Accuracy Analysis of Frequency Converter Estimates in Diagnostic Applications

Transportation of fluids is one of the most common and energy intensive processes in the industrial and HVAC sectors. Pumping systems are frequently subject to engineering malpractice when dimensioned, which can lead to poor operational efficiency. Moreover, pump monitoring requires dedicated measuring equipment, which imply costly investments. Inefficient pump operation and improper maintenance can increase energy costs substantially and even lead to pump failure. A centrifugal pump is commonly driven by an induction motor. Driving the induction motor with a frequency converter can diminish energy consumption in pump drives and provide better control of a process. In addition, induction machine signals can also be estimated by modern frequency converters, dispensing with the use of sensors. If the estimates are accurate enough, a pump can be modelled and integrated into the frequency converter control scheme. This can open the possibility of joint motor and pump monitoring and diagnostics, thereby allowing the detection of reliability-reducing operating states that can lead to additional maintenance costs. The goal of this work is to study the accuracy of rotational speed, torque and shaft power estimates calculated by a frequency converter. Laboratory tests were performed in order to observe estimate behaviour in both steady-state and transient operation. An induction machine driven by a vector-controlled frequency converter, coupled with another induction machine acting as load was used in the tests. The estimated quantities were obtained through the frequency converter’s Trend Recorder software. A high-precision, HBM T12 torque-speed transducer was used to measure the actual values of the aforementioned variables. The effect of the flux optimization energy saving feature on the estimate quality was also studied. A processing function was developed in MATLAB for comparison of the obtained data. The obtained results confirm the suitability of this particular converter to provide accurate enough estimates for pumping applications.

Construction of a supercritical fluid extraction (SFE) equipment: validation using annatto and fennel and extract analysis by thin layer chromatography coupled to image

Abstract The present work describes setting up a laboratory unit for supercritical fluid extraction. In addition to its construction, a survey of cost was done to compare the cost of the homemade unit with that of commercial units. The equipment was validated using an extraction of annatto seeds’ oil, and the extraction and fractionation of fennel oil were used to validate the two separators; for both systems, the solvent was carbon dioxide. The chemical profiles of annatto and fennel extracts were assessed using thin layer chromatography; the images of the chromatographic plates were processed using the free ImageJ software. The cost survey showed that the homemade equipment has a very low cost (~US$ 16,000) compared to commercial equipment. The extraction curves of annatto were similar to those obtained in the literature (yield of 3.8% oil). The separators were validated, producing both a 2.5% fraction of fennel seed extract rich in essential oils and another extract fraction composed mainly of oleoresins. The ImageJ software proved to be a low-cost tool for obtaining an initial evaluation of the chemical profile of the extracts.

Analysis of the late correspondence between our administration and Great Britain & France, with an attempt to show what are the real causes of the failure of the negotiation.

Ten pieces originally published in the Columbian Centinel. A later edition with imprint New York, Printed for E. Sargeant, 1809, contains two additional pieces.

Bayesian Analysis for the Generalized Lognormal Distribution Applied to Failure Time Analysis

There are several versions of the lognormal distribution in the statistical literature, one is based in the exponential transformation of generalized normal distribution (GN). This paper presents the Bayesian analysis for the generalized lognormal distribution (logGN) considering independent non-informative Jeffreys distributions for the parameters as well as the procedure for implementing the Gibbs sampler to obtain the posterior distributions of parameters. The results are used to analyze failure time models with right-censored and uncensored data. The proposed method is illustrated using actual failure time data of computers.

Analysis of the influence of baffles and shields on the cooling of a digital transmission equipment

In this work design criteria for cooling of electronic systems used in a digital transmission equipment are considered. An experimental study using a simulated electronic equipment in which vertically oriented circuit boards are aligned to form vertical channels is carried out. Resistors are used to simulate actual components. The temperature of several components in the printed circuit boards are measured and the influence of the baffles and shields on the cooling effect are discussed. It was observed that the use of the baffles reduce the temperature levels and, the use of shields, although protecting the components from magnetic effects, cause an increase in the temperature levels.

Postmortem diagnosis of acute myocardial infarction in patients with acute respiratory failure - demographics, etiologic and pulmonary histologic analysis

OBJECTIVES: Acute respiratory failure is present in 5% of patients with acute myocardial infarction and is responsible for 20% to 30% of the fatal post-acute myocardial infarction. The role of inflammation associated with pulmonary edema as a cause of acute respiratory failure post-acute myocardial infarction remains to be determined. We aimed to describe the demographics, etiologic data and histological pulmonary findings obtained through autopsies of patients who died during the period from 1990 to 2008 due to acute respiratory failure with no diagnosis of acute myocardial infarction during life. METHODS: This study considers 4,223 autopsies of patients who died of acute respiratory failure that was not preceded by any particular diagnosis while they were alive. The diagnosis of acute myocardial infarction was given in 218 (4.63%) patients. The age, sex and major associated diseases were recorded for each patient. Pulmonary histopathology was categorized as follows: diffuse alveolar damage, pulmonary edema, alveolar hemorrhage and lymphoplasmacytic interstitial pneumonia. The odds ratio of acute myocardial infarction associated with specific histopathology was determined by logistic regression. RESULTS: In total, 147 men were included in the study. The mean age at the time of death was 64 years. Pulmonary histopathology revealed pulmonary edema as well as the presence of diffuse alveolar damage in 72.9% of patients. Bacterial bronchopneumonia was present in 11.9% of patients, systemic arterial hypertension in 10.1% and dilated cardiomyopathy in 6.9%. A multivariate analysis demonstrated a significant positive association between acute myocardial infarction with diffuse alveolar damage and pulmonary edema. CONCLUSIONS: For the first time, we demonstrated that in autopsies of patients with acute respiratory failure as the cause of death, 5% were diagnosed with acute myocardial infarction. Pulmonary histology revealed a significant inflammatory response, which has not previously been reported.

Survival Analysis of Patients with Heart Failure: Implications of Time-Varying Regression Effects in Modeling Mortality

Background: Several models have been designed to predict survival of patients with heart failure. These, while available and widely used for both stratifying and deciding upon different treatment options on the individual level, have several limitations. Specifically, some clinical variables that may influence prognosis may have an influence that change over time. Statistical models that include such characteristic may help in evaluating prognosis. The aim of the present study was to analyze and quantify the impact of modeling heart failure survival allowing for covariates with time-varying effects known to be independent predictors of overall mortality in this clinical setting. Methodology: Survival data from an inception cohort of five hundred patients diagnosed with heart failure functional class III and IV between 2002 and 2004 and followed-up to 2006 were analyzed by using the proportional hazards Cox model and variations of the Cox's model and also of the Aalen's additive model. Principal Findings: One-hundred and eighty eight (188) patients died during follow-up. For patients under study, age, serum sodium, hemoglobin, serum creatinine, and left ventricular ejection fraction were significantly associated with mortality. Evidence of time-varying effect was suggested for the last three. Both high hemoglobin and high LV ejection fraction were associated with a reduced risk of dying with a stronger initial effect. High creatinine, associated with an increased risk of dying, also presented an initial stronger effect. The impact of age and sodium were constant over time. Conclusions: The current study points to the importance of evaluating covariates with time-varying effects in heart failure models. The analysis performed suggests that variations of Cox and Aalen models constitute a valuable tool for identifying these variables. The implementation of covariates with time-varying effects into heart failure prognostication models may reduce bias and increase the specificity of such models.

Postmortem diagnosis of acute myocardial infarction in patients with acute respiratory failure: demographics, etiologic and pulmonary histologic analysis

OBJECTIVES: Acute respiratory failure is present in 5% of patients with acute myocardial infarction and is responsible for 20% to 30% of the fatal post-acute myocardial infarction. The role of inflammation associated with pulmonary edema as a cause of acute respiratory failure post-acute myocardial infarction remains to be determined. We aimed to describe the demographics, etiologic data and histological pulmonary findings obtained through autopsies of patients who died during the period from 1990 to 2008 due to acute respiratory failure with no diagnosis of acute myocardial infarction during life. METHODS: This study considers 4,223 autopsies of patients who died of acute respiratory failure that was not preceded by any particular diagnosis while they were alive. The diagnosis of acute myocardial infarction was given in 218 (4.63%) patients. The age, sex and major associated diseases were recorded for each patient. Pulmonary histopathology was categorized as follows: diffuse alveolar damage, pulmonary edema, alveolar hemorrhage and lymphoplasmacytic interstitial pneumonia. The odds ratio of acute myocardial infarction associated with specific histopathology was determined by logistic regression. RESULTS: In total, 147 men were included in the study. The mean age at the time of death was 64 years. Pulmonary histopathology revealed pulmonary edema as well as the presence of diffuse alveolar damage in 72.9% of patients. Bacterial bronchopneumonia was present in 11.9% of patients, systemic arterial hypertension in 10.1% and dilated cardiomyopathy in 6.9%. A multivariate analysis demonstrated a significant positive association between acute myocardial infarction with diffuse alveolar damage and pulmonary edema. CONCLUSIONS: For the first time, we demonstrated that in autopsies of patients with acute respiratory failure as the cause of death, 5% were diagnosed with acute myocardial infarction. Pulmonary histology revealed a significant inflammatory response, which has not previously been reported.

Fluid dynamic analysis and modelling of industrial chemical equipment

The research is aimed at contributing to the identification of reliable fully predictive Computational Fluid Dynamics (CFD) methods for the numerical simulation of equipment typically adopted in the chemical and process industries. The apparatuses selected for the investigation, specifically membrane modules, stirred vessels and fluidized beds, were characterized by a different and often complex fluid dynamic behaviour and in some cases the momentum transfer phenomena were coupled with mass transfer or multiphase interactions. Firs of all, a novel modelling approach based on CFD for the prediction of the gas separation process in membrane modules for hydrogen purification is developed. The reliability of the gas velocity field calculated numerically is assessed by comparison of the predictions with experimental velocity data collected by Particle Image Velocimetry, while the applicability of the model to properly predict the separation process under a wide range of operating conditions is assessed through a strict comparison with permeation experimental data. Then, the effect of numerical issues on the RANS-based predictions of single phase stirred tanks is analysed. The homogenisation process of a scalar tracer is also investigated and simulation results are compared to original passive tracer homogenisation curves determined with Planar Laser Induced Fluorescence. The capability of a CFD approach based on the solution of RANS equations is also investigated for describing the fluid dynamic characteristics of the dispersion of organics in water. Finally, an Eulerian-Eulerian fluid-dynamic model is used to simulate mono-disperse suspensions of Geldart A Group particles fluidized by a Newtonian incompressible fluid as well as binary segregating fluidized beds of particles differing in size and density. The results obtained under a number of different operating conditions are compared with literature experimental data and the effect of numerical uncertainties on axial segregation is also discussed.

Treatment failure in pneumonia: Impact of antibiotic treatment and cost analysis

The aim of this study was to investigate treatment failure (TF) in hospitalised community-acquired pneumonia (CAP) patients with regard to initial antibiotic treatment and economic impact. CAP patients were included in two open, prospective multicentre studies assessing the direct costs for in-patient treatment. Patients received treatment either with moxifloxacin (MFX) or a nonstandardised antibiotic therapy. Any change in antibiotic therapy after >72 h of treatment to a broadened antibiotic spectrum was considered as TF. Overall, 1,236 patients (mean ± SD age 69.6 ± 16.8 yrs, 691 (55.9%) male) were included. TF occurred in 197 (15.9%) subjects and led to longer hospital stay (15.4 ± 7.3 days versus 9.8 ± 4.2 days; p < 0.001) and increased median treatment costs (€2,206 versus €1,284; p<0.001). 596 (48.2%) patients received MFX and witnessed less TF (10.9% versus 20.6%; p < 0.001). After controlling for confounders in multivariate analysis, adjusted risk of TF was clearly reduced in MFX as compared with β-lactam monotherapy (adjusted OR for MFX 0.43, 95% CI 0.27-0.68) and was more comparable with a β-lactam plus macrolide combination (BLM) (OR 0.68, 95% CI 0.38-1.21). In hospitalised CAP, TF is frequent and leads to prolonged hospital stay and increased treatment costs. Initial treatment with MFX or BLM is a possible strategy to prevent TF, and may thus reduce treatment costs.

Proposal on How To Conduct a Biopharmaceutical Process Failure Mode and Effect Analysis (FMEA) as a Risk Assessment Tool

With the publication of the quality guideline ICH Q9 "Quality Risk Management" by the International Conference on Harmonization, risk management has already become a standard requirement during the life cycle of a pharmaceutical product. Failure mode and effect analysis (FMEA) is a powerful risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to biopharmaceutical processes brings about some difficulties. The proposal presented here is intended to serve as a brief but nevertheless comprehensive and detailed guideline on how to conduct a biopharmaceutical process FMEA. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. The application for such a biopharmaceutical process FMEA is widespread. It can be useful whenever a biopharmaceutical manufacturing process is developed or scaled-up, or when it is transferred to a different manufacturing site. It may also be conducted during substantial optimization of an existing process or the development of a second-generation process. According to their resulting risk ratings, process parameters can be ranked for importance and important variables for process development, characterization, or validation can be identified. LAY ABSTRACT: Health authorities around the world ask pharmaceutical companies to manage risk during development and manufacturing of pharmaceuticals. The so-called failure mode and effect analysis (FMEA) is an established risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to pharmaceutical processes that use modern biotechnology (biopharmaceutical processes) brings about some difficulties, because those biopharmaceutical processes differ from processes in mechanical and electrical industries. The proposal presented here explains how a biopharmaceutical process FMEA can be conducted. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. With the help of this guideline, different details of the manufacturing process can be ranked according to their potential risks, and this can help pharmaceutical companies to identify aspects with high potential risks and to react accordingly to improve the safety of medicines.

Subclinical thyroid dysfunction and the risk of heart failure events: an individual participant data analysis from 6 prospective cohorts

American College of Cardiology/American Heart Association guidelines for the diagnosis and management of heart failure recommend investigating exacerbating conditions such as thyroid dysfunction, but without specifying the impact of different thyroid-stimulation hormone (TSH) levels. Limited prospective data exist on the association between subclinical thyroid dysfunction and heart failure events.