•A new analytical model is developed for stiffness matrix of a linear ball guide.•Carriage flexibility is considered using a new finite element model.•Changes in stiffness coefficients are ...investigated.•Radial displacements of a linear ball guide are validated by measurements.
The stiffness matrices of joint elements, such as rotating and linear bearings, are essential for both static and dynamic analyses of mechanical systems employing such elements. However, few models of fully occupied stiffness matrices of linear guides are available. Here, we develop a comprehensive analytical model for calculation of the stiffness matrix of a linear ball guide. The model features five degrees of freedom (DOF) of loading, and displacement. Contacts between the balls and the rail/carriage are handled using Hertz contact theory. Carriage flexibility is considered using a new finite element model. A 5 × 5 stiffness matrix for a linear ball guide was derived and numerically validated under various loading scenarios using commercial software. Changes in stiffness elements by load, ball arrangement, and certain critical geometric parameters were evaluated. Finally, we built an experimental platform to further verify the model. The calculated displacement of a linear ball guide closely corresponded to the experimental data derived using varying external loads and preloads.
The aim of this study was to evaluate the clinical and anatomical features to predict the long-term outcomes in patients with fractional flow reserve (FFR)–guided deferred lesions, verified by ...intravascular ultrasound (IVUS).
Deferral of nonsignificant lesion by FFR is associated with a low risk of clinical events. However, the impact of combined information on clinical and anatomical factors is not well known.
The study included 459 patients with 552 intermediate lesions who had deferred revascularization on the basis of a nonischemic FFR (>0.80). Grayscale IVUS was examined simultaneously. The primary endpoint was patient-oriented composite outcome (POCO) (a composite of all-cause death, myocardial infarction, and any revascularization) during 5-year follow-up.
The rate of 5-year POCO was 9.8%. Diabetes mellitus (hazard ratio: 3.50; 95% confidence interval CI: 1.86 to 6.57; p < 0.001), left ventricular ejection fraction ≤40% (hazard ratio: 4.80; 95% CI: 1.57 to 14.63; p = 0.006), and positive remodeling (hazard ratio: 2.04; 95% CI: 1.03 to 4.03; p = 0.041) were independent predictors for POCO. When the lesions were classified according to the presence of the adverse clinical characteristics (diabetes, left ventricular ejection fraction ≤40%) or adverse plaque characteristics (positive remodeling, plaque burden ≥70%), the risk of POCO was incrementally increased (4.3%, 13.6%, and 21.3%, respectively; p < 0.001).
In patients with FFR-guided deferred lesions, 5-year clinical outcomes were excellent. Lesion-related anatomical factors from intravascular imaging as well as patient-related clinical factors could provide incremental information about future clinical risks.
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Background Limited data are available on intracranial hemorrhage (ICH) in patients undergoing antithrombotic therapy after percutaneous coronary intervention (PCI). Methods and Results Using the ...Korean National Health Insurance Service database, we identified 219 274 patients without prior ICH and who underwent a first PCI procedure between 2007 and 2016 and analyzed nontraumatic ICH and all‐cause mortality. ICH after PCI occurred in 4171 patients during a median follow‐up of 5.6 years (overall incidence rate: 3.32 cases per 1000 person‐years). The incidence rate of ICH showed an early peak of 21.66 cases per 1000 person‐years within the first 30 days, followed by a sharp decrease to 3.68 cases per 1000 person‐years between 30 days and 1 year, and to <1 case per 1000 patient‐years from the second year until 10 years after PCI. The 1‐year mortality rate was 38.2% after ICH, with most deaths occurring within 30 days (n=999, mortality rate: 24.2%). No significant difference in mortality risk was observed between patients who had ICH within and after 1 year following PCI (adjusted hazard ratio, 1.04; 95% CI, 0.95–1.14; P =0.43). The predictors of post‐PCI ICH were age ≥75 years, hypertension, atrial fibrillation, end‐stage renal disease, history of stroke or transient ischemic attack, dementia, and use of vitamin K antagonists. Conclusions New ICH most frequently occurs in the early period after PCI and is associated with a high risk of early death, regardless of the occurrence time of ICH. Careful implementation of antithrombotic strategies is needed in patients at an increased risk for ICH, particularly in the peri‐PCI period.
Purpose. Pre-treatment prediction of individual blood pressure (BP) response to anti-hypertensive medication is important to determine the specific regimen for promptly and safely achieving a target ...BP. This study aimed to develop supervised machine learning (ML) models for predicting patient-specific treatment effects using 24-hour ambulatory BP monitoring (ABPM) data.
Materials and Methods. A total of 1,129 patients who had both baseline and follow-up ABPM data were randomly assigned into training, validation and test sets in a 3:1:1 ratio. Utilising the features including clinical and laboratory findings, initial ABPM data, and anti-hypertensive medication at baseline and at follow-up, ML models were developed to predict post-treatment individual BP response. Each case was labelled by the mean 24-hour and daytime BPs derived from the follow-up ABPM.
Results. At baseline, 616 (55%) patients had been treated using mono or combination therapy with 45 anti-hypertensive drugs and the remaining 513 (45%) patients had been untreated (drug-naïve). By using CatBoost, the difference between predicted vs. measured mean 24-hour systolic BP at follow-up was 8.4 ± 7.0 mm Hg (% difference of 6.6% ± 5.7%). The difference between predicted vs. measured mean 24-hour diastolic BP was 5.3 ± 4.3 mm Hg (% difference of 6.8% ± 5.5%). There were significant correlations between the CatBoost-predicted vs. the ABPM-measured changes in the mean 24-hour Systolic (r = 0.74) and diastolic (r = 0.68) BPs from baseline to follow-up. Even in the patients with renal insufficiency or diabetes, the correlations between CatBoost-predicted vs. ABPM-measured BP changes were significant.
Conclusion. ML algorithms accurately predict the post-treatment ambulatory BP levels, which may assist clinicians in personalising anti-hypertensive treatment.
The prediction of post-treatment BP response is essential to plan the appropriate optimal treatment strategy for achieving the target BP level.
The poor predictability of the post-treatment BP level is due to the complex pathophysiology of individual BP response, which can partly explain the poor rate to achieve the target systolic BP.
In this current study including both treated and untreated patients with hypertension, machine leaning models predicted the post-treatment mean BP levels on 24-hr ABPM even in high-risk patients and patients with a high BP variability.
Model-derived selection and optimisation of anti-hypertension drugs may facilitate prompt achievement of adequate BP control without drug-related complications and avoiding repeating 24-hour ABPM or multiple visits for drug readjustment.
Invasive fractional flow reserve (FFR) is a standard tool for identifying ischemia-producing coronary stenosis. However, in clinical practice, over 70% of treatment decisions still rely on visual ...estimation of angiographic stenosis, which has limited accuracy (about 60%-65%) for the prediction of FFR < 0.80. One of the reasons for the visual-functional mismatch is that myocardial ischemia can be affected by the supplied myocardial size, which is not always evident by coronary angiography. The aims of this study were to develop an angiography-based machine learning (ML) algorithm for predicting the supplied myocardial volume for a stenosis, as measured using coronary computed tomography angiography (CCTA), and then to build an angiography-based classifier for the lesions with an FFR < 0.80 versus ≥ 0.80.
A retrospective study was conducted using data from 1,132 stable and unstable angina patients with 1,132 intermediate lesions who underwent invasive coronary angiography, FFR, and CCTA at the Asan Medical Center, Seoul, Korea, between 1 May 2012 and 30 November 2015. The mean age was 63 ± 10 years, 76% were men, and 72% of the patients presented with stable angina. Of these, 932 patients (assessed before 31 January 2015) constituted the training set for the algorithm, and 200 patients (assessed after 1 February 2015) served as a test cohort to validate its diagnostic performance. Additionally, external validation with 79 patients from two centers (CHA University, Seongnam, Korea, and Ajou University, Suwon, Korea) was conducted. After automatic contour calibration using the caliber of guiding catheter, quantitative coronary angiography was performed using the edge-detection algorithms (CAAS-5, Pie-Medical). Clinical information was provided by the Asan BiomedicaL Research Environment (ABLE) system. The CCTA-based myocardial segmentation (CAMS)-derived myocardial volume supplied by each vessel (right coronary artery RCA, left anterior descending LAD, left circumflex LCX) and the myocardial volume subtended to a stenotic segment (CAMS-%Vsub) were measured for labeling. The ML for (1) predicting vessel territories (CAMS-%LAD, CAMS-%LCX, and CAMS-%RCA) and CAMS-%Vsub and (2) identifying the lesions with an FFR < 0.80 was constructed. Angiography-based ML, employing a light gradient boosting machine (GBM), showed mean absolute errors (MAEs) of 5.42%, 8.57%, and 4.54% for predicting CAMS-%LAD, CAMS-%LCX, and CAMS-%RCA, respectively. The percent myocardial volumes predicted by ML were used to predict the CAMS-%Vsub. With 5-fold cross validation, the MAEs between ML-predicted percent myocardial volume subtended to a stenotic segment (ML-%Vsub) and CAMS-%Vsub were minimized by the elastic net (6.26% ± 0.55% for LAD, 5.79% ± 0.68% for LCX, and 2.95% ± 0.14% for RCA lesions). Using all attributes (age, sex, involved vessel segment, and angiographic features affecting the myocardial territory and stenosis degree), the ML classifiers (L2 penalized logistic regression, support vector machine, and random forest) predicted an FFR < 0.80 with an accuracy of approximately 80% (area under the curve AUC = 0.84-0.87, 95% confidence intervals 0.71-0.94) in the test set, which was greater than that of diameter stenosis (DS) > 53% (66%, AUC = 0.71, 95% confidence intervals 0.65-0.78). The external validation showed 84% accuracy (AUC = 0.89, 95% confidence intervals 0.83-0.95). The retrospective design, single ethnicity, and the lack of clinical outcomes may limit this prediction model's generalized application.
We found that angiography-based ML is useful to predict subtended myocardial territories and ischemia-producing lesions by mitigating the visual-functional mismatch between angiographic and FFR. Assessment of clinical utility requires further validation in a large, prospective cohort study.
This paper describes nonisolated high step-up DC-DC converters using zero voltage switching (ZVS) boost integration technique (BIT) and their light-load frequency modulation (LLFM) control. The ...proposed ZVS BIT integrates a bidirectional boost converter with a series output module as a parallel-input and series-output (PISO) configuration. It provides many advantages such as high device utilization, high step-up capability, power and thermal stress distribution, switch voltage stress clamping, and soft switching capability. As an example of ZVS BIT, a flyback converter with a voltage-doubler rectifier (VDR) as a series output module is presented and analyzed in detail. In addition, to overcome the efficiency degradation at a light load due to the load-dependent soft switching capability of the proposed ZVS BIT, a control method using a frequency modulation (FM) proportional to the load current is proposed. By means of ZVS BIT and LLFM control, the overall conversion efficiency is significantly improved. The experimental results are presented to clarify the proposed schemes.
To assess the diagnostic accuracy of stress myocardial perfusion computed tomography (CT) by using visual and quantitative analytic methods in patients with coronary artery disease, with fractional ...flow reserve (FFR) as a reference standard.
The institutional review board approved the study, and written informed consent was obtained from all patients. The diagnostic accuracy of myocardial perfusion CT was assessed for 75 patients who underwent myocardial perfusion CT and conventional coronary angiography with reference to hemodynamically significant stenosis, defined as the presence of an FFR of 0.8 or less or an angiographically severe (≥90%) stenosis. Results of quantitative analysis of myocardial perfusion CT data were compared with those of visual analysis by using areas under the receiver operating characteristic curve (AUCs).
Among the 75 patients and 210 epicardial arteries, 61 patients (81%) with 86 arteries (41%) had hemodynamically significant stenosis. The per-patient sensitivity and specificity of the visual assessment of myocardial perfusion CT data for all patients were 89% and 86%, respectively. At per-vessel analysis, the sensitivities and specificities, respectively, of myocardial perfusion CT were 80% and 95% for all vessels, 85% and 100% for 63 vessels with severe coronary calcification (defined as an Agatston score > 400), and 76% and 91% for 56 vessels in patients with multivessel disease. In severely calcified vessels, visual assessment of myocardial perfusion CT data in combination with CT angiography provided incremental value over CT angiography alone for the detection of myocardial ischemia (integrated discrimination improvement index, 0.38; P < .001). Quantitative assessment of transmural perfusion ratio had a lower AUC than visual analysis of myocardial perfusion CT (0.759 vs 0.877, P = .002).
Stress myocardial perfusion CT provides incremental value over CT angiography in patients with a high calcium score for the detection of myocardial ischemia as defined by FFR.
Two photon microscopy and optical coherence tomography (OCT) are two standard methods for measuring flow speeds of red blood cells in microvessels, particularly in animal models. However, traditional ...two photon microscopy lacks the depth of field to adequately capture the full volumetric complexity of the cerebral microvasculature and OCT lacks the specificity offered by fluorescent labeling. In addition, the traditional raster scanning technique utilized in both modalities requires a balance of image frame rate and field of view, which severely limits the study of RBC velocities in the microvascular network. Here, we overcome this by using a custom two photon system with an axicon based Bessel beam to obtain volumetric images of the microvascular network with fluorescent specificity. We combine this with a novel scan pattern that generates pairs of frames with short time delay sufficient for tracking red blood cell flow in capillaries. We track RBC flow speeds in 10 or more capillaries simultaneously at 1 Hz in a 237 µm × 237 µm × 120 µm volume and quantified both their spatial and temporal variability in speed. We also demonstrate the ability to track flow speed changes around stalls in capillary flow and measure to 300 µm in depth.
The high temperature, acidity, and heavy metal-rich environments associated with hot springs have a major impact on biological processes in resident cells. One group of photosynthetic eukaryotes, the ...Cyanidiophyceae (Rhodophyta), has successfully thrived in hot springs and associated sites worldwide for more than 1 billion years. Here, we analyze chromosome-level assemblies from three representative Cyanidiophyceae species to study environmental adaptation at the genomic level. We find that subtelomeric gene duplication of functional genes and loss of canonical eukaryotic traits played a major role in environmental adaptation, in addition to horizontal gene transfer events. Shared responses to environmental stress exist in Cyanidiales and Galdieriales, however, most of the adaptive genes (e.g., for arsenic detoxification) evolved independently in these lineages. Our results underline the power of local selection to shape eukaryotic genomes that may face vastly different stresses in adjacent, extreme microhabitats.
Linear-motion ball guides are one of the most common supporting elements in machine tools. Their design optimization is highly crucial for engineers and users because it can assist geometric and ...operating parameter selection and thereby aid in maximizing the stiffness and operating life while minimizing their friction. In this study, a multi-objective linear ball guide optimization process was performed using the particle swarm optimization (PSO). Five design parameters were selected for optimization: ball diameter, number of balls, groove curvature ratios for balls in contact with carriages and with rails, and initial contact angle. The design optimization objectives were radial stiffness, friction force, and basic dynamic load rating. The bearing stiffness and friction force were calculated using the numerical model proposed by the authors. The basic dynamic load rating was determined according to ISO 14728-1:2017. Pare-to-optimal solutions were used to support optimal design parameter selection. The final selection of an optimal point from points satisfying the Pareto optimality was performed using the cooperative equilibrium point method. The simulation results indicated a good performance of the optimized linear ball guide. Finally, the effects of parametric uncertainties in the optimal design on the performance were extensively investigated through a sensitivity analysis.
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