A novel and safe technique in closed tube thoracostomy

<p>Abstract</p> <p>Background</p> <p>Tube thoracostomy (TT) is the most commonly performed surgical procedure in thoracic surgery clinics. The procedure might have to be repeated due to ineffective drainage in patients with tube malposition (TM), in whom the drain is not directed to the apex or located in the fissure. Trocar technique, which is used to prevent TM, is not recommended because of its potential for severe complications.</p> <p>Methods</p> <p>The study involved 180 patients who required TT application for any etiology within one year. The patients were divided into two groups as Group A, who had undergone classical surgical technique (n = 90) and Group B, who had undergone a combination of surgery and trocar techniques (n = 90). The groups were compared for TM, the effect of TM on the drain removal, and other insertion related complications.</p> <p>Results</p> <p>In Group A, 23 patients had TM, 4 of whom developed associated ineffective drainage, while the patients in Group B had no insertion related complications (p = 0.001). The mean drain removal time of the patients with TM was 5 ± 2.25 days. In the patients who did not develop TM, it was 3.39 ± 1.18 days (p = 0.001).</p> <p>Conclusions</p> <p>The modified combination technique is a reliable method in preventing TM and its potential complications.</p

Traumatic pulmonary pseuodocysts: two case reports

Traumatic pulmonary pseudocyst (TPP) is a rare complication, sometimes encountered after blunt thoracic trauma and even more rarely following penetrating injuries. It is more common among pediatric and young adult patients. Although TPP is usually benign in nature, complications associated with hemoptysis and secondary infection may develop. The treatment is conservative. In this report, we present two rare cases of TPP occuring after a high-speed accident and a stab wound injury, where conservative treatment provided good outcomes

A case of radiation-induced sternal malignant fibrous histiocytoma treated with neoadjuvant chemotherapy and surgical resection

<p>Abstract</p> <p>Background</p> <p>Primary sternal malignant fibrous histiyocytoma (MFH) is highly rare. Effective treatment modality is surgical resection with wide margins. However, to date, the effects of radiotherapy or chemotherapy has not been clearly defined.</p> <p>Case presentation</p> <p>Herein, we aimed to present a 50-year old female patient with MFH occurred in the radiotherapy field who had had surgical procedure for breast cancer 19 years ago and had followed by radiotherapy. Neoadjuvant chemotherapy was applied for MFH due to cardiac and mediastinal vascular invasion. Wide resection was carried out for the mass after having been decreased in size following neoadjuvant chemotherapy.</p> <p>Conclusion</p> <p>Neoadjuvant chemotherapy was an effective method. In planning the surgical resection, the size of the tumor before chemotherapy should be considered as the initial size and surgical margins should be determined accordingly.</p

Fetal Circulatory Variation in an Acute Incident Causing Bradycardia

Umbilical artery\vein, middle cerebral artery, and ductus venosus Doppler velocimetry were performed at 33 weeks of gestation in the settings of an intrauterine growth restricted fetus during a heart rate deceleration. Interestingly, we recorded a sudden onset redistribution of fetal blood flow with fetal bradycardia. Spontaneous normalization of waveforms was observed once fetal heart rate returned to normal. Our case provides evidence to circulatory variation of a human fetus resulting from an acute incident causing bradycardia

Compressive and tensile strength prediction of steel fiber concrete with artificial neural networks

Various fiber types can be added to concrete in different proportions in order to improve the strength properties of concrete A common formulation or modeling has not been encountered to determine the strength properties of fibrous concrete.This situation necessitates experimentation. One of the methods used to predict the results without experimenting is artificial neural networks. Artificial neural networks are an artificial intelligence technology that works on estimating the output from the input values without being linear with a large number of variables. In this study, a Matlab-based artificial neural network is modeled to predict the compressive and tensile strength of the concrete to be formed by using the compressive and tensile strengths of steel fiber concretes, the concrete mix ratio, and the steel fiber type and properties to be added to the mixture. The artificial neural network is structured with 15 elements in the input layer, 10 neurons in the hidden layer, and 1 output value and designed to use forward-back propagation algorithm. Learning was provided by training the artificial neural network with 302 data sets from 24 studies in the literature. By the artificial neural network created, a regression value of 0.95 in estimation of compressive strength and 0.98 in estimation of tensile strength was reached. The neural network was able to predict the tensile strength results with high reliability when new datasets were entered for testing purposes.Betonun dayanım özelliklerini iyileştirmek amacıyla çeşitli lif tipleri çeşitli oranlarda betonlara katılabilmektedir. Lifli betonun dayanım özelliklerini belirlemek amacıyla yaygın bir formülasyon veya modelleme ile karşılaşılmamıştır. Bu durum deney yapma zorunluluğu doğurmaktadır. Deney yapmadan sonuçların tahmin edilebilmesinde kullanılan yöntemlerden birisi de yapay sinir ağlarıdır. Yapay sinir ağları çok sayıda değişken ile doğrusal olmadan, girdi değerlerinden çıktı tahmin etmek üzerine çalışan bir yapay zekâ teknolojisidir. Bu çalışmada çelik lifli betonların basınç ve çekme dayanımlarını beton karışım oranı ve karışıma katılacak çelik lif tipi ve özelliklerinin sayısal verilerini kullanarak oluşacak betonun basınç ve çekme dayanımını tahmin eden MATLAB tabanlı bir yapay sinir ağı modellenmiştir. Yapay sinir ağı 15 elemanlı girdi katmanı, gizli katmanında 10 nöron ve 1 çıktı değeri olacak şeklinde yapılandırılıp ileri yönlü geri yayılım algoritması kullanacak şekilde tasarlanmıştır. Yapay sinir ağı literatürde bulunan 24 araştırmadan 302 veri setiyle eğitilerek öğrenme sağlanmıştır. Oluşturulan yapay sinir ağı ile basınç dayanımı tahmininde 0,95 çekme dayanımı tahmininde 0,98 regresyon değerine ulaşılmıştır. Yapay sinir ağı, test amaçlı yeni veri setleri girildiğinde çekme dayanımı sonuçlarını yüksek güvenilirlikle tahmin edebilmiştir

Small-Signal Stability Modelling and Analysis of Modular Multilevel Converter and its Closed-Loop Controllers

As the transformation of the electricity generation progresses, the number of power electronic-based devices connected to the electricity grid is expected to grow. To ensure the stability of the power system in a scenario with high penetration of power electronic converters, the dynamics and stability characteristics of these devices have to be comprehensively studied. This is especially important for bulk converters — with capacities in the hundreds of megawatts range — such as high-voltage direct current (HVDC) systems.Small-signal analysis is extensively used in power system stability studies. The calculation of the system eigenvalues provides insights regarding the dynamic behavior and the nature of the interactions within the system. However, generating a small-signal representation of power electronic converters is known to be problematic, due to the switched operation of such converters and their complex control structures. Nevertheless, usage of modular multilevel converters (MMC) in HVDC systems is rapidly increasing. This creates the need for extensive studies regarding its dynamic behavior. Due to the MMC unique submodule-based topology, special actions have to be taken if the stability of the converter is to be analyzed.In this thesis, a small-signal model of a generic MMC was developed by linearizing all the converter plant and control equations, to analyze the converter stability. Averaging was used to eliminate nonlinearities brought forth by the converter switching actions.The main contributions of this thesis are the application of classic linear-time invariant theory to a time-varying system by linearizing the full converter model at different points in time, and the application of modal analysis methods to the MMC.The small-signal model was verified against a large-signal one, both developed in Matlab/Simulink. Additionally, the system eigenvalues obtained analytically and numerically —using Matlab/MuPaD and Simulink Control Design Toolbox, respectively — were benchmarked. After obtaining the system state-space matrix, its transfer functions were used to estimate the input impedance of the MMC in the frequency domain. Using the linearized system matrix and an optimization algorithm, namely MVMO, the locations of the converter eigenvalues were optimized by finding a new set of controller gains. Finally, calculating the converter eigenvalues, understanding the effects of these eigenvalues on the system variables and applying advanced tools to tune the controllers of the MMC, and possibly also its main circuit parameters, may aid system designers in controller design and parametrization studies.Electrical Engineerin

Generalized Dynamic Phasor Modeling of the MMC for Small-Signal Stability Analysis

© 2018 IEEE. This paper introduces a dynamic phasor model of a half-bridge modular multilevel converter based on variables in the stationary ABC frame. The application of the dynamic phasor theory makes it possible to use converter eigenvalues to study the effect of steady-state harmonics present in the modular multilevel converter (MMC) on its small-signal stability, since the model is inherently time invariant. Relying on a linear transformation, this paper uses a new set of variables with a modified frequency content, which results in lower order dynamic phasor models. A nonlinear dynamic phasor model is developed and linearized. The linear model is compared with a nonlinear averaged MMC model in time domain. Stability analysis by means of eigenvalues and participation factors is carried out for dynamic phasor models that include different frequency content, and the effect of the circulating current suppression controller is analyzed.status: publishe

Impact of PLL Dynamics on the Small-Signal Stability of the MMC using Dynamic Phasor Modeling in the ABC Frame

status: Published onlin

Equivalent Multiple dq-Frame Model of the MMC using Dynamic Phasor Theory in the αβz-Frame

This paper introduces an equivalent multiple dq-frame model of the modular multilevel converter (MMC) that is derived from a dynamic phasor based small-signal state-space MMC model in the stationary αβz frame. When compared to a model in the stationary ABC frame, the order of the model in the αβz frame can be reduced for balanced operation, during which some voltage and current harmonics are inherently separated in an αβz representation. The proposed method enables further model-order reduction through a generalized transformation towards multiple dq frames. The development of the model and the generalized transformation are explained in detail, and the obtained equivalent multiple dq-frame models are verified against a nonlinear averaged model in MATLAB®/Simulink. An eigenvalue-based small-signal stability analysis highlights the effect of higher-order harmonics in system-level small-signal stability studies, and two case studies of active harmonic suppression illustrate how the presented model allows an in-depth investigation of the impact of extended control functionalities on the small-signal stability.status: Published onlin

Input Admittance Calculation of the Modular Multilevel Converter using a Linearized Dynamic Phasor Model

status: publishe