Preoperative digital three-dimensional planning for rhinoplasty

BACKGROUND: This report describes preoperative digital planning for rhinoplasty using a new three-dimensional (3D) radiologic viewer that allows both patients and surgeons to visualize on a common monitor the 3D real aspect of the nose in its inner and outer sides. METHODS: In the period 2002 to 2008, 210 patients underwent rhinoplasty procedures in the authors' clinic. The patients were randomly divided into three groups according to the type of preoperative planning used: photos only, a simulated result by Adobe Photoshop, or the 3D radiologic viewer. The parameters evaluated included the number of patients that underwent surgery after the first consultation, the number of patients who asked for a reintervention, patient satisfaction (according to a test given to the patients 12 months postoperatively), the surgical time required for a functional intervention, and the improvement in nasal function by postoperative rhinomanometry and subjective evaluation. RESULTS: Computer-aided technologies led to a higher number of patients deciding to undergo a rhinoplasty. Simulation of the postoperative results was not as useful in the postoperative period due to the higher number of reintervention requests. CONCLUSION: The patients undergoing rhinoplasties preferred new technologies in the preoperative period. The advantages of using the 3D radiologic viewer included improved preoperative planning, reduction in intraoperative stress, a higher number of patients undergoing surgery, reduction in postoperative surgical corrections, reduction in surgical time for the functional intervention, a higher rate of improvement in nasal function, a higher percentage of postoperative satisfaction, and reduced costs

Seasonal Correction of Offshore Wind Energy Potential due to Air Density: Case of the Iberian Peninsula

A constant value of air density based on its annual average value at a given location is commonly used for the computation of the annual energy production in wind industry. Thus, the correction required in the estimation of daily, monthly or seasonal wind energy production, due to the use of air density, is ordinarily omitted in existing literature. The general method, based on the implementation of the wind speed’s Weibull distribution over the power curve of the turbine, omits it if the power curve is not corrected according to the air density of the site. In this study, the seasonal variation of air density was shown to be highly relevant for the computation of offshore wind energy potential around the Iberian Peninsula. If the temperature, pressure, and moisture are taken into account, the wind power density and turbine capacity factor corrections derived from these variations are also significant. In order to demonstrate this, the advanced Weather Research and Forecasting mesoscale Model (WRF) using data assimilation was executed in the study area to obtain a spatial representation of these corrections. According to the results, the wind power density, estimated by taking into account the air density correction, exhibits a difference of 8% between summer and winter, compared with that estimated without the density correction. This implies that seasonal capacity factor estimation corrections of up to 1% in percentage points are necessary for wind turbines mainly for summer and winter, due to air density changes.This work has been funded by the Spanish Government’s MINECO project CGL2016-76561-R (AEI/FEDER EU) and the University of the Basque Country (UPV/EHU funded project GIU17/02). The ECMWF ERA-Interim data used in this study have been obtained from the ECMWF-MARS Data Server. The authors wish to express their gratitude to the Spanish Port Authorities (Puertos del Estado) for being kind enough to provide data for this study. The computational resources used in the project were provided by I2BASQUE. The authors thank the creators of the WRF/ARW and WRFDA systems for making them freely available to the community. NOAA_OI_SST_V2 data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, through their web-site at http://www.esrl.noaa.gov/psd/ were used in this paper. National Centres for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce. 2008, updated daily. NCEP ADP Global Upper Air and Surface Weather Observations (PREPBUFR format), May 1997—continuing. Research Data Archive at the National Centre for Atmospheric Research, Computational and Information Systems Laboratory. http://rda.ucar.edu/datasets/ds337.0/ were used. All the calculations have been carried out in the framework of R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org

Global estimations of wind energy potential considering seasonal air density changes

The literature typically considers constant annual average air density when computing the wind energy potential of a given location. In this work, the recent reanalysis ERA5 is used to obtain global seasonal estimates of wind energy production that include seasonally varying air density. Thus, errors due to the use of a constant air density are quantified. First, seasonal air density changes are studied at the global scale. Then, wind power density errors due to seasonal air density changes are computed. Finally, winter and summer energy production errors due to neglecting the changes in air density are computed by implementing the power curve of the National Renewable Energy Laboratorys 5 MW turbine. Results show relevant deviations for three variables (air density, wind power density, and energy production), mainly in the middle-high latitudes (Hudson Bay, Siberia, Patagonia, Australia, etc.). Locations with variations from −6% to 6% are identified from summers to winters in the Northern Hemisphere. Additionally, simulations with the aeroelastic code FAST for the studied turbine show that instantaneous power production can be affected by greater than 20% below the rated wind speed if a day with realistically high or low air density values is compared for the same turbulent wind speed.This work was funded by the Spanish Government's MINECO project CGL2016-76561-R (AEI/FEDER EU) and the University of the Basque Country (UPV/EHU-funded project GIU17/02). The ECMWFERA-5 data used in this study were obtained from the Copernicus Climate Data Store. All the calculations were carried out in the framework of R Core Team (2016). More can be learnt about R, alanguage and an environment for statistical computing, at the website of the R Foundation for Statistical Computing, Vienna,Austria (https://www.R-project.org/)

Using 3DVAR data assimilation to measure offshore wind energy potential at different turbine heights in the West Mediterranean

In this article, offshore wind energy potential is measured around the Iberian Mediterranean coast and the Balearic Islands using the WRF meteorological model without 3DVAR data assimilation (the N simulation) and with 3DVAR data assimilation (the D simulation). Both simulations have been checked against the observations of six buoys and a spatially distributed analysis of wind based on satellite data (second version of Cross-Calibrated Multi-Platform, CCMPv2), and compared with ERA-Interim (ERAI). Three statistical indicators have been used: Pearson’s correlation, root mean square error and the ratio of standard deviations. The simulation with data assimilation provides the best fit, and it is as good as ERAI, in many cases at a 95% confidence level. Although ERAI is the best model, in the spatially distributed evaluation versus CCMPv2 the D simulation has more consistent indicators than ERAI near the buoys. Additionally, our simulation’s spatial resolution is five times higher than ERAI. Finally, regarding the estimation of wind energy potential, we have represented the annual and seasonal capacity factor maps over the study area, and our results have identified two areas of high potential to the north of Menorca and at Cabo Begur, where the wind energy potential has been estimated for three turbines at different heights according to the simulation with data assimilation.This work has been funded by the Spanish Government’s MINECO project CGL2016-76561-R (MINECO/FEDER EU), the University of theBasque Country (project GIU14/03) and the Basque Government (Elkartek 2017 INFORMAR project). SJGR is supported by a FPIPredoctoral Research Grant (MINECO, BES-2014-069977). The ECMWFERA-Interim data used in this study have been obtained from the ECMWF-MARS Data Server thanks to agreements with ECMWF and AEMET. The authors would like to express their gratitude to the Spanish Port Authorities (Puertos del Estado) for kindly providing data for thisstudy. The computational resources used in the project were providedby I2BASQUE. The authors thank the creators of the WRF/ARW and WRFDA systems for making them freely available to the community. NOAA_OI_SST_V2 data provided by the NOAA/OAR/ESRL PSD,Boulder, Colorado, USA, through their web-site athttp://www.esrl.noaa.gov/psd/was used in this paper. National Centers for Environmental Prediction/National Weather Service/NOAA/U.S.Department of Commerce. 2008, updated daily. NCEP ADP GlobalUpper Air and Surface Weather Observations (PREPBUFR format), May1997–Continuing. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory.http://rda.ucar.edu/datasets/ds337.0/were used. All thecalculations have been carried out in the framework of R Core Team(2016). R: A language and environment for statistical computing. RFoundation for Statistical Computing, Vienna, Austria. URLhttps://www.R-project.org/

Changes in the simulation of atmospheric instability over the Iberian Peninsula due to the use of 3DVAR data assimilation

The ability of two downscaling experiments to correctly simulate thermodynamic conditions over the Iberian Peninsula (IP) is compared in this paper. To do so, three parameters used to evaluate the unstable conditions in the atmosphere are evaluated: the total totals index (TT), convective available potential energy (CAPE), and convective inhibition (CIN). The Weather and Research Forecasting (WRF) model is used for the simulations. The N experiment is driven by ERA-Interim's initial and boundary conditions. The D experiment has the same configuration as N, but the 3DVAR data assimilation step is additionally run at 00:00, 06:00, 12:00, and 18:00 UTC. Eight radiosondes are available over the IP, and the vertical temperature and moisture profiles from the radiosondes provided by the University of Wyoming and the Integrated Global Radiosonde Archive (IGRA) were used to calculate three parameters commonly used to represent atmospheric instability by our own methodology using the R package aiRthermo. According to the validation, the correlation, standard deviation (SD), and root mean squared error (RMSE) obtained by the D experiment for all the variables at most of the stations are better than those for N. The different methods produce small discrepancies between the values for TT, but these are larger for CAPE and CIN due to the dependency of these quantities on the initial conditions assumed for the calculation of a lifted air parcel. Similar results arise from the seasonal analysis concerning both WRF experiments: N tends to overestimate or underestimate (depending on the parameter) the variability of the reference values of the parameters, but D is able to capture it in most of the seasons. In general, D is able to produce more reliable results due to the more realistic values of dew point temperature and virtual temperature profiles over the IP. The heterogeneity of the studied variables is highlighted in the mean maps over the IP. According to those for D, the unstable air masses are found along the entire Atlantic coast during winter, but in summer they are located particularly over the Mediterranean coast. The convective inhibition is more extended towards inland at 00:00 UTC in those areas. However, high values are also observed near the southeastern corner of the IP (near Murcia) at 12:00 UTC. Finally, no linear relationship between TT, CAPE, or CIN was found, and consequently, CAPE and CIN should be preferred for the study of the instability of the atmosphere as more atmospheric layers are employed during their calculation than for the TT index.The computational resources were provided by I2BASQUE, and the authors thank the creators of WRF/ARW and WRFDA systems. Authors also thank the anonymous reviewers for their comments, which have helped to improve the paper. Finally, most of the calculations were carried out with R (R Core Team, 2020), and the authors want to thank all the authors of the packages used for it

Antimicrobial Susceptibility Trends Observed in Urinary Pathogens Obtained From New York State

International guidelines recommend using local susceptibility data to direct empiric therapy for acute uncomplicated cystitis. We evaluated outpatient urinary isolate susceptibility trends in New York State. Nitrofurantoin had the lowest resistance prevalence whereas trimethoprim-sulfamethoxazole and fluoroquinolones had higher prevalences. This study highlights the need for local outpatient antimicrobial stewardship programs

Changes in the simulation of atmospheric instability over the Iberian Peninsula due to the use of 3DVAR data assimilation

The ability of two downscaling experiments to correctly simulate thermodynamic conditions over the Iberian Peninsula (IP) is compared in this paper. To do so, three parameters used to evaluate the unstable conditions in the atmosphere are evaluated: the total totals index (TT), convective available potential energy (CAPE), and convective inhibition (CIN). The Weather and Research Forecasting (WRF) model is used for the simulations. The N experiment is driven by ERA-Interim's initial and boundary conditions. The D experiment has the same configuration as N, but the 3DVAR data assimilation step is additionally run at 00:00, 06:00, 12:00, and 18:00 UTC. Eight radiosondes are available over the IP, and the vertical temperature and moisture profiles from the radiosondes provided by the University of Wyoming and the Integrated Global Radiosonde Archive (IGRA) were used to calculate three parameters commonly used to represent atmospheric instability by our own methodology using the R package aiRthermo. According to the validation, the correlation, standard deviation (SD), and root mean squared error (RMSE) obtained by the D experiment for all the variables at most of the stations are better than those for N. The different methods produce small discrepancies between the values for TT, but these are larger for CAPE and CIN due to the dependency of these quantities on the initial conditions assumed for the calculation of a lifted air parcel. Similar results arise from the seasonal analysis concerning both WRF experiments: N tends to overestimate or underestimate (depending on the parameter) the variability of the reference values of the parameters, but D is able to capture it in most of the seasons. In general, D is able to produce more reliable results due to the more realistic values of dew point temperature and virtual temperature profiles over the IP. The heterogeneity of the studied variables is highlighted in the mean maps over the IP. According to those for D, the unstable air masses are found along the entire Atlantic coast during winter, but in summer they are located particularly over the Mediterranean coast. The convective inhibition is more extended towards inland at 00:00 UTC in those areas. However, high values are also observed near the southeastern corner of the IP (near Murcia) at 12:00 UTC. Finally, no linear relationship between TT, CAPE, or CIN was found, and consequently, CAPE and CIN should be preferred for the study of the instability of the atmosphere as more atmospheric layers are employed during their calculation than for the TT index.</p

Pairwise Trajectory Management (PTM): Concept Description and Documentation

Pairwise Trajectory Management (PTM) is an Interval Management (IM) concept that utilizes airborne and ground-based capabilities to enable the implementation of airborne pairwise spacing capabilities in oceanic regions. The goal of PTM is to use airborne surveillance and tools to manage an "at or greater than" inter-aircraft spacing. Due to the accuracy of Automatic Dependent Surveillance-Broadcast (ADS-B) information and the use of airborne spacing guidance, the minimum PTM spacing distance will be less than distances a controller can support with current automation systems that support oceanic operations. Ground tools assist the controller in evaluating the traffic picture and determining appropriate PTM clearances to be issued. Avionics systems provide guidance information that allows the flight crew to conform to the PTM clearance issued by the controller. The combination of a reduced minimum distance and airborne spacing management will increase the capacity and efficiency of aircraft operations at a given altitude or volume of airspace. This document provides an overview of the proposed application, a description of several key scenarios, a high level discussion of expected air and ground equipment and procedure changes, a description of a NASA human-machine interface (HMI) prototype for the flight crew that would support PTM operations, and initial benefits analysis results. Additionally, included as appendices, are the following documents: the PTM Operational Services and Environment Definition (OSED) document and a companion "Future Considerations for the Pairwise Trajectory Management (PTM) Concept: Potential Future Updates for the PTM OSED" paper, a detailed description of the PTM algorithm and PTM Limit Mach rules, initial PTM safety requirements and safety assessment documents, a detailed description of the design, development, and initial evaluations of the proposed flight crew HMI, an overview of the methodology and results of PTM pilot training requirements focus group and human-in-the-loop testing activities, and the PTM Pilot Guide

Functional evaluation and testing of a newly developed Teleost’s Fish Otolith derived biocomposite coating for healthcare

Polymers such as polycaprolactone (PCL) possess biodegradability, biocompatibility and affinity with other organic media that makes them suitable for biomedical applications. In this work, a novel biocomposite coating was synthesised by mixing PCL with layers of calcium phosphate (hydroxyapatite, brushite and monetite) from a biomineral called otolith extracted from Teleost fish (Plagioscion Squamosissimus) and multiwalled carbon nanotubes in different concentrations (0.5, 1.0 and 1.5 g/L). The biocomposite coating was deposited on an osteosynthesis material Ti6Al4V by spin coating and various tests such as Fourier transformation infrared spectroscopy (FTIR), Raman spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), scratch tests, MTT reduction cytotoxicity, HOS cell bioactivity (human osteosarcoma) by alkaline phosphatase (ALP) and fluorescence microscopy were performed to comprehensively evaluate the newly developed biocoating. It was found that an increase in the concentration of carbon nanotube induced microstructural phase changes of calcium phosphate (CP) leading to the formation of brushite, monetite and hydroxyapatite. While we discovered that an increase in the concentration of carbon nanotube generally improves the adhesion of the coating with the substrate, a certain threshold exists such that the best deposition surfaces were obtained as PCL/CP/CNT 0.0 g/L and PCL/CP/CNT 0.5 g/L