Studies of exit pressure recovery coefficient and its effects on dynamic characteristics of annular water seals

Rotordynamic instability and vibration due to fluid forces within annular seals are well-known phenomenons that can occur in pumps as well as in turbines. Traditional theoretical predictions for the fluid reaction forces and equivalent dynamic characteristics of annular seals are computationally efficient compared with CFD method. Exit pressure loss coefficient is one of the main factors that influence the precisions of theoretical analysis. In this paper, exit pressure recovery coefficients at three different static eccentricity ratios under different operating conditions are investigated using CFD method. The numerical result shows that exit coefficient increases exponentially with the ratio of circumferential velocity to axial velocity at all these three eccentricity ratios. Besides, an analysis method for annular plain seals with the introduction of exit pressure recovery coefficient varied with operating conditions is proposed based on the previous analysis results. Comparisons are made between theoretical predictions calculated by the two methods with and without exit coefficient over a wide range of pressure drops and running speeds. The result suggests that damping coefficients are much more sensitive to the change of the exit boundary conditions compared to stiffness coefficients. In addition, the new prediction results of cross-coupled stiffness and direct damping coefficient show relatively smooth change with the increase of velocity ratio than the previous results

MOD-Net: A Machine Learning Approach via Model-Operator-Data Network for Solving PDEs

In this paper, we propose a model-operator-data network (MOD-Net) for solving PDEs. A MOD-Net is driven by a model to solve PDEs based on operator representation with regularization from data. In this work, we use a deep neural network to parameterize the Green's function. The empirical risk consists of the mean square of the governing equation, boundary conditions, and a few labels, which are numerically computed by traditional schemes on coarse grid points with cheap computation cost. With only the labeled dataset or only the model constraints, it is insufficient to accurately train a MOD-Net for complicate problems. Intuitively, the labeled dataset works as a regularization in addition to the model constraints. The MOD-Net is much efficient than original neural operator because the MOD-Net also uses the information of governing equation and the boundary conditions of the PDE rather than purely the expensive labels. Since the MOD-Net learns the Green's function of a PDE, it solves a type of PDEs but not a specific case. We numerically show MOD-Net is very efficient in solving Poisson equation and one-dimensional Boltzmann equation. For non-linear PDEs, where the concept of the Green's function does not apply, the non-linear MOD-Net can be similarly used as an ansatz for solving non-linear PDEs

Cotton Fusarium wilt diagnosis based on generative adversarial networks in small samples

This study aimed to explore the feasibility of applying Generative Adversarial Networks (GANs) for the diagnosis of Verticillium wilt disease in cotton and compared it with traditional data augmentation methods and transfer learning. By designing a model based on small-sample learning, we proposed an innovative cotton Verticillium wilt disease diagnosis system. The system uses Convolutional Neural Networks (CNNs) as feature extractors and applies trained GAN models for sample augmentation to improve classification accuracy. This study collected and processed a dataset of cotton Verticillium wilt disease images, including samples from normal and infected plants. Data augmentation techniques were used to expand the dataset and train the CNNs. Transfer learning using InceptionV3 was applied to train the CNNs on the dataset. The dataset was augmented using GAN algorithms and used to train CNNs. The performances of the data augmentation, transfer learning, and GANs were compared and analyzed. The results have demonstrated that augmenting the cotton Verticillium wilt disease image dataset using GAN algorithms enhanced the diagnostic accuracy and recall rate of the CNNs. Compared to traditional data augmentation methods, GANs exhibit better performance and generated more representative and diverse samples. Unlike transfer learning, GANs ensured an adequate sample size. By visualizing the images generated, GANs were found to generate realistic cotton images of Verticillium wilt disease, highlighting their potential applications in agricultural disease diagnosis. This study has demonstrated the potential of GANs in the diagnosis of cotton Verticillium wilt disease diagnosis, offering an effective approach for agricultural disease detection and providing insights into disease detection in other crops

Changes in EEG Permutation Entropy in the evening and in the transition from wake to sleep

Peer reviewe

Assembly, annotation, and comparative analysis of Ipomoea chloroplast genomes provide insights into the parasitic characteristics of Cuscuta species

In the Convolvulaceae family, around 1650 species belonging to 60 genera are widely distributed globally, mainly in the tropical and subtropical regions of America and Asia. Although a series of chloroplast genomes in Convolvulaceae were reported and investigated, the evolutionary and genetic relationships among the chloroplast genomes of the Convolvulaceae family have not been extensively elucidated till now. In this study, we first reported the complete chloroplast genome sequence of Ipomoea pes-caprae, a widely distributed coastal plant with medical values. The chloroplast genome of I. pes-caprae is 161667 bp in length, and the GC content is 37.56%. The chloroplastic DNA molecule of I. pes-caprae is a circular structure composed of LSC (large-single-copy), SSC (small-single-copy), and IR (inverted repeat) regions, with the size of the three regions being 88210 bp, 12117 bp, and 30670 bp, respectively. The chloroplast genome of I. pes-caprae contains 141 genes, and 35 SSRs are identified in the chloroplast genome. Our research results provide important genomic information for the molecular phylogeny of I. pes-caprae. The Phylogenetic analysis of 28 Convolvulaceae chloroplast genomes showed that the relationship of I. pes-caprae with I. involucrata or I. obscura was much closer than that with other Convolvulaccae species. Further comparative analyses between the Ipomoea species and Cuscuta species revealed the mechanism underlying the formation of parasitic characteristics of Cuscuta species from the perspective of the chloroplast genome

Targeting Inhibition of Accumulation and Function of Myeloid-Derived Suppressor Cells by Artemisinin via PI3K/AKT, mTOR, and MAPK Pathways Enhances Anti-PD-L1 Immunotherapy in Melanoma and Liver Tumors

Despite the remarkable success and efficacy of immune checkpoint blockade (ICB) therapy such as anti-PD-L1 antibody in treating cancers, myeloid-derived suppressor cells (MDSCs) that lead to the formation of the protumor immunosuppressive microenvironment are one of the major contributors to ICB resistance. Therefore, inhibition of MDSC accumulation and function is critical for further enhancing the therapeutic efficacy of anti-PD-L1 antibody in a majority of cancer patients. Artemisinin (ART), the most effective antimalarial drug with tumoricidal and immunoregulatory activities, is a potential option for cancer treatment. Although ART is reported to reduce MDSC levels in 4T1 breast tumor model and improve the therapeutic efficacy of anti-PD-L1 antibody in T cell lymphoma-bearing mice, how ART influences MDSC accumulation, function, and molecular pathways as well as MDSC-mediated anti-PD-L1 resistance in melanoma or liver tumors remains unknown. Here, we reported that ART blocks the accumulation and function of MDSCs by polarizing M2-like tumor-promoting phenotype towards M1-like antitumor one. This switch is regulated via PI3K/AKT, mTOR, and MAPK signaling pathways. Targeting MDSCs by ART could significantly reduce tumor growth in various mouse models. More importantly, the ART therapy remarkably enhanced the efficacy of anti-PD-L1 immunotherapy in tumor-bearing mice through promoting antitumor T cell infiltration and proliferation. These findings indicate that ART controls the functional polarization of MDSCs and targeting MDSCs by ART provides a novel therapeutic strategy to enhance anti-PD-L1 cancer immunotherapy

Developing a new treatment for superficial fungal infection using antifungal Collagen-HSAF dressing

Fungal pathogens are common causes of superficial clinical infection. Their increasing drug resistance gradually makes existing antifungal drugs ineffective. Heat stable antifungal factor (HSAF) is a novel antifungal natural product with a unique structure. However, the application of HSAF has been hampered by very low yield in the current microbial producers and from extremely poor solubility in water and common solvents. In this study, we developed an effective mode of treatment applying HSAF to superficial fungal infections. The marine-derived Lysobacter enzymogenes YC36 contains the HSAF biosynthetic gene cluster, which we activated by the interspecific signaling molecule indole. An efficient extraction strategy was used to significantly improve the purity to 95.3%. Scanning electron microscopy images revealed that the Type I collagen-based HSAF (Col-HSAF) has a transparent appearance and good physical properties, and the in vitro sustained-release effect of HSAF was maintained for more than 2 weeks. The effective therapeutic concentration of Col-HSAF against superficial fungal infection was explored, and Col-HSAF showed good biocompatibility, lower clinical scores, mild histological changes, and antifungal capabilities in animals with Aspergillus fumigatus keratitis and cutaneous candidiasis. In conclusion, Col-HSAF is an antifungal reagent with significant clinical value in the treatment of superficial fungal infections

Characterization of auxin transporter AUX, PIN and PILS gene families in pineapple and evaluation of expression profiles during reproductive development and under abiotic stresses

Polar auxin transport in plant is mediated by influx and efflux transporters, which are encoded by AUX/LAX, PIN and PILS genes, respectively. The auxin transporter gene families have been characterized in several species from monocots and eudicots. However, a genome-wide overview of auxin transporter gene families in pineapple is not yet available. In this study, we identified a total of threeAcAUX genes, 12 AcPIN genes, and seven AcPILS genes in the pineapple genome, which were variably located on 15 chromosomes. The exon-intron structure of these genes and properties of deduced proteins were relatively conserved within the same family. Most protein motifs were widespread in the AUX, PIN or PILS proteins, whereas a few motifs were absent in only one or two proteins. Analysis of the expression profiles of these genes elucidated that several genes exhibited either preferential or tissue-specific expression patterns in vegetative and/or reproductive tissues. AcAUX2 was specifically expressed in the early developmental ovules, while AcPIN1b and AcPILS2 were strongly expressed in stamens and ovules. AcPIN9b, AcPILS1, AcPILS6a, 6b and 6c were abundantly expressed in stamens. Furthermore, qRT-PCR results showed that several genes in these families were responsive to various abiotic stresses. Comparative analysis indicated that the genes with close evolutionary relationships among pineapple, rice and Arabidopsis exhibited similar expression patterns. Overexpression of the AcAUX1 in Arabidopsis rescued the phenotype in aux1-T, and resulted in increased lateral roots in WT. These results will provide new insights into auxin transporter genes of pineapple and facilitate our understanding of their roles in pineapple growth and development

The bracteatus pineapple genome and domestication of clonally propagated crops

Domestication of clonally propagated crops such as pineapple from South America was hypothesized to be a 'one-step operation'. We sequenced the genome of Ananas comosus var. bracteatus CB5 and assembled 513 Mb into 25 chromosomes with 29,412 genes. Comparison of the genomes of CB5, F153 and MD2 elucidated the genomic basis of fiber production, color formation, sugar accumulation and fruit maturation. We also resequenced 89 Ananas genomes. Cultivars 'Smooth Cayenne' and 'Queen' exhibited ancient and recent admixture, while 'Singapore Spanish' supported a one-step operation of domestication. We identified 25 selective sweeps, including a strong sweep containing a pair of tandemly duplicated bromelain inhibitors. Four candidate genes for self-incompatibility were linked in F153, but were not functional in self-compatible CB5. Our findings support the coexistence of sexual recombination and a one-step operation in the domestication of clonally propagated crops. This work guides the exploration of sexual and asexual domestication trajectories in other clonally propagated crops