. The experiment consisted of four N addition treatments: N0 (0 g N m−2 yr−1), N3 (3 g N m−2 yr−1), N6 (6 g N m−2 yr−1), and N9 (9 g N m−2 yr−1). The response of rhizosphere soil microbial community composition from four main plant species to atmospheric N deposition was explored.Nitrogen addition significantly affected rhizosphere soil bacterial community composition of Bothriochloa ischaemum and Stipa bungeana but had no effect on that of Artemisia gmelinii and Cleistogenes squarrosa. Furthermore, it also significantly affected rhizosphere soil fungal community composition of S.bungeana; however, no effects were observed on the other three plant species. Compared with the complexity of rhizosphere soil bacterial network, low N addition rates had a greater effect on the complexity of the rhizosphere soil fungal network.This study revealed that rhizosphere soil bacterial community composition of plant species with a higher niche breadth is generally more sensitive to atmospheric N deposition. Our study highlights the distinct roles of plant species with different niche breadths in maintaining rhizosphere soil microbial community composition under conditions of global N enrichment.Methods: Human activities have more than doubled the input of atmospheric reactive nitrogen into terrestrial ecosystems, affecting plant and soil microbial communities. This study aimed to investigate the effect of atmospheric N deposition on the rhizosphere soil microbial community composition of the main plant species with different niches in grassland.An N addition experiment was performed in a semi-arid grassland on the Loess Plateau, China. The experiment consisted of four N addition treatments: N0 (0 g N m−2 yr−1), N3 (3 g N m−2 yr−1), N6 (6 g N m−2 yr−1), and N9 (9 g N m−2 yr−1). The response of rhizosphere soil microbial community composition from four main plant species to atmospheric N deposition was explored.Nitrogen addition significantly affected rhizosphere soil bacterial community composition of Bothriochloa ischaemum and Stipa bungeana but had no effect on that of Artemisia gmelinii and Cleistogenes squarrosa. Furthermore, it also significantly affected rhizosphere soil fungal community composition of S.bungeana; however, no effects were observed on the other three plant species. Compared with the complexity of rhizosphere soil bacterial network, low N addition rates had a greater effect on the complexity of the rhizosphere soil fungal network.This study revealed that rhizosphere soil bacterial community composition of plant species with a higher niche breadth is generally more sensitive to atmospheric N deposition. Our study highlights the distinct roles of plant species with different niche breadths in maintaining rhizosphere soil microbial community composition under conditions of global N enrichment.Results: Human activities have more than doubled the input of atmospheric reactive nitrogen into terrestrial ecosystems, affecting plant and soil microbial communities. This study aimed to investigate the effect of atmospheric N deposition on the rhizosphere soil microbial community composition of the main plant species with different niches in grassland.An N addition experiment was performed in a semi-arid grassland on the Loess Plateau, China. The experiment consisted of four N addition treatments: N0 (0 g N m−2 yr−1), N3 (3 g N m−2 yr−1), N6 (6 g N m−2 yr−1), and N9 (9 g N m−2 yr−1). The response of rhizosphere soil microbial community composition from four main plant species to atmospheric N deposition was explored.Nitrogen addition significantly affected rhizosphere soil bacterial community composition of Bothriochloa ischaemum and Stipa bungeana but had no effect on that of Artemisia gmelinii and Cleistogenes squarrosa. Furthermore, it also significantly affected rhizosphere soil fungal community composition of S.bungeana; however, no effects were observed on the other three plant species. Compared with the complexity of rhizosphere soil bacterial network, low N addition rates had a greater effect on the complexity of the rhizosphere soil fungal network.This study revealed that rhizosphere soil bacterial community composition of plant species with a higher niche breadth is generally more sensitive to atmospheric N deposition. Our study highlights the distinct roles of plant species with different niche breadths in maintaining rhizosphere soil microbial community composition under conditions of global N enrichment.Conclucsions: Human activities have more than doubled the input of atmospheric reactive nitrogen into terrestrial ecosystems, affecting plant and soil microbial communities. This study aimed to investigate the effect of atmospheric N deposition on the rhizosphere soil microbial community composition of the main plant species with different niches in grassland.An N addition experiment was performed in a semi-arid grassland on the Loess Plateau, China. The experiment consisted of four N addition treatments: N0 (0 g N m−2 yr−1), N3 (3 g N m−2 yr−1), N6 (6 g N m−2 yr−1), and N9 (9 g N m−2 yr−1). The response of rhizosphere soil microbial community composition from four main plant species to atmospheric N deposition was explored.Nitrogen addition significantly affected rhizosphere soil bacterial community composition of Bothriochloa ischaemum and Stipa bungeana but had no effect on that of Artemisia gmelinii and Cleistogenes squarrosa. Furthermore, it also significantly affected rhizosphere soil fungal community composition of S.bungeana; however, no effects were observed on the other three plant species. Compared with the complexity of rhizosphere soil bacterial network, low N addition rates had a greater effect on the complexity of the rhizosphere soil fungal network.This study revealed that rhizosphere soil bacterial community composition of plant species with a higher niche breadth is generally more sensitive to atmospheric N deposition. Our study highlights the distinct roles of plant species with different niche breadths in maintaining rhizosphere soil microbial community composition under conditions of global N enrichment. [ABSTRACT FROM AUTHOR]

This study aimed to improve lipid and gamma-linolenic acid (GLA) production of an oleaginous fungus, Mucor plumbeus, through coculturing with Bacillus subtilis bacteria, optimising the environmental and nutritional culture conditions, and scaling them for batch fermentation. The maximum levels of biomass, lipid, fatty acid, and GLA in a 5 L bioreactor containing cellobiose and ammonium sulfate as the optimal carbon and nitrogen sources, respectively, achieved during the coculturing processes were 14.5 ± 0.4 g/L, 41.5 ± 1.3, 24 ± 0.8, and 20 ± 0.5%, respectively. This strategy uses cellobiose in place of glucose, decreasing production costs. The nutritional and abiotic factor results suggest that the highest production efficiency is achieved at 6.5 pH, 30 °C temperature, 10% (v/v) inoculum composition, 200 rpm agitation speed, and a 5-day incubation period. Interestingly, the GLA concentration of cocultures (20.0 ± 0.5%) was twofold higher than that of monocultures (8.27 ± 0.11%). More importantly, the GC chromatograms of cocultures indicated the presence of one additional peak corresponding to decanoic acid (5.32 ± 0.20%) that is absent in monocultures, indicating activation of silent gene clusters via cocultivation with bacteria. This study is the first to show that coculturing of Mucor plumbeus with Bacillus subtilis is a promising strategy with industrialisation potential for the production of GLA-rich microbial lipids and prospective biosynthesis of new products. [ABSTRACT FROM AUTHOR]

A novel biodegradable porous hydrogel (gelatin/chitosan/β-cyclodextrin, GEL/CS/β-CD) was prepared via a simple one-pot polymerization of gelatin, chitosan, and β-cyclodextrin. The chemical structure, morphology, and thermal stability were characterized by Fourier transform infrared (FT-IR), scanning electron microscopy (SEM), and thermogravimetric (TG) analysis, respectively. Due to a great number of active groups, such as amino groups, hydroxyl groups, and carboxyl groups of the hydrogel providing enough adsorption active sites, the hydrogel had excellent adsorption performances. Various organic dyes, such as malachite green (MG), crystalline violet (CV), congo red (CR), methylene blue (MB), acid fuchsin (AF), and methyl orange (MO), could be effectively removed. For 30 mg /L of MB and AF, the removal rate was between 80.0 and 93.3%. At 298 K, the adsorption capacities of AF and MB were as high as 1111 mg/g and 667 mg/g, respectively. Adsorption thermodynamics study indicated that the adsorption was a spontaneous process with a negative ΔG. The adsorption process followed the pseudo-second-order kinetic model and the Langmuir isotherm model. Moreover, the GEL/CS/β-CD hydrogel had good biodegradability and it degraded completely in soil extract solution for 30 days. Herein, the prepared GEL/CS/β-CD hydrogel has potential application as a green and environmentally friendly adsorbent for the effective removal of organic dyes in printing and dyeing wastewater. [ABSTRACT FROM AUTHOR]

Wireless device-free human sensing is an emerging technique of Internet of Things, which holds great potential for ubiquitous location-based services and human-interaction applications. Although existing studies can detect human appearance, they still neglect to further identify whether a user is approaching a sensor or not, which is critical for fine-grained recognition of human behaviors. In this paper, we first conduct comprehensive experiments to measure relationships between signal fading and human positions. The experimental results show that signal fading stepwise changes with different distances of the human to a sensor. Moreover, the signal fading is worse when the human is located closer to an antenna of the sensor. Motivated by these observations, we propose NSee, a novel system for device-free near-field human sensing without site-survey fingerprints. Specifically, we cluster signal fading features of different antennas by a Gaussian mixture model, and further propose a cluster identification algorithm to identify clusters in correspondence to different near-field subareas of human appearance. Based on cluster characteristics, NSee can recognize near-field human presence with online sensing. We implement a prototype of NSee system based on a commercial WiFi card with multiple antennas. Extensive experimental results illustrate that the proposed system can achieve an averaged accuracy of 90% in device-free near-field human recognition. [ABSTRACT FROM AUTHOR]

Automatic analysis of large-scale 3D flow field promotes the combination of topological analysis and integration curve analysis methods. Critical point detection and location are one of the key core algorithms of topological analysis. Dealing with large-scale flow fields in parallel, eliminating memory constraints, and obtaining high-precision position of critical points robustly are still primary challenges. Therefore, a novel parallel detection and location method on the GPU is proposed and denoted by HybridDualCP. It uses the duality property of the cartesian coordinate system and the velocity vector space inside each grid cell. It achieves high locality, has the ability of large-scale parallelization, and can quickly detect and locate critical points in large-scale 3D flow fields. Furthermore, based on the Inverse Distance Weighting (IDW) interpolation algorithm in the dual space, it eliminates the computation of solving systems of high-order or linear equations and can support any dimensional simplex mesh type. HybridDualCP provides the position classification of critical points relative to the grid cell by explicitly considering the inside/facet/edge/vertex. By detecting critical points in 29 typical 3D flow fields, HybridDualCP is faster, more robust and comprehensive than currently widely used methods. This paper also shows the effect of streamline visualization guided by critical points and the necessity of distinguishing critical points at different locations relative to the grid cell. [ABSTRACT FROM AUTHOR]

Herein, a porous, biodegradable and recyclable Gelatin/Chitosan hydrogel was fabricated as an effective adsorbent for organic pollutant. The synthesized Gelatin/Chitosan hydrogel composite was utilized in the removal of multiple dyes from aqueous solution using batch adsorption experiments. Among them, the Gelatin/Chitosan hydrogel had excellent adsorption capacity for various dyes. The maximum adsorption capacities for crystalline violet, methyl orange, acid fuchsin, congo red, malachite green, and methylene blue were 233.4 mg/g, 294.1 mg/g, 454.5 mg/g, 221.2 mg/g, 186.7 mg/g, and 209.2 mg/g, respectively. Moreover, the adsorption process could be well described by the Langmuir isotherm model and pseudo-second-order kinetic model. The dye removal efficiency was still more than 50% after five consecutive cycles of dye adsorption–desorption. Therefore, the Gelatin/Chitosan hydrogel composite is a potential candidate towards dye pollution remediation owing to its environment friendliness, high adsorption potential and regeneration capability. [ABSTRACT FROM AUTHOR]

Deception attacks aim to destroy the integrity of data and will further lead to instability of dynamical systems. How to develop an effective analysis and synthesis approach based on system intrinsic characteristics is constantly being explored and faces great challenges. In this paper, we investigate the stabilization problem for singularly perturbed switched systems subject to unmodeled dynamics and deception attacks. Unlike most existing control schemes specialized for SPSSs, in which neither cyber attacks nor unmodeled dynamics are considered and the full system information is required, an observer equipped with a robust term is designed to estimate the system states and deception attacks bound, and an ε -dependent integral sliding mode surface is then constructed to introduce multiple time scales feature to the sliding mode dynamics. By using ε -dependent multiple Lyapunov functions and average dwell time technique, some well-conditioned stability conditions are given to ensure the stability of the state estimation error systems and the sliding mode dynamics. Moreover, an adaptive sliding mode control law is synthesized to ensure the reachability of the prescribed sliding surface, which further leads to the stability of the closed-loop system. Finally, a numerical simulation is given to show the validity of the obtained results. [ABSTRACT FROM AUTHOR]

Crossed-dipole acoustic logging technology is mainly used to measure shear wave and determine the anisotropy or fractures of formation in the field of acoustic logging. Based on the propagation characteristics of dipole flexural waves in cased holes, and the wavefield of fundamental flexural mode at three bonding conditions: good cement bonding, poorly bonded interface I, and poorly bonded interface II. The dispersion curves of flexural waves are calculated, and the effects of cement parameters (elastic parameters and geometric dimensions) on dispersion curves are investigated. The RAI method is used to calculate the dipole full waveforms in a cased hole with conventional or ultralight cement surrounded by a soft formation. Then, the weighted spectral semblance is used to conduct the dispersion analysis of the full waves. The numerical results show that the cutoff frequency of flexural waves exceeds the frequency band of the current dipole logging tools in the well-bonded cased hole with conventional cement in soft formations. However, when ultralight cement is used, the cutoff frequency shifts toward low values, and the ultralight cement bonding is conducive to measuring flexural waves in soft formations. When interface I is poorly bonded, the cutoff frequency shifts toward low values, and the change is evident in soft formations. The cutoff frequency in the case of ultralight cement bonding is more evident than that of conventional cement bonding. If only interface II is poorly bonded, regardless of the cement used, the cutoff frequencies are all below 2 kHz. The dipole full-wave analysis of different bonding conditions further illustrates that the dispersion characteristics of flexural waves are sensitive to the cement bonding quality of cased holes. [ABSTRACT FROM AUTHOR]

Attributed community search is to find a subgraph with some specific attributes online in terms of given vertices. It can help us retrieve information on a subgraph rather than the whole graph, thus enable down-stream graph search applications. However, it is difficult for users to specify exact query vertices if they are unfamiliar with the required graph. Most existing community search methods depend on the query vertices strictly and cause the searched community to shift from the truth community. Meanwhile, due to the incompleteness of original graph data, there exist many latent relationships between vertices, which may influence the search results. But most existing methods ignore these latent relationships and usually lead to a result with low F1 scores. Therefore, this research proposes an improved attributed community search method considering community focusing and latent relationships. We first build a structure attribute network embedding model to learn representations for vertices. Based on this model, the latent relationships are discovered and added to the original graph. Then a community shifting correction algorithm is presented to solve community focusing problem and achieve a more desired community. The experimental work on real-world networks confirms that our method can achieve better performance than existing methods. [ABSTRACT FROM AUTHOR]

Background: Bacterial blight (BB), caused by Xanthomonas oryzae pv. oryzae (Xoo), is one of the most devastating diseases in rice all over the world. Due to the diversity and rapid evolution of Xoo, identification and use of the non-race specific quantitative resistance QTLs has been considered the preferred strategy for effective control of this disease. Although numerous QTLs for BB resistance have been identified, they haven't been effectively used for improvement of BB resistance in rice due to their small effects and lack of knowledge on the function of genes underlying the QTLs. Results: In the present study, a genome-wide association study of BB resistance was performed in a rice core collection from South China. A total of 17 QTLs were identified to be associated with BB resistance. Among them, 13 QTLs were newly identified in the present study and the other 4 QTLs were co-localized with the previously reported QTLs or Xa genes that confer qualitative resistance to Xoo strains. Particularly, the qBBR11–4 on chromosome 11 explained the largest phenotypic variation in this study and was co-localized with the previously identified QTLs for BB and bacterial leaf streak (BLS) resistance against diverse strains in three studies, suggesting its broad-spectrum resistance and potential value in rice breeding. Through combined analysis of differential expression and annotations of the predicted genes within qBBR11–4 between two sets of rice accessions selected based on haplotypes and disease phenotypes, we identified the transcription factor OsMYB21 as the candidate gene for qBBR11–4. The OsMYB21 overexpressing plants exhibited decreased resistance to bacterial blight, accompanied with down-regulation of several defense-related genes compared with the wild-type plants. Conclusion: The results suggest that OsMYB21 negatively regulates bacterial blight resistance in rice, and this gene can be a promising target in rice breeding by using the gene editing method. In addition, the potential candidate genes for the 13 novel QTLs for BB resistance were also analyzed in this study, providing a new source for cloning of genes associated with BB resistance and molecular breeding in rice. [ABSTRACT FROM AUTHOR]

Background: Although panicle blast is more destructive to yield loss than leaf blast in rice, the cloned genes that function in panicle blast resistance are still very limited and the molecular mechanisms underlying panicle blast resistance remain largely unknown. Results: In the present study, we have confirmed that the three Oxalate oxidase (OXO) genes, OsOXO2, OsOXO3 and OsOXO4 from a blast-resistant cultivar BC10 function in panicle blast resistance in rice. The expression of OsOXO2, OsOXO3 and OsOXO4 were induced by panicle blast inoculation. Subcellular localization analysis revealed that the three OXO proteins are all localized in the nucleus and cytoplasm. Simultaneous silencing of OsOXO2, OsOXO3 and OsOXO4 decreased rice resistance to panicle blast, whereas the OsOXO2, OsOXO3 and OsOXO4 overexpression rice plants individually showed enhanced panicle blast resistance. More H2O2 and higher expression levels of PR genes were observed in the overexpressing plants than in the control plants, while the silencing plants exhibited less H2O2 and lower expression levels of PR genes compared to the control plants. Moreover, phytohormone treatment and the phytohormone signaling related gene expression analysis showed that panicle blast resistance mediated by the three OXO genes was associated with the activation of JA and ABA signaling pathways but suppression of SA signaling pathway. Conclusion: OsOXO2, OsOXO3 and OsOXO4 positively regulate panicle blast resistance in rice. The OXO genes could modulate the accumulation of H2O2 and expression levels of PR gene in plants. Moreover, the OXO genes mediated panicle blast resistance could be regulated by ABA, SA and JA, and may be associated with the activation of JA and ABA signaling pathways but suppression of the SA signaling pathway. [ABSTRACT FROM AUTHOR]

Adsorptive removal of dyes from industrial wastewater has attracted intensive interests in recent years. Hydrogels is a kind of promising adsorbent in dyes removal owing to the simple synthesis and convenient application. A biodegradable and recyclable gelatin hydrogel (GH) was synthesized by a convenient approach in this work. The as-prepared GH was used to remove dyes in aqueous solution. The results indicated that the GH had excellent adsorption capacity for various dyes and the maximum adsorption capacities of crystalline violet (CV), methyl orange (MO), acid fuchsin (AF), congo red (CR), malachite green (MG), and methylene blue (MB) were 138.89 mg/g, 72.63 mg/g, 66.29 mg/g, 64.84 mg/g, 64.64 mg/g, and 60.32 mg/g, respectively. Moreover, the dye removal efficiency was still more than 60% after five consecutive adsorption–desorption cycles and the shape of the GH kept well. Therefore, GH can be used as an environmentally friendly and effective adsorbent to remove virous dyes from printing and dyeing wastewater. [ABSTRACT FROM AUTHOR]

Background: Direct seeding is an efficient rice cultivation practice. However, its application is often limited due to O2 deficiency following submergence, leading to poor seed germination, seedling establishment, and consequently yield loss. Identification of genes associated with tolerance to submergence and understanding their regulatory mechanisms is the fundamental way to address this problem. Unfortunately, the molecular mechanism of rice response to submergence stress is still not well understood. Results: Here, we have performed a genome-wide identification of FCS-like zinc finger (FLZ) proteins and assessed their involvement in submergence response in rice. We identified 29 FLZ genes in rice, and the expression analysis revealed that several genes actively responded to submergence stress. Eight OsFLZ proteins interact with SnRK1A. As a case study, we demonstrated that OsFLZ18 interacted with SnRK1A and inhibited the transcriptional activation activity of SnRK1A in modulating the expression of its target gene αAmy3, a positive regulator in rice flooding tolerance. In line with this, OsFLZ18-overexpression lines displayed retarded early seedling growth and shorter coleoptile following submergence. Conclusions: These data provide the most comprehensive information of OsFLZ genes in rice, and highlight their roles in rice submergence response. [ABSTRACT FROM AUTHOR]

As more and more applications migrate to clouds, the type and amount of malware attack against virtualized environments are increasing, which is a key factor that restricts the widespread deployment and application of cloud platforms. Traditional in-VM-based security software is not effective against malware attacks, as the security software itself becomes the target of malware attacks and can easily be tampered with or even subverted. In this paper, we propose a new malware detection method to improve virtual machine security performance and ensure the security of the entire cloud platform. This paper uses the virtual machine introspection(VMI) combined with the memory forensics analysis(MFA) technology to extract multiple types of dynamic features from the virtual machine memory, the hypervisor layer and the hardware layer. Furthermore, this paper proposes an adaptive feature selection method. By combining three different search strategies, three types of features are compared and analyzed from three aspects: effectiveness, system load and security. By adjusting the weight of each feature, it meets the detection requirements of different malware in the cloud environment as expected. Finally, the detection method improves the detection accuracy and generalization ability of the overall classifier using the AdaBoost ensemble learning method with Voting's combination strategy. The experiment used a large number of real malicious samples, and achieved an accuracy of 0.999 (AUC), with a maximum performance overhead of 5.6%. [ABSTRACT FROM AUTHOR]

Acoustic/ultrasonic sensors are devices that can convert mechanical energy into electrical signals. The Fabry–Perot cavity is processed on the end face of the double-clad fiber by a two-photon three-dimensional lithography machine. In this study, the outer diameter of the core cladding was 250 μm, the diameter of the core was 9 μm, and the microcavity sensing unit was only 30 μm. It could measure ultrasonic signals with high precision. The characteristics of the proposed ultrasonic sensor were investigated, and its feasibility was proven through experiments. Its design has a small size and can replace a larger ultrasonic detector device for photoacoustic signal detection. The sensor is applicable to the field of biomedical information technology, including medical diagnosis, photoacoustic endoscopy, and photoacoustic imaging. [ABSTRACT FROM AUTHOR]

A new covalent organic framework (COF) has been prepared with 1,3,6,8-tetra(4-formyl phenyl) pyrene (TFPPy) and 2,6-diaminopyridine (DP) as building units through a Schiff base reaction by a simple tube oven heating procedure and the structure of the COF has been characterized in detail. The obtained DP-Py COF is employed to fabricate a novel electrochemical sensing platform for sensitive and selective determination of theophylline (TP) and caffeine (CAF) simultaneously through compounding with AuNPs; the peak positions of TP and CAF are 0.95 V and 1.28 V, respectively. The synergistic effect between DP-Py COF and AuNPs effectively enhances the analytical sensitivity for the target analytes. Under the optimized experimental conditions, the electrochemical sensing platform shows a sensitive voltammetric response and wide linear range to both TP and CAF, and the detection limits are 0.19 μM and 0.076 μM (S/N = 3), respectively. This method has been successfully used for the determination of TP and CAF in compound paracetamol capsules and black tea samples. The recovery and relative standard deviations (RSD) of TP are 99.3~101% and 97.6~101% and 1.3~2.0% and 1.3~2.1%, respectively, and the recovery and RSD of CAF are 96.1~102% and 99.4~104% and 2.8~3.9% and 1.7~3.2%, respectively. Compared with traditional detection methods, the constructed sensing platform has better performance and is expected to be widely used also in other real sample analyses. [ABSTRACT FROM AUTHOR]

The source and evolution of ore-forming fluids is important to understand the genesis of Carlin-type gold deposit. Constraints on the source and evolution of ore fluid components by the conventional geochemical methods have long been a challenge due to the very fine-grained nature and complex textures of hydrothermal minerals in these deposits. In this study, we present the crush-leach analyzed solute data of fluid inclusion extracts within quartz, calcite, realgar, and fluorite from the Shuiyindong, Nibao, and Yata gold deposits in the Youjiang Basin, providing new insights into the source and evolution of ore-forming fluids. The results show that the high molar Cl/Br ratios up to 2 508 in fluid inclusion extracts are indicative of a contribution of magmatic hydrothermal fluids. Fluids mixing between basinal and magmatic-hydrothermal fluids are evident on the plots of Cl/Br versus Na/K ratios, showing that ore-stage milky quartz near the magmatic-hydrothermal fluids reflects magma origin of the ore-forming fluids, whereas late ore-stage drusy quartz and realgar near the defined basinal fluids suggest the later input of basinal fluids in late-ore stage. Although the predominately host rocks in Shuiyindong, Nibao and Yata gold deposit are bioclastic limestone, sedimentary tuff, and calcareous siltstone, respectively, the solute data of fluid inclusion extracts records they underwent the similar fluid-rocks reactions between the Na-rich magmatic hydrothermal fluids and the Ca- and Mg-rich host rocks. This study highlights the solute data of fluid inclusion extracts obtained by crush-leach analyses have the potential to fingerprint the source and evolution of ore-forming fluids of the Carlin-type gold deposit. [ABSTRACT FROM AUTHOR]