40 research outputs found

    Fuzzy control applied to an electrical power generation system mounted on tractors for driving of agricultural implements

    Get PDF
    CAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORThe demand of the agricultural sector for more operationally efficient machines and implements motivated the development of alternatives for driving of this equipment. Aiming an electrical supply to apply in agricultural implements, this study proposes a system that uses the tractor power take off to activate a synchronous generator, using a fuzzy logic controller designed to regulate the generated voltage level. Different control architectures were tested and evaluated by simulations. In the initial stage were evaluated fuzzy PI, fuzzy PD and fuzzy PID controllers of multiple inputs and single output (MISO) and the error of the generated voltage as state variable. Subsequently, it was evaluated a fuzzy PI controller of single input and multiple outputs (SIMO) with a modified rule base for the system. In the final stage, the angular drive speed was included as state variable of the controller. The behavior of each architecture was analyzed by means of performance indexes. The results show that among the tested controllers, the modified fuzzy PI SIMO presented the best performance values while maintaining the operating variables within the established limits.The demand of the agricultural sector for more operationally efficient machines and implements motivated the development of alternatives for driving of this equipment. Aiming an electrical supply to apply in agricultural implements, this study proposes a365846857CAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIORsem informaçã

    Identification of MicroRNAs as Potential Prognostic Markers in Ependymoma

    Get PDF
    INTRODUCTION: We have examined expression of microRNAs (miRNAs) in ependymomas to identify molecular markers of value for clinical management. miRNAs are non-coding RNAs that can block mRNA translation and affect mRNA stability. Changes in the expression of miRNAs have been correlated with many human cancers. MATERIALS AND METHODS: We have utilized TaqMan Low Density Arrays to evaluate the expression of 365 miRNAs in ependymomas and normal brain tissue. We first demonstrated the similarity of expression profiles of paired frozen tissue (FT) and paraffin-embedded specimens (FFPE). We compared the miRNA expression profiles of 34 FFPE ependymoma samples with 8 microdissected normal brain tissue specimens enriched for ependymal cells. miRNA expression profiles were then correlated with tumor location, histology and other clinicopathological features. RESULTS: We have identified miRNAs that are over-expressed in ependymomas, such as miR-135a and miR-17-5p, and down-regulated, such as miR-383 and miR-485-5p. We have also uncovered associations between expression of specific miRNAs which portend a worse prognosis. For example, we have identified a cluster of miRNAs on human chromosome 14q32 that is associated with time to relapse. We also found that miR-203 is an independent marker for relapse compared to the parameters that are currently used. Additionally, we have identified three miRNAs (let-7d, miR-596 and miR-367) that strongly correlate to overall survival. CONCLUSION: We have identified miRNAs that are differentially expressed in ependymomas compared with normal ependymal tissue. We have also uncovered significant associations of miRNAs with clinical behavior. This is the first report of clinically relevant miRNAs in ependymomas

    Global Demethylation of Rat Chondrosarcoma Cells after Treatment with 5-Aza-2′-Deoxycytidine Results in Increased Tumorigenicity

    Get PDF
    Abnormal patterns of DNA methylation are observed in several types of human cancer. While localized DNA methylation of CpG islands has been associated with gene silencing, the effect that genome-wide loss of methylation has on tumorigenesis is not completely known. To examine its effect on tumorigenesis, we induced DNA demethylation in a rat model of human chondrosarcoma using 5-aza-2-deoxycytidine. Rat specific pyrosequencing assays were utilized to assess the methylation levels in both LINEs and satellite DNA sequences following 5-aza-2-deoxycytidine treatment. Loss of DNA methylation was accompanied by an increase in invasiveness of the rat chondrosarcoma cells, in vitro, as well as by an increase in tumor growth in vivo. Subsequent microarray analysis provided insight into the gene expression changes that result from 5-aza-2-deoxycytidine induced DNA demethylation. In particular, two genes that may function in tumorigenesis, sox-2 and midkine, were expressed at low levels in control cells but upon 5-aza-2-deoxycytidine treatment these genes became overexpressed. Promoter region DNA analysis revealed that these genes were methylated in control cells but became demethylated following 5-aza-2-deoxycytidine treatment. Following withdrawal of 5-aza-2-deoxycytidine, the rat chondrosarcoma cells reestablished global DNA methylation levels that were comparable to that of control cells. Concurrently, invasiveness of the rat chondrosarcoma cells, in vitro, decreased to a level indistinguishable to that of control cells. Taken together these experiments demonstrate that global DNA hypomethylation induced by 5-aza-2-deoxycytidine may promote specific aspects of tumorigenesis in rat chondrosarcoma cells

    Pervasive gaps in Amazonian ecological research

    Get PDF

    Pervasive gaps in Amazonian ecological research

    Get PDF
    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

    Get PDF
    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
    corecore