Quantification of surface runoff in Patiala-Ki-Rao watersheds using modified NRCS model: a case study

Quantification of the surface runoff in a watershed is of vital importance for solution of many water resource problems. It can be quantified by employing large number of estimation approaches. Of these, SCS-CN approach is quite simple effective and requires less number of parameters. Thus, the objective of the study was to employ soil conservation service-curve number (SCS-CN) approach and their modifications to estimate surface runoff for Patiala-Ki-Rao watershed, district SAS, Nagar, Punjab and to choose the best model of the 8-different employed models. Soil moisture retention parameter was characterised and optimised by using the descriptive statistics and later used in the models. The mean and median valueof soil moisture retention parameter was 47.2 mm and 35.9 mm for June to September months and 35.4 to 30.8 mm for October to March months. The models were evaluated on the basis of Root Mean Square Error (RMSE), Nash- Scutcliffe Efficiency (NSE), Coefficient of Determination (R2) and Per cent Bias (PB). Of the evaluated and tested models, NRCS model (M5) performed best with the highest score of 32 and 31 by employing mean andmedian values of soil moisture retention parameter in Patiala-Ki-Rao watersheds over the other models. Further, the results of the study suggested in evaluating the performance of NRCS model (M5) in other treated micro-watersheds at Patiala-Ki-Rao, Punjab, over the control.

Modeling of the Renal Kinetics of the AT1 Receptor Specific PET Radioligand [11C]KR31173

Purpose. The radioligand [11C]KR31173 has been introduced for PET imaging of the angiotensin II subtype 1 receptor (AT1R). The purpose of the present project was to employ and validate a compartmental model for quantification of the kinetics of this radioligand in a porcine model of renal ischemia followed by reperfusion (IR).Procedures. Ten domestic pigs were included in the study: five controls and five experimental animals with IR of the left kidney. To achieve IR, acute ischemia was created with a balloon inserted into the left renal artery and inflated for 60 minutes. Reperfusion was achieved by deflation and removal of the balloon. Blood chemistries, urine specific gravity and PH values, and circulating hormones of the renin angiotensin system were measured and PET imaging was performed one week after IR. Cortical time-activity curves obtained from a 90 min [11C]KR31173 dynamic PET study were processed with a compartmental model that included two tissue compartments connected in parallel. Radioligand binding quantified by radioligand retention (80 min value to maximum value ratio) was compared to the binding parameters derived from the compartmental model. A binding ratio was calculated asDVR=DVS/DVNS, whereDVSandDVNSrepresented the distribution volumes of specific binding and nonspecific binding. Receptor binding was also determined by autoradiographyin vitro.Results. Correlations between rate constants and binding parameters derived by the convolution and deconvolution curve fittings were significant(r>0.9). Also significant was the correlation between the retention parameter derived from the tissue activity curve (Yret) and the retention parameter derived from the impulse response function (fret). Furthermore, significant correlations were found between these two retention parameters and DVR. Measurements with PET showed no significant changes in the radioligand binding parameters caused by IR, and thesein vivofindings were confirmed by autoradiography performedin vitro.Conclusions. Correlations between various binding parameters support the concept of the parallel connectivity compartmental model. If an arterial input function cannot be obtained, simple radioligand retention may be adequate for estimation ofin vivoradioligand binding.

Conditional percolation on one-dimensional lattices

Conditioning independent and identically distributed bond percolation with retention parameter p on a one-dimensional periodic lattice on the event of having a bi-infinite path from -∞ to ∞ is shown to make sense, and the resulting model exhibits a Markovian structure that facilitates its analysis. Stochastic monotonicity in p turns out to fail in general for this model, but a weaker monotonicity property does hold: the average edge density is increasing in p.

Conditional percolation on one-dimensional lattices

Conditioning independent and identically distributed bond percolation with retention parameter p on a one-dimensional periodic lattice on the event of having a bi-infinite path from -∞ to ∞ is shown to make sense, and the resulting model exhibits a Markovian structure that facilitates its analysis. Stochastic monotonicity in p turns out to fail in general for this model, but a weaker monotonicity property does hold: the average edge density is increasing in p.

RP-HPLC determination of lipophilicity in series of quinoline derivatives

In the present paper we describe results on the synthesis and lipophilicity determination of a series of biologically active compounds based on their heterocyclic structure. For synthesis of styrylquinoline-based compounds we applied microwave irradiation and solid phase techniques. The correlation between RP-HPLC retention parameter log k (the logarithm of retention factor k) and log P data calculated in various ways is discussed, as well as, the relationships between the lipophilicity and the chemical structure of the studied compounds.

Uniqueness in two-dimensional rigidity percolation

For bond percolation on the two-dimensional triangular lattice with arbitrary retention parameter p ∈ [0, 1], we show that the number of infinite rigid components is a.s. at most 1. This proves a conjecture by Holroyd. Further results, concerning simultaneous uniqueness, and continuity (in p) of the probability that a given edge is in an infinite rigid component, are also obtained.