Search

In order to achieve better motion accuracy and higher robustness of the shipborne rocket launcher position servo system driven by a permanent magnet synchronous motor (PMSM), a passivity-based controller based on active disturbance rejection control (ADRC) optimized by improved particle swarm optimization-back propagation (IPSO-BP) algorithm is proposed in this paper. The convenient method of interconnection and damping assignment and passivity-based control (IDA-PBC) is adopted to establish the port controlled Hamiltonian system with dissipation (PCHD) model of PMSM. To further enhance the robustness and adaptability of traditional ADRC, an BP algorithm is introduced to on-line update the proportional, integral, and derivative gains of ADRC. Furthermore, to improve the learning capability, the improved PSO algorithm is adopted to optimize the learning rates of the back propagation neural networks. The results of numerical simulation and prototype test indicate that the proposed IPSO-BP-ADRC-PBC controller has better static and dynamic performance than the ADRC-PBC and BP-ADRC-PBC controller with fixed learning rate. [ABSTRACT FROM AUTHOR]

Many organisms, including the fathead minnow (Pimephales promelas), a toxicological model organism, establish social hierarchies. The social rank of each male in a population is under the control of the hypothalamic-pituitary-gonadal (HPG) axis mainly through regulation of circulating androgen concentrations, which in turn drive the expression of secondary sex characteristics (SSCs). As dominant and subordinate males in an exposure study are initially under different physiological conditions (i.e., differing plasma androgen concentrations), we proposed that they belong to different subpopulations in the context of exposure to compounds that may interact with the HPG axis. Using a meta-analysis of our data from several previously published studies, we corroborated the hypothesis that social status, as indicated by SSCs, results in distinct clusters (eigenvalues >0.8 explaining >80% of variability) with differential expression of plasma vitellogenin, a commonly used biomarker of exposure to contaminants of emerging concern (CEC). Furthermore, we confirmed our predictions that exposure to estrogenic CECs would homogenize plasma vitellogenin response (E1: cluster mean SSC values decreased to 4.33 and 4.86 relative to those of control; E2: decreased to 4.8 and 5.37) across the social hierarchy. In contrast, serotonin-specific reuptake inhibitors expand this response range (cluster mean SSC increased to 5.21 and 6.5 relative to those of control). Our results demonstrated that social hierarchies in male fathead minnows result in heterogeneous responses to chemical exposure. These results represent a cautionary note for the experimental design of single-sex exposure studies. We anticipate our study to be a starting point for the re-evaluation of toxicological data analyses in single sex exposure experiments. [ABSTRACT FROM AUTHOR]

Fundamental questions remain about the application of omics in environmental risk assessments, such as the consistency of data across laboratories. The objective of the present study was to determine the congruence of transcript data across 6 independent laboratories. Male fathead minnows were exposed to a measured concentration of 15.8 ng/L 17α-ethinylestradiol (EE2) for 96 h. Livers were divided equally and sent to the participating laboratories for transcriptomic analysis using the same fathead minnow microarray. Each laboratory was free to apply bioinformatics pipelines of its choice. There were 12 491 transcripts that were identified by one or more of the laboratories as responsive to EE2. Of these, 587 transcripts (4.7%) were detected by all laboratories. Mean overlap for differentially expressed genes among laboratories was approximately 50%, which improved to approximately 59.0% using a standardized analysis pipeline. The dynamic range of fold change estimates was variable between laboratories, but ranking transcripts by their relative fold difference resulted in a positive relationship for comparisons between any 2 laboratories (mean R2 > 0.9, p < 0.001). Ten estrogen-responsive genes encompassing a fold change range from dramatic (>20-fold; e.g., vitellogenin) to subtle (∼2-fold; i.e., block of proliferation 1) were identified as differentially expressed, suggesting that laboratories can consistently identify transcripts that are known a priori to be perturbed by a chemical stressor. Thus, attention should turn toward identifying core transcriptional networks using focused arrays for specific chemicals. In addition, agreed-on bioinformatics pipelines and the ranking of genes based on fold change (as opposed to p value) should be considered in environmental risk assessment. These recommendations are expected to improve comparisons across laboratories and advance the use of omics in regulations. Environ Toxicol Chem 2017;36:2593-2601. © 2017 SETAC [ABSTRACT FROM AUTHOR]

In this article, authors focus on genetic variation in terms of toxicogenomics. They mention that genetic variation has an impact on organisms' transcritomic responses to chemical stressors, molecular mechanism and their biomakers. They highlight that transcriptomic variations has a wide range among species and study of variations depends on genetics, physiology, ecology and evolution.

Aiming at the characteristics of PLC application technology course, and improving teaching effect of PLC practice, a PLC simulation training system based on MCGS configuration software is designed and realized. Three classic PLC control subsystems are embedded in the simulation system. Control method of each subsystem is using the MCGS monitoring system and combining with Siemens 200 PLC control scheme. Subsystem control function is realized through PLC and dynamic real-time monitoring of system, working process is realized by configuration software MCGS. This paper gives the hardware design and software design of the system in detail. [ABSTRACT FROM AUTHOR]

Fathead minnow and zebrafish are among the most intensively studied fish species in environmental toxicogenomics. To aid the assessment and interpretation of subtle transcriptomic effects from treatment conditions of interest, better characterization and understanding are needed for natural variation in gene expression among fish individuals from lab cultures. Leveraging the transcriptomics data from a number of our toxicogenomics studies conducted over the years, we conducted a meta-analysis of nearly 600 microarrays generated from the ovary tissue of untreated, reproductively mature fathead minnow and zebrafish samples. As expected, there was considerable batch-to-batch transcriptomic variation; this “batch-effect” appeared to differentially impact subsets of fish transcriptomes in a nonsystematic way. Temporally more closely spaced batches tended to share a greater transcriptomic similarity among one another. The overall level of within-batch variation was quite low in fish ovary tissue, making it a suitable system for studying chemical stressors with subtle biological effects. The observed differences in the within-batch variability of gene expression, at the levels of both individual genes and pathways, were probably both technical and biological. This suggests that biological interpretation and prioritization of genes and pathways targeted by experimental conditions should take into account both their intrinsic variability and the size of induced transcriptional changes. There was significant conservation of both the genomes and transcriptomes between fathead minnow and zebrafish. The high degree of conservation offers promising opportunities in not only studying fish molecular responses to environmental stressors by a comparative biology approach, but also effective sharing of a large amount of existing public transcriptomics data for developing toxicogenomics applications. [ABSTRACT FROM AUTHOR]

Environmental health risk assessors are challenged to understand and incorporate new data streams as the field of toxicology continues to adopt new molecular and systems biology technologies. Systematic screening reviews can help risk assessors and assessment teams determine which studies to consider for inclusion in a human health assessment. A tool for systematic reviews should be standardized and transparent in order to consistently determine which studies meet minimum quality criteria prior to performing in-depth analyses of the data. The Systematic Omics Analysis Review (SOAR) tool is focused on assisting risk assessment support teams in performing systematic reviews of transcriptomic studies. SOAR is a spreadsheet tool of 35 objective questions developed by domain experts, focused on transcriptomic microarray studies, and including four main topics: test system, test substance, experimental design, and microarray data. The tool will be used as a guide to identify studies that meet basic published quality criteria, such as those defined by the Minimum Information About a Microarray Experiment standard and the Toxicological Data Reliability Assessment Tool. Seven scientists were recruited to test the tool by using it to independently rate 15 published manuscripts that study chemical exposures with microarrays. Using their feedback, questions were weighted based on importance of the information and a suitability cutoff was set for each of the four topic sections. The final validation resulted in 100% agreement between the users on four separate manuscripts, showing that the SOAR tool may be used to facilitate the standardized and transparent screening of microarray literature for environmental human health risk assessment. [ABSTRACT FROM AUTHOR]

Reports on a study of genetic manipulation during maize domestication from teosinte in middle America. Study of the gene teosinte branched 1 (tb1); Determination of traits; Sequence of a large portion of tb1 from various samples; Discovery of the greatest variation in the promoter region, which controls the amount of expression.