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Object and purpose of research. This paper discusses electric propulsion system of leader icebreaker. Its purpose was to develop mathematical and computer-based model of electric propulsion drive powered by asynchronous motor with three stator windings for further investigation of steady, transitional, asymmetric and emergency operation scenarios of electric power and propulsion system for the leader icebreaker. Materials and methods. Hardware and methods for computer-based simulation of complex engineering structures. Main results. Development of the mathematical model representing asynchronous motor with three windings in phase coordinates. Computational studies on direct startup of 15 MW propulsion motor, as well as on steady and transitional operational conditions of ship electric power system consisting of 36 MW synchronous genset, two-winding transformers and electric propulsion drive with 15 MW asynchronous motor in phase coordinates with three stator windings and three-level frequency converter. Calculation of voltage non-sinusoidality ratio for MSB buses with operation of 15 MW propulsion motor driven by 36 MW synchronous genset. Conclusion. Mathematical model of asynchronous motor suggested in this paper could be used to calculate steady and transitional operation scenarios of marine power systems with frequency-controlled three-winding asynchronous motor, as well as to calculate electromechanical and electromagnetic processes and refine frequency control algorithms. This is especially relevant because each of the asynchronous electric machines used in the electromechanical assemblies of leader icebreaker propulsion motors has three stator windings, and this icebreaker is the first experience of applying a 15 MW marine electric drive.

Evidence robustly demonstrates that ischemia, rather than anatomy, is the optimal target for coronary revascularization. In the cardiac catheter laboratory, fractional flow reserve (FFR) and corresponding diastolic indices are regarded as the gold standard for physiological lesion assessment and ischemia detection (Table 1). Yet, despite a wealth of supporting data and indications in international guidelines, the use of FFR remains surprisingly low in the diagnostic assessment of coronary artery disease across the world.1, 2 To address this, multiple groups have developed methods for computing FFR from invasive angiography, without the need for passing a pressure wire or inducing hyperemia, thus removing the main barriers to uptake. Angiography‐derived FFR therefore has the potential to extend the benefits of physiological coronary lesion assessment to considerably more patients. Given the size of the interventional cardiology market, clinical and commercial motivation to deliver these tools as quickly as possible could hardly be greater. Several models are now approved as medical devices. Imminently, physicians and healthcare providers will have to decide whether to use these tools. But do they truly deliver physiology, and are they accurate enough? There are 3 particular areas of that deserve close scrutiny.

Object and purpose of research. The object of this study is electric propulsion drive of the electric propulsion system aboard Project 22220 multi-purpose nuclear icebreaker now under construction. The purpose of the study is to developcomputer-based model of electric propulsion drive for this icebreaker. The drive is frequency-regulated and has vector control algorithm. The model is intended to both analyse electromechanical processes taking place in the channels of the electric drive and to synthesize its control system. Materials and methods. The study was based on scientific & technical information available in literature on electric drive theory, as well as on personal findings of the authors and on their profound experience accumulated over many years of R&D in the sphere of marine electric propulsion systems. Solution to this problem is based on the possibility to simulate various electromechanical equipment and systems by means of Simulik application software and Sim Power Systems block library of MatLab package. Main results. The computer-based model developed under this work and representing electric propulsion drive of Project 22220 multi-purpose nuclear icebreaker makes it possible to investigate electromechanical processes taking place in different operational conditions of this drive. Virtual oscillograms were obtained for currents, voltages, RPM, power, electromagnetic moment, etc. These oscillograms characterize operation of the electric drive in the conditions of RPM regulation, power regulation, change of rotation direction, shaft cranking, ice milling, propeller jamming, decrease and increase of static load moment. The model can also be used to update the software governing microchip-based control system of the electric drive (this update becomes necessary during pre-commissioning set-to-work activities). Conclusion. The model of electric propulsion drive for Project 22220 icebreaker is an engineering tool that enables, already at early design stages, investigation and analysis of electromechanical processes: these data are necessary for proper selection of electric drive equipment. After corresponding update, this model can be used in detailed design of electric propulsion plants for ice-breaking ships of other designs.

Cardiac resynchronization therapy (CRT) is an effective treatment for heart failure (HF) patients with an electrical substrate pathology causing ventricular dyssynchrony. However 40-50% of patients do not respond to treatment. Cardiac modeling of the electrophysiology, electromechanics, and hemodynamics of the heart has been used to study mechanisms behind HF pathology and CRT response. Recently, multi-scale dyssynchronous HF models have been used to study optimal device settings and optimal lead locations, investigate the underlying cardiac pathophysiology, as well as investigate emerging technologies proposed to treat cardiac dyssynchrony. However the breadth of patient and experimental data required to create and parameterize these models and the computational resources required currently limits the use of these models to small patient numbers. In the future, once these technical challenges are overcome, biophysically based models of the heart have the potential to become a clinical tool to aid in the diagnosis and treatment of HF.

Background The ability to accurately predict the occurrence of in‐hospital death after percutaneous coronary intervention is important for clinical decision‐making. We sought to utilize the New York Percutaneous Coronary Intervention Reporting System in order to elucidate the determinants of in‐hospital mortality in patients undergoing percutaneous coronary intervention across New York State. Methods and Results We examined 479 804 patients undergoing percutaneous coronary intervention between 2004 and 2012, utilizing traditional and advanced machine learning algorithms to determine the most significant predictors of in‐hospital mortality. The entire data were randomly split into a training (80%) and a testing set (20%). Tuned hyperparameters were used to generate a trained model while the performance of the model was independently evaluated on the testing set after plotting a receiver‐operator characteristic curve and using the output measure of the area under the curve ( AUC ) and the associated 95% CIs. Mean age was 65.2±11.9 years and 68.5% were women. There were 2549 in‐hospital deaths within the patient population. A boosted ensemble algorithm (AdaBoost) had optimal discrimination with AUC of 0.927 (95% CI 0.923–0.929) compared with AUC of 0.913 for XGB oost (95% CI 0.906–0.919, P =0.02), AUC of 0.892 for Random Forest (95% CI 0.889–0.896, P AUC of 0.908 for logistic regression (95% CI 0.907–0.910, P Conclusions A big data approach that utilizes advanced machine learning algorithms identifies new associations among risk factors and provides high accuracy for the prediction of in‐hospital mortality in patients undergoing percutaneous coronary intervention.

Background The relative impact of right ventricular ( RV ) electromechanical dyssynchrony versus pulmonary regurgitation ( PR ) on exercise capacity and RV function after tetralogy of Fallot repair is unknown. We aimed to delineate the relative effects of these factors on RV function and exercise capacity. Methods and Results We retrospectively analyzed 81 children with tetralogy of Fallot repair using multivariable regression. Predictor parameters were electrocardiographic QRS duration reflecting electromechanical dyssynchrony and PR severity by cardiac magnetic resonance. The outcome parameters were exercise capacity (percentage predicted peak oxygen consumption) and cardiac magnetic resonance ejection fraction (RV ejection fraction). To understand the relative effects of RV dyssynchrony versus PR on exercise capacity and RV function, virtual patient simulations were performed using a closed‐loop cardiovascular system model (CircAdapt), covering a wide spectrum of disease severity. Eighty‐one patients with tetralogy of Fallot repair (median [interquartile range { IQR} ] age, 14.48 [11.55–15.91] years) were analyzed. All had prolonged QRS duration (median [IQR], 144 [123–152] ms), at least moderate PR (median [IQR], 40% [29%–48%]), reduced exercise capacity (median [IQR], 79% [68%–92%] predicted peak oxygen consumption), and reduced RV ejection fraction (median [IQR], 48% [44%–52%]). Longer QRS duration, more than PR , was associated with lower oxygen consumption and lower RV ejection fraction. In a multivariable regression analysis, oxygen consumption decreased with both increasing QRS duration and PR severity. CircAdapt modeling showed that RV dyssynchrony exerts a stronger limiting effect on exercise capacity and on RV ejection fraction than does PR , regardless of contractile function. Conclusions In both patient data and computer simulations, RV dyssynchrony, more than PR , appears to be associated with reduced exercise capacity and RV systolic dysfunction in patients after TOF repair.

Background Ventricular tachyarrhythmias are often preceded by short sequences of premature ventricular complexes. In a previous study, a restitution‐based computational model predicted which sequences of stimulated premature complexes were most likely to induce ventricular fibrillation in canines in vivo. However, the underlying mechanism, based on discordant‐alternans dynamics, could not be verified in that study. The current study seeks to elucidate the mechanism by determining whether the spatiotemporal evolution of action potentials and initiation of ventricular fibrillation in in vitro experiments are consistent with model predictions. Methods and Results Optical mapping voltage signals from canine right‐ventricular tissue (n=9) were obtained simultaneously from the entire epicardium and endocardium during and after premature stimulus sequences. Model predictions of action potential propagation along a 1‐dimensional cable were developed using action potential duration versus diastolic interval data. The model predicted sign‐change patterns in action potential duration and diastolic interval spatial gradients with posterior probabilities of 91.1%, and 82.1%, respectively. The model predicted conduction block with 64% sensitivity and 100% specificity. A generalized estimating equation logistic‐regression approach showed that model‐prediction effects were significant for both conduction block ( P −15 , coefficient 44.36) and sustained ventricular fibrillation ( P =0.0046, coefficient, 1.63) events. Conclusions The observed sign‐change patterns favored discordant alternans, and the model successfully identified sequences of premature stimuli that induced conduction block. This suggests that the relatively simple discordant‐alternans‐based process that led to block in the model may often be responsible for ventricular fibrillation onset when preceded by premature beats. These observations may aid in developing improved methods for anticipating block and ventricular fibrillation.

Background Structural remodeling of human atria plays a key role in sustaining atrial fibrillation ( AF ), but insufficient quantitative analysis of human atrial structure impedes the treatment of AF . We aimed to develop a novel 3‐dimensional (3D) structural and computational simulation analysis tool that could reveal the structural contributors to human reentrant AF drivers. Methods and Results High‐resolution panoramic epicardial optical mapping of the coronary‐perfused explanted intact human atria (63‐year‐old woman, chronic hypertension, heart weight 608 g) was conducted during sinus rhythm and sustained AF maintained by spatially stable reentrant AF drivers in the left and right atrium. The whole atria (107×61×85 mm 3 ) were then imaged with contrast‐enhancement MRI (9.4 T, 180×180×360‐μm 3 resolution). The entire 3D human atria were analyzed for wall thickness (0.4–11.7 mm), myofiber orientations, and transmural fibrosis (36.9% subendocardium; 14.2% midwall; 3.4% subepicardium). The 3D computational analysis revealed that a specific combination of wall thickness and fibrosis ranges were primarily present in the optically defined AF driver regions versus nondriver tissue. Finally, a 3D human heart–specific atrial computer model was developed by integrating 3D structural and functional mapping data to test AF induction, maintenance, and ablation strategies. This 3D model reproduced the optically defined reentrant AF drivers, which were uninducible when fibrosis and myofiber anisotropy were removed from the model. Conclusions Our novel 3D computational high‐resolution framework may be used to quantitatively analyze structural substrates, such as wall thickness, myofiber orientation, and fibrosis, underlying localized AF drivers, and aid the development of new patient‐specific treatments.

Objective: Over one hundred predictive models were defined in the past for head injury (HI) prognosis, but none of them have been widely used up to the present. The aim of this study is to predict the prognosis of isolated HI patients by simply using data from the first day after injury. Materials and Methods: Data of head injury patients in Trakya University Hospital between January 1996 and December 2006 were obtained from records. The age, gender, causes of HI, basic neurologic examination findings, radiologic findings and discharge status are examined. Results: Most of the data were simplified as absent (0) and present (1), and mortality rates for each groups were accepted weighted values. All data were processed statistically and two models were created. Model 1 with Glasgow Coma Scale (GCS) score predicted the mortality/vegetative event at a rate of 56.5%, and the conscious survival event at 98.7%. Model 2, without the GCS score, predicted the mortality/vegetative event at 55.1% rate and the conscious survival event at 99.2%. Conclusion: Both models could be used for informing the patient and relatives and helping them to understand the severity of HI in busy working conditions of emergency departments.

Objective: To translate the individual abdominal aortic aneurysm (AAA) patient's biomechanical rupture risk profile to risk-equivalent diameters, and to retrospectively test their predictability in ruptured and non-ruptured aneurysms. Methods: Biomechanical parameters of ruptured and non-ruptured AAAs were retrospectively evaluated in a multicenter study. General patient data and high resolution computer tomography angiography (CTA) images from 203 non-ruptured and 40 ruptured aneurysmal infrarenal aortas. Three-dimensional AAA geometries were semi-automatically derived from CTA images. Finite element (FE) models were used to predict peak wall stress (PWS) and peak wall rupture index (PWRI) according to the individual anatomy, gender, blood pressure, intraluminal thrombus (ILT) morphology, and relative aneurysm expansion. Average PWS diameter and PWRI diameter responses were evaluated, which allowed for the PWS equivalent and PWRI equivalent diameters for any individual aneurysm to be defined. Results: PWS increased linearly and PWRI exponentially with respect to maximum AAA diameter. A size-adjusted analysis showed that PWS equivalent and PWRI equivalent diameters were increased by 7.5 mm (p = .013) and 14.0 mm (p < .001) in ruptured cases when compared to non-ruptured controls, respectively. In non-ruptured cases the PWRI equivalent diameters were increased by 13.2 mm (p < .001) in females when compared with males. Conclusions: Biomechanical parameters like PWS and PWRI allow for a highly individualized analysis by integrating factors that influence the risk of AAA rupture like geometry (degree of asymmetry, ILT morphology, etc.) and patient characteristics (gender, family history, blood pressure, etc.). PWRI and the reported annual risk of rupture increase similarly with the diameter. PWRI equivalent diameter expresses the PWRI through the diameter of the average AAA that has the same PWRI, i.e. is at the same biomechanical risk of rupture. Consequently, PWRI equivalent diameter facilitates a straightforward interpretation of biomechanical analysis and connects to diameter-based guidelines for AAA repair indication. PWRI equivalent diameter reflects an additional diagnostic parameter that may provide more accurate clinical data for AAA repair indication. QC 20140228