Electromechanical response of multilayered piezoelectric BaTiO3/PZT-7A composites with wavy architecture

Electromechanical laminated composites with piezoelectric phases are increasingly being explored as multifunctional materials providing energy conversion between electric and mechanical energies. The current work explores thus-far undocumented combined microstructural effects of amplitude-to-wavelength ratio, volume fraction, poling direction of piezoelectric phases on both the homogenized properties and localized stress/electric field distributions in multilayered configurations under fully coupled electro-mechanical loading. In particular, the Multiphysics Finite-Volume Direct Averaging Micromechanics (FVDAM) and its counterpart, an in-house micromechanical multiphysics finite-element model, are utilized to investigate the homogenized and localized responses of wavy multilayered piezoelectric BaTiO3/PZT-7A architectures. These two methods generate highly agreeable results. Moreover, we critically examine the convergence of the finite-volume and finite element-based approaches via the Average Stress Theorem and Average Electric Displacement Theorem. The comparison shows the finite volume-based approach possesses a better numerical convergence. This study illustrates the FVDAM’s ability toward the analysis and design of engineered multilayered piezoelectric materials with wavy architecture.The first author W. Tu acknowledges the support of Jiangsu University Research Startup Fund for Senior Talent

Identification of nutrient partitioning genes participating in rice grain filling by singular value decomposition (SVD) of genome expression data

BACKGROUND: In order to identify rice genes involved in nutrient partitioning, microarray experiments have been done to quantify genomic scale gene expression. Genes involved in nutrient partitioning, specifically grain filling, will be used to identify other co-regulated genes, and DNA binding proteins. Proper identification of the initial set of bait genes used for further investigation is critical. Hierarchical clustering is useful for grouping genes with similar expression profiles, but decreases in utility as data complexity and systematic noise increases. Also, its rigid classification of genes is not consistent with our belief that some genes exhibit multifaceted, context dependent regulation. RESULTS: Singular value decomposition (SVD) of microarray data was investigated as a method to complement current techniques for gene expression pattern recognition. SVD's usefulness, in finding likely participants in grain filling, was measured by comparison with results obtained previously via clustering. 84 percent of these known grain-filling genes were re-identified after detailed SVD analysis. An additional set of 28 genes exhibited a stronger grain-filling pattern than those grain-filling genes that were unselected. They also had upstream sequence containing motifs over-represented among grain filling genes. CONCLUSIONS: The pattern-based perspective that SVD provides complements to widely used clustering methods. The singular vectors provide information about patterns that exist in the data. Other aspects of the decomposition indicate the extent to which a gene exhibits a pattern similar to those provided by the singular vectors. Thus, once a set of interesting patterns has been identified, genes can be ranked by their relationship with said patterns

Deep learning in heterogeneous materials: Targeting the thermo-mechanical response of unidirectional composites

In this communication, a multi-task deep learning-driven homogenization scheme is proposed for predicting the effective thermomechanical response of unidirectional composites consisting of a random array of inhomogeneity. Toward this end, 40 000 repeating unit cells (RUCs) comprising an arbitrary number of locally irregular inclusions are generated over a wide range of fiber volume fractions. The finite-volume direct averaging micromechanics is then employed to evaluate the homogenized thermo-mechanical moduli of each RUC. Subsequently, a two-dimensional deep convolution neural network (CNN) is constructed as a surrogate model to extract the statistical correlations between the RUC geometrical information and the corresponding homogenized response. The RUC images together with their homogenized moduli are divided into two datasets in a ratio of 9:1 with the former part used for training the CNN model and the latter part used for verification. The results presented in this contribution demonstrate that the deep CNN predictions exhibit remarkable correlations with the theoretical values generated by the finite-volume micromechanics, with a maximum relative prediction error of less than 8%, providing good support for the data-based homogenization approach

The global role of ppGpp synthesis in morphological differentiation and antibiotic production in Streptomyces coelicolor A3(2)

The induction of ppGpp synthesis in Streptomyces coelicolor influenced the expression of several genomic elements characteristic of streptomycete biology, including antibiotic gene clusters, conservons, and morphogenetic proteins

Contribution of transcriptional regulation to natural variations in Arabidopsis

BACKGROUND: Genetic control of gene transcription is a key component in genome evolution. To understand the transcriptional basis of natural variation, we have studied genome-wide variations in transcription and characterized the genetic variations in regulatory elements among Arabidopsis accessions. RESULTS: Among five accessions (Col-0, C24, Ler, WS-2, and NO-0) 7,508 probe sets with no detectable genomic sequence variations were identified on the basis of the comparative genomic hybridization to the Arabidopsis GeneChip microarray, and used for accession-specific transcriptome analysis. Two-way ANOVA analysis has identified 60 genes whose mRNA levels differed in different accession backgrounds in an organ-dependent manner. Most of these genes were involved in stress responses and late stages of plant development, such as seed development. Correlation analysis of expression patterns of these 7,508 genes between pairs of accessions identified a group of 65 highly plastic genes with distinct expression patterns in each accession. CONCLUSION: Genes that show substantial genetic variation in mRNA level are those with functions in signal transduction, transcription and stress response, suggesting the existence of variations in the regulatory mechanisms for these genes among different accessions. This is in contrast to those genes with significant polymorphisms in the coding regions identified by genomic hybridization, which include genes encoding transposon-related proteins, kinases and disease-resistance proteins. While relatively fewer sequence variations were detected on average in the coding regions of these genes, a number of differences were identified from the upstream regions, several of which alter potential cis-regulatory elements. Our results suggest that nucleotide polymorphisms in regulatory elements of genes encoding controlling factors could be primary targets of natural selection and a driving force behind the evolution of Arabidopsis accessions

Expression Profile Matrix of Arabidopsis Transcription Factor Genes Suggests Their Putative Functions in Response to Environmental Stresses

Numerous studies have shown that transcription factors are important in regulating plant responses to environmental stress. However, specific functions for most of the genes encoding transcription factors are unclear. In this study, we used mRNA profiles generated from microarray experiments to deduce the functions of genes encoding known and putative Arabidopsis transcription factors. The mRNA levels of 402 distinct transcription factor genes were examined at different developmental stages and under various stress conditions. Transcription factors potentially controlling downstream gene expression in stress signal transduction pathways were identified by observed activation and repression of the genes after certain stress treatments. The mRNA levels of a number of previously characterized transcription factor genes were changed significantly in connection with other regulatory pathways, suggesting their multifunctional nature. The expression of 74 transcription factor genes responsive to bacterial pathogen infection was reduced or abolished in mutants that have defects in salicylic acid, jasmonic acid, or ethylene signaling. This observation indicates that the regulation of these genes is mediated at least partly by these plant hormones and suggests that the transcription factor genes are involved in the regulation of additional downstream responses mediated by these hormones. Among the 43 transcription factor genes that are induced during senescence, 28 of them also are induced by stress treatment, suggesting extensive overlap responses to these stresses. Statistical analysis of the promoter regions of the genes responsive to cold stress indicated unambiguous enrichment of known conserved transcription factor binding sites for the responses. A highly conserved novel promoter motif was identified in genes responding to a broad set of pathogen infection treatments. This observation strongly suggests that the corresponding transcription factors play general and crucial roles in the coordinated regulation of these specific regulons. Although further validation is needed, these correlative results provide a vast amount of information that can guide hypothesis-driven research to elucidate the molecular mechanisms involved in transcriptional regulation and signaling networks in plants

A genomic analysis of the archaeal system Ignicoccus hospitalis-Nanoarchaeum equitans

Sequencing of the complete genome of Ignicoccus hospitalis gives insight into its association with another species of Archaea, Nanoarchaeum equitans

Impact of elevated nitrate on sulfate-reducing bacteria: A comparative study of Desulfovibrio vulgaris

Sulfate-reducing bacteria have been extensively studied for their potential in heavy-metal bioremediation. However, the occurrence of elevated nitrate in contaminated environments has been shown to inhibit sulfate reduction activity. Although the inhibition has been suggested to result from the competition with nitrate-reducing bacteria, the possibility of direct inhibition of sulfate reducers by elevated nitrate needs to be explored. Using Desulfovibrio vulgaris as a model sulfate-reducing bacterium, functional genomics analysis reveals that osmotic stress contributed to growth inhibition by nitrate as shown by the upregulation of the glycine/betaine transporter genes and the relief of nitrate inhibition by osmoprotectants. The observation that significant growth inhibition was effected by 70 mM NaNO{sub 3} but not by 70 mM NaCl suggests the presence of inhibitory mechanisms in addition to osmotic stress. The differential expression of genes characteristic of nitrite stress responses, such as the hybrid cluster protein gene, under nitrate stress condition further indicates that nitrate stress response by D. vulgaris was linked to components of both osmotic and nitrite stress responses. The involvement of the oxidative stress response pathway, however, might be the result of a more general stress response. Given the low similarities between the response profiles to nitrate and other stresses, less-defined stress response pathways could also be important in nitrate stress, which might involve the shift in energy metabolism. The involvement of nitrite stress response upon exposure to nitrate may provide detoxification mechanisms for nitrite, which is inhibitory to sulfate-reducing bacteria, produced by microbial nitrate reduction as a metabolic intermediate and may enhance the survival of sulfate-reducing bacteria in environments with elevated nitrate level

Continuous Glucose Monitoring Reduce Duration of Hypoglycemia in Preterm Infants: A Meta-Analysis of Randomized Controlled Trials

Background: Continuous glucose monitoring (CGM) has the potential to be a valuable tool for measuring glucose concentrations in preterm neonates, but its actual effect on infants is still unclear. Therefore, we conducted a meta-analysis to evaluate the clinical effect of CGM on blood glucose levels in preterm infants requiring intensive care. Methods: We searched PubMed, Embase, CINAHL, Web of Science, Cochrane Library, and Cochrane Database of Systematic Reviews for randomized controlled trials (RCTs) comparing CGM with other interventions, and identified five studies that met our eligibility criteria. The quality of the included studies was assessed using Cochrane’s Collaboration tool. Results: Our meta-analysis demonstrated that CGM, when combined with a protocol for adjusting glucose infusion, was associated with a decrease in the average duration of hypoglycemia, a greater percentage of time spent in the euglycemic range, and reduced time spent in mild and severe hypoglycemia compared with other interventions and controls. Conclusions: Our findings suggest that CGM, with a protocol for adjusting glucose infusion, increases the time spent in the euglycemic range, and reduces the duration of hypoglycemia in preterm infants during the first week of life

Correlation between Carotid Atherosclerotic Plaques and Acute Ischemic Stroke

Objective: Carotid artery computed tomography angiography (CTA) was used to analyze carotid atherosclerotic plaques and explore the correlation of plaque properties and other factors with the occurrence of acute ischemic stroke. The aim was to provide a basis for the prevention and treatment of acute ischemic stroke. Methods: Patients who underwent carotid artery CTA and magnetic resonance diffusion-weighted imaging (DWI) within 2 weeks before or after carotid artery CTA were analyzed retrospectively. Based on magnetic resonance DWI data, these patients were divided into the acute ischemic stroke group (n=95) and non-acute ischemic stroke group (n=102). The clinical data, laboratory data, and nature and surface morphology of the carotid plaques on CTA were compared between the two groups. Variables with P<0.05 were included in a multivariate logistic regression analysis to determine the risk factors of acute ischemic stroke. Results: Age, hypertension history, and levels of total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL), homocysteine (Hcy), cystatin C (Cys-C), and glycated hemoglobin (HbA1c) differed significantly between the two groups. Multivariate regression analysis revealed that age ≥65 years (odds ratio [OR]: 4.95), hypertension (OR: 9.91), high TC (OR: 2.78), high Hcy (OR: 3.07), high HbA1c (OR: 4.60), and lipid plaque (OR: 4.89) were the independent risk factors for acute ischemic stroke. A high HDL level (OR of 0.13) was identified as a protective factor for the development of acute ischemic stroke. Conclusion: Carotid atherosclerosis is related to acute ischemic stroke occurrence. Furthermore, the presence of lipid plaques is a risk factor for acute ischemic stroke. Combined with some laboratory indicators, carotid artery CTA can judge the nature of carotid plaques and provide a basis for the prevention and treatment of acute ischemic stroke