Inflow Time Research Articles

Optimization of furrow irrigation performance of sugarcane fields based on inflow and geometric parameters using WinSRFR in Southwest of Iran

Accurate design, suitable management and optimization of irrigation design parameters play an important role in increasing the performance of furrow irrigation. The main objective of this study was to optimize the performance of furrow irrigation using WinSRFR in the fields of Salman Farsi Agro Industry sugarcane, located in the southwest of Iran. For this purpose, field experiments were conducted under nine blocked-ended furrows with the length of 250 m, the top width of 1.83 m and slope of 0.04 % and in three inflow treatments (1.0, 1.5 and 2.0 L/s) with three repetitions. The WinSRFR software was employed to optimize the combination of irrigation parameters such as inflow rate, cut-off time and field geometry. Objective function (OF) including application efficiency, distribution uniformity and deep percolation was also employed to optimize the performance. The results showed that using 1.0 L/s inflow rate could increase OF by 35.99 % which was the best performance compared to 1.5 and 2.0 l/s. Changing furrow length from 250 m to 200 m showed that OF value increased by 39.8.% ; however, changing it to 300 m, OF decreased by 7.7 %. In addition, changing slope from 0.04 to 0.03 % decreased OF by 0.9.%, while changing it to 0.05 % OF was improved by 1 %. On the other hand, changing the inflow and cut-off time, field length and combinations of them led to the increased OF by 25, 8.39 and 31 %, respectively. Finally, to obtain the maximum performance in sugarcane fields, inflow rate of 3 L/s and cut-off time of 379.5 min were suggested.

Comparison of support vector regression and extreme gradient boosting for decomposition-based data-driven 10-day streamflow forecasting

We recently addressed data-driven monthly streamflow forecasting using a decomposition-based model that relies on Fourier transform (FT) to decompose the monthly streamflow time series into 4 components, with each component comprising of contiguous frequencies and being forecasted independently by support vector regression (SVR). The model, called FT-SVR, is capable of achieving near-perfect monthly inflow forecasting for China’s Three Gorges Dam (TGD). In this paper, we adapt FT-SVR to 10-day streamflow forecasting and the TGD is still taken as the case for study. The 10-day inflow time series is decomposed into 7 components, and each component contains an appropriate small number of contiguous frequencies. We also investigate forecasting each decomposed component by extreme gradient boosting (XGBoost) and the investigated model is accordingly named as FT-XGBoost. XGBoost uses an ensemble of trees as the input–output mapping. The maximum number of iterations for solving convex quadratic programming in SVR is considerably reduced and the parameter calibration process to develop each independent SVR or XGBoost model is enhanced. We compare FT-SVR and FT-XGBoost on three different decomposition strategies: the centered 10-day inflow time series, 4 decomposed components like our previous work, and 7 components. Experimental results on the TGD case study demonstrate that FT-SVR with the decomposition strategy of 7 components is able to derive again near-perfect 10-day streamflow forecasting results, significantly better than FT-SVR with the other decomposition strategies and FT-XGBoost with all the decomposition strategies, while with parameter calibration being performed as efficiently as FT-XGBoost on each decomposition strategy.

Estimating daily inflows of large lakes using a water‐balance‐based runoff coefficient scaling approach

AbstractDaily river inflow time series are highly valuable for water resources and water environment management of large lakes. However, the availability of continuous inflow data for large lakes is still relatively limited, especially for large lakes situated within humid plain regions with tens or even hundreds of tributaries. In this study, we choose the fifth largest freshwater Lake Chaohu in China as our study area to introduce a new approach to reconstruct historical daily inflows at ungauged subcatchments of large lakes. This approach makes use of water level, lake surface rainfall, evaporation from the lake, and catchment rainfall observations. Rainfall–runoff relationship at a reference catchment was analysed to select rainfall input and estimate run‐off coefficient firstly, and the run‐off coefficient was then transferred to ungauged subcatchments to initially estimate daily inflows. Run‐off coefficient was scaled to adjust daily inflows at ungauged subcatchments according to water balance of the lake. This approach was evaluated using sparsely measured inflows at eight subcatchments of Lake Chaohu and compared with the commonly used drainage area ratio method. Results suggest that the inflow time series reconstructed from this approach consistent well to corresponding observations, with mean R2 and Nash–Sutcliffe efficiency values of 0.69 and 0.6, respectively. This approach outperforms drainage area ratio method in terms of mean R2 and Nash–Sutcliffe efficiency values. Accuracy of this approach holds well when the number of water‐level station being used decreased from four to one.

Quasi-periodicity of Supermassive Binary Black Hole Accretion Approaching Merger

Abstract In this paper we continue the first ever study of magnetized mini-disks coupled to circumbinary accretion in a supermassive binary black hole (SMBBH) approaching merger reported in Bowen et al. We extend this simulation from 3 to 12 binary orbital periods. We find that relativistic SMBBH accretion acts as a resonant cavity, where quasi-periodic oscillations tied to the frequency at which the black hole’s (BH’s) orbital phase matches a nonlinear m = 1 density feature, or “lump,” in the circumbinary accretion disk permeate the system. The rate of mass accretion onto each of the mini-disks around the BHs is modulated at the beat frequency between the binary frequency and the lump’s mean orbital frequency, i.e., , while the total mass accretion rate of this equal-mass binary is modulated at two different frequencies, and . The instantaneous rotation rate of the lump itself is also modulated at two frequencies close to the modulation frequencies of the total accretion rate, and . Because of the compact nature of the mini-disks in SMBBHs approaching merger, the inflow times within the mini-disks are comparable to the period on which their mass supply varies, so that their masses—and the accretion rates they supply to their BHs—are strongly modulated at the same frequency. In essence, the azimuthal symmetry of the circumbinary disk is broken by the dynamics of orbits near a binary, and this m = 1 asymmetry then drives quasi-periodic variation throughout the system, including both accretion and disk-feeding. In SMBBHs approaching merger, such time variability could introduce distinctive, increasingly rapid, fluctuations in their electromagnetic emission.

Early warning of burst passenger flow in public transportation system

Burst passenger flow in the public transportation system is serious to public safety. Existing works mainly focused on prediction and monitoring of regular passenger flow, which are not suitable for burst passenger flow. In this article, we first formulate the problem as early warning of burst passenger flow. Next, we design a novel framework to solve this problem by our observation that a burst passenger in-flow usually comes after an abnormal passenger out-flow for a subway station, especially when there is a large-scale social crowd event. Our framework consists of two models: (1) Abnormal out-flow detection (AOFD) which detects abnormal out-flows and warns the city administration of the burst in-flow fairly ahead of time. (2) Burst in-flow peak estimation (BIFPE) which estimates burst in-flow peak time and volume. We evaluate our framework with real-world smartcard data of the largest city in China and use large-scale social crowd event data to further explain our model. The result shows that: (1) AOFD can detect abnormal out-flows that would later result in bursts in-flows with better performance and can send warning signal ahead of the time of burst passenger in-flow. (2) BIFPE can effectively estimate the peak time of burst in-flow and can reduce peak volume estimation error compared with the traditional passenger flow prediction models.

A Multi-Objective Risk-Based Game Theoretic Approach to Reservoir Operation Policy in Potential Future Drought Condition

In this paper, by using the concept of Conditional Value at Risk (CVaR), a Leader-Follower game (LFG) based multi-objective optimization model is developed to determine the optimum 12-month operation policy of a reservoir in potential future dry periods. The minimization of CVaRs of storage loss and agricultural and environmental deficits along with maximization of planned allocation to agricultural sector are considered as leader’s objectives, while the followers try to maximize their share of water rights using Nash bargaining (NB) method. This framework is then used to model the operation policy of Dorudzan basin in Fars province, southwestern Iran. Water demand and daily climate data in the period of 2003 to 2015 for this basin, as well as future projections from fifteen IPCC-AR4 global circulation models (GCMs) for 2018–2030 under A2, B1 and A1B emission scenarios are considered to evaluate future dam operation policies. Future projections are downscaled using the LARS-WG model, which then feeds the HMETS watershed model to simulate the corresponding reservoir inflow time-series. Thereafter, three-hundred 12-month rainfall, evaporation and inflow time series with least inflow volume are used as input for the optimization model, which is solved using NSGA-II and GA algorithms. The results show while the model can determine the operation policy that keeps the associated risks in the acceptable range, it can satisfy the followers demands with respect to the available resources. The results also show that the agricultural sector of the study area can be hugely affected by potential future droughts.

Inflow Occlusion on Beating Heart Technique for Removal of Migrated Intravenous Access Catheter

Large numbers of therapeutic and diagnostic intravenous devices are inserted into patients around the world every day. Although these devices and the techniques for insertion have changed to improve ease of procedure and safety to the patient, the rare complication of migrated intravenous device – necessitating removal via median sternotomy – continues to occur [ [1] Gokalp O. et al. Comparison of inflow occlusion on the beating heart with cardiopulmonary bypass in the extraction of a mass lesion or a foreign body from the right heart. Eur J Cardio-thorac Surg. 2011; 39: 689-692 Crossref PubMed Scopus (7) Google Scholar ]. There is a safe technique for removal without using cardiopulmonary bypass that has been used for decades: Inflow occlusion on beating heart. This paper described the process of successful surgical removal via the above technique of a migrated 17-cm remnant of central venous catheter that was unable to be removed from a patient's left pulmonary artery via endovascular snare techniques. Inflow occlusion times of >3 minutes are not recommended, due to the risk of cardiac and neurological complications due to systemic and cerebral malperfusion [ 1 Gokalp O. et al. Comparison of inflow occlusion on the beating heart with cardiopulmonary bypass in the extraction of a mass lesion or a foreign body from the right heart. Eur J Cardio-thorac Surg. 2011; 39: 689-692 Crossref PubMed Scopus (7) Google Scholar , 2 Torabi A.J. Dobrilovic N. Raman J.S. Off-pump right atrial surgery: Vena caval inflow occlusion in cardiac lesions. Asian Cardiovasc Thorac Ann. 2015; 23: 809-813 Crossref PubMed Scopus (3) Google Scholar ]. The total inflow occlusion time was 56 seconds and the patient recovered with only a transient episode of rapid atrial fibrillation. He was discharged home on postoperative day 4 and had no complications at his 6-week postoperative appointment.

A high-resolution hydro power time-series model for energy systems analysis: Validated with Chinese hydro reservoirs

We expand the renewable technology model palette and present a validated high resolution hydro power time series model for energy systems analysis. Among the weather-based renewables, hydroelectricity shows unique storage-like flexibility, which is particularly important given the high variability of wind and solar power. Often limited by data availability or computational performance, a high resolution, globally applicable and validated hydro power time series model has not been available. For a demonstration, we focus on 41 Chinese reservoir-based hydro stations as a demo, determine their upstream basin areas, estimate their inflow based on gridded surface runoff data and validate their daily inflow time series in terms of both flow volume and potential power generation. Furthermore, we showcase an application of these time series with hydro cascades in energy system long term investment planning. Our method's novelty lies in:•it is based on highly resolved spatial-temporal datasets;•both data and algorithms used here are globally applicable;•it includes a hydro cascade model that can be integrated into energy system simulations.

Development of Multidecomposition Hybrid Model for Hydrological Time Series Analysis

Accurate prediction of hydrological processes is key for optimal allocation of water resources. In this study, two novel hybrid models are developed to improve the prediction precision of hydrological time series data based on the principal of three stages as denoising, decomposition, and decomposed component prediction and summation. The proposed architecture is applied on daily rivers inflow time series data of Indus Basin System. The performances of the proposed models are compared with traditional single‐stage model (without denoised and decomposed), the hybrid two‐stage model (with denoised), and existing three‐stage hybrid model (with denoised and decomposition). Three evaluation measures are used to assess the prediction accuracy of all models such as Mean Relative Error (MRE), Mean Absolute Error (MAE), and Mean Square Error (MSE). The proposed, three‐stage hybrid models have shown improvement in prediction accuracy with minimum MRE, MAE, and MSE for all case studies as compared to other existing one‐stage and two‐stage models. In summary, the accuracy of prediction is improved by reducing the complexity of hydrological time series data by incorporating the denoising and decomposition.

Fate of wastewater contaminants in rivers: Using conservative-tracer based transfer functions to assess reactive transport

Interpreting the fate of wastewater contaminants in streams is difficult because their inputs vary in time and several processes synchronously affect reactive transport. We present a method to disentangle the various influences by performing a conservative-tracer test while sampling a stream section at various locations for chemical analysis of micropollutants. By comparing the outflow concentrations of contaminants with the tracer signal convoluted by the inflow time series, we estimated reaction rate coefficients and calculated the contaminant removal along a river section. The method was tested at River Steinlach, Germany, where 38 contaminants were monitored. Comparing day-time and night-time experiments allowed distinguishing photo-dependent degradation from other elimination processes. While photo-dependent degradation showed to be highly efficient for the removal of metroprolol, bisoprolol, and venlafaxine, its impact on contaminant removal was on a similar scale to the photo-independent processes when averaged over 24 h. For a selection of compounds analyzed in the present study, bio- and photodegradation were higher than in previous field studies. In the Steinlach study, we observed extraordinarily effective removal processes that may be due to the higher proportion of treated wastewater, temperature, DOC and nitrate concentrations, but also a higher surface to volume ratio from low flow conditions that favorizes photodegradation through the shallow water column and a larger transient storage than observed in comparable studies.

Extreme AGN variability: evidence of magnetically elevated accretion?

ABSTRACT Rapid, large amplitude variability at optical to X-ray wavelengths is now seen in an increasing number of Seyfert galaxies and luminous quasars. The variations imply a global change in accretion power, but are too rapid to be communicated by inflow through a standard thin accretion disc. Such discs are long known to have difficulty explaining the observed optical/UV emission from active galactic nuclei. Here we show that alternative models developed to explain these observations have larger scale heights and shorter inflow times. Accretion discs supported by magnetic pressure in particular are geometrically thick at all luminosities, with inflow times as short as the observed few year time-scales in extreme variability events to date. Future time-resolved, multiwavelength observations can distinguish between inflow through a geometrically thick disc as proposed here, and alternative scenarios of extreme reprocessing of a central source or instability-driven limit cycles.

Magnetic anisotropy and stress-magnetoimpedance (S-MI) in current-annealed Co-rich glass-coated microwires with positive magnetostriction

Abstract Effects of a dc current annealing, in terms of magnitude and inflow time, on magnetic hysteresis properties, magnetoimpedance (MI) and stress-magnetoimpedance (S-MI) in glass-coated amorphous Co71Fe5B11Si10Cr3 microwires with a small positive magnetostriction were investigated in this work. The annealing process combining Joule-heating and circular magnetic field leads to the creation of a specific magnetic anisotropy of a helical or circular type, and consequently, is helpful to control the MI and S-MI behaviours making them more suitable for particular sensing applications. After annealing, the magnetoimpedance plots transformed from a bell-shaped typical of an axial easy anisotropy to the shape with two symmetrical peaks, the magnitude and position of which are controlled with the annealing current parameters. Applying a tensile stress on the annealed wires changes the easy anisotropy direction which leads to the potential for highly sensitive S-MI without use of dc bias fields. A stress sensitivity of more than 260% at σ ex = 250 MPa at zero magnetic field is achieved.

Dynamic inflow effects in measurements and high-fidelity computations

Abstract. A wind turbine experiences an overshoot in loading after, for example, a collective step change in pitch angle. This overshoot occurs because the wind turbine wake does not immediately reach its new equilibrium, an effect usually referred to as dynamic inflow. Vortex cylinder models and actuator disc simulations predict that the time constants of this dynamic inflow effect should decrease significantly towards the blade tip. As part of the NASA Ames Phase VI experiment, pitch steps have been performed on a turbine in controlled conditions in the wind tunnel. The measured aerodynamic forces from these experiments seemed to show much less radial dependency of the dynamic inflow time constants than expected when pitching towards low loading. Moreover the dynamic inflow effect seemed fundamentally different when pitching from low to high loading, and the reason for this behavior remained unclear in previous analyses of the experiment. High-fidelity computational fluid dynamics and free-wake vortex code computations yielded the same behavior as the experiments. In the present work these observations from the experiments and high-fidelity computations are explained based on a simple vortex cylinder wake model.

Ramipril and left ventricular diastolic function in stable patients with pulmonary regurgitation after repair of tetralogy of Fallot

BackgroundMeasures of left ventricular (LV) systolic and diastolic function are known predictors of mortality after repair of tetralogy of Fallot. We aimed to characterise LV reverse remodelling achievable with ramipril therapy. Methods and resultsA blinded post-hoc analysis of baseline and 6-month follow-up echocardiograms from the APPROPRIATE (ISRCTN: 97515585) randomised double-blinded placebo-controlled trial of ramipril therapy was performed in 64 patients: 32 in ramipril and 32 in placebo group. Tissue Doppler systolic and diastolic myocardial velocities, mitral inflow velocities and time intervals were measured. Left atrial area and left atrial emptying fraction were calculated.There was significant increase in long axis shortening mean (standard deviation); MAPSE [1.9 (4.2) mm vs −0.2 (3.7) mm; p = 0.030], peak lateral systolic velocity; S′ lateral [1.0 (2.0) cm/s vs −0.3 (2.2) cm/s; p = 0.025], peak lateral early diastolic velocity; E′ lateral [0.57 (2.4) cm/s vs −3.3 (3.9) cm/s; p < 0.001], transmitral to lateral mitral annular early diastolic velocity ratio; E/E′ lateral [−0.7 (1.9) vs 1.5 (1.9); p < 0.001] over the study period in the ramipril compared to the placebo group. Significantly higher measurements were observed in the ramipril arm of the subgroup of patients with right ventricular restrictive physiology in terms of peak late diastolic velocity; A [5.9 (13.5) cm/s vs −5.8 (12.5) cm/s; p = 0.041] and early to late diastolic transmitral velocity ratio; E/A [−0.18 (0.42) vs 0.23 (0.48); p = 0.037]. ConclusionSix months' ramipril treatment appears to limit progression of both diastolic and systolic LV function in adults late after tetralogy of Fallot repair. With increased appreciation that even subtle LV disease predicts tetralogy of Fallot outcomes, further clinical trials of drug therapies are justified.

Reservoir Inflow Forecast Using a Clustered Random Deep Fusion Approach in the Three Gorges Reservoir, China

Reservoir inflow forecast plays a crucial part in programming, development, operation, and management of water resource systems. To better reveal the complex properties of daily reservoir inflow, a clustered deep fusion (CDF) approach is proposed in this paper. First, variational mode decomposition (VMD) is used to decompose the daily reservoir inflow series into multiple modes, which are clustered into different sets by fuzzy c-means according to the Xie-Beni index in view of attribute domain. In each cluster, a deep autoencoder model (DAE) is developed for deep representations of the attributes in the deep domain. DAE outputs are finally fused at the synthesis domain into the forecasting results using random forest (RF). In this way, the inflow time series may be successively observed in the attribute domain, deep domain, and synthesis domain, which results in a clearer understanding of reservoir inflow trend. The present approach is modeled and evaluated using historical data collected from the Three Gorges Reservoir, China. For comparison, two kinds of learning patterns—deep learning (VMD-DAE-RF and DAE) and shallow learning (feed-forward neural network, least-squares support regression, and RF)—are applied to the same case. The results indicate that the proposed CDF model outperforms all comparison models in terms of mean absolute percentage error (6.174%), root mean-square error (1,077.428 m3/s), and correlation coefficient criteria (0.987). Thus, it is concluded that deep learning in the cluster fusion architecture is more promising.

Improved technical success, postnatal outcome and refined predictors of outcome for fetal aortic valvuloplasty.

Fetal aortic valvuloplasty (FAV) may prevent progression of mid-gestation aortic stenosis to hypoplastic left heart syndrome (HLHS). The aim of this study was to evaluate whether technical success and biventricular (Biv) outcome after FAV have changed from an earlier (2000-2008) to a more recent (2009-2015) era and identify pre-FAV predictors of Biv outcome. We evaluated procedural and postnatal outcomes in 123 fetuses that underwent FAV for evolving HLHS at Boston Children's Hospital between 2000 and 2015. The primary outcome measure was circulation type (Biv vs single ventricle) at the time of neonatal hospital discharge. Classification and regression tree (CART) analysis was performed to construct a stratification algorithm to predict Biv circulation based on pre-FAV fetal variables. The FAV procedure was technically successful in 101/123 (82%) fetuses, with a higher technical success rate in the more recent era than in the earlier one (49/52 (94%) vs 52/71 (73%); P = 0.003). In liveborn patients, the incidence of Biv outcome was higher in the recent than in the earlier era, both in the entire liveborn cohort (29/49 (59%) vs 16/62 (26%); P = 0.001) and in those in whom the procedure was technically successful (27/46 (59%) vs 15/47 (32%); P = 0.007). Independent predictors of Biv outcome were higher left ventricular (LV) pressure, larger ascending aorta, better LV diastolic function and higher LV long-axis Z-score. On CART analysis, fetuses with LV pressure > 47 mmHg and ascending aorta Z-score ≥ 0.57 had a 92% probability of Biv outcome (n = 24). Those with a lower LV pressure, or mitral dimension Z-score < 0.1 and mitral valve inflow time Z-score < -2 (n = 34) were unlikely to have Biv (probability of 9%). The remainder of the patients had an intermediate (∼40-60%) likelihood of Biv circulation. The proportion of patients achieving Biv outcome after FAV has increased, probably owing to an improved technical success rate and modified selection criteria. Fetal factors, including LV pressure, size of the ascending aorta and diastolic function, are associated with likelihood of Biv circulation after FAV. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

Many-Objective Multi-Scenario Algorithm for Optimal Reservoir Operation Under Future Uncertainties

An increase in greenhouse gases in future can exacerbate the climate change phenomenon and may have negative consequences on different elements of hydrologic system, including rainfall, temperature, and streamflow. Since the reservoir operation is highly dependent on the timing and magnitude of inflow, the impact of potential climate change on inflow sequences should be considered in deriving the system operation rule. Nevertheless, existing algorithms are only able to optimize the operation policy for a single predetermined climate scenario. Thus, the derived operation rule would not work well if the scenario changes. This paper proposes an algorithm which is able to handle simultaneously multiple scenarios in finding optimum system operation rule. Thus, it can overcome drawbacks caused by uncertainties in the occurrence of future scenarios. The proposed algorithm is used to optimize reservoir operation policy considering various climate change scenarios (RCPs). To evaluate the performance of the proposed algorithm, a five-reservoir system within Tehran region with several objectives including municipal, agricultural, environmental, and hydropower demands is employed as the case study. Results show that in all cases the multi-scenario rule derived by the proposed method performs as good as the operation rule derived for any specific scenario using a powerful optimization algorithm when evaluated for that scenario. While, in all other models as the future scenario changes to the one other than that used in deriving the operation rule, the model performance declines as compared to the proposed model.

Using ensemble precipitation forecasts and a rainfall-runoff model for hourly reservoir inflow forecasting during typhoon periods

This study proposes an integrated hydrometeorological system combining a fully physically based rainfall-runoff model (i.e., kinematic-wave-based geomorphologic instantaneous unit hydrograph model, KW-GIUH) with a numerical weather model (i.e., Taiwan cooperative precipitation ensemble forecast experiment, TAPEX) for performing hourly reservoir inflow forecasting patterns in the Shihmen Reservoir, in Northern Taiwan. If there is an accurate reservoir inflow with enough lead time, it could help reservoir operators to efficiently operate reservoirs in both dry and wet times of the year. Five historical typhoons, having severe impacts on the study reservoir, were used for model calibration, validation, and further application. For accurate reservoir inflow forecasting, it is necessary to understand a series of uncertainties that occur in this system. Therefore, the present study assessed the forecast uncertainty of the peak inflow and cumulative reservoir inflow on the basis of several TAPEX runs. Using the average forecasting result derived from all TAPEX runs could be less uncertain than randomly choosing a run’s result. For example, the results for Typhoon Saola (2013) showed that the uncertainty in the cumulative reservoir inflow ranged −31.3% (first TAPEX run) to 27.0% (sixth run); otherwise, its average forecasting result was only −0.9%. On the basis of the analyzed typhoons, the proposed system can provide accurate forecasts of the magnitude and timing of the peak inflow when rainfall distribution is concentrated during typhoon events. The results demonstrated that the proposed hydrometeorological system can substantially represent reservoir inflow forecasting in the Shihmen Reservoir and provide valuable information for operating reservoirs.

Cerebral perfusion characteristics show differences in younger versus older children with sickle cell anaemia: Results from a multiple-inflow-time arterial spin labelling study.

Sickle cell anaemia (SCA) is associated with chronic anaemia and oxygen desaturation, which elevate cerebral blood flow (CBF) and increase the risk of neurocognitive complications. Arterial spin labelling (ASL) provides a methodology for measuring CBF non-invasively; however, ASL techniques using only a single inflow time are not sufficient to fully characterize abnormal haemodynamic behaviour in SCA. This study investigated haemodynamic parameters from a multi-inflow-time ASL acquisition in younger (8-12years) and older (13-18years) children with SCA with and without silent cerebral infarction (SCI+/-) (n=20 and 19 respectively, 6 and 4 SCI+ respectively) and healthy controls (n=9 and 7 respectively). Compared with controls, CBF was elevated globally in both groups of patients. In the younger SCA patients, blood oxygen content was negatively correlated with CBF in the middle and posterior cerebral artery territories and significantly positively correlated with bolus arrival time (BAT) in the anterior and middle cerebral artery territories. In older children, SCA patients had significantly shorter BAT than healthy controls and there was a significant negative correlation between CBF and oxygen content only in the territory of the posterior cerebral artery, with a trend for a correlation in the anterior cerebral artery but no relationship for the middle cerebral artery territory. In the younger group, SCI+ patients had significantly higher CBF in the posterior cerebral artery territory (SCI+ mean=92.78ml/100g/min; SCI- mean=72.71ml/100g/min; F=4.28, p=0.04), but this no longer reached significance when two children with abnormal transcranial Doppler and one with haemoglobin SC disease were excluded, and there were no significant differences between patients with and without SCI in the older children. With age, there appears to be increasing disparity between patients and controls in terms of the relationship between CBF and oxygen content in the anterior circulation, potentially predicting the risk of acute and chronic compromise of brain tissue.

Factors behind the variability of phosphorus accumulation in Finnish lakes

Phosphorus retention (TPacc) is one of the major water quality regulators in lakes. The current study aimed at ascertaining the specific lake characteristics regulating TPacc. Moreover, we were interested whether NAO (North Atlantic Oscillation), a proxy of climatic forcing, can explain variability in TPacc, additionally to that ascribed to lake characteristics. Sediment cores were obtained from 21 Finnish lakes, subject to radiometric dating and measurements of TP concentrations. Principal components (PCs) were generated using lake characteristics that are usually included into the modelling of TPacc (e.g. lake area, lake depth, catchment area, P inflow) but also the parameters that the classical models usually missed (e.g. anoxic factor). We used significant principal components (PCs), specific combinations of lake characteristics and monthly NAO values as predictors of TPacc. Lake characteristics explained the bulk of TPacc variability. The most influential factors (positive drivers) behind TPacc included PC1 (representing mainly deep lakes), PC2 (small lakes with high levels of anoxia and water column stability), PC3 (productive lakes with large catchment area and short water residence time), PC4 (lakes with high water column stability, low anoxic factor and relatively high sediment focusing) and PC5 (lakes with high levels of P inflow, anoxia and long water residence time). Additionally, we found a potential negative effect of NAO in October on the annual TPacc. This NAO was significantly positively related to temperatures in surface and near-bottom water layer (also their difference) in autumn, suggesting the possible implications for the internal P dynamics. Increased mineralization of organic matter is the most likely explanation for the reduced TPacc associated with NAO-driven water temperature increase. The analysis presented here contributes to the knowledge of the factors controlling P retention. Moreover, this spatially and temporally comprehensive sediment data can potentially be a valuable source for modelling climate change implications.