50 research outputs found

    Diversities of disability caused by lung cancer in the 66 Belt and Road initiative countries: a secondary analysis from the Global Burden of Disease Study 2019

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    ObjectivesDue to the increase in life expectancy and the aging of the global population, the “Belt and Road” (“B&R”) countries are faced with varying degrees of lung cancer threat. The purpose of this study is to analyze the differences in the burden and trend of lung cancer disability in the “B&R” countries from 1990 to 2019 so as to provide an analytical strategic basis to build a healthy “B&R”.MethodsData were derived from the Global Burden of Disease 2019 (GBD 2019). Incidence, mortality, prevalence, the years lived with disability (YLDs), and disability-adjusted life years (DALYs) of lung cancer and those attributable to different risk factors were measured from 1990 to 2019. Trends of disease burden were estimated by using the average annual percent change (AAPC), and the 95% uncertainty interval (UI) was reported.ResultsChina, India, and the Russian Federation were the three countries with the highest burden of lung cancer in 2019. From 1990 to 2019, the AAPC of incidence, prevalence, mortality, and DALYs generally showed a downward trend in Central Asia (except Georgia) and Eastern Europe, while in China, South Asia (except Bangladesh), most countries in North Africa, and the Middle East, the trend was mainly upward. The AAPC of age-standardized incidence was 1.33% (1.15%–1.50%); the AAPC of prevalence, mortality, and DALYs from lung cancer in China increased by 24% (2.10%–2.38%), 0.94% (0.74%–1.14%), and 0.42% (0.25%–0.59%), respectively. A downward trend of the AAPC values of age-standardized YLD rate in men was shown in the vast majority of “B&R” countries, but for women, most countries had an upward trend. For adults aged 75 years or older, the age-standardized YLD rate showed an increasing trend in most of the “B&R” countries. Except for the DALY rate of lung cancer attributable to metabolic risks, a downward trend of the DALY rate attributable to all risk factors, behavioral risks, and environmental/occupational risks was shown in the vast majority of “B&R” countries.ConclusionThe burden of lung cancer in “B&R” countries varied significantly between regions, genders, and risk factors. Strengthening health cooperation among the “B&R” countries will help to jointly build a community with a shared future for mankind

    Slip-Flow and Heat Transfer of a Non-Newtonian Nanofluid in a Microtube

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    The slip-flow and heat transfer of a non-Newtonian nanofluid in a microtube is theoretically studied. The power-law rheology is adopted to describe the non-Newtonian characteristics of the flow, in which the fluid consistency coefficient and the flow behavior index depend on the nanoparticle volume fraction. The velocity profile, volumetric flow rate and local Nusselt number are calculated for different values of nanoparticle volume fraction and slip length. The results show that the influence of nanoparticle volume fraction on the flow of the nanofluid depends on the pressure gradient, which is quite different from that of the Newtonian nanofluid. Increase of the nanoparticle volume fraction has the effect to impede the flow at a small pressure gradient, but it changes to facilitate the flow when the pressure gradient is large enough. This remarkable phenomenon is observed when the tube radius shrinks to micrometer scale. On the other hand, we find that increase of the slip length always results in larger flow rate of the nanofluid. Furthermore, the heat transfer rate of the nanofluid in the microtube can be enhanced due to the non-Newtonian rheology and slip boundary effects. The thermally fully developed heat transfer rate under constant wall temperature and constant heat flux boundary conditions is also compared

    Analysis of Flow Cytometric Fluorescence Lifetime with Time-Delay Estimation of Pulse Signals

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    The measurement of fluorescence lifetimes emerged in flow cytometry because it is not impacted by the non-linearity, which occurs in fluorescence intensity measurements. However, this significantly increases the cost and complexity of a traditional flow cytometer. This work reports a simple method of fluorescence lifetime measurement of a flow cytometer based on the cytometric fluorescence pulse time-delay estimation and hardware time-delay calibration. The modified chirp Z-transform (MCZT) algorithm, combined with the algorithm of fine interpolation of correlation peak (FICP), is applied to improve the temporal resolution of the cross-correlation function of the scattering and fluorescence signals, which in turn improves the time-delay estimation accuracy. The estimation accuracy is verified by Gauss fitting. Cells that were labeled simultaneously with three-color reagents are measured; the statistical results of 5000 cells are compared with reference values and are verified with the pulse width variation. The results show the potential of fluorescence lifetime measurements in the traditional flow cytometer

    Representation Method for Spectrally Overlapping Signals in Flow Cytometry Based on Fluorescence Pulse Time-Delay Estimation

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    Flow cytometry is being applied more extensively because of the outstanding advantages of multicolor fluorescence analysis. However, the intensity measurement is susceptible to the nonlinearity of the detection method. Moreover, in multicolor analysis, it is impossible to discriminate between fluorophores that spectrally overlap; this influences the accuracy of the fluorescence pulse signal representation. Here, we focus on spectral overlap in two-color analysis, and assume that the fluorescence follows the single exponential decay model. We overcome these problems by analyzing the influence of the spectral overlap quantitatively, which enables us to propose a method of fluorescence pulse signal representation based on time-delay estimation (between fluorescence and scattered pulse signals). First, the time delays are estimated using a modified chirp Z-transform (MCZT) algorithm and a fine interpolation of the correlation peak (FICP) algorithm. Second, the influence of hardware is removed via calibration, in order to acquire the original fluorescence lifetimes. Finally, modulated signals containing phase shifts associated with these lifetimes are created artificially, using a digital signal processing method, and reference signals are introduced in order to eliminate the influence of spectral overlap. Time-delay estimation simulation and fluorescence signal representation experiments are conducted on fluorescently labeled cells. With taking the potentially overlap of autofluorescence as part of the observed fluorescence spectrum, rather than distinguishing the individual influence, the results show that the calculated lifetimes with spectral overlap can be rectified from 8.28 and 4.86 ns to 8.51 and 4.63 ns, respectively, using the comprehensive approach presented in this work. These values agree well with the lifetimes (8.48 and 4.67 ns) acquired for cells stained with single-color fluorochrome. Further, these results indicate that the influence of spectral overlap can be eliminated effectively. Moreover, modulation, mixing with reference signals, and low-pass filtering are performed with a digital signal processing method, thereby obviating the need for a high-speed analog device and complex circuit system. Finally, the flexibility of the comprehensive method presented in this work is significantly higher than that of existing methods

    Multi-Level Thresholding Image Segmentation Based on Improved Slime Mould Algorithm and Symmetric Cross-Entropy

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    Multi-level thresholding image segmentation divides an image into multiple regions of interest and is a key step in image processing and image analysis. Aiming toward the problems of the low segmentation accuracy and slow convergence speed of traditional multi-level threshold image segmentation methods, in this paper, we present multi-level thresholding image segmentation based on an improved slime mould algorithm (ISMA) and symmetric cross-entropy for global optimization and image segmentation tasks. First, elite opposition-based learning (EOBL) was used to improve the quality and diversity of the initial population and accelerate the convergence speed. The adaptive probability threshold was used to adjust the selection probability of the slime mould to enhance the ability of the algorithm to jump out of the local optimum. The historical leader strategy, which selects the optimal historical information as the leader for the position update, was found to improve the convergence accuracy. Subsequently, 14 benchmark functions were used to evaluate the performance of ISMA, comparing it with other well-known algorithms in terms of the optimization accuracy, convergence speed, and significant differences. Subsequently, we tested the segmentation quality of the method proposed in this paper on eight grayscale images and compared it with other image segmentation criteria and well-known algorithms. The experimental metrics include the average fitness (mean), standard deviation (std), peak signal to noise ratio (PSNR), structure similarity index (SSIM), and feature similarity index (FSIM), which we utilized to evaluate the quality of the segmentation. The experimental results demonstrated that the improved slime mould algorithm is superior to the other compared algorithms, and multi-level thresholding image segmentation based on the improved slime mould algorithm and symmetric cross-entropy can be effectively applied to the task of multi-level threshold image segmentation

    Do tracking by clustering anchors output from region proposal network

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    Most existing clustering algorithms suffer from the computation of similarity function and the representation of each object. In this paper, we propose a clustering tracker based on region proposal network (RPN-C) to do tracking by clustering anchors output by region proposal network into potential centers. We first cut off the second part of Faster RCNN and then cast clustering algorithms in feature space of anchors, including K-Means, mean shift and density peak clustering strategy in terms of anchors’ centroid and scale information. Without fully connected layers, the RPN-C tracker can lower the computational cost up to 60% and still, it can effectively maintain an accurate prediction for the localization in next frame. To evaluate the robustness of this tracker, we establish a dataset containing over 2000 training images and 7 testing sequences of 8 kinds of fruits. The experimental results on our own datasets demonstrate that the proposed tracker performs excellently both in location of object and the decision of scale and has a strong advantage of stability in the context of occlusion and complicated background

    Large-Range Switchable Asymmetric Transmission and Circular Conversion Dichroism in a VO<sub>2</sub> Based Metasurface

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    Reconfigurable chiral metasurfaces with a dynamic polarization manipulation capability are highly required in optical integrated systems. In this paper, we simultaneously realized giant and large-range switchable asymmetric transmission (AT) and circular conversion dichroism (CCD) in a vanadium dioxide (VO2) based metasurface. The AT and CCD of the insulator VO2 based metasurface reached 0.95 and 0.92, respectively. Utilizing the insulator-to-metallic phase transition of VO2, the AT and CCD could be continuously switched to near zero. Furthermore, the physics mechanism of the giant and switchable AT and CCD were analyzed. The proposed metasurface with large-range switchable AT and CCD is promising in applications of biochemistry detection, chiral imaging, and biosensing

    Robust Carbon-Stabilization of Few-Layer Black Phosphorus for Superior Oxygen Evolution Reaction

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    Few-layer exfoliated black phosphorus (Ex-BP) has attracted tremendous attention owing to its promising applications, including in electrocatalysis. However, it remains a challenge to directly use few-layer Ex-BP as oxygen-involved electrocatalyst because it is quite difficult to restrain structural degradation caused by spontaneous oxidation and keep it stable. Here, a robust carbon-stabilization strategy has been implemented to prepare carbon-coated Ex-BP/N-doped graphene nanosheet (Ex-BP/NGS@C) nanostructures at room temperature, which exhibit superior oxygen evolution reaction (OER) activity under alkaline conditions. Specifically, the as-synthesized Ex-BP/NGS@C hybrid presents a low overpotential of 257 mV at a current density of 10 mA cm&minus;2 with a small Tafel slope of 52 mV dec&minus;1 and shows high durability after long-term testing

    Effect of guidewire on the accuracy of trans-stenotic pressure measurement-A computational study

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    Accurate measurement of trans-stenotic pressure drop is vital for risk stratification in coronary artery disease. Currently, in vivo pressure measurement relies mostly on a pressure guidewire inserted into the artery, which inevitably alters local hemodynamics. To precisely assess the impact of guidewire insertion on the accuracy of pressure measurement, this study conducts numerical simulations with both an idealized straight-tube model and a patient-specific model. Results with and without a guidewire model are compared and analyzed. Results from the idealized model reveal that the insertion of a guidewire shifts velocity distribution, increases resistance, and amplifies the pressure drop across the stenosis. The patient-specific model also demonstrates that the guidewire causes non-negligible flow redistribution among the arterial branches, but the influence on pressure drop remains mostly localized. An analytical model for trans-stenotic pressure drop that takes the guidewire into consideration is also proposed and validated against the 3D simulation results. It is observed that the maximum relative error is around 3.0% in the patient-specific model, indicating the effectiveness of the analytical model in physiologically accurate settings. The proposed model can be used to align computed tomography-derived fractional flow reserve values with clinically recognized FFR standards established through guidewire measurements

    Suppression of hollow droplet rebound on super-repellent surfaces

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    Abstract Droplet rebound is ubiquitous on super-repellent surfaces. Conversion between kinetic and surface energies suggests that rebound suppression is unachievable due to negligible energy dissipation. Here, we present an effective approach to suppressing rebounds by incorporating bubbles into droplets, even in super-repellent states. This suppression arises from the counteractive capillary effects within bubble-encapsulated hollow droplets. The capillary flows induced by the deformed inner-bubble surface counterbalance those driven by the outer-droplet surface, resulting in a reduction of the effective take-off momentum. We propose a double-spring system with reduced effective elasticity for hollow droplets, wherein the competing springs offer distinct behavior from the classical single-spring model employed for single-phase droplets. Through experimental, analytical, and numerical validations, we establish a comprehensive and unified understanding of droplet rebound, by which the behavior of single-phase droplets represents the exceptional case of zero bubble volume and can be encompassed within this overarching framework
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