bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Predictive Value of Arteriogenic Erectile Dysfunction for Coronary Artery Disease in Men
Authors: Azab Sherif Salah , El Din Hosni Hossam , El Far Taha A. , Ismail Nashaat Nabil , El Bakdady Yasser K. , Mohamed Ahmed F. 
Published: May 2018

Abstract

Background
Erectile dysfunction (ED) is assumed to be connected with vascular disease caused by endothelial dysfunction, and characterized by the incapability of the smooth muscle cells lining the arterioles to relax, therefore, inhibit vasodilatation.

Aim
To assess the predictive value of arteriogenic ED for coronary artery disease in men above the age of 40 years.

Methods
75 Patients reporting arteriogenic ED and 25 men with normal erectile function were enrolled in the study. Both patients and controls were subjected to the following investigations: lipid profile, fasting blood sugar, body mass index (BMI), waist circumference, penile duplex study, stress electrocardiography (ECG) test, International Index of Erectile Function (IIEF) Type 5 (Arabic version), and cardiovascular (CV) 10-year risk assessment using Framingham and Prospective Cardiovascular Münster (PROCAM) scoring systems.

Outcomes
We compare between the study groups regarding the interpretation of exercise testing.

Results
We observed significant increase in the mean value of age, systolic blood pressure, BMI, weight, height, and waist circumference in the cases; significant prevalence of obesity and overweight in the cases (P &lt; .001); significant increase in the mean value of total cholesterol, triglycerides (TG), and low-density lipoprotein; and decrease in mean value of high-density lipoprotein in the cases (P &lt; .001). Additionally, there was high incidence of positive stress ECG in the cases (25.3%) vs that in controls (12%), and significant difference between patients with positive stress ECG test and those with negative stress ECG test regarding their lipid profile, age, BMI, and waist circumference with higher values in positive stress ECG for total cholesterol, TG, and low-density lipoprotein, and lower value for high-density lipoprotein (P &lt; .001). According to PROCAM and Framingham scoring systems 10-year risk assessment, there was a high significant difference between the cases and control groups with a higher score in cases than the control group with 30.7% of cases having ≥ 30% risk of developing coronary heart disease, and significant positive correlations between CV risk and BMI, and negative correlations with IIEF-5 cases (P &lt; .001).

Clinical Translation
Ischemic heart disease events were higher in men with documented arteriogenic ED than those without ED.

Conclusions
All items of metabolic syndrome were investigated and analyzed and we evaluated our groups using both PROCAM and Framingham scoring system. An exercise ECG is suggested before starting treatment of vasculogenic ED at least in patients with CV risk factors.
Successful transcarotid transcatheter aortic valve replacement in a 34-kg patient with Schimke immuno-osseous dysplasia and severe biscuspid aortic stenosis
Authors: Sullivan Katie E. O’ , Griffin Alan P. , Casserly Ivan P. 
Published: May 2018

AbstractWe present the case of transcatheter aortic valve replacement in a 20-year-old woman with severe bicuspid aortic stenosis and Schmike immuno-osseous dysplasia who was unfit for surgical aortic valve replacement. Meticulous pre-procedural planning and a multidisciplinary team approach can enable successful transcatheter aortic valve replacement in complex patients with genetic syndromes.
Urban backyards as a new model of pineapple germplasm conservation
Authors: da Silva Ronilze Leite , de Souza Everton Hilo , Ledo Carlos Alberto da Silva , Pelacani Claudinéia Regina , Duarte Souza Fernanda V. 
Published: May 2018

AbstractThe conservation of pineapple in urban backyards is an innovative strategy that aims to involve city residents. A program of this nature requires careful planning and monitoring because of the involvement of people who do not have technical knowledge. This paper reports the implementation and evaluation of 30 gardens in urban backyards in Cabaceiras do Paraguaçú, Bahia, Brazil, to establish the parameters to allow creating a model for pineapple germplasm conservation cells with the collaboration of urban residents. A questionnaire was applied in two steps to people interested in participating, from which it was possible to choose and evaluate a general profile of the participants. Thirty pineapple accessions from the Active Germplasm Bank (AGB) of the Embrapa were selected for testing in the gardens. Two production cycles were considered, during which quantitative and qualitative traits of the plants and fruits were evaluated. The data were compared with the characteristics of the same accessions in the Pineapple AGB and were analysed by mixed principal component analysis. With respect to adequate maintenance, 20 gardens were well cared for until the end of the assessments, five were reasonably well tended and five were lost, due to home remodelling or lack of care by the guardians. Despite the loss of the five gardens, no accession was totally lost, thanks to the experimental design with three plants of each accession in three different gardens. The plants preserved in the gardens did not differ from those maintained by the AGB, demonstrating the effectiveness of this conservation strategy.
Weakened Lithosphere Beneath Greenland Inferred From Effective Elastic Thickness: A Hot Spot Effect?
Authors: Steffen Rebekka , Audet Pascal , Lund Björn 
Published: May 2018

AbstractThe effective elastic thickness (Te) of the lithosphere provides geophysical information about long‐term flexural strength and can be used to constrain thermorheological properties of the lithosphere. Te is typically calculated from the spectral analysis of gravity and topography data; variations in Te are, however, not well resolved in Greenland due to poor constraints on crustal structure (including crustal thickness) and complications due to ice loading. In addition, geological and geophysical constraints on the tectonic history of Greenland are sparse due to the thick ice cover. Here we use the global gravity model EIGEN‐6C4 together with a new model of the crust‐mantle boundary to obtain a high‐resolution Te map of Greenland. The distribution of Te indicates reduced strength in the lower crust and lithospheric mantle beneath southern and central Greenland, which may be due to the passage of the Iceland hot spot during the last 100 Ma. In contrast, the northern part of Greenland shows a large Te, implying mechanical coupling between crust and uppermost mantle and suggesting the existence of a cold and strong tectonic unit. In a relative sense, the distribution of Te values is consistent with estimates of lithospheric thickness based on seismic velocity models, indicating a dominantly thermal control on lithospheric structure and evolution.
Episodic Southern Ocean Heat Loss and Its Mixed Layer Impacts Revealed by the Farthest South Multiyear Surface Flux Mooring
Authors: Ogle S. E. , Tamsitt V. , Josey S. A. , Gille S. T. , Cerovečki I. , Talley L. D. , Weller R. A. 
Published: May 2018

AbstractThe Ocean Observatories Initiative air‐sea flux mooring deployed at 54.08°S, 89.67°W, in the southeast Pacific sector of the Southern Ocean, is the farthest south long‐term open ocean flux mooring ever deployed. Mooring observations (February 2015 to August 2017) provide the first in situ quantification of annual net air‐sea heat exchange from one of the prime Subantarctic Mode Water formation regions. Episodic turbulent heat loss events (reaching a daily mean net flux of −294 W/m2) generally occur when northeastward winds bring relatively cold, dry air to the mooring location, leading to large air‐sea temperature and humidity differences. Wintertime heat loss events promote deep mixed layer formation that lead to Subantarctic Mode Water formation. However, these processes have strong interannual variability; a higher frequency of 2 σ and 3 σ turbulent heat loss events in winter 2015 led to deep mixed layers (>300 m), which were nonexistent in winter 2016.
Reconstructing Depth‐Averaged Open‐Channel Flows Using Image Velocimetry and Photogrammetry
Authors: Piton Guillaume , Recking Alain , Le Coz Jérôme , Bellot Hervé , Hauet Alexandre , Jodeau Magali 
Published: May 2018

AbstractSteep streams with massive sediment supply are among the most complex systems to study, even in the laboratory. Their shallow sediment‐laden flows create self‐adjusting bed geometries that evolve rapidly. Often, morphological changes and flow processes cannot be dissociated. Because these very shallow and unstable flows cannot be equipped with measurement sensors, image analysis techniques, such as photogrammetry (e.g., structure‐from‐motion, SfM) and large‐scale particle image velocimetry (LSPIV), are interesting options for capturing the characteristics of these systems. The present work describes a complete procedure using both techniques to measure spatially distributed surface velocity and bed properties (deposit patterns, channel slope, and local roughness). The velocity data are used to assess the local flow directions along which the channel slope and roughness are extracted from the SfM digital elevation models. Fergusons “variable power equation” friction law, having been previously validated by comparison with approximately 100 local flow depth measurements, was used in a second step with the collected data to reconstruct a complete mapping of the depth‐averaged flows, thereby enabling a comprehensive analysis of the hydrogeomorphic system where shallow water equations apply. The assumptions, details, use of the friction law with roughness standard deviation rather than diameter as parameter and limitations of the procedure as well as possible sources of errors are discussed here, along with possibilities for improvements. This affordable and simple‐to‐implement procedure can provide a large amount of data, allowing for a more comprehensive analysis of complex hydraulic systems.
An Information Theory Approach to Identifying a Representative Subset of Hydro‐Climatic Simulations for Impact Modeling Studies
Authors: Pechlivanidis I.G. , Gupta H. , Bosshard T. 
Published: May 2018

AbstractUncertainties in hydro‐climatic projections are (in part) related to various components of the production chain. An ensemble of numerous projections is usually considered to characterize the overall uncertainty; however in practice a small set of scenario combinations are constructed to provide users with a subset that is manageable for decision‐making. Since projections are unavoidably uncertain, and multiple projections are typically informationally redundant to a considerable extent, it would be helpful to identify an informationally representative subset in a large model ensemble. Here a framework rooted in the information theoretic Maximum Information Minimum Redundancy concept is proposed for identifying a representative subset from an available ensemble of hydro‐climatic projections. We analyze an ensemble of 16 precipitation and temperature projections for Sweden, and use these as inputs to the HBV hydrological model to project river discharge until the mid of this century. Representative subsets are judged in terms of different statistical properties of three essential climate variables (precipitation, temperature and discharge), whilst we further assess the sensitivity of the optimized subset for different seasons and future periods. Our results indicate that a quarter to a third of the available set of projections can represent more than 80% of the total information of hydro‐climatic changes. We find that the representative subsets are sensitive to the regional hydro‐climatic characteristics and the choice of variables, seasons and periods of interest. Therefore we recommend that any selection process should not be solely driven by climatic variables but, rather, should also consider variables of the impact model.
Copula‐Based Chance‐Constrained Hydro‐Economic Optimization Model for Optimal Design of Reservoir‐Irrigation District Systems under Multiple Interdependent Sources of Uncertainty
Authors: Alizadeh Hosein , Mousavi S. Jamshid , Ponnambalam Kumaraswamy 
Published: May 2018

AbstractThis paper presents a new explicit stochastic hydro‐economic optimization model for reservoir‐irrigation district systems design affected by multiple interdependent sources of uncertainties. The model solution determines both optimal design and long‐term operation policies of the systems while accounting for uncertainties of reservoir inflow, rainfall, crop yield, crop price, and production costs. The problem is formulated as a chance‐constrained program in which the dependence structure of discrete and continuous random coefficients is accounted for using copula. In addition to design variables such as the sizing of reservoir capacity and the irrigable area, optimal reservoir operation policies and irrigation management strategies are determined. The model performance and significance is tested in the case study of Chamshir hydrosystem in Iran, consisting of Chamshir Dam and downstream irrigation districts. Various scenarios assessing baseline conditions, risk attitude, and the impacts of change in climatic inputs and upstream conditions are also evaluated. The model results are used to quantify the interrelationships and trade‐offs among optimal values of design parameters, optimal irrigation policy, decision‐makers' risk‐attitude, uncertainty levels of agro‐economic factors, and target reliability levels of meeting crop yield and water requirement. The results demonstrate that smaller sizes of the reservoir and the irrigation district and stress‐avoidance irrigation policies, rather than deficit‐irrigation policies, are preferred when the decision maker is risk‐averse and uncertainties in agro‐economic factors and reliability levels are large. Additionally, we show how the optimal cropping pattern and irrigation strategies are affected by climate change‐induced rainfall variations and the alteration of conditions upstream of the project.
Nonstationary Hydrologic Behavior in Forested Watersheds Is Mediated by Climate‐Induced Changes in Growing Season Length and Subsequent Vegetation Growth
Authors: Hwang Taehee , Martin Katherine L. , Vose James M. , Wear David , Miles Brian , Kim Yuri , Band Lawrence E. 
Published: May 2018

AbstractForested watersheds provide important ecosystem services through the provision of high quality freshwater, mitigation of floods, and maintenance of base flows. How alteration of these services under ongoing climate change is mediated by vegetation dynamics is not fully understood. Combining independent remote sensing based vegetation information and distributed hydrological modeling, we investigated the impact of climate‐induced vegetation dynamics on long‐term non‐stationary hydrologic behavior in two forested watersheds in the southern Appalachians. We found significant increases in precipitation‐runoff deficit (defined as annual precipitation minus annual runoff), equivalent to annual evapotranspiration plus storage changes, over the last three decades. This non‐stationary hydrologic behavior was significantly correlated with long‐term and interannual changes in growing season length and subsequent vegetation growth. These patterns in vegetation phenology were attributed primarily to minimum temperature regimes, which showed steeper and more consistent increases than temperature maxima. Using a distributed modeling framework, we also found that the long‐term non‐stationary hydrologic behavior could not be simulated unless full vegetation dynamics, including vegetation phenology and long‐term growth, were incorporated into the model. Incorporating seasonal vegetation dynamics also led to the improved simulation in streamflow dynamics, while its effect spread out through the following dormant seasons. Our study indicates that non‐stationary hydrologic behavior has been closely mediated by long‐term seasonal and structural forest canopy interaction with climate variables rather than directly driven by climatic variables. This study emphasizes the importance of understanding the ecosystem responses to ongoing climate change for predictions of future freshwater regimes.
A New Fully Distributed Model of Nitrate Transport and Removal at Catchment Scale
Authors: Yang Xiaoqiang , Jomaa Seifeddine , Zink Matthias , Fleckenstein Jan H. , Borchardt Dietrich , Rode Michael 
Published: May 2018

AbstractHydrological water quality models have gained wide acceptance from environmental scientists and water managers to address deterioration of surface water quality. Higher spatiotemporal accuracy of such models is increasingly required for better understanding the functional heterogeneity of catchments and improving management decisions at different governance levels. However, balancing spatial representation and model complexity remains challenging. We present a new flexibly designed, fully distributed nitrate transport and removal model (mHM‐Nitrate) at catchment scale. The model was developed mainly based on the mesoscale Hydrological Model (mHM) and the Hydrological Predictions for the Environment (HYPE) model. The mHM‐Nitrate model was tested in the Selke catchment (Central Germany), which is characterized by heterogeneous physiographic and land‐use conditions, using adequate observed hydrological and nitrate data at three nested gauging stations. Long term (1997–2015) daily simulations showed that the model well reproduced the seasonal dynamics of biweekly nitrate observations in forested, agricultural and urban areas. High‐frequency measurements (2010‐2015) were additionally used to validate model performance of simulating short‐term changes in stream‐water concentrations that reflect changes in runoff partitioning and event‐based dilution effects. Uncertainty analysis confirmed the model's robustness. Moreover, model calculations showed that mean terrestrial nitrate input/output (in total 105 kg ha−1 yr−1) and in‐stream removal (8% of mean nitrate load) were in comparable ranges with literature, respectively. The new mHM‐Nitrate model is capable of providing detailed spatial information on nitrate concentrations and fluxes, which can motivate more specific catchment investigations on nitrate transport processes and provide guidance on spatially differentiated agricultural practices and measures.
Using Sensor Data to Dynamically Map Large‐Scale Models to Site‐Scale Forecasts: A Case Study Using the National Water Model
Authors: Fries Kevin J. , Kerkez Branko 
Published: May 2018

AbstractThere has been an explosive growth in the ability to model large water systems. While these models are effective at routing water across massive scales, they do not yet forecast the street‐level information desired by local decision makers. Simultaneously, the increasing affordability of sensors has made it possible for even small communities to measure the state of their watersheds. However, these real‐time measurements are often not attached to a predictive model, thus making them less useful for applications like flood warnings. In this paper, we ask the question: how can highly localized forecasts be generated by fusing site‐scale sensor measurements with outputs from large‐scale models? Rather than altering the larger physical model, our approach uses the outputs of the unmodified model as the inputs to a dynamical system. To evaluate the approach, a case study is carried out across the U.S. state of Iowa using publicly available measurements from over 180 water level sensors and outputs from the National Water Model. The approach performs well across a third of the studied sites, as quantified by a high normalized root mean squared error. A performance classification is carried out based on Principal Component Analysis and Random Forests. We discuss how these results will enable stakeholders with local measurements to quickly benefit from large‐scale models without needing to run or modify the models themselves. The results are also placed into a broader sensor‐placement context to provide guidance on how investments into local measurements can be made to maximize predictive benefits.
New Insights on Coastal Foredune Growth: The Relative Contributions of Marine and Aeolian Processes
Authors: Cohn Nicholas , Ruggiero Peter , de Vries Sierd , Kaminsky George M. 
Published: May 2018

AbstractCoastal foredune growth is typically associated with aeolian sediment transport processes, while foredune erosion is associated with destructive marine processes. New data sets collected at a high energy, dissipative beach suggest that total water levels in the collision regime can cause dunes to accrete—requiring a paradigm shift away from considering collisional wave impacts as unconditionally erosional. From morphologic change data sets, it is estimated that marine processes explain between 9% and 38% of annual dune growth with aeolian processes accounting for the remaining 62% to 91%. The largest wind‐driven dune growth occurs during the winter, in response to high wind velocities, but out of phase with summertime beach growth via intertidal sandbar welding. The lack of synchronization between maximum beach sediment supply and wind‐driven dune growth indicates that aeolian transport at this site is primarily transport, rather than supply, limited, likely due to a lack of fetch limitations.
The Influence of Internal Atmospheric Variability on the Ionosphere Response to a Geomagnetic Storm
Authors: Pedatella N. M. , Liu H.‐L. 
Published: May 2018

AbstractThe Whole Atmosphere Community Climate Model eXtended is used to investigate the extent to which neglecting the realistic day‐to‐day lower atmospheric variability introduces uncertainty in the ionosphere response to an idealized geomagnetic storm. A 10‐member ensemble is generated by adding small temperature perturbations in the lower atmosphere 30 days prior to the imposed geomagnetic storm. Chaotic divergence, and internal atmospheric variability, leads to the geomagnetic storm occurring under an arbitrarily different, though climatically similar, atmospheric state for each ensemble member. The intra‐ensemble variability, which we characterize by the ensemble standard deviation, of the day‐to‐day change in total electron content is generally ∼10%–20% during geomagnetically quiet time. During an idealized storm with a Kp of 7 the ensemble standard deviation of the change in total electron content increases to ∼20%–40% at low and middle latitudes, with localized regions exceeding 100%. Examination of individual ensemble members illustrates that they all capture the same large‐scale features of the storm time changes in the ionosphere but can exhibit notable (50%) differences regionally, especially during later stages of the storm. The results thus demonstrate that in order to accurately capture smaller‐scale features of the upper atmosphere response to geomagnetic storms, it is necessary to include the effects of lower atmosphere variability.