From Disks to Channels: Dynamics of Active Nematics Confined to an Annulus

Confinement can be used to systematically tame turbulent dynamics occurring in active fluids. Although periodic channels are the simplest geometries to study confinement numerically, the corresponding experimental realizations require closed racetracks. Here, we computationally study 2D active nematics confined to such a geometry -- an annulus. By systematically varying the annulus inner radius and channel width, we bridge the behaviors observed in the previously studied asymptotic limits of the annulus geometry: a disk and an infinite channel. We identify new steady-state behaviors, which reveal the influence of boundary curvature and its interplay with confinement. We also show that, below a threshold inner radius, the dynamics are insensitive to topological constraints imposed by boundary conditions. We explain this insensitivity through a simple scaling analysis. Our work sheds further light on design principles for using confinement to control the dynamics of active nematics

A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems [Discussion Forum]

© 2005-2012 IEEE. Fuzzy Sets and Systems is an area of computational intelligence, pioneered by Lotfi Zadeh over 50 years ago in a seminal paper in Information and Control. Fuzzy Sets (FSs) deal with uncertainty in our knowledge of a particular situation. Research and applications in FSs have grown steadily over 50 years. More recently, we have seen a growth in Type-2 Fuzzy Set (T2 FS) related papers, where T2 FSs are utilized to handle uncertainty in realworld problems. In this paper, we have used bibliometric methods to obtain a broad overview of the area of T2 FSs. This method analyzes information on the bibliographic details of published journal papers, which includes title, authors, author address, journals and citations, extracted from the Science and Social Science Citation Indices in the Web of Science (WoS) database for the last 20 years (1997-2017). We have compared the growth of publications in the field of FSs, and its subset T2 FSs, identified highly cited papers in T2 FSs, highly cited authors, key institutions, and main countries with researchers involved in T2 FS related research

A Machine Learning Approach to Robustly Determine Director Fields and Analyze Defects in Active Nematics

Active nematics are dense systems of rodlike particles that consume energy to drive motion at the level of the individual particles. They exist in natural systems like biological tissues and artificial materials such as suspensions of self-propelled colloidal particles or synthetic microswimmers. Active nematics have attracted significant attention in recent years due to their spectacular nonequilibrium collective spatiotemporal dynamics, which may enable applications in fields such as robotics, drug delivery, and materials science. The director field, which measures the direction and degree of alignment of the local nematic orientation, is a crucial characteristic of active nematic and is essential for studying topological defects. However, determining the director field is a significant challenge in many experimental systems. Although director fields can be derived from images of active nematics using traditional imaging processing methods, the accuracy of such methods are highly sensitive to the settings of the algorithms. These settings must be tuned from image-to-image due to experimental noise, intrinsic noise of the imaging technology, and perturbations caused by changes in experimental conditions. This sensitivity currently limits automatic analysis of active nematics. To address this, we developed a machine learning model for extracting reliable director fields from raw experimental images, which enables accurate analysis of topological defects. Application of the algorithm to experimental data demonstrates that the approach is robust and highly generalizable to experimental settings that are different from those in the training data. It could be a promising tool for investigating active nematics and may be generalized to other active matter systems

Clinical Characteristics of Patients Classified as Very High Risk and Not Very High Risk Based on the 2018 AHA/ACC Multi-Society Cholesterol Guideline

Background The 2018 AHA/ACC Cholesterol Guideline recommendation to classify ASCVD patients as very high-risk (VHR) vs not-VHR (NVHR) has important implications for ezetimibe and PCSK9 inhibitor eligibility. We aimed to define the clinical characteristics of these two groups within a large multi-state healthcare system in the Western U.S. Methods We performed a retrospective cohort analysis of patients defined as having ASCVD in 2018 using EHR ICD-10 codes. VHR was defined by ≥2 major ASCVD events (ACS ≤12 months, history of MI \u3e12 months, ischemic stroke, or symptomatic PAD) or 1 major ASCVD event and ≥2 high-risk conditions (age ≥65, DM, HTN, smoking, HeFH, CKD, CHF, persistently elevated LDL-C, or prior CABG/PCI). Patients not meeting these criteria were classified as NVHR. Results A total of 180,669 ASCVD patients were identified: 104,123 (58%) were VHR and 76,546 (42%) were NVHR. Mean age and gender was 70.1±13.4 years, 54% male and 73.1±11.9 years, 55% male for the NVHR and VHR groups, respectively. Among patients with a history of MI or recent ACS, 99% and 96% were classified as VHR, respectively (Table). Age ≥65, HTN and DM were the most prevalent high-risk conditions. Conclusion Criteria used to predict future CV risk largely divide ASCVD patients into groups of similar prevalence. Nearly all ACS/MI patients were VHR. With growing emphasis on individualized risk assessment and intense LDL-C reduction, opportunity exists to further refine risk prediction within these two at-risk groups

Accuracy of 23 Equations for Estimating LDL Cholesterol in a Clinical Laboratory Database of 5,051,467 Patients

Background: Alternatives to the Friedewald low-density lipoprotein cholesterol (LDL-C) equation have been proposed. Objective: To compare the accuracy of available LDL-C equations with ultracentrifugation measurement. Methods: We used the second harvest of the Very Large Database of Lipids (VLDbL), which is a population-representative convenience sample of adult and pediatric patients (N = 5,051,467) with clinical lipid measurements obtained via the vertical auto profile (VAP) ultracentrifugation method between October 1, 2015 and June 30, 2019. We performed a systematic literature review to identify available LDL-C equations and compared their accuracy according to guideline-based classification. We also compared the equations by their median error versus ultracentrifugation. We evaluated LDL-C equations overall and stratified by age, sex, fasting status, and triglyceride levels, as well as in patients with atherosclerotic cardiovascular disease, hypertension, diabetes, kidney disease, inflammation, and thyroid dysfunction. Results: Analyzing 23 identified LDL-C equations in 5,051,467 patients (mean±SD age, 56±16 years; 53.3% women), the Martin/Hopkins equation most accurately classified LDL-C to the correct category (89.6%), followed by the Sampson (86.3%), Chen (84.4%), Puavilai (84.1%), Delong (83.3%), and Friedewald (83.2%) equations. The other 17 equations were less accurate than Friedewald, with accuracy as low as 35.1%. The median error of equations ranged from –10.8 to 18.7 mg/dL, and was best optimized using the Martin/Hopkins equation (0.3, IQR–1.6 to 2.4 mg/dL). The Martin/Hopkins equation had the highest accuracy after stratifying by age, sex, fasting status, triglyceride levels, and clinical subgroups. In addition, one in five patients who had Friedewald LDL-C 70 mg/dL by the Martin/Hopkins equation. Conclusions: Most proposed alternatives to the Friedewald equation worsen LDL-C accuracy, and their use could introduce unintended disparities in clinical care. The Martin/Hopkins equation demonstrated the highest LDL-C accuracy overall and across subgroups

Evaluation of a social franchising and telemedicine programme and the care provided for childhood diarrhoea and pneumonia, Bihar, India

OBJECTIVE: To evaluate the impact on the quality of the care provided for childhood diarrhoea and pneumonia in Bihar, India, of a large-scale, social franchising and telemedicine programme - the World Health Partners' Sky Program. METHODS: We investigated changes associated with the programme in the knowledge and performance of health-care providers by carrying out 810 assessments in a representative sample of providers in areas where the programme was and was not implemented. Providers were assessed using hypothetical patient vignettes and the standardized patient method both before and after programme implementation, in 2011 and 2014, respectively. Differences in providers' performance between implementation and nonimplementation areas were assessed using multivariate difference-in-difference linear regression models. FINDINGS: The programme did not significantly improve health-care providers' knowledge or performance with regard to childhood diarrhoea or pneumonia in Bihar. There was a persistent large gap between knowledge of appropriate care and the care actually delivered. CONCLUSION: Social franchising has received attention globally as a model for delivering high-quality care in rural areas in the developing world but supporting data are scarce. Our findings emphasize the need for sound empirical evidence before social franchising programmes are scaled up