Post-Pericardiotomy Syndrome Disguised as Fever of Unknown Origin

Introduction: Post -Pericardiotomy syndrome (PPS) is a clinical diagnosis characterized by fever, pericardial or pleural effusions, and a pericardial friction rub occurring over several days after cardiac surgery. The infrequency of PPS can cause delay in recognition and management, thus leading to significant morbidity. We present a case of fever of unknown origin, pericardial and pleural effusion secondary to postpericardiotomy syndrome 10 days after an Aortic Valve Replacement (AVR) Poster presented at: American College of Physicians Southeast Regional Meeting on October 15th, 201

Real-time grid parameter estimation methods using model based predictive control for grid-connected converters

In recent years, renewable and distributed generation (DG) systems have contributed towards an efficient and an economic way of transporting electricity to end-users as the generation sources are in general located nearer the loads. DG and renewable energy systems are modifying the old concept of distribution network by instigating a bi-directional power flow into the grid, facilitated through the use of power electronic grid-connected converters. A challenge associated with grid-connected converters arises when they are interacted with a grid that is not stiff, like weak micro grids. Small grid parameter variations in these systems can considerably affect the performance of the converter control and lead to higher values in current total harmonic distortion (THD) and loss of control and synchronization. Thus, the control of grid-connected power converters needs to be regularly updated with latest variation in grid parameters. Model Predictive Direct Power Control (MP-DPC) has been chosen as the control strategy for the work presented in this thesis due to its advantages over traditional control techniques such as multivariable control, no need of phase-locked loops (PLLs) for grid synchronization and avoidance of cascaded control loops. Two novel methods for estimating the grid impedance variation, and hence the grid voltage, are presented in this thesis along with a detailed literature review on control of grid-connected converters with special emphasis on impedance estimation techniques. The first proposed estimation method is based on the difference in grid voltage magnitudes at two consecutive sampling instants while the second method is based on a model-fitting algorithm similar to the concept of cost-function optimization in model predictive control. The proposed estimation methods in this thesis are integrated within the MP-DPC, therefore updating the MP-DPC in real-time with the latest variation in grid impedance. The proposed algorithms provide benefits such as: quick response to transient variations, operation under low values of short-circuit-ratio (SCR), robust MP-DPC control, good reference tracking to grid parameter variations and operation under unbalanced grid voltages. The thesis also presents the advantages and drawbacks of the proposed methods and areas where further improvement can be researched. The work presented has been tested on a three phase two-level grid-connected converter prototype, which is connected to a low voltage substation highly dominated by inductive component of grid impedance. It can be adapted and modified to be used for general grid impedance estimation, medium or high voltage applications, in case of multilevel grid-connected converter topologies or photo-voltaic (PV) grid-connected applications

Aplicación del modelo de gravedad aumentada de las TIC: análisis por sectores en la región de Asia Pacífico

The use of information and communication technologies (ICT) in commerce improves the commercial structure and economic capacity of a country. This study empirically assesses the impact of ICTs on international trade in 36 countries in Asia and the Pacific, at the sectoral level, between 2007 and 2018. The study evaluates whether ICTs improve international trade by hiring the gravity model of international trade and increasing it with the ICT variable. An ICT development indicator (IDI) is formed by joining seven different ICT variables that show ICT infrastructure, use, and skills. Using the Poisson pseudo-maximum likelihood (PPML) estimation technique, this study shows that ICTs improve trade by reducing transaction costs. The findings reveal that information and communication technology positively and significantly influence international trade in all sectors of the Asia-Pacific region, and that trade intensifies when both trading partners have a high endowment of information and communications technology. The study recommends that governments in developing countries upgrade their ICT infrastructure levels.El uso de las tecnologías de la información y las comunicaciones (TIC) en el comercio mejora la estructura comercial y la capacidad económica de un país. Este estudio evalúa empíricamente el impacto de las TIC en el comercio internacional en 36 países de Asia y el Pacífico a nivel sectorial entre 2007 y 2018. El estudio prueba si las TIC mejoran el comercio internacional mediante la contratación del modelo de gravedad del comercio internacional al aumentarlo con la variable TIC. Un indicador de desarrollo de las TIC (IDI) se forma uniendo siete variables TIC diferentes que muestran la infraestructura, el uso y las habilidades de las TIC. Al emplear la técnica de estimación de Poisson pseudo-máxima verosimilitud (PPML), este estudio muestra que las TIC mejoran el comercio al reducir los costos de transacción. Las conclusiones revelan que la tecnología de la información y las comunicaciones influye positiva y significativamente en el comercio internacional en todos los sectores de la región de Asia y el Pacífico y que el comercio se intensifica cuando ambos interlocutores comerciales tienen una alta dotación de tecnología de la información y las comunicaciones. El estudio recomienda que los gobiernos de los países en desarrollo actualicen sus niveles de infraestructura TIC

Real-time grid parameter estimation methods using model based predictive control for grid-connected converters

In recent years, renewable and distributed generation (DG) systems have contributed towards an efficient and an economic way of transporting electricity to end-users as the generation sources are in general located nearer the loads. DG and renewable energy systems are modifying the old concept of distribution network by instigating a bi-directional power flow into the grid, facilitated through the use of power electronic grid-connected converters. A challenge associated with grid-connected converters arises when they are interacted with a grid that is not stiff, like weak micro grids. Small grid parameter variations in these systems can considerably affect the performance of the converter control and lead to higher values in current total harmonic distortion (THD) and loss of control and synchronization. Thus, the control of grid-connected power converters needs to be regularly updated with latest variation in grid parameters. Model Predictive Direct Power Control (MP-DPC) has been chosen as the control strategy for the work presented in this thesis due to its advantages over traditional control techniques such as multivariable control, no need of phase-locked loops (PLLs) for grid synchronization and avoidance of cascaded control loops. Two novel methods for estimating the grid impedance variation, and hence the grid voltage, are presented in this thesis along with a detailed literature review on control of grid-connected converters with special emphasis on impedance estimation techniques. The first proposed estimation method is based on the difference in grid voltage magnitudes at two consecutive sampling instants while the second method is based on a model-fitting algorithm similar to the concept of cost-function optimization in model predictive control. The proposed estimation methods in this thesis are integrated within the MP-DPC, therefore updating the MP-DPC in real-time with the latest variation in grid impedance. The proposed algorithms provide benefits such as: quick response to transient variations, operation under low values of short-circuit-ratio (SCR), robust MP-DPC control, good reference tracking to grid parameter variations and operation under unbalanced grid voltages. The thesis also presents the advantages and drawbacks of the proposed methods and areas where further improvement can be researched. The work presented has been tested on a three phase two-level grid-connected converter prototype, which is connected to a low voltage substation highly dominated by inductive component of grid impedance. It can be adapted and modified to be used for general grid impedance estimation, medium or high voltage applications, in case of multilevel grid-connected converter topologies or photo-voltaic (PV) grid-connected applications

Diagnostic utility of fine needle aspiration cytology in thyroid lesions

Background: Thyroid fine needle aspiration cytology (FNAC) is an important screening tool and thereby dictates clinical management. The exclusion of non-invasive follicular variant of papillary carcinoma (NIFVPTC) from thyroid malignancies and its reclassification as non-malignant entity i.e., non-invasive follicular thyroid neoplasm with papillary like nuclear features (NIFTP) has added a new dimension. Aim of this study was to study the role of fine needle aspiration cytology in screening thyroid lesions by correlation with histopathological examination and to calculate diagnostic accuracy of FNAC considering NIFTP as non-malignant and compare it with pre NIFTP era.Methods: It was an observational study done over a period of 2 years (2017-2018). It included the cases where FNAC was followed subsequently by histopathology. FNAC results were correlated with histopathological diagnosis established thereof.Results: A total of 107 patients were included in this study. Considering NIFTP as non-malignant, sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy were 92.97%, 100%, 100%, 92.73% and 96.23% respectively, that is significantly higher if authors considered NIFTP as malignant.Conclusions: FNAC plays an indispensable role in making preliminary diagnosis in thyroid lesions. There is a notable increase in diagnostic accuracy of FNAC in thyroid lesions and significant decrease in risk of malignancy by considering NIFTP as non-malignant

Chemotherapy-induced changes in tumor consistency can allow gross total resection of previously unresectable brainstem pilocytic astrocytoma

Background: Low-grade gliomas (LGG) are described by the World Health Organization as Grades I and II. Among LGGs, the most common primary brain tumor is pilocytic astrocytoma (PA) and carries an excellent prognosis when treated with complete surgical resection. Cases, in which this is not possible, are associated with less favorable outcomes and worse progression-free survival. Case Description: This report describes a case of a 22-year-old male, who presented with progression of a primary brainstem tumor previously treated with stereotactic radiosurgery and chemotherapy. Patient underwent surgical exploration and was diagnosed with juvenile PA, but debulking was limited by the very dense and fibrous tumor. Complete surgical resection was not possible at this time. Despite efforts to treat with chemotherapy, the patient presented a year later with clinical deterioration and severe neurologic deficits, prompting surgical re-exploration. During the second operation, the tumor was found to have undergone very significant softening in consistency, allowing for gross total resection (GTR) Conclusion: Aggressive treatment of brainstem LGG should be pursued whenever possible, given its generally favorable prognosis. Repeat microsurgical resection, even with a different approach, might be reasonable and safe. Finally, chemotherapy may be associated with changes in the tumor consistency that can render previously unresectable lesions amenable to successful aggressive resection

Better Physical Activity Classification using Smartphone Acceleration Sensor

Obesity is becoming one of the serious problems for the health of worldwide population. Social interactions on mobile phones and computers via internet through social e-networks are one of the major causes of lack of physical activities. For the health specialist, it is important to track the record of physical activities of the obese or overweight patients to supervise weight loss control. In this study, acceleration sensor present in the smartphone is used to monitor the physical activity of the user. Physical activities including Walking, Jogging, Sitting, Standing, Walking upstairs and Walking downstairs are classified. Time domain features are extracted from the acceleration data recorded by smartphone during different physical activities. Time and space complexity of the whole framework is done by optimal feature subset selection and pruning of instances. Classification results of six physical activities are reported in this paper. Using simple time domain features, 99 % classification accuracy is achieved. Furthermore, attributes subset selection is used to remove the redundant features and to minimize the time complexity of the algorithm. A subset of 30 features produced more than 98 % classification accuracy for the six physical activities

Grid Parameter estimation using Model Predictive Direct Power Control

This paper presents a novel Finite Control Set Model Predictive Control (FS-MPC) approach for grid-connected converters. The control performance of such converters may get largely affected by variations in the supply impedance, especially for systems with low Short Circuit Ratio (SCR) values. A novel idea for estimating the supply impedance variation, and hence the grid voltage, using an algorithm embedded in the MPC is presented in this paper. The estimation approach is based on the difference in grid voltage magnitudes at two consecutive sampling instants, calculated on the basis of supply currents and converter voltages directly within the MPC algorithm, achieving a fast estimation and integration between the controller and the impedance estimator. The proposed method has been verified, using simulation and experiments, on a 3-phase 2-level converter

Effect logs of double diffusion on MHD Prandtl nano fluid adjacent to stretching surface by way of numerical approach

AbstractThe current communication is carried to contemplate the unique and novel characteristics of nanofluids by constructing formulation of Prandtl fluid model. The fascinating aspects of thermo diffusion effects are also accounted in this communication. Mathematical modelling is performed by employing boundary layer approach. Afterwards, similarity variables are selected to convert dimensional non-linear system into dimensionless expressions. The solution of governing dimensionless problem is executed by shooting method (SM). Graphical evaluation is displayed to depict the intrinsic behavior of embedded parameters on dimensionless velocity, temperature, solutal concentration and nanoparticle concentration profiles. Furthermore, the numerical variation for skin friction coefficient, local Nusselt number, Sherwood number and nano Sherwood number is scrutinized through tables. The assurance of current analysis is affirmed by developing comparison with previous findings available in literature, which sets a benchmark for implementation of computational approach. It is inferred from the computation that concentration profile increases whereas Sherwood number decreases for progressive values of Dufour solutal number