THREE-DIMENSIONAL MODELING OF FLOW IN WATER-PUMP INTAKES

SILVA JOSE MATOS,DUARTE ALEXANDRE CAIMOTO,ECA LUIS 한국수자원학회 2005 한국수자원학회 학술대회 Vol.2005 No.1

Health Monitoring System (HMS) for structural assessment

e Matos, Jose Campos,Garcia, Oscar,Henriques, Antonio Abel,Casas, Joan Ramon,Vehi, Josep Techno-Press 2009 Smart Structures and Systems, An International Jou Vol.5 No.3

As in any engineering application, the problem of structural assessment should face the different uncertainties present in real world. The main source of uncertainty in Health Monitoring System (HMS) applications are those related to the sensor accuracy, the theoretical models and the variability in structural parameters and applied loads. In present work, two methodologies have been developed to deal with these uncertainties in order to adopt reliable decisions related to the presence of damage. A simple example, a steel beam analysis, is considered in order to establish a liable comparison between them. Also, such methodologies are used with a developed structural assessment algorithm that consists in a direct and consistent comparison between sensor data and numerical model results, both affected by uncertainty. Such algorithm is applied to a simple concrete laboratory beam, tested till rupture, to show it feasibility and operational process. From these applications several conclusions are derived with a high value, regarding the final objective of the work, which is the implementation of this algorithm within a HMS, developed and applied into a prototype structure.

A method using artificial neural networks to morphologically assess mouse blastocyst quality

Matos, Felipe Delestro,Rocha, Jose Celso,Nogueira, Marcelo Fabio Gouveia Korean Society of Animal Sciences and Technology 2014 한국축산학회지 Vol.56 No.4

Background: Morphologically classifying embryos is important for numerous laboratory techniques, which range from basic methods to methods for assisted reproduction. However, the standard method currently used for classification is subjective and depends on an embryologist's prior training. Thus, our work was aimed at developing software to classify morphological quality for blastocysts based on digital images. Methods: The developed methodology is suitable for the assistance of the embryologist on the task of analyzing blastocysts. The software uses artificial neural network techniques as a machine learning technique. These networks analyze both visual variables extracted from an image and biological features for an embryo. Results: After the training process the final accuracy of the system using this method was 95%. To aid the end-users in operating this system, we developed a graphical user interface that can be used to produce a quality assessment based on a previously trained artificial neural network. Conclusions: This process has a high potential for applicability because it can be adapted to additional species with greater economic appeal (human beings and cattle). Based on an objective assessment (without personal bias from the embryologist) and with high reproducibility between samples or different clinics and laboratories, this method will facilitate such classification in the future as an alternative practice for assessing embryo morphologies.

RESEARCH : Open Access ; A method using artificial neural networks to morphologically assess mouse blastocyst quality

( Felipe Delestro Matos ),( Jose Celso Rocha ),( Marcelo Fabio Gouveia Nogueira ) 한국동물자원과학회(구 한국축산학회) 2014 한국축산학회지 Vol.56 No.15

Background: Morphologically classifying embryos is important for numerous laboratory techniques, which range from basic methods to methods for assisted reproduction. However, the standard method currently used for classification is subjective and depends on an embryologist’s prior training. Thus, our work was aimed at developing software to classify morphological quality for blastocysts based on digital images. Methods: The developed methodology is suitable for the assistance of the embryologist on the task of analyzing blastocysts. The software uses artificial neural network techniques as a machine learning technique. These networks analyze both visual variables extracted from an image and biological features for an embryo. Results: After the training process the final accuracy of the system using this method was 95%. To aid the end-users in operating this system, we developed a graphical user interface that can be used to produce a quality assessment based on a previously trained artificial neural network. Conclusions: This process has a high potential for applicability because it can be adapted to additional species with greater economic appeal (human beings and cattle). Based on an objective assessment (without personal bias from the embryologist) and with high reproducibility between samples or different clinics and laboratories, this method will facilitate such classification in the future as an alternative practice for assessing embryo morphologies.

The Phospholipid Linoleoylglycerophosphocholine as a Biomarker of Directly Measured Insulin Resistance

Maria Camila Pérez-Matos,Martha Catalina Morales-Álvarez,Freddy Jean Karlo Toloza,Maria Laura Ricardo-Silgado,Jose Oscar Mantilla-Rivas,Jairo Arturo Pinzón-Cortes,Maritza Perez-Mayorga,Elizabeth Jimén 대한당뇨병학회 2017 Diabetes and Metabolism Journal Vol.41 No.6

Background: Plasma concentrations of some lysophospholipids correlate with metabolic alterations in humans, but their potential as biomarkers of insulin resistance (IR) is insufficiently known. We aimed to explore the association between plasma linoleoylglycerophosphocholine (LGPC) and objective measures of IR in adults with different metabolic profiles. Methods: We studied 62 men and women, ages 30 to 69 years, (29% normal weight, 59% overweight, 12% obese). Participants underwent a 5-point oral glucose tolerance test (5p-OGTT) from which we calculated multiple indices of IR and insulin secretion. Fifteen participants additionally underwent a hyperinsulinemic-euglycemic clamp for estimation of insulin-stimulated glucose disposal. Plasma LGPC was determined using high performance liquid chromatography/time-of-flight mass spectrometry. Plasma LGPC was compared across quartiles defined by the IR indices. Results: Mean LGPC was 15.4±7.6 ng/mL in women and 14.1±7.3 ng/mL in men. LGPC did not correlate with body mass index, percent body fat, waist circumference, blood pressure, glycosylated hemoglobin, log-triglycerides, or high density lipoprotein cholesterol. Plasma LGPC concentrations was not systematically associated with any of the studied 5p-OGTT-derived IR indices. However, LGPC exhibited a significant negative correlation with glucose disposal in the clamp (Spearman r=–0.56, P=0.029). Despite not being diabetic, participants with higher plasma LGPC exhibited significantly higher post-challenge plasma glucose excursions in the 5p-OGTT (P trend=0.021 for the increase in glucose area under the curve across quartiles of plasma LGPC). Conclusion: In our sample of Latino adults without known diabetes, LGPC showed potential as a biomarker of IR and impaired glucose metabolism.

Prediction of the remaining service life of existing concrete bridges in infrastructural networks based on carbonation and chloride ingress

Ivan Zambon,Anja Vidović,Alfred Strauss,Jose Matos,Norbert Friedl 국제구조공학회 2018 Smart Structures and Systems, An International Jou Vol.21 No.3

The second half of the 20th century was marked with a significant raise in amount of railway bridges in Austria made of reinforced concrete. Today, many of these bridges are slowly approaching the end of their envisaged service life. Current methodology of assessment and evaluation of structural condition is based on visual inspections, which, due to its subjectivity, can lead to delayed interventions, irreparable damages and additional costs. Thus, to support engineers in the process of structural evaluation and prediction of the remaining service life, the Austrian Federal Railways (oBB) commissioned the formation of a concept for an anticipatory life cycle management of engineering structures. The part concerning concrete bridges consisted of forming a bridge management system (BMS) in a form of a web-based analysis tool, known as the LeCIE_tool. Contrary to most BMSs, where prediction of a condition is based on Markovian models, in the LeCIE_tool, the time-dependent deterioration mechanisms of chloride- and carbonation-induced corrosion are used as the most common deterioration processes in transportation infrastructure. Hence, the main aim of this article is to describe the background of the introduced tool, with a discussion on exposure classes and crucial parameters of chloride ingress and carbonation models. Moreover, the article presents a verification of the generated analysis tool through service life prediction on a dozen of bridges of the Austrian railway network, as well as a case study with a more detailed description and implementation of the concept applied.

Prohibitin 1 Regulates the H19-Igf2 Axis and Proliferation in Hepatocytes

Ramani, Komal,Mavila, Nirmala,Ko, Kwang Suk,Mato, José,M.,Lu, Shelly C. American Society for Biochemistry and Molecular Bi 2016 The Journal of biological chemistry Vol.291 No.46

<P>Prohibitin 1 (PHB1) is a mitochondrial chaperone that regulates cell growth. Phb1 knock-out mice exhibit liver injury and hepatocellular carcinoma (HCC). Phb1 knock-out livers show induction of tumor growth-associated genes, H19 and insulin-like growth factor 2 (Igf2). These genes are controlled by the imprinting control region (ICR) containing CCCTC-binding transcription factor (CTCF)-binding sites. Because Phb1 knock-out mice exhibited induction of H19 and Igf2, we hypothesized that PHB1-mediated regulation of the H19-Igf2 axis might control cell proliferation in normal hepatocytes. H19 and Igf2 were induced (8-20-fold) in 3-week-old Phb1 knock-out livers, in Phb1 siRNA-treated AML12 hepatocytes (2-fold), and HCC cell lines when compared with control. Phb1 knockdown lowered CTCF protein in AML12 by approximate to 30% when compared with control. CTCF overexpression lowered basal H19 and Igf2 expression by 30% and suppressed Phb1 knockdown-mediated induction of these genes. CTCF and PHB1 co-immunoprecipitated and co-localized on the ICR element, and Phb1 knockdown lowered CTCF ICR binding activity. The results suggest that PHB1 and CTCF cooperation may control the H19-Igf2 axis. Human HCC tissues with high levels of H19 and IGF2 exhibited a 40-50% reduction in PHB1 and CTCF expression and their ICR binding activity. Silencing Phb1 or overexpressing H19 in the mouse HCC cell line, SAMe-D, induced cell growth. Blocking H19 induction prevented Phb1 knockdown-mediated growth, whereas H19 overexpression had the reverse effect. Interestingly H19 silencing induced PHB1 expression. Taken together, our results demonstrate that the H19-Igf2 axis is negatively regulated by CTCF-PHB1 cooperation and that H19 is involved in modulating the growth-suppressive effect of PHB1 in the liver.</P>

Prediction of the remaining service life of existing concrete bridges in infrastructural networks based on carbonation and chloride ingress

Zambon, Ivan,Vidovic, Anja,Strauss, Alfred,Matos, Jose,Friedl, Norbert Techno-Press 2018 Smart Structures and Systems, An International Jou Vol.21 No.3

The second half of the 20th century was marked with a significant raise in amount of railway bridges in Austria made of reinforced concrete. Today, many of these bridges are slowly approaching the end of their envisaged service life. Current methodology of assessment and evaluation of structural condition is based on visual inspections, which, due to its subjectivity, can lead to delayed interventions, irreparable damages and additional costs. Thus, to support engineers in the process of structural evaluation and prediction of the remaining service life, the Austrian Federal Railways (${\ddot{O}}$ BB) commissioned the formation of a concept for an anticipatory life cycle management of engineering structures. The part concerning concrete bridges consisted of forming a bridge management system (BMS) in a form of a web-based analysis tool, known as the LeCIE_tool. Contrary to most BMSs, where prediction of a condition is based on Markovian models, in the LeCIE_tool, the time-dependent deterioration mechanisms of chloride- and carbonation-induced corrosion are used as the most common deterioration processes in transportation infrastructure. Hence, the main aim of this article is to describe the background of the introduced tool, with a discussion on exposure classes and crucial parameters of chloride ingress and carbonation models. Moreover, the article presents a verification of the generated analysis tool through service life prediction on a dozen of bridges of the Austrian railway network, as well as a case study with a more detailed description and implementation of the concept applied.