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Objective: In recent years, the early diagnosis and treatment of coronary microvascular dysfunction (CMD) have become crucial for preventing coronary heart disease. This paper aims to develop a computer-assisted autonomous diagnosis method for CMD by using ECG features and expert features. Approach: Clinical electrocardiogram (ECG), myocardial contrast echocardiography (MCE), and coronary angiography (CAG) are used in our method. Firstly, morphological features, temporal features, and T-wave features of ECG are extracted by multi-channel residual network with BiLSTM (MCResnet-BiLSTM) model and the multi-source T-wave features (MTF) extraction model, respectively. And these features are fused to form ECG features. In addition, the CFR$_\text{MCE}$ is calculated based on the parameters related to the MCE at rest and stress state, and the Angio-IMR is calculated based on CAG. The combination of CFR$_\text{MCE}$ and Angio-IMR is termed as expert features. Furthermore, the hybrid features, fused from the ECG features and the expert features, are input into the multilayer perceptron to implement the identification of CMD. And the weighted sum of the softmax loss and center loss is used as the total loss function for training the classification model, which optimizes the classification ability of the model. Result: The proposed method achieved 93.36% accuracy, 94.46% specificity, 92.10% sensitivity, 95.89% precision, and 93.95% F1 score on the clinical dataset of the Second Affiliated Hospital of Zhejiang University. Conclusion: The proposed method accurately extracts global ECG features, combines them with expert features to obtain hybrid features, and uses weighted loss to significantly improve diagnostic accuracy. It provides a novel and practical method for the clinical diagnosis of CMD.

The Florida peninsula in the USA has a frequent occurrence of sea breeze (SB) thunderstorms. In this study, the numerical simulation of a Florida SB and its associated convective initiation (CI) is simulated using the mesoscale community Weather Research and Forecasting (WRF) model in one-way nested domains at different horizontal resolutions. Results are compared with observations to examine the accuracy of model-simulated SB convection and factors that influence SB CI within the simulation.

The relationship between soil moisture (SM) and temperature at 2‐m height (T2) is examined with long‐term meteorological and soil observations and a single‐column model. With the information flow (IF) and correlation analysis methods, results show that the distribution of SM depends on land use and land cover, while an increase in vegetation fraction corresponds to an increase in SM, and this dependence decreases with soil depth. There is causality between T2 and SM at all soil levels. Compared with those in deeper soil, higher IF values and correlations appear in the top soil levels, implying a stronger interaction between the top soil layer and the atmosphere. Meanwhile, most correlation coefficient values rank weak or moderate, and negative feedback is predominant with low IF values, indicating that the causality between them is relatively weak and also proving that SM is not the sole factor that influences changes of near‐surface temperature. The single‐column model demonstrates that an increase (decrease) in SM will result in cooler (warmer) T2 through the redistribution of surface heat flux, while changes in SM in the top soil layers have a stronger influence on T2 compared to those in deep soil layers. The duration of the atmospheric temperature inversion layer is also prolonged (reduced) with an increase (decrease) in SM. Impacts of SM on T2 vary with land use or vegetation fraction and also are more significant in warm months and the daytime than in cold months and nighttime. Moreover, large‐scale and local circulations have steady influences on T2 in different weather conditions. Soil moisture at all levels and the near‐surface atmospheric temperature have weak to moderate causality with seasonal variabilityDistribution of soil moisture depends on land use and land cover, and this dependence decreases with soil depthThere is a strong interaction between top soil layer and atmosphere; impacts of soil moisture on near‐surface temperature are significant

The NASA Cyclone Global Navigation Satellite System (CYGNSS) was launched in December 2016, providing an unprecedented opportunity to obtain ocean surface wind speeds including wind estimates over the hurricane inner‐core region. This study demonstrates the influence of assimilating an early version of CYGNSS observations of ocean surface wind speeds on numerical simulations of two notable landfalling hurricanes, Harvey and Irma (2017). A research version of the National Centers for Environmental Prediction operational Hurricane Weather Research and Forecasting model and the Gridpoint Statistical Interpolation‐based hybrid ensemble three‐dimensional variational data assimilation system are used. It is found that the assimilation of CYGNSS data results in improved track, intensity, and structure forecasts for both hurricane cases, especially for the weak phase of a hurricane, implying potential benefits of using such data for future research and operational applications. The NASA Cyclone Global Navigation Satellite System (CYGNSS) was launched in December 2016. It provides an unprecedented opportunity to obtain ocean surface wind speeds over a hurricane inner‐core region. In this study, we combined the early version of CYGNSS data with all other observations that are currently available for operational forecasts to form initial conditions (inputs data) for a numerical weather prediction model. A research version of the National Oceanic and Atmospheric Administration operational hurricane forecast model named the Hurricane Weather Research and Forecast (HWRF) model is used. Results show that adding CYGNSS data into HWRF model results in improved track, intensity, and structure forecasts for two notable landfalling hurricanes, Harvey and Irma (2017), demonstrating the potential benefits of using CYGNSS data for future research and operational applications. The NASA Cyclone Global Navigation Satellite System (CYGNSS) provides an unprecedented opportunity to obtain ocean surface wind data over a hurricane inner‐core regionThis study found that the assimilation of CYGNSS data results in improved track, intensity, and structure forecasts for two notable landfalling hurricanes, Harvey and Irma (2017)

This study analyzes observations collected by multilevel towers to estimate turbulence parameters in the atmospheric surface layer of two landfalling tropical cyclones (TCs). The momentum flux, turbulent kinetic energy (TKE) and dissipation rate increase with the wind speed independent of surface types. However, the momentum flux and TKE are much larger over land than over the coastal ocean at a given wind speed range. The vertical eddy diffusivity is directly estimated using the momentum flux and strain rate, which more quickly increases with the wind speed over a rougher surface. Comparisons of the eddy diffusivity estimated using the direct flux method and that using the friction velocity and height show good agreement. On the other hand, the traditional TKE method overestimates the eddy diffusivity compared to the direct flux method. The scaling coefficients in the TKE method are derived for the two different surface types to better match with the vertical eddy diffusivity based on the direct flux method. Some guidance to improve vertical diffusion parameterizations for TC landfall forecasts in weather simulations are also provided. Improved understanding of small‐scale processes near the surface is important for advancement of tropical cyclone intensity prediction. Observational data collected by multilevel towers are analyzed to study the turbulent mixing process and structure in the atmospheric surface layer of two landfalling storms. Turbulence parameters such momentum flux, turbulent kinetic energy (TKE) and dissipation rate are estimated, which shows a wind speed independence regardless of surface types. The magnitudes of the momentum flux and TKE are much larger over land than over the ocean at a given wind speed range. The turbulent mixing strength measured by the vertical eddy diffusivity are estimated and compared using three different methods. The scaling coefficient in the eddy diffusivity parameterization is derived based on observations. This newly derived coefficient would potentially lead to improved tropical cyclone forecasts when used in numerical models. The relationship between the vertical eddy diffusivity and wind speed is different over different underlying surface typesThe vertical eddy diffusivity estimated using the flux and strain rate is comparable to that using the friction velocity and heightThe scaling coefficient for estimating the vertical eddy diffusivity using turbulent kinetic energy varies with surface roughness length The relationship between the vertical eddy diffusivity and wind speed is different over different underlying surface types The vertical eddy diffusivity estimated using the flux and strain rate is comparable to that using the friction velocity and height The scaling coefficient for estimating the vertical eddy diffusivity using turbulent kinetic energy varies with surface roughness length

Accurate forecasting of the intensity changes of hurricanes is an important yet challenging problem in numerical weather prediction. The rapid intensification of Hurricane Katrina (2005) before its landfall in the southern US is studied with the Advanced Research version of the WRF (Weather Research and Forecasting) model. The sensitivity of numerical simulations to two popular planetary boundary layer (PBL) schemes, the Mellor–Yamada–Janjic (MYJ) and the Yonsei University (YSU) schemes, is investigated. It is found that, compared with the YSU simulation, the simulation with the MYJ scheme produces better track and intensity evolution, better vortex structure, and more accurate landfall time and location. Large discrepancies (e.g., over 10 hPa in simulated minimum sea level pressure) are found between the two simulations during the rapid intensification period. Further diagnosis indicates that stronger surface fluxes and vertical mixing in the PBL from the simulation with the MYJ scheme lead to enhanced air–sea interaction, which helps generate more realistic simulations of the rapid intensification process. Overall, the results from this study suggest that improved representation of surface fluxes and vertical mixing in the PBL is essential for accurate prediction of hurricane intensity changes.

A large eddy simulation (LES) embedded in the mesoscale community Weather Research and Forecasting model is used to examine the effects of turbulence on cold fog formation over Heber Valley in northern Utah in the U.S. The LES results indicate that large‐scale turbulent eddies prevail and dominate the mixing effects in the planetary boundary layer (PBL). The combination of turbulence mixing effects, mountain‐valley flow, and ultra‐cold valley temperature lead to fog formation in the LES simulation. The omission of the turbulent eddies in the PBL parameterization results in a weak mixing effect in the PBL and weakens the near‐surface air cooling, thus failing to reproduce the fog in the simulation. This study indicates the essential role of turbulence in fog formation over complex terrain. Turbulent eddies exist over complex terrain and can enhance mixing effects, and thus the conditions for fog formation. Turbulence mixing can affect the temperature and moisture exchange in the atmospheric boundary layer, the lower part of the atmosphere near the earth's surface. The planetary boundary layer parameterization scheme of mesoscale models cannot resolve the contributions of turbulent eddies to weather phenomena due to the coarser grid spacing of mesoscale models. This study conducted a large‐eddy simulation at fine resolution to simulate a fog event over the Heber Valley. It is found that large‐scale turbulent eddies are critical for fog formation over complex terrain. Large‐scale turbulent eddies are critical for fog formation over complex terrainTurbulent eddies exist under stable planetary boundary layer|planet boundary layer (PBL) and can help mixing effects, thus enhancing conditions for fog formation over complex terrainOmission of turbulent eddies in the PBL parameterization scheme results in weak mixing effects in the PBL, thus failing to simulate the fog Large‐scale turbulent eddies are critical for fog formation over complex terrain Turbulent eddies exist under stable planetary boundary layer|planet boundary layer (PBL) and can help mixing effects, thus enhancing conditions for fog formation over complex terrain Omission of turbulent eddies in the PBL parameterization scheme results in weak mixing effects in the PBL, thus failing to simulate the fog

The vertical eddy diffusivity (VED) in the planetary boundary layer (PBL) affects tropical cyclones' structure and evolution. Uncertainties of VED in the PBL parametrization scheme of a mesoscale model could be caused by the model's inability to represent large eddies (LEs). Using a large‐eddy simulation (LES) of Hurricane Harvey (2017) as a benchmark, the YSU PBL scheme is improved by adding effects of LEs derived from the LES. It is found that LEs' maximum intensity is linearly significantly related to the square of mean horizontal divergence below 400 m of height at the same air column with a slope coefficient of 1.97. The revised YSU scheme relates the VED of momentum (Km) to the square root of LEs' intensity with a slope coefficient of 0.08 in PBL and 0.20 in a free atmosphere. Compared to the original scheme, the modified YSU scheme leads to improved forecasts of landfalling hurricanes. The turbulent transport in the boundary layer, the low part of the atmosphere near the Earth's surface, affects tropical cyclones' structure and evolution. Its effects are represented by the vertical eddy diffusivity (VED) in the planetary boundary layer (PBL) parameterization scheme of a mesoscale model. Due to the coarser grid spacing of the mesoscale model, the effects of large eddies in the boundary layer cannot be resolved. In this study, a large‐eddy simulation (LES) of Hurricane Harvey (2017) is used as a benchmark to relate the effects of large eddies to the VED of momentum. The derived relationship is then applied to improve a popular PBL parameterization scheme, which has been widely used in the mesoscale models. It is found that compared to the original scheme, the modified YSU scheme leads to improved forecasts of landfalling hurricanes. Large eddies LE)s' maximum intensity is linearly related to the square of mean horizontal divergence below 400 mThe revised YSU scheme relates the vertical eddy diffusivity of momentum to the square root of the LEs' intensityThe modified YSU scheme leads to improved forecasts of landfalling hurricanes Large eddies LE)s' maximum intensity is linearly related to the square of mean horizontal divergence below 400 m The revised YSU scheme relates the vertical eddy diffusivity of momentum to the square root of the LEs' intensity The modified YSU scheme leads to improved forecasts of landfalling hurricanes

After a tropical storm makes landfall, its vortex interacts with the surrounding environment and the underlying surface. It is expected that diurnal variation over land will affect storm structures. However, this has not yet been explored in previous studies. In this paper, numerical simulation of postlandfall Tropical Storm Bill (2015) is conducted using a research version of the NCEP Hurricane Weather Research and Forecasting (HWRF) model. Results indicate that during the storm's interaction with midlatitude westerlies over the Great Plains, the simulated storm with the SLAB land‐surface scheme is stronger, with faster eastward movement and attenuation, and more asymmetric structures than that with the NOAH land‐surface scheme. More symmetric structures correspond with a slower weakening and slower eastward movement of the storm over land. Further diagnoses suggest an obvious response of the storm's asymmetric structures to diurnal effects over land. Surface diabatic heating in the storm environment is important for the storm's symmetric structures and intensity over land. Specifically, during the transition from nighttime to daytime, the evident strengthening of convective instability, atmospheric baroclinicity, and the lateral advection of high θeair in the storm environment, associated with the rapid increase in surface diabatic heating, are conducive to the development of vertical vorticity and storm‐relative helicity, thus contributing to the maintenance of the storm's symmetric structures and intensity after landfall. An evident response of the storm's asymmetric structures to diurnal effects over land are revealedSurface diabatic heating in the storm environment is important for the evolution of the storm's symmetric structures and intensity over landEffects of surface diabatic heating storm's symmetric structure and intensity over land are mainly manifested in storm's upshear quadrants An evident response of the storm's asymmetric structures to diurnal effects over land are revealed Surface diabatic heating in the storm environment is important for the evolution of the storm's symmetric structures and intensity over land Effects of surface diabatic heating storm's symmetric structure and intensity over land are mainly manifested in storm's upshear quadrants

Cloud‐permitting scale (3 km) simulations are made to investigate the diurnal cycle of precipitation (DCP) over the Indo‐Pacific Maritime Continent under the modulation of the Madden‐Julian Oscillation (MJO), focusing on January–February 2018 during the Years of the Maritime Continent (YMC). Comparisons with satellite precipitation and global reanalysis products show that the simulations reasonably capture main features of diurnal wind and precipitation. The MJO modulates the amplitude, timing, and propagation of the DCP through affecting both large‐scale and local circulation and convection. Under local suppressed conditions, much strengthened sea/valley breezes are generally responsible for the enhanced and earlier‐triggered (2‐ to 3‐hr lead) DCP over land. Meanwhile, stronger cooling induced by enhanced stratiform rainfall excites well‐developed gravity waves spreading outward and upward, accompanied by continuous decreases in low‐level temperature and amplified land breezes, which cause stronger and further offshore‐propagating DCP. The opposite is true under local active conditions. Modulated by the passing of MJO, the enhanced DCP also displays a systematic shift from the west to the east coasts of large islands, forming a unique dipolar structure in the anomalous island DCP. The DCP exhibits island‐dependent characteristics: With topographical elevation, the triggering mechanism of island convection transforms from later penetrating sea breeze fronts over mountain foothills to early‐excited valley winds over mountain tops. Steep topography also supports stronger intraseasonal variations of the DCP, which can be well explained by regional variations in land‐sea/mountain‐valley breezes, terrain lifting, and ambient wind‐induced advective and vertical wind shear effects. Cloud‐permitting simulations demonstrate the roles of land‐sea breezes, elevated terrain, valley winds, and gravity waves in diurnal precipitation over the Maritime ContinentThe MJO modulates the amplitude, timing, and propagation of diurnal precipitation through a combination of varying large‐scale and local circulations and convectionThe diurnal precipitation cycle under the MJO modulation varies among islands depending on their size and topography

Ultrasound-targeted microbubble destruction (UTMD) has been proposed as a new technique for organ-specific gene transfer and drug delivery. This study was performed to investigate the effect of UTMD on marrow mesenchymal stem cells (MSCs) transfected with pcDNA3.1−-hVEGF165.pcDNA3.1−-hVEGF165 were transfected into the third passage of MSCs, with or without UTMD under different ultrasound conditions. Protein expression was quantified by hVEGF165-ELISA kit after transfection for 24, 48, and 72 hours. UTMD-mediated transfection of MSCs yielded a significant protein expression. UTMD of mechanic index (MI) 0.6 for 90 seconds led to the highest level of protein expression.