Aumento de COP de bombas de calor para produção de água quente sanitária

Mestrado em Engenharia MecânicaO presente trabalho propõe-se estudar a melhoria do COP em bombas de calor para produção de água quente sanitária. Este estudo foi efectuado em parceria com a empresa BOSCH e todos os equipamentos analisados perten-cem a esta. Para aferir que alterações podem vir a dar origem a um aumento do COP, foi construído um modelo que simula o funcionamento de todo o sis-tema. Este integra subprogramas para cada componente principal (compres-sor, condensador, válvula de expansão e evaporador), incluindo o tanque de água quente e os permutadores de calor. Como o modelo de estratificação térmica do tanque se mostrou inadequado, os testes de COP “virtuais” não foram realizados segundo a norma EN 16147. No final são apresentadas as alternativas mais promissoras nas quais se integram alterações a nível do compressor e até mesmo a inserção de um componente extra.The present work proposes to study the improvement of the COP in heat pump water heaters. This study was conducted in partnership with BOSCH and all the analyzed equipment belong to this company. To find which changes are most likely to result in a COP improvement, a model was constructed to simu-late the system. This model includes a subprogram to each of every main parts (compressor, condenser, expansion valve and evaporator), including the hot water tank and the heat exchangers. As the model of thermal stratification tank proved inadequate, the COP "virtual" tests were not performed in accordance with EN 16147. At the end, the most promising alternatives, such as changes to the compressor and even the inclusion of an extra component, are presented

Segmentation of quantum generated sequences by using the Jensen-Shannon divergence

The Jensen-Shannon divergence has been successfully applied as a segmentation tool for symbolic sequences, that is to separate the sequence into subsequences with the same symbolic content. In this work, we propose a method, based on the the Jensen-Shannon divergence, for segmentation of what we call \textit{quantum generated sequences}, which consist in symbolic sequences generated from measuring a quantum system. For one-qubit and two-qubit systems, we show that the proposed method is adequate for segmentation

A Personal Robot as an Improvement to the Customers’ In- Store Experience

Robotics is a growing industry with applications in numerous markets, including retail, transportation, manufacturing, and even as personal assistants. Consumers have evolved to expect more from the buying experience, and retailers are looking at technology to keep consumers engaged. In today’s highly competitive business climate, being able to attract, serve, and satisfy more customers is a key to success. It is our belief that smart robots will play a significant role in physical retail in the future. One successful example is wGO, a robotic shopping assistant developed by Follow Inspiration. The wGO is an autonomous and self-driven shopping cart, designed to follow people with reduced mobility (the elderly, people in wheelchair, pregnant women, those with temporary reduced mobility, etc.) in commercial environments. With the Retail Robot, the user can control the shopping cart without the need to push it. This brings numerous advantages and a higher level of comfort since the user does not need to worry about carrying the groceries or pushing the shopping cart. The wGO operates under a vision-guided approach based on user-following with no need for any external device. Its integrated architecture of control, navigation, perception, planning, and awareness is designed to enable the robot to successfully perform personal assistance, while the user is shopping

Plasma and stool metabolomic biomarkers of non-alcoholic fatty liver disease in Argentina

Background: Non-invasive biomarkers are urgently needed to identify patients with non-alcoholic fatty liver disease (NAFLD) at risk of disease progression, particularly in high prevalence areas such as Latin America. In this regard, targeted metabolomics is a powerful technology for discovering new gut microbiome-derived metabolites. Thus, we aimed to identify potential metabolomic biomarkers related to NAFLD stage in Argentina, and to assess their relationship with clinical and host genetic factors. Methods: Adult healthy volunteers (HV) and biopsy-proven simple steatosis (SS) or non-alcoholic steatohepatitis (NASH) patients were recruited. Demographic, clinical and food frequency consumption data, as well as plasma and stool samples were collected. SNP rs738409 (PNPLA3 gene) was determined in all volunteers. HPLC and flow injection analysis with MS/MS in tandem was applied for metabolomic studies using the MxP Quant 500 Kit (Biocrates Life Sciences AG, Austria). Significantly different metabolites among groups were identified with MetaboAnalyst v4.0. Bivariate and multivariate analyses were used to identify variables that were independently related to NAFLD stage. Forward stepwise logistic regression models were constructed to design the best feature combination that could distinguish between study groups. Receiver Operating Characteristic (ROC) curves were used to evaluate models? accuracy.Results: 19 HV, 12 SS and 22 NASH patients were recruited. Diet was similar between groups. The concentration of 33 out of 424 detected metabolites (25 in plasma and 8 in stool) was significantly different among study groups. Levels of triglycerides (TG) were higher among NAFLD patients, whereas levels of phosphatidylcholines (PC) and lysoPC were higher among HV. The PNPLA3 risk genotype for NAFLD and NASH (GG) was related to higher plasma levels of eicosenoic acid FA(20:1) (p<0.001). Plasma metabolites showed a higher accuracy for diagnosis of NAFLD and NASH when compared to stool metabolites (Table 1). Body mass index (BMI) and plasma levels of PC aa C24:0, FA(20:1) and TG(16:1_34:1) showed high accuracy for diagnosis of NAFLD; whereas the best AUROC for discriminating NASH from SS was that of plasma levels of PC aa C24:0 and PC ae C40:1 (Table 1).Conclusions: Gut microbiome-derived metabolomic biomarkers were identified in plasma and stool, but plasma metabolites were better diagnostic biomarkers of NAFLD and NASH in Argentina. Further validation studies are needed.Fil: Mazzini, Flavia Noelia. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Cook, Frank. Novartis Institutes For Biomedical Research; Estados UnidosFil: Gounarides, John. Novartis Institutes For Biomedical Research; Estados UnidosFil: Marciano, Sebastian. Hospital Italiano; ArgentinaFil: Haddad, Leila. Hospital Italiano; ArgentinaFil: Tamaroff, Ana Jesica. Hospital Italiano; ArgentinaFil: Casciato, Paola. Hospital Italiano; ArgentinaFil: Narvaez, Adriana Haydée. Hospital Italiano; ArgentinaFil: Mascardi, María Florencia. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Anders, Margarita. Hospital Alemán; ArgentinaFil: Orozco, Federico. Hospital Alemán; ArgentinaFil: Quiroz, Nicolas. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Risk, Marcelo. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Gutt, Susana. Hospital Italiano; ArgentinaFil: Gadano, Adrián Carlos. Hospital Italiano; ArgentinaFil: Mendez Garcia, Celia. Hospital Italiano; ArgentinaFil: Marro, Martin. Novartis Institutes For Biomedical Research; Estados UnidosFil: Penas Steinhardt, Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Trinks, Julieta. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional e Ingeniería Biomédica - Hospital Italiano. Instituto de Medicina Traslacional e Ingeniería Biomédica.- Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional e Ingeniería Biomédica; ArgentinaThe Liver Meeting Digital ExperienceEstados UnidosAmerican Association for the Study of the Liver Diseas

Plasma and stool metabolomic biomarkers of non-alcoholic fatty liver disease in Argentina

Non-invasive biomarkers are urgently needed to identify NAFLD patients at risk of progression to non-alcoholic steatohepatitis (NASH), particularly in high prevalence areas such as Latin America. Thus, we aimed to identify potential metabolomic biomarkers related to NAFLD stage in Argentina, and to assess their relationship with clinical and host genetic factors.Healthy volunteers (n=19) and biopsy-proven simple steatosis (n=12) or non-alcoholic steatohepatitis (n=22) patients with similar food intake data were recruited. Plasma and stool samples, as well as demographic and clinical data were collected. SNP rs738409 (PNPLA3 gene) was determined in all volunteers. HPLC and flow injection analysis with MS/MS in tandem was applied for metabolomic studies using the MxP Quant 500 Kit (Biocrates Life Sciences AG, Austria) and MetaboAnalyst v4.0. Bivariate and multivariate analyses identified variables independently related to NAFLD stage. Forward stepwise logistic regression models were constructed to diagnose NAFLD and NASH. ROC curves were used to evaluate models? accuracy.The concentration of 33 out of the 424 detected metabolites (25 in plasma and 8 in stool) significantly differed among groups. Levels of triglycerides (TG) were higher among NAFLD patients, whereas levels of phosphatidylcholines (PC) and lysoPC were lower among them. The PNPLA3 risk genotype was related to higher plasma levels of eicosenoic acid FA(20:1) (p<0.001). Plasma metabolites showed a higher accuracy for diagnosis of NAFLD and NASH (AUROC=1) than stool metabolites (AUROC=0.79 and 0.90, respectively). Body mass index and plasma levels of PC aa C24:0, FA(20:1) and TG(16:1_34:1) showed high accuracy for diagnosis of NAFLD (AUROC=1); whereas plasma levels of PC aa C24:0 and PC ae C40:1 showed AUROC=1 for discriminating NAFLD stages.In conclusion, potential metabolomic biomarkers for diagnosis and progression of NAFLD were identified in Argentina. Further validation studies are needed.Fil: Mazzini, Flavia. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Cook, Frank. Novartis Institutes For Biomedical Research; Estados UnidosFil: Gounarides, John. Novartis Institutes For Biomedical Research; Estados UnidosFil: Marciano, Sebastian. Hospital Italiano; ArgentinaFil: Haddad, Leila. Hospital Italiano; ArgentinaFil: Tamaroff, Ana Jesica. Hospital Italiano; ArgentinaFil: Casciato, Paola. Hospital Italiano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Narvaez, Adriana Haydée. Hospital Italiano; ArgentinaFil: Mascardi, Maria Florencia. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Anders, Margarita. Hospital Alemán; ArgentinaFil: Orozco, F.. Hospital Alemán; ArgentinaFil: Quiroz, Nicolas. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Risk, Marcelo. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Gutt, Susana. Hospital Italiano; ArgentinaFil: Gadano, Adrián. Hospital Italiano; ArgentinaFil: Méndez García, Celia. Novartis Institutes For Biomedical Research; Estados UnidosFil: Marro, Martin. Novartis Institutes For Biomedical Research; Estados UnidosFil: Penas Steinhardt, Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Lujan. Departamento de Cs.basicas. Laboratorio de Genomica Computacional.; ArgentinaFil: Trinks, Julieta. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaReunión Anual de Sociedades de BiocienciasArgentinaSociedad Argentina de Investigación ClínicaSociedad Argentina de InmunologíaSociedad Argentina de Fisiologí

Plasma and stool metabolomics to identify microbiota derived-biomarkers of metabolic dysfunction-associated fatty liver disease: effect of PNPLA3 genotype

Introduction: Non-invasive biomarkers are needed for metabolic dysfunction-associated fatty liver disease (MAFLD), especially for patients at risk of disease progression in high-prevalence areas. The microbiota and its metabolites represent a niche for MAFLD biomarker discovery. However, studies are not reproducible as the microbiota is variable. Objectives: We aimed to identify microbiota-derived metabolomic biomarkers that may contribute to the higher MAFLD prevalence and different disease severity in Latin America, where data is scarce. Methods: We compared the plasma and stool metabolomes, gene patatin-like phospholipase domain-containing 3 (PNPLA3) rs738409 single nucleotide polymorphism (SNP), diet, demographic and clinical data of 33 patients (12 simple steatosis and 21 steatohepatitis) and 19 healthy volunteers (HV). The potential predictive utility of the identified biomarkers for MAFLD diagnosis and progression was evaluated by logistic regression modelling and ROC curves. Results: Twenty-four (22 in plasma and 2 in stool) out of 424 metabolites differed among groups. Plasma triglyceride (TG) levels were higher among MAFLD patients, whereas plasma phosphatidylcholine (PC) and lysoPC levels were lower among HV. The PNPLA3 risk genotype was related to higher plasma levels of eicosenoic acid or fatty acid 20:1 (FA(20:1)). Body mass index and plasma levels of PCaaC24:0, FA(20:1) and TG (16:1_34:1) showed the best AUROC for MAFLD diagnosis, whereas steatosis and steatohepatitis could be discriminated with plasma levels of PCaaC24:0 and PCaeC40:1. Conclusion: This study identified for the first time MAFLD potential non-invasive biomarkers in a Latin American population. The association of PNPLA3 genotype with FA(20:1) suggests a novel metabolic pathway influencing MAFLD pathogenesis.Fil: Mazzini, Flavia Noelia. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Cook, Frank. Novartis Institutes For Biomedical Research; Estados UnidosFil: Gounarides, John. Novartis Institutes For Biomedical Research; Estados UnidosFil: Marciano, Sebastián. Hospital Italiano; ArgentinaFil: Haddad, Leila. Hospital Italiano; ArgentinaFil: Tamaroff, Ana Jesica. Hospital Italiano; ArgentinaFil: Casciato, Paola. Hospital Italiano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional e Ingeniería Biomédica - Hospital Italiano. Instituto de Medicina Traslacional e Ingeniería Biomédica.- Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional e Ingeniería Biomédica; ArgentinaFil: Narvaez, Adrián. Hospital Italiano; ArgentinaFil: Mascardi, María Florencia. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Anders, Margarita. Hospital Alemán; ArgentinaFil: Orozco, Federico. Hospital Alemán; ArgentinaFil: Quiroz, Nicolas. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Risk, Marcelo. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; ArgentinaFil: Gutt, Susana. Hospital Italiano; ArgentinaFil: Gadano, Adrián Carlos. Hospital Italiano; ArgentinaFil: Méndez García, Celia. Novartis Institutes For Biomedical Research; Estados UnidosFil: Marro, Martin L.. Novartis Institutes For Biomedical Research; Estados UnidosFil: Penas Steinhardt, Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Lujan. Departamento de Cs.basicas. Laboratorio de Genomica Computacional.; ArgentinaFil: Trinks, Julieta. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Hospital Italiano. Instituto de Medicina Traslacional E Ingenieria Biomedica. - Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional E Ingenieria Biomedica.; Argentin