bluuebunny/crossref_metadata_2025_split huggingface dataset:
EFFECTS OF SAND THERAPY ON FLUID DYNAMICS OF BLOOD IN THE POPLITEAL ARTERY BASED ON THE EULER MULTIPHASE MODEL
Authors: WU HUI , FU RONGCHANG , LI XIANZHENG , YANG XIAOYU 
Published: August 2022

The effect of sand therapy on the hemodynamics of the popliteal artery (POA) was investigated to elucidate its mechanism in atherosclerosis physiotherapy. The hemodynamic parameters of the POA before and after sand therapy were obtained from 58 subjects and statistically analyzed. A three-dimensional finite element model of POA bifurcation was established. Blood was regarded as a triple-phase flow composed of plasma, red blood cells (RBCs), and white blood cells (WBCs). Using computational fluid dynamics (CFD), blood flow velocity, wall shear stress (WSS), and blood cell volume distribution before and after sand therapy were calculated. Sand therapy could reduce the vortex and reflux in blood vessels. The maximum increase in blood axial velocity was 34.38%. The maximum WSS increased by 22.82 Pa and the blood cells gradually moved away from the vessel wall and toward the axis of the blood vessel. The reduction in vortex and reflux, and the increase in blood axial velocity after sand therapy are beneficial in reducing the accumulation of cholesterol and other substances, thereby alleviating the formation of atherosclerotic plaques and lipid streaks. The rise in WSS slows the tendency of arterial vascular thickening in regions of low WSS. The movement of blood cells to the axis of blood vessels can reduce the possibility of thrombosis caused by blood cells squeezing on the blood vessel walls. These findings suggest that sand therapy may slow atherosclerosis progression.
A Blood-Based Metabolite Panel for Distinguishing Ovarian Cancer from Benign Pelvic Masses
Authors: Irajizad Ehsan , Han Chae Y. , Celestino Joseph , Wu Ranran , Murage Eunice , Spencer Rachelle , Dennison Jennifer B. , Vykoukal Jody , Long James P. , Do Kim Anh , Drescher Charles , Lu Karen , Lu Zhen , Bast Robert C. , Hanash Sam , Fahrmann Johannes F. 
Published: August 2022

Abstract

Purpose:
To assess the contributions of circulating metabolites for improving upon the performance of the risk of ovarian malignancy algorithm (ROMA) for risk prediction of ovarian cancer among women with ovarian cysts.

Experimental Design:
Metabolomic profiling was performed on an initial set of sera from 101 serous and nonserous ovarian cancer cases and 134 individuals with benign pelvic masses (BPM). Using a deep learning model, a panel consisting of seven cancer-related metabolites [diacetylspermine, diacetylspermidine, N-(3-acetamidopropyl)pyrrolidin-2-one, N-acetylneuraminate, N-acetyl-mannosamine, N-acetyl-lactosamine, and hydroxyisobutyric acid] was developed for distinguishing early-stage ovarian cancer from BPM. The performance of the metabolite panel was evaluated in an independent set of sera from 118 ovarian cancer cases and 56 subjects with BPM. The contributions of the panel for improving upon the performance of ROMA were further assessed.

Results:
A 7-marker metabolite panel (7MetP) developed in the training set yielded an AUC of 0.86 [95% confidence interval (CI): 0.76–0.95] for early-stage ovarian cancer in the independent test set. The 7MetP+ROMA model had an AUC of 0.93 (95% CI: 0.84–0.98) for early-stage ovarian cancer in the test set, which was improved compared with ROMA alone [0.91 (95% CI: 0.84–0.98); likelihood ratio test P: 0.03]. In the entire specimen set, the combined 7MetP+ROMA model yielded a higher positive predictive value (0.68 vs. 0.52; one-sided P &lt; 0.001) with improved specificity (0.89 vs. 0.78; one-sided P &lt; 0.001) for early-stage ovarian cancer compared with ROMA alone.

Conclusions:
A blood-based metabolite panel was developed that demonstrates independent predictive ability and complements ROMA for distinguishing early-stage ovarian cancer from benign disease to better inform clinical decision making.
Effects on Mortality and Major Bleeding of Radial Versus Femoral Artery Access for Coronary Angiography or Percutaneous Coronary Intervention: Meta-Analysis of Individual Patient Data From 7 Multicenter Randomized Clinical Trials
Authors: Gargiulo Giuseppe , Giacoppo Daniele , Jolly Sanjit S. , Cairns John , Le May Michel , Bernat Ivo , Romagnoli Enrico , Rao Sunil V. , van Leeuwen Maarten A.H. , Mehta Shamir R. , Bertrand Olivier F. , Wells George A. , Meijers Thomas A. , Siontis George C.M. , Esposito Giovanni , Windecker Stephan , Jüni Peter , Valgimigli Marco ,   for the Radial Trialists’ Collaboration
Published: August 2022

Background:
In some randomized clinical trials, transradial access (TRA) compared with transfemoral access (TFA) was associated with lower mortality in patients with coronary artery disease undergoing invasive management. We analyzed the effects of TRA versus TFA across multicenter randomized clinical trials and whether these associations are modified by patient or procedural characteristics.

Methods:
We performed an individual patient data meta-analysis of multicenter randomized clinical trials comparing TRA with TFA among patients undergoing coronary angiography with or without percutaneous coronary intervention. The primary outcome was all-cause mortality and the co–primary outcome was major bleeding at 30 days. The primary analysis was conducted by 1-stage mixed-effects models on the basis of the intention-to-treat cohort. The effect of access site on mortality and major bleeding was assessed further by multivariable analysis. The relationship among access site, bleeding, and mortality was investigated by natural effect model mediation analysis with multivariable adjustment.

Results:

A total of 21 600 patients (10 775 TRA, 10 825 TFA) from 7 randomized clinical trials were included. The median age was 63.9 years, 31.9% were women, 95% presented with acute coronary syndrome, and 75.2% underwent percutaneous coronary intervention. All-cause mortality (1.6% versus 2.1%; hazard ratio, 0.77 [95% CI, 0.63–0.95];
P
=0.012) and major bleeding (1.5% versus 2.7%; odds ratio, 0.55 [95% CI, 0.45–0.67];
P
<0.001) were lower with TRA. Subgroup analyses for mortality showed consistent results, except for baseline hemoglobin level (
P
interaction
=0.003), indicating that the benefit of TRA was substantial in patients with moderate or severe anemia, whereas it was not significant in patients with milder or no baseline anemia. After adjustment, TRA remained associated with 24% and 51% relative risk reduction of all-cause mortality and major bleeding, respectively. A mediation analysis showed that the benefit of TRA on mortality was only partially driven by major bleeding prevention and ancillary mechanisms are required to fully explain the causal association.

Conclusions:
TRA is associated with lower all-cause mortality and major bleeding at 30 days compared with TFA. The effect on mortality was driven by patients with anemia. The reduction in major bleeding only partially explains the mortality benefit.

Registration:

URL:
https://www.crd.york.ac.uk/prospero
; Unique identifier: CRD42018109664.
How Lévy Flights Triggered by the Presence of Defectors Affect Evolution of Cooperation in Spatial Games
Authors: Ichinose Genki , Miyagawa Daiki , Chiba Erika , Sayama Hiroki 
Published: August 2022

AbstractCooperation among individuals has been key to sustaining societies. However, natural selection favors defection over cooperation. Cooperation can be favored when the mobility of individuals allows cooperators to form a cluster (or group). Mobility patterns of animals sometimes follow a Lévy flight. A Lévy flight is a kind of random walk but it is composed of many small movements with a few big movements. The role of Lévy flights for cooperation has been studied by Antonioni and Tomassini, who showed that Lévy flights promoted cooperation combined with conditional movements triggered by neighboring defectors. However, the optimal condition for neighboring defectors and how the condition changes with the intensity of Lévy flights are still unclear. Here, we developed an agent-based model in a square lattice where agents perform Lévy flights depending on the fraction of neighboring defectors. We systematically studied the relationships among three factors for cooperation: sensitivity to defectors, the intensity of Lévy flights, and population density. Results of evolutionary simulations showed that moderate sensitivity most promoted cooperation. Then, we found that the shortest movements were best for cooperation when the sensitivity to defectors was high. In contrast, when the sensitivity was low, longer movements were best for cooperation. Thus, Lévy flights, the balance between short and long jumps, promoted cooperation in any sensitivity, which was confirmed by evolutionary simulations. Finally, as the population density became larger, higher sensitivity was more beneficial for cooperation to evolve. Our study highlights that Lévy flights are an optimal searching strategy not only for foraging but also for constructing cooperative relationships with others.
Astrocytes Learn to Detect and Signal Deviations From Critical Brain Dynamics
Authors: Ivanov Vladimir A. , Michmizos Konstantinos P. 
Published: August 2022

Abstract
Astrocytes are nonneuronal brain cells that were recently shown to actively communicate with neurons and are implicated in memory, learning, and regulation of cognitive states. Interestingly, these information processing functions are also closely linked to the brain's ability to self-organize at a critical phase transition. Investigating the mechanistic link between astrocytes and critical brain dynamics remains beyond the reach of cellular experiments, but it becomes increasingly approachable through computational studies. We developed a biologically plausible computational model of astrocytes to analyze how astrocyte calcium waves can respond to changes in underlying network dynamics. Our results suggest that astrocytes detect synaptic activity and signal directional changes in neuronal network dynamics using the frequency of their calcium waves. We show that this function may be facilitated by receptor scaling plasticity by enabling astrocytes to learn the approximate information content of input synaptic activity. This resulted in a computationally simple, information-theoretic model, which we demonstrate replicating the signaling functionality of the biophysical astrocyte model with receptor scaling. Our findings provide several experimentally testable hypotheses that offer insight into the regulatory role of astrocytes in brain information processing.
Automated Identification of “Dunkelflaute” Events: A Convolutional Neural Network–Based Autoencoder Approach
Authors: Li Bowen , Basu Sukanta , Watson Simon J. 
Published: August 2022

Abstract
As wind and solar power play increasingly important roles in the European energy system, unfavorable weather conditions, such as “Dunkelflaute” (extended calm and cloudy periods), will pose ever greater challenges to transmission system operators. Thus, accurate identification and characterization of such events from open data streams (e.g., reanalysis, numerical weather prediction, and climate projection) are going to be crucial. In this study, we propose a two-step, unsupervised deep learning framework [wind and solar network (WISRnet)] to automatically encode spatial patterns of wind speed and insolation, and subsequently, identify Dunkelflaute periods from the encoded patterns. Specifically, a deep convolutional neural network (CNN)–based autoencoder (AE) is first employed for feature extraction from the spatial patterns. These two-dimensional CNN-AE patterns encapsulate both amplitude and spatial information in a parsimonious way. In the second step of the WISRnet framework, a variant of the well-known k-means algorithm is used to divide the CNN-AE patterns in region-dependent meteorological clusters. For the validation of the WISRnet framework, aggregated wind and solar power production data from Belgium are used. Using a simple criterion from published literature, all the Dunkelflaute periods are directly identified from this 6-year-long dataset. Next, each of these periods is associated with a WISRnet-derived cluster. Interestingly, we find that the majority of these Dunkelflaute periods are part of only 5 clusters (out of 25). We show that in lieu of proprietary power production data, the WISRnet framework can identify Dunkelflaute periods from public-domain meteorological data. To further demonstrate the prowess of this framework, it is deployed to identify and characterize Dunkelflaute events in Denmark, Sweden, and the United Kingdom.
Vertical Structure and Ice Production Processes of Shallow Convective Postfrontal Clouds over the Southern Ocean in MARCUS. Part II: Modeling Study
Authors: Hu Yishi , Lebo Zachary J. , Geerts Bart , Wang Yonggang , Hu Yazhe 
Published: August 2022

Abstract
Part I of this series presented a detailed overview of postfrontal mixed-phase clouds observed during the Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) field campaign. In Part II, we focus on a multiday (23–26 February 2018) case with the aim of understanding ice production as well as model sensitivity to ice process parameterizations using the Weather Research and Forecasting (WRF) Model. The control simulation with the Predicted Particle Properties (P3) microphysics scheme underestimates the ice content and overestimates the supercooled liquid water content, contrary to the bias common in global climate models. The simulations targeted at ice production processes show negligible sensitivity to cloud droplet number concentrations. Further, neither increasing ice nuclei particle (INP) concentrations to an unrealistic level nor adjusting it to MARCUS field estimations alone guarantees more ice production in the model. However, the simulated clouds are found to be highly sensitive to the implementation of immersion freezing, the thresholding of condensation/deposition freezing initiation, and the rime splintering process. By increasing immersion freezing of cloud droplets, relaxing thresholds for condensation/deposition freezing, or removing rime splintering thresholds, the model significantly improves its performance in producing ice. The relaxation of the immersion freezing temperature threshold to the observed cloud-top temperature suggests an in-cloud seeder–feeder mechanism. The results of this work call for an increase in observations of INP, especially over the remote Southern Ocean and at relatively high temperatures, and measurements of ice particle size distributions to better constrain ice nucleating processes in models.
Dependencies of Four Mechanisms of Secondary Ice Production on Cloud-Top Temperature in a Continental Convective Storm
Authors: Waman Deepak , Patade Sachin , Jadav Arti , Deshmukh Akash , Gupta Ashok Kumar , Phillips Vaughan T. J. , Bansemer Aaron , DeMott Paul J. 
Published: August 2022

Abstract
Various mechanisms of secondary ice production (SIP) cause multiplication of numbers of ice particle, after the onset of primary ice. A measure of SIP is the ice enhancement ratio (“IE ratio”) defined here as the ratio between number concentrations of total ice (excluding homogeneously nucleated ice) and active ice-nucleating particles (INPs). A convective line observed on 11 May 2011 over the Southern Great Plains in the Mesoscale Continental Convective Cloud Experiment (MC3E) campaign was simulated with the “Aerosol–Cloud” (AC) model. AC is validated against coincident MC3E observations by aircraft, ground-based instruments, and satellite. Four SIP mechanisms are represented in AC: the Hallett–Mossop (HM) process of rime splintering, and fragmentation during ice–ice collisions, raindrop freezing, and sublimation. The vertical profile of the IE ratio, averaged over the entire simulation, is almost uniform (102 to 103) because fragmentation in ice–ice collisions dominates at long time scales, driving the ice concentration toward a theoretical maximum. The IE ratio increases with both the updraft (HM process, fragmentation during raindrop freezing, and ice–ice collisions) and downdraft speed (fragmentation during ice–ice collisions and sublimation). As reported historically in aircraft sampling, IE ratios were predicted to peak near 103 for cloud-top temperatures close to the −12°C level, mostly due to the HM process in typically young clouds with their age less than 15 min. At higher altitudes with temperatures of −20° to −30°C, the predicted IE ratios were smaller, ranging from 10 to 102, and mainly resulted from fragmentation in ice–ice collisions.
Shallow Cumulus Entrainment Dynamics in a Sheared Environment
Authors: McMichael Lucas A. , Mechem David B. , Heus Thijs 
Published: August 2022

Abstract
Vertical wind shear has long been known to tilt convective towers and reduce thermal ascent rates. The purpose of this study is to better understand the physical mechanisms responsible for reduced ascent rates in shallow convection. In particular, the study focuses on cloud-edge mass flux to assess how shear impacts mass-flux profiles of both the ensemble and individual clouds of various depths. A compositing algorithm is used to distill large-eddy simulation (LES) output to focus on up- and down-shear cloud edges that are not influenced by complex cloud geometry or nearby clouds. A direct entrainment algorithm is used to estimate the mass flux through the cloud surface. We find that the dynamics on the up- and down-shear sides are fundamentally different, with the entrainment of environmental momentum and dilution of buoyancy being primarily responsible for the reduced down-shear ascent rates. Direct estimates of fluid flow through the cloud interface indicate a counter-shear organized flow pattern that entrains on the down-shear side and detrains on the up-shear side, resulting from the subcloud shear being lifted into the cloud layer by the updraft. In spite of organized regions of entrainment and detrainment, the overall net lateral mass flux remains unchanged with respect to the no shear run, with weak detrainment present throughout cloud depth.
Cloud Radiative Effects on MJO Development in DYNAMO
Authors: Hu Qi , Han Zihang , Wang Shuguang 
Published: August 2022

Abstract
Observed Madden–Julian oscillation (MJO) events are examined with the aid of regional model simulations to understand the role of cloud radiative effects in the MJO development. The importance of this role is demonstrated by the absence of the MJO in the model simulations that contain no cloud radiative effects. Comparisons of model simulations with and without the cloud radiative effects and observation help identify the major processes arising from those effects. Those processes develop essentially from heating in the upper troposphere due to shortwave absorption within anvil clouds in the upper troposphere and the convergence of longwave radiation in the middle to upper troposphere, with a peak at 300 hPa, during deep convection. First, that heating adds extra buoyancy and accelerates the rising motion in the upper troposphere in deep convection. The vertical acceleration in the upper troposphere creates a vacuum effect and demands for more deep convection to develop. Second, in response to that demand and required by mass balance arises the large-scale horizontal and vertical mass, moisture, and energy convergence. It strengthens deep convection and, with the feedback from continuing cloud radiative effect, creates conditions that can perpetuate deep convection and MJO development. That perpetuation does not occur however because those processes arising from the cloud radiative heating in the upper troposphere stabilize the troposphere until it supports no further deep convection. Weakening deep convection reduces cloud radiative effects. The subsequent reduction of the vacuum effect in the upper troposphere diminishes deep convection completing an MJO cycle. These results advance our understanding of the development of the MJO in the radiative–convective system over warm waters in the tropics. They show that while the embryo of intraseasonal oscillation may exist in the system its growth/development is largely dependent on cloud radiative effects and feedbacks.
Quantifying Heavy Precipitation throughout the Entire Tropical Cyclone Life Cycle
Authors: Bower Erica , Reed Kevin A. , Ullrich Paul A. , Zarzycki Colin M. , Pendergrass Angeline G. 
Published: August 2022

Abstract
Tropical cyclones (TCs) and their associated precipitation can have devastating impacts on the areas affected, with outcomes ranging from mudslides to inland flash flooding. Previous studies have used a fixed radius around the TC to isolate storm-related precipitation. One previous study instead used a dynamic radius of 8 m s−1 winds, but the wind field of the TC can deteriorate or shift quickly after landfall or the onset of extratropical transition (ET). This study uses a dynamical radius derived from the 500-hPa geopotential height in and around the TC to define TC- and post-tropical cyclone (PTC)-related heavy precipitation, allowing for the analysis of precipitation with tropical origins after the official demise of the original TC. Climatologies are constructed, indicating a maximum in TC- and PTC-related heavy precipitation in the west North Pacific and a secondary maximum in the east North Pacific. PTC-related heavy precipitation accounts for as much as 40% of the annual heavy precipitation in the northwest portion of the west North Pacific basin and 3.13% of heavy precipitation globally. We observe that the major hurricane stage contributes on average 2.6% of the global TC- and PTC-related precipitation, while the less intense but more common tropical storm stages of the TC life cycle contribute 85.7% of this observed precipitation. This analysis framework can be further extended to assess model biases and climate projections of TC and PTC precipitation.
Estimation of Daily Evaporation from Shallow Groundwater Using Empirical Models with a Temperature Coefficient
Authors: Gao Huibin , Ju Qin , Jiang Peng , Yan Wenming , Wang Wei , Fu Xiaolei , Hao Zhenchun 
Published: August 2022

Abstract
Shallow groundwater evaporation (Eg) is a major component of the hydrological cycle, especially in semiarid and arid locations. Empirical methods are commonly used to estimate Eg. However, most of these methods can only weakly represent Eg variations along the soil depth and do not consider the energy driver. In this paper, a temperature coefficient was proposed and incorporated into two preferred empirical models to characterize the impacts of soil temperature and air temperature lags on Eg. The method was evaluated using in situ daily data obtained from nonweighing bare soil lysimeters. The results indicated that the models that considered the temperature gradient variable (T) conformed to the changes in the actual Eg values with depth more appropriately than the original models, accompanied by 4.3%–8.8% accuracy improvements overall. Shallow groundwater evaporation Eg was found to be influenced by the water table depth (H), T, and pan evaporation (E0) in descending order, and strong interactions were found between H and T. Moreover, the impact of precipitation on Eg was investigated; measurements from dry days without precipitation revealed the actual Eg process, the relative errors in the cumulative Eg values derived at different depths demonstrated a positive relationship with infiltration recharge, and the errors related to precipitation induced 6.7%–8.3% Eg underestimations. These results contribute to a better understanding of evaporative losses from shallow groundwater and the typical Eg situation that occurs simultaneously with recharge, and they provide promising perspectives for corresponding integrated hydrologic modeling research.