Gutzwiller density functional calculations of the electronic structure of FeAs-based superconductors: Evidence for a three-dimensional Fermi surface

The electronic structures of FeAs-compounds strongly depend on the Fe-As bonding, which can not be described successfully by the local density approximation (LDA). Treating the multi-orbital fluctuations from $ab$-$initio$ by LDA+Gutzwiller method, we are now able to predict the correct Fe-As bond-length, and find that Fe-As bonding-strength is 30% weaker, which will explain the observed "soft phonon". The bands are narrowed by a factor of 2, and the $d_{3z^2-r^2}$ orbital is pushed up to cross the Fermi level, forming 3-dimensional Fermi surfaces, which suppress the anisotropy and the ($\pi,\pi$) nesting. The inter-orbital Hund's coupling $J$ rather than $U$ plays crucial roles to obtain these results.Comment: 4 pages, 4 figures, 1 tabl

Coronary angiography review in 21 children with Kawasaki disease complicated with coronary artery disease

Objective·To analyze the progression of children with severe coronary artery lesions due to Kawasaki disease by coronary artery angiography, and evaluate the diagnostic value of echocardiography in these children.Methods·A retrospective analysis was performed to enroll children with Kawasaki disease whose coronary artery lesions were graded Ⅳ or above from Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, from January 2013 to January 2023. The subjects were required to have received at least 2 times of coronary angiogram, and their clinical and imaging data were collected to analyze the progression of the lesions. Echocardiography results were compared with the results of the coronary angiogram.Results·A total of 21 children were included, including 15 males and 6 females, with a median age at onset of 3 years and 6 months, a median age at initial coronary angiography of 7 years and 11 months, a median interval of 4 years and 5 months between the time of onset and initial angiography, a median age at angiographic review of 9 years and 2 months, and a median interval of 1 year and 3 months between the time of initial angiography and review. Coronary stenosis or occlusion was detected in 13 children in the initial angiography, of whom 6 underwent coronary artery bypass grafting (CABG) and had their angiography reviews 1 year later. The review results showed that the bridging vessels were unobstructed and no obvious stenosis was observed. Fifteen children had progression of the lesions detected by echocardiography in the subsequent follow-up and had their angiogram reviews, of whom 8 had significant progression of the coronary lesions. Intracoronary balloon dilatation was performed in 1 case, and CABG was performed in another case. Sixteen lesions of coronary stenosis or occlusion were detected in the initial angiography in 21 children, while only 1 lesion of coronary stenosis was detected by echocardiography during the same period of time. Twenty-eight medium- to large-sized coronary aneurysms were detected in the initial angiography in the 21 children, and the diameters of the 28 aneurysms measured by echocardiography and coronary angiogram were subjected to the Bland-Altman analysis. The Bland-Altman analysis showed that the difference in maximum diameter between 2 methods was (1.63±2.33) mm, with 95%CI of -2.95‒6.21 mm.Conclusion·Coronary artery lesions due to Kawasaki disease may be progressive; in the children with severe lesions, coronary artery stenosis or occlusion may be missed or misdiagnosed and some errors may exist in the measurement of diameters of aneurysms by echocardiography. Regular review of coronary angiography is needed

Ventricular flow analysis and its association with exertional capacity in repaired tetralogy of Fallot: 4D flow cardiovascular magnetic resonance study

Background: Four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) allows quantification of biventricular blood flow by flow components and kinetic energy (KE) analyses. However, it remains unclear whether 4D flow parameters can predict cardiopulmonary exercise testing (CPET) as a clinical outcome in repaired tetralogy of Fallot (rTOF). Current study aimed to (1) compare 4D flow CMR parameters in rTOF with age- and gender-matched healthy controls, (2) investigate associations of 4D flow parameters with functional and volumetric right ventricular (RV) remodelling markers, and CPET outcome. Methods: Sixty-three rTOF patients (14 paediatric, 49 adult; 30 ± 15 years; 29 M) and 63 age- and gender-matched healthy controls (14 paediatric, 49 adult; 31 ± 15 years) were prospectively recruited at four centers. All underwent cine and 4D flow CMR, and all adults performed standardized CPET same day or within one week of CMR. RV remodelling index was calculated as the ratio of RV to left ventricular (LV) end-diastolic volumes. Four flow components were analyzed: direct flow, retained inflow, delayed ejection flow and residual volume. Additionally, three phasic KE parameters normalized to end-diastolic volume (KEi EDV), were analyzed for both LV and RV: peak systolic, average systolic and peak E-wave. Results: In comparisons of rTOF vs. healthy controls, median LV retained inflow (18% vs. 16%, P = 0.005) and median peak E-wave KEi EDV (34.9 µJ/ml vs. 29.2 µJ/ml, P = 0.006) were higher in rTOF; median RV direct flow was lower in rTOF (25% vs. 35%, P < 0.001); median RV delayed ejection flow (21% vs. 17%, P < 0.001) and residual volume (39% vs. 31%, P < 0.001) were both greater in rTOF. RV KEi EDV parameters were all higher in rTOF than healthy controls (all P < 0.001). On multivariate analysis, RV direct flow was an independent predictor of RV function and CPET outcome. RV direct flow and RV peak E-wave KEi EDV were independent predictors of RV remodelling index. Conclusions: In this multi-scanner multicenter 4D flow CMR study, reduced RV direct flow was independently associated with RV dysfunction, remodelling and, to a lesser extent, exercise intolerance in rTOF patients. This supports its utility as an imaging parameter for monitoring disease progression and therapeutic response in rTOF. Clinical Trial Registrationhttps://www.clinicaltrials.gov. Unique identifier: NCT03217240

Association of respiratory symptoms and lung function with occupation in the multinational Burden of Obstructive Lung Disease (BOLD) study

Background Chronic obstructive pulmonary disease has been associated with exposures in the workplace. We aimed to assess the association of respiratory symptoms and lung function with occupation in the Burden of Obstructive Lung Disease study. Methods We analysed cross-sectional data from 28 823 adults (≥40 years) in 34 countries. We considered 11 occupations and grouped them by likelihood of exposure to organic dusts, inorganic dusts and fumes. The association of chronic cough, chronic phlegm, wheeze, dyspnoea, forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1)/FVC with occupation was assessed, per study site, using multivariable regression. These estimates were then meta-analysed. Sensitivity analyses explored differences between sexes and gross national income. Results Overall, working in settings with potentially high exposure to dusts or fumes was associated with respiratory symptoms but not lung function differences. The most common occupation was farming. Compared to people not working in any of the 11 considered occupations, those who were farmers for ≥20 years were more likely to have chronic cough (OR 1.52, 95% CI 1.19–1.94), wheeze (OR 1.37, 95% CI 1.16–1.63) and dyspnoea (OR 1.83, 95% CI 1.53–2.20), but not lower FVC (β=0.02 L, 95% CI −0.02–0.06 L) or lower FEV1/FVC (β=0.04%, 95% CI −0.49–0.58%). Some findings differed by sex and gross national income. Conclusion At a population level, the occupational exposures considered in this study do not appear to be major determinants of differences in lung function, although they are associated with more respiratory symptoms. Because not all work settings were included in this study, respiratory surveillance should still be encouraged among high-risk dusty and fume job workers, especially in low- and middle-income countries.publishedVersio

Cohort Profile: Burden of Obstructive Lung Disease (BOLD) study

The Burden of Obstructive Lung Disease (BOLD) study was established to assess the prevalence of chronic airflow obstruction, a key characteristic of chronic obstructive pulmonary disease, and its risk factors in adults (≥40 years) from general populations across the world. The baseline study was conducted between 2003 and 2016, in 41 sites across Africa, Asia, Europe, North America, the Caribbean and Oceania, and collected high-quality pre- and post-bronchodilator spirometry from 28 828 participants. The follow-up study was conducted between 2019 and 2021, in 18 sites across Africa, Asia, Europe and the Caribbean. At baseline, there were in these sites 12 502 participants with high-quality spirometry. A total of 6452 were followed up, with 5936 completing the study core questionnaire. Of these, 4044 also provided high-quality pre- and post-bronchodilator spirometry. On both occasions, the core questionnaire covered information on respiratory symptoms, doctor diagnoses, health care use, medication use and ealth status, as well as potential risk factors. Information on occupation, environmental exposures and diet was also collected

Granular Elastic Network Regression with Stochastic Gradient Descent

Linear regression is the use of linear functions to model the relationship between a dependent variable and one or more independent variables. Linear regression models have been widely used in various fields such as finance, industry, and medicine. To address the problem that the traditional linear regression model is difficult to handle uncertain data, we propose a granule-based elastic network regression model. First we construct granules and granular vectors by granulation methods. Then, we define multiple granular operation rules so that the model can effectively handle uncertain data. Further, the granular norm and the granular vector norm are defined to design the granular loss function and construct the granular elastic network regression model. After that, we conduct the derivative of the granular loss function and design the granular elastic network gradient descent optimization algorithm. Finally, we performed experiments on the UCI datasets to verify the validity of the granular elasticity network. We found that the granular elasticity network has the advantage of good fit compared with the traditional linear regression model

Noncoherent Demodulation with Viterbi Decoding for Partial Response Continuous Phase Modulation

ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NVWith the characteristics of constant envelope and continuous phase, Continuous Phase Modulation (CPM) signal has higher spectrum efficiency and power efficiency than other modulation forms. A noncoherent demodulation with Viterbi decoding for partial response CPM signals is proposed. Simulation results indicate that the demodulation performance of proper partial response CPM is better than the traditional PCM-FM, which is a typical modulation of full response CPM. And higher spectral efficiency is also obtained by partial response CPM.International Foundation for TelemeteringProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection

Template-Based 3D Road Modeling for Generating Large-Scale Virtual Road Network Environment

The 3D road network scene helps to simulate the distribution of road infrastructure and the corresponding traffic conditions. However, the existing road modeling methods have limitations such as inflexibility in different types of road construction, inferior quality in visual effects and poor efficiency for large-scale model rendering. To tackle these challenges, a template-based 3D road modeling method is proposed in this paper. In this method, the road GIS data is first pre-processed before modeling. The road centerlines are analyzed to extract topology information and resampled to improve path accuracy and match the terrain. Meanwhile, the road network is segmented and organized using a hierarchical block data structure. Road elements, including roadbeds, road facilities and moving vehicles are then designed based on templates. These templates define the geometric and semantic information of elements along both the cross-section and road centerline. Finally, the road network scene is built by the construction algorithms, where roads, at-grade intersections, grade separated areas and moving vehicles are modeled and simulated separately. The proposed method is tested by generating large-scale virtual road network scenes in the World Wind, an open source software package. The experimental results demonstrate that the method is flexible and can be used to develop different types of road models and efficiently simulate large-scale road network environments

Intelligent ship anti-rolling control system based on a deep deterministic policy gradient algorithm and the Magnus effect

Anti-rolling devices are widely used in modern shipboard components. In particular, ship anti-rolling control systems are developed to achieve a wide range of ship speeds and efficient anti-rolling capabilities. However, factors that are challenging to solve accurately, such as strong nonlinearities, a complex working environment, and hydrodynamic system parameters, limit the investigation of the rolling motion of ships at sea. Moreover, current anti-rolling control systems still face several challenges, such as poor nonlinear adaptability and manual parameter adjustment. In this regard, this study developed a dynamic model for a ship anti-rolling system. In addition, based on deep reinforcement learning (DRL), an efficient anti-rolling controller was developed using a deep deterministic policy gradient (DDPG) algorithm. Finally, the developed system was applied to a ship anti-rolling device based on the Magnus effect. The advantages of reinforcement learning adaptive control enable controlling an anti-rolling system under various wave angles, ship speeds, and wavelengths. The results revealed that the anti-rolling efficiency of the intelligent ship anti-rolling control method using the DDPG algorithm surpassed 95% and had fast convergence. This study lays the foundation for developing a DRL anti-rolling controller for full-scale ships