665 research outputs found

    Understanding the Mode of Action of Essential Oil Nanoemulsions to Inhibit Fusarium Growth and Mycotoxin Production in Cereal

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    Deoxynivalenol (DON) is a commonly occurred mycotoxin in cereal-based food, which is mainly produced by Fusarium spp. in the field. It is unfeasible to entirely avoid DON contamination in cereal grains with good agricultural practices. Therefore, it is of great importance to have a strategy for preventing DON contamination in our final food products. In recent years, utilization of plant extracts such as essential oils (EOs) as antifungal and mycotoxin inhibitory agents in foods have gained popularity. Depending on the EO type and chemical composition of EOs, the antifungal and mycotoxin inhibitory efficacies of different EOs might be varied. In addition, their antifungal mode of actions (MOA) against Fusarium spp. growth remains unknown. Therefore, the overall objectives of this project were to understand how different type of clove EOs (clove bud EO and clove leave EO), hop essential oil (HEO) impact their antifungal and mycotoxin inhibitory efficacies, and their corresponding antifungal MOA. Finally, HEO in nanoemulsion form was applied to evaluate their application during micro malting process using naturally Fusarium infected barley grains. Results denoted that physically stable 5 wt% EO in-water nanoemulsions with the mean particle sizes less than 170 nm can be built by blending either corn oil or medium chain triglyceride (MCT) with EOs. The largest percentage of chemical constituent in clove essential oils (CO) and HEO was eugenol (phenol type) and ?-myrcene (monoterpene type), respectively. In terms of their application as antifungal agents, CO had better antifungal and mycotoxin inhibitory efficacy against Fusarium graminearum growth and DON production in vitro as compared to HEO because of their high percentage of eugenol content. The major antifungal MOA of EO nanoemulsions included altering total lipid content in cell, chitin content in outer spore cell membrane, and damaging cytoplasmic membrane. In the application case study, results indicated that Fusarium biomass (Tri 5 DNA) and DON contents were reduced at each malting stage with the treatments of HEO nanoemulsion by malting Fusarium infected barley. This study provided the valuable information on utilization of EO nanoemulsions as natural antifungal agents during food processing

    Motion Blur Decomposition with Cross-shutter Guidance

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    Motion blur is a frequently observed image artifact, especially under insufficient illumination where exposure time has to be prolonged so as to collect more photons for a bright enough image. Rather than simply removing such blurring effects, recent researches have aimed at decomposing a blurry image into multiple sharp images with spatial and temporal coherence. Since motion blur decomposition itself is highly ambiguous, priors from neighbouring frames or human annotation are usually needed for motion disambiguation. In this paper, inspired by the complementary exposure characteristics of a global shutter (GS) camera and a rolling shutter (RS) camera, we propose to utilize the ordered scanline-wise delay in a rolling shutter image to robustify motion decomposition of a single blurry image. To evaluate this novel dual imaging setting, we construct a triaxial system to collect realistic data, as well as a deep network architecture that explicitly addresses temporal and contextual information through reciprocal branches for cross-shutter motion blur decomposition. Experiment results have verified the effectiveness of our proposed algorithm, as well as the validity of our dual imaging setting.Comment: Accepted to CVPR 202

    Research on Large-scale Energy Storage of Chinese Power System Based on Demand Analysis

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    With the construction and development of a low carbon and environmental protection society, China is promoting the construction of a clean, low carbon, safe and efficient energy supply system, the most critical of which is to promote the rapid construction of new energy installed capacity. However, with the continuous expansion of the new energy installed capacity, the random volatility of the power supply has become an important factor that puzzles the power balance of the current power system, not only formed a larger peak pressure, but also became one of the important factors restricting the development of new energy. At the same time, the new energy power electronic equipment has weak supporting characteristics, which also makes the proportion of new energy power system continues to increase, and has a high impact on security. In this context, this paper carries out a demand analysis, firstly discussing the demand for large-scale energy storage in the development of new energy for power system, and secondly analyzing the demand for large-scale energy storage in the safe operation of large power grid, so as to promote the construction of GW-level electrochemical energy storage power station and effectively deal with the power imbalance and safety problems

    OCGEC: One-class Graph Embedding Classification for DNN Backdoor Detection

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    Deep neural networks (DNNs) have been found vulnerable to backdoor attacks, raising security concerns about their deployment in mission-critical applications. There are various approaches to detect backdoor attacks, however they all make certain assumptions about the target attack to be detected and require equal and huge numbers of clean and backdoor samples for training, which renders these detection methods quite limiting in real-world circumstances. This study proposes a novel one-class classification framework called One-class Graph Embedding Classification (OCGEC) that uses GNNs for model-level backdoor detection with only a little amount of clean data. First, we train thousands of tiny models as raw datasets from a small number of clean datasets. Following that, we design a ingenious model-to-graph method for converting the model's structural details and weight features into graph data. We then pre-train a generative self-supervised graph autoencoder (GAE) to better learn the features of benign models in order to detect backdoor models without knowing the attack strategy. After that, we dynamically combine the GAE and one-class classifier optimization goals to form classification boundaries that distinguish backdoor models from benign models. Our OCGEC combines the powerful representation capabilities of graph neural networks with the utility of one-class classification techniques in the field of anomaly detection. In comparison to other baselines, it achieves AUC scores of more than 98% on a number of tasks, which far exceeds existing methods for detection even when they rely on a huge number of positive and negative samples. Our pioneering application of graphic scenarios for generic backdoor detection can provide new insights that can be used to improve other backdoor defense tasks. Code is available at https://github.com/jhy549/OCGEC.Comment: v

    Similarities and differences of functional connectivity in drug-naïve, first-episode adolescent and young adult with major depressive disorder and schizophrenia

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    Major depressive disorder (MDD) and schizophrenia (SZ) are considered two distinct psychiatric disorders. Yet, they have considerable overlap in symptomatology and clinical features, particularly in the initial phases of illness. The amygdala and prefrontal cortex (PFC) appear to have critical roles in these disorders; however, abnormalities appear to manifest differently. In our study forty-nine drug-naïve, first-episode MDD, 45 drug-naïve, first-episode SZ, and 50 healthy control (HC) participants from 13 to 30 years old underwent resting-state functional magnetic resonance imaging. Functional connectivity (FC) between the amygdala and PFC was compared among the three groups. Significant differences in FC were observed between the amygdala and ventral PFC (VPFC), dorsolateral PFC (DLPFC), and dorsal anterior cingulated cortex (dACC) among the three groups. Further analyses demonstrated that MDD showed decreased amygdala-VPFC FC and SZ had reductions in amygdala-dACC FC. Both the diagnostic groups had significantly decreased amygdala-DLPFC FC. These indicate abnormalities in amygdala-PFC FC and further support the importance of the interaction between the amygdala and PFC in adolescents and young adults with these disorders. Additionally, the alterations in amygdala-PFC FC may underlie the initial similarities observed between MDD and SZ and suggest potential markers of differentiation between the disorders at first onset

    Three Dimensional Quantitative Structure-Activity Relationships of Sulfonamides Binding Monoclonal Antibody by Comparative Molecular Field Analysis

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    The three-dimensional quantitative structure-activity relationship (3D-QSAR) model of sulfonamide analogs binding a monoclonal antibody (MabSMR) produced against sulfamerazine, was carried out by comparative molecular field analysis (CoMFA). The affinities of MabSMR, expressed as Log10IC50, for 17 sulfonamide analogs were determined by competitive fluorescence polarization immunoassay (FPIA). Removal of two outliers from the initial set of 17 sulfonamide analogs improved the predictability of the models. The 3D-QSAR model of 15 sulfonamides resulted in q2cv values of 0.600, and r2 values of 0.995, respectively. This novel study combining FPIA with CoMFA demonstrates that multidisciplinary research can be used as a useful tool to investigate antigen-antibody interactions and provide information required for design of novel haptens, which may result in new antibodies with properties already optimized by an antibody-based immunoassay

    High sensitivity HI image of diffuse gas and new tidal features in M51 observed by FAST

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    We observed the classical interacting galaxy M51 with FAST and obtain high sensitivity HI image with column density down to 3.8 ×\times 1018^{18} cm−2^{-2}. In the image we can see a diffuse extended envelope around the system and several new tidal features. We also get a deeper look at M51b's probable gas, which has an approximated velocity range of 560 to 740 km s−1^{-1} and a flux of 7.5 Jy km s−1^{-1}. Compared to the VLA image, we observe more complete structures of the Southeast Tail, Northeast Cloud and Northwest Plume, as well as new features of the Northwest Cloud and Southwest Plume. M51's most prominent tidal feature, the Southeast Tail, looks very long and broad, in addition with two small detached clouds at the periphery. Due to the presence of optical and simulated counterparts, the Northwest cloud appears to be the tail of M51a, while the Northwest Plume is more likely a tidal tail of M51b. The large mass of the Northwest Plume suggests that M51b may have been as gas-rich as M51a before the interaction. In addition, the formation process of the Northeast Cloud and Southwest Plume is obscured by the lack of optical and simulated counterparts. These novel tidal features, together with M51b's probable gas, will inspire future simulations and provide a deeper understanding of the evolution of this interacting system.Comment: 11 pages, 9 figures, accepted for publication in MNRA

    Allocation of nitrogen and phosphorus in the leaves, stems, and roots of Artemisia: a case study in phylogenetic control

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    IntroductionThe allocation of nitrogen (N) and phosphorus (P) among plant organs is an important strategy affecting growth and development as well as ecological processes in terrestrial ecosystems. However, due to lack of systematic investigation data, the allocation strategies of N and P in the three primary plant organs (e.g., leaves, stems and roots) are still unclear.MethodsA total of 912 individuals of 62 Artemisia species were examined across a broad environmental expanse in China, and the N and P concentrations of leaves, stems and roots were measured to explore the allocation strategies in different subgenera, ecosystem types, and local sites.Results and discussionAcross all 62 species, the N vs. P scaling exponents for leaves, stems and roots were 0.67, 0.59 and 0.67, respectively. However, these numerical values differed among subgenera, ecosystem types, and local sites. Overall, the numerical values of N vs. P scaling exponents comply with a 2/3-power function for each Artemisia organ-type reflecting a phylogenetically conserved allocation strategy that has nevertheless diversified with respect to local environmental conditions. These results inform our understanding of N and P stoichiometric patterns and responses to abiotic factors in an ecologically broadly distributed angiosperm genus
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