Short- and long-term changes in corneal aberrations and axial length induced by orthokeratology in children are not correlated

PURPOSE: To assess the correlation between changes in corneal aberrations and the 2-year change in axial length in children fitted with orthokeratology (OK) contact lenses. METHODS: Thirty-one subjects 6 to 12 years of age and with myopia −0.75 to −4.00DS and astigmatism ≤1.00DC were fitted with OK. Measurements of axial length and corneal topography were taken at regular intervals over a 2-year period. Corneal topography at baseline and after 3 and 24 months of OK lens wear was used to derive higher-order corneal aberrations (HOA) that were correlated with OK-induced axial length changes at 2 years. RESULTS: Significant changes in C3, C4, C4, root mean square (RMS) secondary astigmatism and fourth and total HOA were found with both 3 and 24 months of OK lens wear in comparison with baseline (all P0.05). Coma angle of orientation changed significantly pre-OK in comparison with 3 and 24 months post-OK as well as secondary astigmatism angle of orientation pre-OK in comparison with 24 months post-OK (all P0.05). DISCUSSION: Short-term and long-term OK lens wear induces significant changes in corneal aberrations that are not significantly correlated with changes in axial elongation after 2-years.

Differences between younger and older adults in the structure of suicidal intent and its correlates

OBJECTIVE: To analyze differences in the variables associated with severity of suicidal intent and in the main factors associated with intent when comparing younger and older adults. DESIGN: Observational, descriptive cross-sectional study. SETTING: Four general hospitals in Madrid, Spain. PARTICIPANTS: Eight hundred seventy suicide attempts by 793 subjects split into two groups: 18-54 year olds and subjects older than 55 years. MEASUREMENTS: The authors tested the factorial latent structure of suicidal intent through multigroup confirmatory factor analysis for categorical outcomes and performed statistical tests of invariance across age groups using the DIFFTEST procedure. Then, they tested a multiple indicators-multiple causes (MIMIC) model including different covariates regressed on the latent factor "intent" and performed two separate MIMIC models for younger and older adults to test for differential patterns. RESULTS: Older adults had higher suicidal intent than younger adults (z = 2.63, p = 0.009). The final model for the whole sample showed a relationship of intent with previous attempts, support, mood disorder, personality disorder, substance-related disorder, and schizophrenia and other psychotic disorders. The model showed an adequate fit (chi²[12] = 22.23, p = 0.035; comparative fit index = 0.986; Tucker-Lewis index = 0.980; root mean square error of approximation = 0.031; weighted root mean square residual = 0.727). All covariates had significant weights in the younger group, but in the older group, only previous attempts and mood disorders were significantly related to intent severity. CONCLUSIONS: The pattern of variables associated with suicidal intent varies with age. Recognition, and treatment of geriatric depression may be the most effective measure to prevent suicidal behavior in older adults.

A population dynamical model of Operophtera brumata, L. extended by climatic factors

Setting out from the database of Operophtera brumata, L. in between 1973 and 2000 due to the Light Trap Network in Hungary, we introduce a simple theta-logistic population dynamical model based on endogenous and exogenous factors, only. We create an indicator set from which we can choose some elements with which we can improve the fitting results the most effectively. Than we extend the basic simple model with additive climatic factors. The parameter optimization is based on the minimized root mean square error. The best model is chosen according to the Akaike Information Criterion. Finally we run the calibrated extended model with daily outputs of the regional climate model RegCM3.1, regarding 1961-1990 as reference period and 2021-2050 with 2071-2100 as future predictions. The results of the three time intervals are fitted with Beta distributions and compared statistically. The expected changes are discussed.

Thermodynamic description and phase transformation of highly symmetrical monoatomic structures

Based on theoretical considerations an explanation for the temperature dependence of the thermal expansion and the bulk modulus is proposed. A new equation state is also derived. Additionally a physical explanation for the latent heat of fusion is presented. These theoretical predictions are tested against experiments on highly symmetrical monatomic structures. ^ The volume is not an independent variable and must be broken down into its fundamental components when the relationships to the pressure and temperature are defined. Using zero pressure and temperature reference frame, the initial parameters, volume at zero pressure and temperature[V°], bulk modulus at zero temperature [K°] and volume coefficient of thermal expansion at zero pressure[α°] are defined. ^ The new derived EoS is tested against the experiments on perovskite and epsilon iron. The Root-mean-square-deviations (RMSD) of the residuals of the molar volume, pressure, and temperature are in the range of the uncertainty of the experiments. ^ Separating the experiments into 200 K ranges, the new EoS was compared to the most widely used finite strain, interatomic potential, and empirical isothermal EoSs such as the Burch-Murnaghan, the Vinet, and the Roy-Roy respectively. Correlation coefficients, RMSD's of the residuals, and Akaike Information Criteria were used for evaluating the fitting. Based on these fitting parameters, the new p-V-T EoS is superior in every temperature range relative to the investigated conventional isothermal EoS. ^ The new EoS for epsilon iron reproduces the preliminary-reference earth-model (PREM) densities at 6100-7400 K indicating that the presence of light elements might not be necessary to explain the Earth's inner core densities. ^ It is suggested that the latent heat of fusion supplies the energy required for overcoming on the viscous drag resistance of the atoms. The calculated energies for melts formed from highly symmetrical packing arrangements correlate very well with experimentally determined latent heat values. ^ The optical investigation of carhonado-diamond is also part of the dissertation. The collected first complete infrared FTIR absorption spectra for carhonado-diamond confirm the interstellar origin for the most enigmatic diamonds known as carbonado. ^

An improved framework for dynamic origin-destination (O-D) matrix estimation

This dissertation aims to improve the performance of existing assignment-based dynamic origin-destination (O-D) matrix estimation models to successfully apply Intelligent Transportation Systems (ITS) strategies for the purposes of traffic congestion relief and dynamic traffic assignment (DTA) in transportation network modeling. The methodology framework has two advantages over the existing assignment-based dynamic O-D matrix estimation models. First, it combines an initial O-D estimation model into the estimation process to provide a high confidence level of initial input for the dynamic O-D estimation model, which has the potential to improve the final estimation results and reduce the associated computation time. Second, the proposed methodology framework can automatically convert traffic volume deviation to traffic density deviation in the objective function under congested traffic conditions. Traffic density is a better indicator for traffic demand than traffic volume under congested traffic condition, thus the conversion can contribute to improving the estimation performance. The proposed method indicates a better performance than a typical assignment-based estimation model (Zhou et al., 2003) in several case studies. In the case study for I-95 in Miami-Dade County, Florida, the proposed method produces a good result in seven iterations, with a root mean square percentage error (RMSPE) of 0.010 for traffic volume and a RMSPE of 0.283 for speed. In contrast, Zhou's model requires 50 iterations to obtain a RMSPE of 0.023 for volume and a RMSPE of 0.285 for speed. In the case study for Jacksonville, Florida, the proposed method reaches a convergent solution in 16 iterations with a RMSPE of 0.045 for volume and a RMSPE of 0.110 for speed, while Zhou's model needs 10 iterations to obtain the best solution, with a RMSPE of 0.168 for volume and a RMSPE of 0.179 for speed. The successful application of the proposed methodology framework to real road networks demonstrates its ability to provide results both with satisfactory accuracy and within a reasonable time, thus establishing its potential usefulness to support dynamic traffic assignment modeling, ITS systems, and other strategies.

Multi-temporal monitoring of wetland water levels in the Florida Everglades using interferometric synthetic aperture radar (InSAR)

Interferometric synthetic aperture radar (InSAR) techniques can successfully detect phase variations related to the water level changes in wetlands and produce spatially detailed high-resolution maps of water level changes. Despite the vast details, the usefulness of the wetland InSAR observations is rather limited, because hydrologists and water resources managers need information on absolute water level values and not on relative water level changes. We present an InSAR technique called Small Temporal Baseline Subset (STBAS) for monitoring absolute water level time series using radar interferograms acquired successively over wetlands. The method uses stage (water level) observation for calibrating the relative InSAR observations and tying them to the stage's vertical datum. We tested the STBAS technique with two-year long Radarsat-1 data acquired during 2006–2008 over the Water Conservation Area 1 (WCA1) in the Everglades wetlands, south Florida (USA). The InSAR-derived water level data were calibrated using 13 stage stations located in the study area to generate 28 successive high spatial resolution maps (50 m pixel resolution) of absolute water levels. We evaluate the quality of the STBAS technique using a root mean square error (RMSE) criterion of the difference between InSAR observations and stage measurements. The average RMSE is 6.6 cm, which provides an uncertainty estimation of the STBAS technique to monitor absolute water levels. About half of the uncertainties are attributed to the accuracy of the InSAR technique to detect relative water levels. The other half reflects uncertainties derived from tying the relative levels to the stage stations' datum.

Correspondence of historic salinity fluctuations in Florida Bay, USA, to atmospheric variability and anthropogenic changes

Florida Bay is a highly dynamic estuary that exhibits wide natural fluctuations in salinity due to changes in the balance of precipitation, evaporation and freshwater runoff from the mainland. Rapid and large-scale modification of freshwater flow and construction of transportation conduits throughout the Florida Keys during the late nineteenth and twentieth centuries reshaped water circulation and salinity patterns across the ecosystem. In order to determine long-term patterns in salinity variation across the Florida Bay estuary, we used a diatom-based salinity transfer function to infer salinity within 3.27 ppt root mean square error of prediction from diatom assemblages from four ~130 year old sediment records. Sites were distributed along a gradient of exposure to anthropogenic shifts in the watershed and salinity. Precipitation was found to be the primary driver influencing salinity fluctuations over the entire record, but watershed modifications on the mainland and in the Florida Keys during the late-1800s and 1900s were the most likely cause of significant shifts in baseline salinity. The timing of these shifts in the salinity baseline varies across the Bay: that of the northeastern coring location coincides with the construction of the Florida Overseas Railway (AD 1906–1916), while that of the east-central coring location coincides with the drainage of Lake Okeechobee (AD 1881–1894). Subsequent decreases occurring after the 1960s (east-central region) and early 1980s (southwestern region) correspond to increases in freshwater delivered through water control structures in the 1950s–1970s and again in the 1980s. Concomitant increases in salinity in the northeastern and south-central regions of the Bay in the mid-1960s correspond to an extensive drought period and the occurrence of three major hurricanes, while the drop in the early 1970s could not be related to any natural event. This paper provides information about major factors influencing salinity conditions in Florida Bay in the past and quantitative estimates of the pre- and post-South Florida watershed modification salinity levels in different regions of the Bay. This information should be useful for environmental managers in setting restoration goals for the marine ecosystems in South Florida, especially for Florida Bay.

Compilation of planktonic foraminiferal census counts from the Southern Hemisphere Oceans

We present an improved database of planktonic foraminiferal census counts from the Southern Hemisphere Oceans (SHO) from 15°S to 64°S. The SHO database combines 3 existing databases. Using this SHO database, we investigated dissolution biases that might affect faunal census counts. We suggest a depth/[DCO3]2- threshold of ~3800 m/[DCO3]2- = ~-10 to -5 µmol/kg for the Pacific and Indian Oceans, and ~4000 m/[DCO3]2- = ~0 to 10 µmol/kg for the Atlantic Ocean, under which core-top assemblages can be affected by dissolution and are less reliable for paleo-sea surface temperature (SST) reconstructions. We removed all core-tops beyond these thresholds from the SHO database. This database has 598 core-tops and is able to reconstruct past SST variations from 2° to 25.5°C, with a root mean square error of 1.00°C, for annual temperatures. To inspect dissolution affects SST reconstruction quality, we tested the data base with two "leave-one-out" tests, with and without the deep core-tops. We used this database to reconstruct Summer SST (SSST) over the last 20 ka, using the Modern Analog Technique method, on the Southeast Pacific core MD07-3100. This was compared to the SSST reconstructed using the 3 databases used to compile the SHO database. Thus showing that the reconstruction using the SHO database is more reliable, as its dissimilarity values are the lowest. The most important aspect here is the importance of a bias-free, geographic-rich, database. We leave this dataset open-ended to future additions; the new core-tops must be carefully selected, with their chronological frameworks, and evidence of dissolution assessed.

Efeito do treinamento muscular inspiratório com diferentes cargas na força e função de músculos respiratórios

Background: The inspiratory muscle training (IMT) has been considered an option in reversing or preventing decrease in respiratory muscle strength, however, little is known about the adaptations of these muscles arising from the training with charge. Objectives: To investigate the effect of IMT on the diaphragmatic muscle strength and function neural and structural adjustment of diaphragm in sedentary young people, compare the effects of low intensity IMT with moderate intensity IMT on the thickness, mobility and electrical activity of diaphragm and in inspiratory muscles strength and establish a protocol for conducting a systematic review to evaluate the effects of respiratory muscle training in children and adults with neuromuscular diseases. Materials and Methods: A randomized, double-blind, parallel-group, controlled trial, sample of 28 healthy, both sexes, and sedentary young people, divided into two groups: 14 in the low load training group (G10%) and 14 in the moderate load training group (G55%). The volunteers performed for 9 weeks a home IMT protocol with POWERbreathe®. The G55% trained with 55% of maximal inspiratory pressure (MIP) and the G10% used a charge of 10% of MIP. The training was conducted in sessions of 30 repetitions, twice a day, six days per week. Every two weeks was evaluated MIP and adjusted the load. Volunteers were submitted by ultrasound, surface electromyography, spirometry and manometer before and after IMT. Data were analyzed by SPSS 20.0. Were performed Student's t-test for paired samples to compare diaphragmatic thickness, MIP and MEP before and after IMT protocol and Wilcoxon to compare the RMS (root mean square) and median frequency (MedF) values also before and after training protocol. They were then performed the Student t test for independent samples to compare mobility and diaphragm thickness, MIP and MEP between two groups and the Mann-Whitney test to compare the RMS and MedF values also between the two groups. Parallel to experimental study, we developed a protocol with support from the Cochrane Collaboration on IMT in people with neuromuscular diseases. Results: There was, in both groups, increased inspiratory muscle strength (P <0.05) and expiratory in G10% (P = 0.009) increase in RMS and thickness of relaxed muscle in G55% (P = 0.005; P = 0.026) and there was no change in the MedF (P> 0.05). The comparison between two groups showed a difference in RMS (P = 0.04) and no difference in diaphragm thickness and diaphragm mobility and respiratory muscle strength. Conclusions: It was identified increased neural activity and diagrammatic structure with consequent increase in respiratory muscle strength after the IMT with moderate load. IMT with load of 10% of MIP cannot be considered as a placebo dose, it increases the inspiratory muscle strength and IMT with moderate intensity is able to enhance the recruitment of muscle fibers of diaphragm and promote their hypertrophy. The protocol for carrying out the systematic review published in The Cochrane Library.

Diatom abundance in surface sediments of the Southern Ocean

Based on the quantitative analysis of diatom assemblages preserved in 274 surface sediment samples recovered in the Pacific, Atlantic and western Indian sectors of the Southern Ocean we have defined a new reference database for quantitative estimation of late-middle Pleistocene Antarctic sea ice fields using the transfer function technique. The Detrended Canonical Analysis (DCA) of the diatom data set points to a unimodal distribution of the diatom assemblages. Canonical Correspondence Analysis (CCA) indicates that winter sea ice (WSI) but also summer sea surface temperature (SSST) represent the most prominent environmental variables that control the spatial species distribution. To test the applicability of transfer functions for sea ice reconstruction in terms of concentration and occurrence probability we applied four different methods, the Imbrie and Kipp Method (IKM), the Modern Analog Technique (MAT), Weighted Averaging (WA), and Weighted Averaging Partial Least Squares (WAPLS), using logarithm-transformed diatom data and satellite-derived (1981-2010) sea ice data as a reference. The best performance for IKM results was obtained using a subset of 172 samples with 28 diatom taxa/taxa groups, quadratic regression and a three-factor model (IKM-D172/28/3q) resulting in root mean square errors of prediction (RMSEP) of 7.27% and 11.4% for WSI and summer sea ice (SSI) concentration, respectively. MAT estimates were calculated with different numbers of analogs (4, 6) using a 274-sample/28-taxa reference data set (MAT-D274/28/4an, -6an) resulting in RMSEP's ranging from 5.52% (4an) to 5.91% (6an) for WSI as well as 8.93% (4an) to 9.05% (6an) for SSI. WA and WAPLS performed less well with the D274 data set, compared to MAT, achieving WSI concentration RMSEP's of 9.91% with WA and 11.29% with WAPLS, recommending the use of IKM and MAT. The application of IKM and MAT to surface sediment data revealed strong relations to the satellite-derived winter and summer sea ice field. Sea ice reconstructions performed on an Atlantic- and a Pacific Southern Ocean sediment core, both documenting sea ice variability over the past 150,000 years (MIS 1 - MIS 6), resulted in similar glacial/interglacial trends of IKM and MAT-based sea-ice estimates. On the average, however, IKM estimates display smaller WSI and slightly higher SSI concentration and probability at lower variability in comparison with MAT. This pattern is a result of different estimation techniques with integration of WSI and SSI signals in one single factor assemblage by applying IKM and selecting specific single samples, thus keeping close to the original diatom database and included variability, by MAT. In contrast to the estimation of WSI, reconstructions of past SSI variability remains weaker. Combined with diatom-based estimates, the abundance and flux pattern of biogenic opal represents an additional indication for the WSI and SSI extent.

Determinação de teor de biodieseis de algodão e pinhão manso em misturas com diesel usando espectroscopia no infravermelho médio e quadrados mínimos parciais

Biodiesel is a renewable fuel derived from vegetable oils or animal fats, which can be a total or partial substitute for diesel. Since 2005, this fuel was introduced in the Brazilian energy matrix through Law 11.097 that determines the percentage of biodiesel added to diesel oil as well as monitoring the insertion of this fuel in market. The National Agency of Petroleum, Natural Gas and Biofuels (ANP) establish the obligation of adding 7% (v/v) of biodiesel to diesel commercialized in the country, making crucial the analytical control of this content. Therefore, in this study were developed and validated methodologies based on the use of Mid Infrared Spectroscopy (MIR) and Multivariate Calibration by Partial Least Squares (PLS) to quantify the methyl and ethyl biodiesels content of cotton and jatropha in binary blends with diesel at concentration range from 1.00 to 30.00% (v/v), since this is the range specified in standard ABNT NBR 15568. The biodiesels were produced from two routes, using ethanol or methanol, and evaluated according to the parameters: oxidative stability, water content, kinematic viscosity and density, presenting results according to ANP Resolution No. 45/2014. The built PLS models were validated on the basis of ASTM E1655-05 for Infrared Spectroscopy and Multivariate Calibration and ABNT NBR 15568, with satisfactory results due to RMSEP (Root Mean Square Error of Prediction) values below 0.08% (<0.1%), correlation coefficients (R) above 0.9997 and the absence of systematic error (bias). Therefore, the methodologies developed can be a promising alternative in the quality control of this fuel.

Numerical Simulations for the Design of Novel Integrated Parallel Reception, Excitation, and Shimming (iPRES) Coil Arrays

Magnetic field inhomogeneity results in image artifacts including signal loss, image blurring and distortions, leading to decreased diagnostic accuracy. Conventional multi-coil (MC) shimming method employs both RF coils and shimming coils, whose mutual interference induces a tradeoff between RF signal-to-noise (SNR) ratio and shimming performance. To address this issue, RF coils were integrated with direct-current (DC) shim coils to shim field inhomogeneity while concurrently emitting and receiving RF signal without being blocked by the shim coils. The currents applied to the new coils, termed iPRES (integrated parallel reception, excitation and shimming), were optimized in the numerical simulation to improve the shimming performance. The objectives of this work is to offer a guideline for designing the optimal iPRES coil arrays to shim the abdomen.

In this thesis work, the main field () inhomogeneity was evaluated by root mean square error (RMSE). To investigate the shimming abilities of iPRES coil arrays, a set of the human abdomen MRI data was collected for the numerical simulations. Thereafter, different simplified iPRES(N) coil arrays were numerically modeled, including a 1-channel iPRES coil and 8-channel iPRES coil arrays. For 8-channel iPRES coil arrays, each RF coil was split into smaller DC loops in the x, y and z direction to provide extra shimming freedom. Additionally, the number of DC loops in a RF coil was increased from 1 to 5 to find the optimal divisions in z direction. Furthermore, switches were numerically implemented into iPRES coils to reduce the number of power supplies while still providing similar shimming performance with equivalent iPRES coil arrays.

The optimizations demonstrate that the shimming ability of an iPRES coil array increases with number of DC loops per RF coil. Furthermore, the z direction divisions tend to be more effective in reducing field inhomogeneity than the x and y divisions. Moreover, the shimming performance of an iPRES coil array gradually reach to a saturation level when the number of DC loops per RF coil is large enough. Finally, when switches were numerically implemented in the iPRES(4) coil array, the number of power supplies can be reduced from 32 to 8 while keeping the shimming performance similar to iPRES(3) and better than iPRES(1). This thesis work offers a guidance for the designs of iPRES coil arrays.

Retrieval of grassland biophysical parameters using multitemporal optical and radar satellite data

The amount and quality of available biomass is a key factor for the sustainable livestock industry and agricultural management related decision making. Globally 31.5% of land cover is grassland while 80% of Ireland’s agricultural land is grassland. In Ireland, grasslands are intensively managed and provide the cheapest feed source for animals. This dissertation presents a detailed state of the art review of satellite remote sensing of grasslands, and the potential application of optical (Moderate–resolution Imaging Spectroradiometer (MODIS)) and radar (TerraSAR-X) time series imagery to estimate the grassland biomass at two study sites (Moorepark and Grange) in the Republic of Ireland using both statistical and state of the art machine learning algorithms. High quality weather data available from the on-site weather station was also used to calculate the Growing Degree Days (GDD) for Grange to determine the impact of ancillary data on biomass estimation. In situ and satellite data covering 12 years for the Moorepark and 6 years for the Grange study sites were used to predict grassland biomass using multiple linear regression, Neuro Fuzzy Inference Systems (ANFIS) models. The results demonstrate that a dense (8-day composite) MODIS image time series, along with high quality in situ data, can be used to retrieve grassland biomass with high performance (R2 = 0:86; p < 0:05, RMSE = 11.07 for Moorepark). The model for Grange was modified to evaluate the synergistic use of vegetation indices derived from remote sensing time series and accumulated GDD information. As GDD is strongly linked to the plant development, or phonological stage, an improvement in biomass estimation would be expected. It was observed that using the ANFIS model the biomass estimation accuracy increased from R2 = 0:76 (p < 0:05) to R2 = 0:81 (p < 0:05) and the root mean square error was reduced by 2.72%. The work on the application of optical remote sensing was further developed using a TerraSAR-X Staring Spotlight mode time series over the Moorepark study site to explore the extent to which very high resolution Synthetic Aperture Radar (SAR) data of interferometrically coherent paddocks can be exploited to retrieve grassland biophysical parameters. After filtering out the non-coherent plots it is demonstrated that interferometric coherence can be used to retrieve grassland biophysical parameters (i. e., height, biomass), and that it is possible to detect changes due to the grass growth, and grazing and mowing events, when the temporal baseline is short (11 days). However, it not possible to automatically uniquely identify the cause of these changes based only on the SAR backscatter and coherence, due to the ambiguity caused by tall grass laid down due to the wind. Overall, the work presented in this dissertation has demonstrated the potential of dense remote sensing and weather data time series to predict grassland biomass using machine-learning algorithms, where high quality ground data were used for training. At present a major limitation for national scale biomass retrieval is the lack of spatial and temporal ground samples, which can be partially resolved by minor modifications in the existing PastureBaseIreland database by adding the location and extent ofeach grassland paddock in the database. As far as remote sensing data requirements are concerned, MODIS is useful for large scale evaluation but due to its coarse resolution it is not possible to detect the variations within the fields and between the fields at the farm scale. However, this issue will be resolved in terms of spatial resolution by the Sentinel-2 mission, and when both satellites (Sentinel-2A and Sentinel-2B) are operational the revisit time will reduce to 5 days, which together with Landsat-8, should enable sufficient cloud-free data for operational biomass estimation at a national scale. The Synthetic Aperture Radar Interferometry (InSAR) approach is feasible if there are enough coherent interferometric pairs available, however this is difficult to achieve due to the temporal decorrelation of the signal. For repeat-pass InSAR over a vegetated area even an 11 days temporal baseline is too large. In order to achieve better coherence a very high resolution is required at the cost of spatial coverage, which limits its scope for use in an operational context at a national scale. Future InSAR missions with pair acquisition in Tandem mode will minimize the temporal decorrelation over vegetation areas for more focused studies. The proposed approach complements the current paradigm of Big Data in Earth Observation, and illustrates the feasibility of integrating data from multiple sources. In future, this framework can be used to build an operational decision support system for retrieval of grassland biophysical parameters based on data from long term planned optical missions (e. g., Landsat, Sentinel) that will ensure the continuity of data acquisition. Similarly, Spanish X-band PAZ and TerraSAR-X2 missions will ensure the continuity of TerraSAR-X and COSMO-SkyMed.