Invazívne mykotické infekcie predstavujú závažnú infekčnú komplikáciu imunokompromitovaných pacientov. V porovnaní s bakteriálnymi infekciami je ich výskyt menej častý, na druhú stranu mortalita s nimi spojená je výrazne vyššia než je tomu u infekcií bakteriálnych. Posledné dve desaťročia priniesli významné zmeny v epidemiológii invazívnych mykóz a behom posledných niekoľkých rokov došlo k značným pokrokom v diagnostike a liečbe., Invasive fungal infections are serious life-threatening complication in immunocompromised patients. They are rare in comparison with bacterial infection but attributable mortality is higher. Last two decades brought significant changes in epidemiology of invasive fungal diseases and the last few years brought much progress in diagnostics and treatment., Martina Tošková, Jana Winterová, Iva Kocmanová, Zdeněk Ráčil, and Literatura
Global climate change is projected to continue and result in prolonged and more intense droughts, which can
increase soil water repellency (SWR). To be able to estimate the consequences of SWR on vadose zone hydrology, it is
important to determine soil hydraulic properties (SHP). Sequential modeling using HYDRUS (2D/3D) was performed on
an experimental field site with artificially imposed drought scenarios (moderately M and severely S stressed) and a control
plot. First, inverse modeling was performed for SHP estimation based on water and ethanol infiltration experimental data, followed by model validation on one selected irrigation event. Finally, hillslope modeling was performed to assess water balance for 2014. Results suggest that prolonged dry periods can increase soil water repellency. Inverse modeling was successfully performed for infiltrating liquids, water and ethanol, with R2 and model efficiency (E) values both > 0.9. SHP derived from the ethanol measurements showed large differences in van Genuchten-Mualem (VGM) parameters for the M and S plots compared to water infiltration experiments. SWR resulted in large saturated hydraulic conductivity (Ks) decrease on the M and S scenarios. After validation of SHP on water content measurements during a selected irrigation event, one year simulations (2014) showed that water repellency increases surface runoff in non-structured soils at hillslopes.
An accurate representation of reality in numerical variably-saturated flow models requires reliable estimates of necessary model parameters. Inverse modeling seeks to estimate parameters such as the saturated and residual water contents, the saturated hydraulic conductivity, the shape parameters of the soil hydraulic functions, using easily attainable observations of actual or cumulative water fluxes, pressure heads, water contents, and concentrations. The inverse procedure usually combines the nonlinear leastsquares-based (SSQ) parameter optimization method with a numerical solution of the variably-saturated flow and transport equations. The SSQ-based inverse method is however sensitive to outliers. A novel Squared ε-Insensitive Loss Function (SILF) approach is introduced in this study. The SILF approach is inspired by the ε-insensitive loss function proposed by Vapnik (1995). The objective function used in the SILF approach is similar to the least-squares objective function, except that it penalizes only for errors greater than a certain predefined acceptable error term ε. The SILF approach shows an improved performance over the SSQ approach in estimating the soil hydraulic parameters. Apart from providing robust estimates of the soil hydraulic parameters, the SILF approach also gives an approximation of the relative measurement error during sampling. and Presná reprezentácia skutočností v numerických modeloch prúdenia vo vodou nenasýtenej pôde vyžaduje spoľahlivé určenie potrebných parametrov modelu. Inverzným modelovaním sa snažíme o určenie takých parametrov, ako sú reziduálna vlhkosť pôdy, nasýtená hydraulická vodivosť, tvarové parametre hydraulických funkcií pôdy, využijúc ľahko realizovateľné pozorovania momentálnych alebo kumulatívnych tokov vody, tlakových výšok, vlhkostí pôdy a koncentrácií rozpustených látok. Inverzná procedúra obyčajne kombinuje nelineárnu optimalizáciu parametrov založenú na metóde najmenších štvorcov (SSQ) s numerickým riešením transportných rovníc vo vodou nenasýtenej pôde. Táto metóda (SSQ) je však citlivá na náhodné chyby. Nová, necitlivostná stratová funkcia s necitlivosťou ε(SILF), použitá v tejto štúdii, bola inšpirovaná návrhom publikovaným Vapnikom (1995). Optimalizovaná funkcia použitá v prístupe SILF je podobná tej, ktorá sa používa v metóde najmenších štvorcov s tou výnimkou, že táto penalizuje len chyby väčšie ako je určitá preddefinovaná akceptovateľná chyba ε. Pri určovaní hydraulických parametrov pôdy táto metóda SILF preukázala svoje prednosti pred prístupom SSQ. Okrem toho, že metóda SILF dáva robustné odhady hydraulických parametrov pôdy, umožňuje tiež aproximáciu relatívnych chýb merania počas odberu vzoriek.
This paper investigates the impact of surface soil moisture assimilation on the estimation of both parameters and states in the Soil and Water Assessment Tool (SWAT) model using the ensemble Kalman filter (EnKF) method in upper Huai River basin. The investigation is carried out through a series of synthetic experiments and real world tests using a merged soil moisture product (ESA CCI SM) developed by the European Space Agency, and considers both the joint state-parameter updating and only state updating schemes. The synthetic experiments show that with joint stateparameter update, the estimation of model parameter SOL_AWC (the available soil water capacity) and model states (the soil moisture in different depths) can be significantly improved by assimilating the surface soil moisture. Meanwhile, the runoff modeling for the whole catchment is also improved. With only state update, the improvement on runoff modeling shows less significance and robustness. Consistent with the synthetic experiments, the assimilation of the ESA CCI SM with joint state-parameter update shows considerable capability in the estimation of SOL_AWC. Both the joint stateparameter update and the only state update scheme could improve the streamflow modeling although the optimal model and observation error parameters for them are quite different. However, due to the high vegetation coverage of the study basin, and the strong spatial mismatch between the satellite and the model simulated soil moisture, it is still challenging to significantly benefit the runoff estimates by assimilating the ESA CCI SM.