Transit Time Estimation Research Articles

Can the young water fraction reduce predictive uncertainty in water transit time estimations?

Transit time distributions (TTDs) of streamflow are informative descriptors of catchment hydrological functioning and solute transport mechanisms. Conventional methods for estimating TTDs generally require model calibration against extensive tracer data time series, which are often limited to well-studied experimental catchments. We challenge this limitation and propose an alternative approach that uses the young water fraction (Fywobs), an increasingly used water age metric which represents the proportion of streamflow with a transit time younger than 2-3 months, and that can be robustly estimated with sparsely measured tracer data. To this end, we conducted a proof of concept study by modelling TTDs using StorAge Selection (SAS) functions with oxygen isotopes (δ18O) measurements for 23 diverse catchments in Germany. In a Monte-Carlo approach, we computed the (averaged) marginal TTDs of a prior parameter distribution and derived a model-based Fyw (Fywsim). We compared Fywsim with Fywobs, obtained from δ18O measurements, and constrained the prior SAS parameters distribution. Subsequently, we derived a posterior distribution of parameters and resulting model simulations. Our findings showed that using Fywobs to constrain the model effectively reduced parameter equifinality and simulation uncertainty. However, the value of Fywobs on reducing model uncertainty varied across sites, with larger values (Fywobs≥0.10) leading to simulations with a narrower uncertainty band and higher model efficiency, whilst smaller values (Fywobs≤0.05) had limited influence on reducing model output uncertainty. We discussed the potential and limitations of combining SAS functions with Fywobs, and considered broader implications of this approach for enhancing our understanding of catchment functioning and water quality status.

Deep Learning-Based Real-Time Organ Localization and Transit Time Estimation in Wireless Capsule Endoscopy.

Wireless capsule endoscopy (WCE) has significantly advanced the diagnosis of gastrointestinal (GI) diseases by allowing for the non-invasive visualization of the entire small intestine. However, machine learning-based methods for organ classification in WCE often rely on color information, leading to decreased performance when obstacles such as food debris are present. This study proposes a novel model that integrates convolutional neural networks (CNNs) and long short-term memory (LSTM) networks to analyze multiple frames and incorporate temporal information, ensuring that it performs well even when visual information is limited. We collected data from 126 patients using PillCam™ SB3 (Medtronic, Minneapolis, MN, USA), which comprised 2,395,932 images. Our deep learning model was trained to identify organs (stomach, small intestine, and colon) using data from 44 training and 10 validation cases. We applied calibration using a Gaussian filter to enhance the accuracy of detecting organ boundaries. Additionally, we estimated the transit time of the capsule in the gastric and small intestine regions using a combination of a convolutional neural network (CNN) and a long short-term memory (LSTM) designed to be aware of the sequence information of continuous videos. Finally, we evaluated the model's performance using WCE videos from 72 patients. Our model demonstrated high performance in organ classification, achieving an accuracy, sensitivity, and specificity of over 95% for each organ (stomach, small intestine, and colon), with an overall accuracy and F1-score of 97.1%. The Matthews Correlation Coefficient (MCC) and Geometric Mean (G-mean) were used to evaluate the model's performance on imbalanced datasets, achieving MCC values of 0.93 for the stomach, 0.91 for the small intestine, and 0.94 for the colon, and G-mean values of 0.96 for the stomach, 0.95 for the small intestine, and 0.97 for the colon. Regarding the estimation of gastric and small intestine transit times, the mean time differences between the model predictions and ground truth were 4.3 ± 9.7 min for the stomach and 24.7 ± 33.8 min for the small intestine. Notably, the model's predictions for gastric transit times were within 15 min of the ground truth for 95.8% of the test dataset (69 out of 72 cases). The proposed model shows overall superior performance compared to a model using only CNN. The combination of CNN and LSTM proves to be both accurate and clinically effective for organ classification and transit time estimation in WCE. Our model's ability to integrate temporal information allows it to maintain high performance even in challenging conditions where color information alone is insufficient. Including MCC and G-mean metrics further validates the robustness of our approach in handling imbalanced datasets. These findings suggest that the proposed method can significantly improve the diagnostic accuracy and efficiency of WCE, making it a valuable tool in clinical practice for diagnosing and managing GI diseases.

40Ar diffusion in phlogopite: [formula omitted] atomistic calibration and implications for Ar–melt–solid kinetic interactions and ascent dynamics of mantle xenoliths and kimberlites

40Ar/39Ar ages of phlogopite from kimberlite-hosted mantle xenoliths are commonly older than the kimberlite eruption, despite the fact that argon is supposed not to be retained by phlogopite at temperatures above hydrothermally-derived Ar closure temperatures (<500°C). Combining Molecular Dynamics (MD) with Nudged Elastic Band (NEB) and Transition State Theory (TST), we investigate 40Ar−PVT (Pressure−Volume−Temperature) relationships in pristine, defect-free, phlogopite and show that 40Ar diffusivity is several orders of magnitude slower than existing estimates with a strong effect of pressure on diffusion rates and retention of 40Ar at mantle conditions. These results imply to fundamentally revise residence- and transit-time estimates based on Ar kinetics in phlogopite assuming simple diffusive relaxation during upwelling. When accounting for pressure, 40Ar retention trends in phlogopite predict substantially slower kimberlite ascent rates than documented by independent chronometers, indicating that 40Ar resetting during ascent in phlogopite does not result from simple decompression-driven diffusive relaxation. We argue that 40Ar remobilization probably involves secondary structural–textural modifications induced by reaction-driven recrystallization or rim overgrowth. These findings have far-reaching consequences in terms of argon isotopic mobility at mantle depths as well as for dating and tracing metasomatic events during crust−mantle interactions in the evolution of the subcontinental mantle.

Effect of chewing gum in bowel preparation for patients undergoing small bowel and colon capsule endoscopy: Systematic review with meta-analysis.

Background and study aims Quality of bowel preparation and successful transit are critical factors for complete small bowel capsule endoscopy (SBCE) and colon capsule endoscopy (CCE). The aim of this systematic review with meta-analysis was to assess the impact of chewing gum as part of the bowel preparation regimen on the completion rate in both SBCE and CCE. Methods A systematic literature search was conducted in PubMed, Cochrane, Web of Science and Embase. Data were extracted upon quality assessment of included studies. Two reviewers conducted the screening process according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Eighty-four studies met the search criteria and four randomized controlled trials were included in the meta-analysis, these were assessed for bias using Minors. Pooled completion rate of SBCE studies was defined as the primary outcome. Results Three randomized controlled trials were SBCE studies and one was a CCE study. The pooled completion rate (91%) was not significantly higher in SBCE patients who were given chewing gum after capsule ingestion compared to those who were not (85%). Variance information was not reported in all studies, and therefore, pooled transit time estimates could not be calculated. Conclusions Chewing gum has a good safety profile but has only been used as a booster in one CCE study and a few SBCE studies. More prospective randomized controlled trials, therefore, are needed to investigate the efficacy of chewing gum for achieving complete capsule examination.

Optimization and validation of a suprasystolic brachial cuff-based method for noninvasively estimating central aortic blood pressure.

Clinical studies have extensively demonstrated that central aortic blood pressure (CABP) has greater clinical significance in comparison with peripheral blood pressure. Despite the existence of various techniques for noninvasively measuring CABP, the clinical applications of most techniques are hampered by the unsatisfactory accuracy or large variability in measurement errors. In this study, we proposed a new method for noninvasively estimating CABP with improved accuracy and reduced uncertain errors. The main idea was to optimize the estimation of the pulse wave transit time from the aorta to the occluded lumen of the brachial artery under a suprasystolic cuff by identifying and utilizing the characteristic information of the cuff oscillation wave, thereby improving the accuracy and stability of the CABP estimation algorithms under various physiological conditions. The method was firstly developed and verified based on large-scale virtual subject data (n = 800) generated by a computational model of the cardiovascular system coupled to a brachial cuff, and then validated with small-scale in vivo data (n = 34). The estimation errors for the aortic systolic pressure were -0.05 ± 0.63 mmHg in the test group of the virtual subjects and -1.09 ± 3.70 mmHg in the test group of the patients, both demonstrating a good performance. In particular, the estimation errors were found to be insensitive to variations in hemodynamic conditions and cardiovascular properties, manifesting the high robustness of the method. The method may have promising clinical applicability, although further validation studies with larger-scale clinical data remain necessary.

Cerebral Blood Flow and Arterial Transit Time Variations in Elders with Long COVID

AbstractBackgroundMany COVID‐19 patients experience persistant neurological symptoms that often extend beyond the period of acute infection, referred to as “Long COVID”, where most patients reported brain fog and cognitive dysfunction. While elderly individuals are more vulnerable to possible enduring cognitive impairments after acute COVID‐19 requiring hospitalization, there is increasing concern that older patients with Long COVID will be at high risk for developing Alzheimer’s disease (AD) and dementia. Although there is emerging recognition of Long COVID, its underlying neuropathology remains unknown. This study aimed to investigate neurovascular function using advanced MRI perfusion in elder patients with Long COVID.MethodWell‐matched elderly Long COVID patients (n = 14, mean age = 60.1±4.3 years, 12F, 2M) and control subjects (n = 25, mean age = 60.4±7.2 years, 19F, 6M) underwent neurocognitive testing as well as neuroimaging. Patients were seen 711.57 ± 165.02 days after the initial mild non‐hospitalized COVID‐19 infection. Clinical cognitive complaints of Long COVID patients included memory changes (n = 12, 85.7%), attention (n = 12, 85.7%), speech/writing (n = 9, 64.3%), and multitasking (n = 9, 64.3%). Brain perfusion was evaluated using an advanced 3D pseudo‐continuous arterial spin labeling (pCASL) sequence with Hadamard encoded multiple post‐labeling delays (PLDs), enabling estimation of Cerebral Blood Flow (CBF) and Arterial Transit Time (ATT) ATT and ATT corrected CBF.ResultConventional MRI scans (T1, T2, and FlAIR) appear normal in all subjects. Voxelwise comparisons between Long‐COVID and control subjects showed a significant global decrease in the ATT (p &lt; 0.05, cluster corrected at a &lt; 0.05), along default mode and other key networks, where there is a trend of decreased CBF (p&lt;0.05, uncorrected) specifically in the frontal lobe in those with Long COVID.ConclusionThese preliminary results in an aging group indicate that neurocognitive effects of Long COVID could be attributed to neurovascular dysfunction, even in those cases with initial non‐hospitalized mild COVID‐19 of more than 500 days. The novel finding of diffusely decreased ATT could be something attributable to the unique neurovascular mechanism of Long COVID. Future longitudinal research following the progression of those elderly Long COVID patients with known abnormal neurovascular function to fully evaluate their risk for developing AD and dementia.

Cerebral Blood Flow and Arterial Transit Time Variations in Elders with Long COVID

AbstractBackgroundMany COVID‐19 patients experience persistant neurological symptoms that often extend beyond the period of acute infection, referred to as “Long COVID”, where most patients reported brain fog and cognitive dysfunction. While elderly individuals are more vulnerable to possible enduring cognitive impairments after acute COVID‐19 requiring hospitalization, there is increasing concern that older patients with Long COVID will be at high risk for developing Alzheimer’s disease (AD) and dementia. Although there is emerging recognition of Long COVID, its underlying neuropathology remains unknown. This study aimed to investigate neurovascular function using advanced MRI perfusion in elder patients with Long COVID.MethodWell‐matched elderly Long COVID patients (n = 14, mean age = 60.1±4.3 years, 12F, 2M) and control subjects (n = 25, mean age = 60.4±7.2 years, 19F, 6M) underwent neurocognitive testing as well as neuroimaging. Patients were seen 711.57 ± 165.02 days after the initial mild non‐hospitalized COVID‐19 infection. Clinical cognitive complaints of Long COVID patients included memory changes (n = 12, 85.7%), attention (n = 12, 85.7%), speech/writing (n = 9, 64.3%), and multitasking (n = 9, 64.3%). Brain perfusion was evaluated using an advanced 3D pseudo‐continuous arterial spin labeling (pCASL) sequence with Hadamard encoded multiple post‐labeling delays (PLDs), enabling estimation of Cerebral Blood Flow (CBF) and Arterial Transit Time (ATT) ATT and ATT corrected CBF.ResultConventional MRI scans (T1, T2, and FlAIR) appear normal in all subjects. Voxelwise comparisons between Long‐COVID and control subjects showed a significant global decrease in the ATT (p &lt; 0.05, cluster corrected at α &lt; 0.05), along default mode and other key networks, where there is a trend of decreased CBF (p&lt;0.05, uncorrected) specifically in the frontal lobe in those with Long COVID.ConclusionThese preliminary results in an aging group indicate that neurocognitive effects of Long COVID could be attributed to neurovascular dysfunction, even in those cases with initial non‐hospitalized mild COVID‐19 of more than 500 days. The novel finding of diffusely decreased ATT could be something attributable to the unique neurovascular mechanism of Long COVID. Future longitudinal research following the progression of those elderly Long COVID patients with known abnormal neurovascular function to fully evaluate their risk for developing AD and dementia.

Core laboratory comparative assessment of angiography-derived index of microvascular resistance (IMR) in patients with wire-based IMR

Abstract Background Coronary microvascular disease (CMD) is responsible for nearly half of angina in the general population. The index of microvascular resistance (IMR) is the gold standard for the diagnosis of CMD. Abnormal IMR is independently associated with adverse outcomes and persistent angina after percutaneous coronary intervention (PCI) regardless of the achieved fractional flow reserve (FFR). However, the implementation of IMR in clinical practice is low due to cost and the need for hyperemia. Thus, multiple software and formulas have been developed to calculate wireless IMR via angiography analysis. However, these angiography-derived IMRs have never been compared head-to-head by an independent core laboratory. Aim In this study, we aim to investigate the diagnostic accuracies of five angiography-derived IMR software/formulas by an independent core lab in a retrospective cohort undergoing follow-up angiograms after successful PCI. Methods We analyzed 43 patients from the FUNCOMBO trial and 34 patients from the RETROFI II trial. All patients have received successful PCI for STEMI, and wire-based IMR was measured at six months (for FUNCOMBO) and three years follow-up (for RETROFI II). Angiography-derived IMR was calculated with the QFR®2.1 software, the Flashangio CaIMR® software, and the AngioPlus software. In addition, using QFR-derived data, we calculated the angio-IMR using the formula of Escaned et al. [angio-IMR = (Pa–[0.1*Pa])*QFR*e-Tmn (where e-Tmn is an estimation of hyperaemic mean transit time)] and Scarsini et al. [NH-IMRangio=Pa(resting)x QFR x N frame(resting)/frame per second]. The threshold of CMD diagnosis is 25 for all five angiography-derived IMR methods. The correlation and agreement of the five methods were evaluated against wire-based IMR measurement. Results The wire-based IMR was significantly correlated with Medis IMR (r= 0.396, p=0.001) and NH-IMRangio (r=0.378, p=0.001). The agreements between IMR and the angiography-derived IMRs are demonstrated in figure 1. The sensitivity, specificity, positive predicted value, negative predicted value, and accuracy were demonstrated in figure 2, which showed that using the published criteria, the accuracy of diagnosis was 52%, 68%, 67%, 68%, and 49% for Medis IMR, CaIMR, AngioPlus IMR, angio-IMR, and NH-IMRangio, respectively. Comparison of all angiography-derived IMR with wire-based IMR yielded the AUC’s of 0.648, 0.561, 0.606, 0.674, 0.688 for Medis IMR, CaIMR, AngioPlus IMR, angio-IMR, and NH-IMRangio respectively. (Figure 2.) Conclusion In this small validation cohort, we found that all five angiography-derived IMR calculation methods had either poor or very poor diagnostic accuracy. Among the five methods, the Medis IMR, Angio-IMR, and NH-IMRangio may be viable options for wireless CMD diagnosis.Figure 1Figure 2

Objective estimation of colonic transit time using radiopaque markers in an abdominal X-ray after laparoscopic colorectal resection: secondary analysis of a randomized clinical trial.

Objective estimation of colonic transit time using radiopaque markers in an abdominal X-ray after laparoscopic colorectal resection: secondary analysis of a randomized clinical trial.

Tracing Atlantic water transit times in the Arctic Ocean: Coupling reprocessing-derived 236U and colored dissolved organic matter to distinguish different pathways

The Fram Strait is a key region for investigating the exchange of Atlantic water with the Arctic Ocean. Uranium-236 (236U) from the two European nuclear reprocessing plants (NRPs) at La Hague and Sellafield provides a unique fingerprint in Atlantic water which can be used for studying its circulation patterns in the Arctic Ocean. And NRPs-derived 236U (236UNRPs) can be identified by its 233U/236U signature. In this study, we use colored dissolved organic matter (CDOM) absorption to constrain the selection of three Atlantic branch waters that carried different inputs of 236UNRPs in Fram Strait. This can potentially provide better estimates of transit times of Atlantic waters in the Arctic Ocean. High CDOM levels (a350≥0.35 m−1) in Fram Strait reflect the passage of Atlantic water transported to the Arctic by the Norwegian Coastal Current (NCC) and its extension and subsequently along the Siberian continental slope and shelf where the Ob, Yenisei and Lena rivers supply terrestrial organic matter with significantly high CDOM content. Conversely, low CDOM water represents Atlantic water that has remained off the shelf. Based on CDOM absorption, potential temperature (Θ), potential density (σΘ) and 236U concentration, the path of a given body of Atlantic water could be inferred and an appropriate NRPs input function constrained so that transit times could be estimated. Our results indicate that Arctic High CDOM Water (a350≥0.35 m−1) sourced from the NCC and Barents Sea Branch Water (BSBW) in the Barents Sea Opening has an average of 7–27 yrs transit time in the upper ∼200 m of the western shelf of the Fram Strait. Atlantic Low CDOM Water (a350<0.35 m−1, Θ>2°C) sourced from the Fram Strait Branch Water (FSBW) has a short pathway from the eastern Fram Strait. Arctic Low CDOM / High 236U Water (a350<0.35 m−1, Θ≤2°C, σΘ≤27.97 or 236U concentration ≥15 × 106 atom/L) sourced from the BSBW and the FSBW has an average of 22–28 yrs transit time. These findings demonstrate how combining measurements of CDOM with 236UNRPs can improve the robustness in estimation of transit times of different Atlantic water pathways in the Arctic Ocean. There are limited ways to empirically derive estimates and the values provided offer unique data for comparison with estimates from regional circulation models.

A new system for cuffless blood pressure measurement

High blood pressure (HBP) increases the risk of cardiovascular, brain, and renal diseases which can lead to severe illness and death. Due to the variability of BP values at different times during the day, continuous BP measurement would allow more effective early diagnosis of elevated blood pressure, and aid in the management of treatment. Various techniques have been proposed for cuffless BP measurement, often relying on the estimation of pulse transit time (PTT) to infer BP. However, challenges such as computational complexity and limited availability of BP monitoring sensors hinder the reliable and widespread implementation of continuous BP measurement. The proposed wristwatch-based system uses speech sounds together with photoplethysmogram (PPG) and electrocardiogram (ECG) signals, and uses a mathematical model which estimates the systolic BP (SBP) and diastolic BP (DBP) from these inputs.We have obtained Pearson correlation coefficient (PCC)s of 0.6094 for systolic BP and 0.6001 for diastolic BP in these experiments. The mean average errors (MAE) obtained are 8.06 mmHg for systolic BP and 7.48 mmHg for diastolic BP, respectively. This study provides meaningful results based on experimental outputs, demonstrating the feasibility of using speech signals in conjunction with PPG and ECG signals for BP estimation. The simplicity of our mathematical model enables efficient and practical implementation in real-time BP monitoring. As a pilot study, our work establishes a foundation for further research, emphasizing the need for enhancing accuracy and reliability, expanding the dataset, and exploring additional physiological parameters to advance continuous BP estimation.Our findings advance the development of cuffless BP monitoring, and address the computational complexity and real-time processing requirements. Future studies should build upon our work to refine and optimize the proposed approach, ultimately leading to improved continuous BP estimation in diverse populations.

Uncertainty in water transit time estimation with StorAge Selection functions and tracer data interpolation

Abstract. Transit time distributions (TTDs) of streamflow are useful descriptors for understanding flow and solute transport in catchments. Catchment-scale TTDs can be modeled using tracer data (e.g. oxygen isotopes, such as δ18O) in inflow and outflows by employing StorAge Selection (SAS) functions. However, tracer data are often sparse in space and time, so they need to be interpolated to increase their spatiotemporal resolution. Moreover, SAS functions can be parameterized with different forms, but there is no general agreement on which one should be used. Both of these aspects induce uncertainty in the simulated TTDs, and the individual uncertainty sources as well as their combined effect have not been fully investigated. This study provides a comprehensive analysis of the TTD uncertainty resulting from 12 model setups obtained by combining different interpolation schemes for δ18O in precipitation and distinct SAS functions. For each model setup, we found behavioral solutions with satisfactory model performance for in-stream δ18O (KGE &gt; 0.55, where KGE refers to the Kling–Gupta efficiency). Differences in KGE values were statistically significant, thereby showing the relevance of the chosen setup for simulating TTDs. We found a large uncertainty in the simulated TTDs, represented by a large range of variability in the 95 % confidence interval of the median transit time, varying at the most by between 259 and 1009 d across all tested setups. Uncertainty in TTDs was mainly associated with the temporal interpolation of δ18O in precipitation, the choice between time-variant and time-invariant SAS functions, flow conditions, and the use of nonspatially interpolated δ18O in precipitation. We discuss the implications of these results for the SAS framework, uncertainty characterization in TTD-based models, and the influence of the uncertainty for water quality and quantity studies.

Development of a PPG-based hardware and software system deployable on elbow and thumb for real-time estimation of pulse transit time.

Blood pressure (BP) is a vital parameter used by clinicians to diagnose issues in the human cardiovascular system. Cuff-based BP devices are currently the standard method for on-the-spot and ambulatory BP measurements. However, cuff-based devices are not comfortable and are not suitable for long-term BP monitoring. Many studies have reported a significant correlation between pulse transit time (PTT) with blood pressure. However, this relation is impacted by many internal and external factors which might lower the accuracy of the PTT method. In this paper, we present a novel hardware system consisting of two custom photoplethysmography (PPG) sensors designed particularly for the estimation of PTT. In addition, a software interface and algorithms have been implemented to perform a real-time assessment of the PTT and other features of interest from signals gathered between the brachial artery and the thumb. A preclinical study has been conducted to validate the system. Five healthy volunteer subjects were tested and the results were then compared with those gathered using a reference device. The analysis reports a mean difference among subjects equal to -3.75±7.28 ms. Moreover, the standard deviation values obtained for each individual showed comparable results with the reference device, proving to be a valuable tool to investigate the factors impacting the BP-PTT relationship.Clinical Relevance- The proposed system proved to be a feasible solution to detect blood volume changes providing good quality signals to be used in the study of BP-PTT relationship.

Transit time estimation of drying springs in Uttarakhand region using environmental tritium concentration

Many parts of the Uttarakhand state, situated in the hilly terrain of the Himalayan region of India are facing acute water crisis due to the drying up of the perennial springs which are the only source of potable water in those regions. Tritium (3H), the radioactive isotope of hydrogen (half-life of 12.32 years) and also a part of water molecule (in the form of HTO) acts as a very useful tracer in estimating the transit time of the hydrological systems. Tritium concentrations of three springs (S-1, S-2 and S-3) were monitored consecutively for three years (2017–2019) to better constrain the transit time estimation. The tritium concentrations of the springs are found to vary between 3.66 and 4.15 TU. All the springs show gradual decrease in tritium concentration with the passage of time indicating the diminishing percentage of freshly recharged modern water component. Among various lumped parameter models, the piston-flow model (PFM), exponential mixing model (EMM), exponential piston-flow model (EPM) and partial exponential mixing model (PEM) have been employed in this study. The historical record of weighted mean concentration of tritium in precipitation available for the Uttarakhand region is taken as input function in the modelling procedure. The application of various LPMs (PFM, EMM, EPM and PEM) indicates that the transit time of the S-1 spring ranges from 1.26 to 1.46 years whereas for S-2 spring, the transit time is found to vary from 5 months to 1.1 years. The MTT of S-3 spring ranges from 5 months to 11 months. The relatively short residence time of these springs indicates the actively recharged system. The estimation of accurate transit time is thus very crucial for understanding the renewability of the spring water systems.

Using isotopic tracers to enhance routine watershed monitoring – Insights from an intensively managed agricultural catchment

Experimental (research-based) and non-research-based watershed monitoring programs often differ with respect to sampling frequency, monitored variables, and monitoring objectives. Isotopic variables, which are more commonly incorporated in research-based programs, can provide an indication of water sources and the transit time of water in a catchment. These variables may be a valuable complement to traditional water quality monitoring variables and have the potential to support improved hydrologic process-related insights from long term monitoring programs that typically have low resolution sampling. The purpose of this investigation is to explore the utility of incorporating isotopic variables (specifically δ18O, δ2H, and 222Rn) into routine monthly sampling regimes by comparing insights gained from these variables to monitoring only specific conductivity and chloride. A complete annual cycle of monthly groundwater and surface water monitoring data collected from the Upper Parkhill watershed in southwestern Ontario, Canada was used to characterize baseline watershed conditions, evaluate watershed resilience to climate change, and examine contamination vulnerability. Study results provide an improved understanding of appropriate tracer use in agricultural regions with isotopic variables able to provide important insights into the seasonality of hydrologic phenomena, such as the timing of groundwater recharge. A comparison of monitoring variables to present-day hydro-meteorological conditions suggests the importance of a winter dominated hydrologic regime and the potential influence of changes in precipitation on groundwater-surface water interactions. Estimated transit time dynamics indicate the likelihood for rapid contaminant transport through surface and shallow subsurface flow and highlight the possible effects of agricultural tile drainage. The sampling approach and data analysis methods adopted in this study provide the basis for improving routine watershed monitoring programs in agricultural regions.

A Novel Equivalent Time Sampling-Based Method for Pulse Transit Time Estimation with Applications into the Cardiovascular Disease Diagnosis.

The increasing incidence of cardiovascular diseases (CVDs) is reflected in additional costs for healthcare systems all over the world. To date, pulse transit time (PTT) is considered a key index of cardiovascular health status and for diagnosis of CVDs. In this context, the present study focuses on a novel image analysis-based method for PTT estimation through the application of equivalent time sampling. The method, which post-processes color Doppler videos, was tested on two different setups: a Doppler flow phantom set in pulsatile mode and an in-house arterial simulator. In the former, the Doppler shift was due to the echogenic properties of the blood mimicking fluid only, since the phantom vessels are non-compliant. In the latter, the Doppler signal relied on the wall movement of compliant vessels in which a fluid with low echogenic properties was pumped. Therefore, the two setups allowed the measurement of the flow average velocity (FAV) and the pulse wave velocity (PWV), respectively. Data were collected through an ultrasound diagnostic system equipped with a phased array probe. Experimental outcomes confirm that the proposed method can represent an alternative tool for the local measurement of both FAV in non-compliant vessels and PWV in compliant vessels filled with low echogenic fluids.

Land cover influence on catchment scale subsurface water storage investigated by multiple methods: Implications for UK Natural Flood Management

Study regionUnited Kingdom (UK). Study Focus‘Natural flood management’ (NFM) schemes manipulating land use and other catchment features to control runoff are increasingly promoted across the UK. Catchment water storage and mixing processes influence runoff, but our understanding of the effects of land cover change on these processes is still limited. This study combined hydrometric, isotopic and geochemical measurements to investigate land cover versus potential topographic, soil and geological controls. It compared storage-discharge dynamics in nine nested catchments within a 67 km2 managed upland catchment in southern Scotland. Storage and mixing dynamics were characterised from hydrometric data using recession analysis and from isotopic data using mean transit time and young water fraction estimates. To give information on water sources, groundwater fraction was estimated from end member mixing analysis based on acid neutralising capacity. New hydrological insightsThe analysis showed low but variable sub-catchment scale dynamic storage (16–200 mm), mean transit times (134–370 days) and groundwater fractions (0.20–0.52 of annual stream runoff). Soil hydraulic conductivity was most significantly positively correlated with storage and mixing measures, whilst percentage forest cover was inversely correlated. Any effects of forest cover on increasing catchment infiltration and storage are masked by soil hydraulic properties even in the most responsive catchments. This highlights the importance of understanding dominant controls on catchment storage when using tree planting as a flood management strategy.

Assessment of Arterial Transit Time and Cerebrovascular Reactivity in Moyamoya Disease by Simultaneous PET/MRI.

We investigated the relationship between MRI-arterial spin labeling (ASL) parameters and PET-cerebral blood flow (CBF)/cerebrovascular reactivity (CVR) simultaneously obtained by PET/MRI in Moyamoya disease. Twelve patients underwent 15O-water PET/MRI with the acetazolamide (ACZ) challenge test. PET-CBF and PET-CVR were measured using 15O-water PET. Pseudo-continuous ASL obtained the robust arterial transit time (ATT) and ASL-CBF estimation. ASL parameters were compared with PET-CBF and PET-CVR. Before ACZ loading, absolute and relative ASL-CBF were significantly correlated with absolute and relative PET-CBF (r = 0.44, p < 0.0001, and r = 0.55, p < 0.0001, respectively). After ACZ loading, absolute and relative ASL-CBF were significantly correlated with absolute and relative PET-CBF (r = 0.56, p < 0.001, and r = 0.75, p < 0.0001, respectively), and ΔASL-CBF was significantly correlated with ΔPET-CBF (r = 0.65, p < 0.0001). Baseline ASL-ATT had strong negative correlations with ΔPET-CBF and PET-CVR (r = -0.72, p < 0.0001, and r = -0.66, p < 0.0001, respectively). Baseline ASL-ATT of MCA territories with CVR <30% (1546 ± 79 ms) was significantly higher than that with CVR > 30% (898 ± 197 ms). ASL-ATT ratio of MCA territories with CVR < 30% (94.0 ± 10.5%) was significantly higher than that with CVR > 30% (81.4 ± 11.3%). ATT correction using multiple postlabeling delays increased the accuracy of ASL-CBF quantitation. Baseline ASL-ATT is a hemodynamic parameter and may represent an efficient alternative to PET-CVR.

A Novel Approach to Quantify Sediment Transfer and Storage in Rivers—Testing Feldspar Single‐Grain pIRIR Analysis and Numerical Simulations

AbstractQuantifying sediment transport and storage in fluvial systems is fundamental for understanding the transfer of eroded materials from source to sink. Here, we investigated the potential of a combined approach using a luminescence measured in modern fluvial sediments and numerical simulations to quantify transport and storage in rivers. We acquired luminescence data at the single‐grain scale on feldspar sediments of Waimakariri and Rakaia braided rivers (New Zealand) using a post infra‐red infra‐red stimulated luminescence protocol. We considered three metrics from the analysis of luminescence equivalent dose (De) distribution: the percentage of bleached and the percentage of saturated grains, and the meanDe. All three metrics show similar longitudinal trends along both rivers. To derive quantitative information on sediment transfer from these data, we developed a numerical model that simulates the longitudinal evolution ofDedistribution of a population of grains during transport and storage in floodplains. The model considers four main parameters: the transport length of grains during floods, their resting time between successive transport events, the bleaching probability (probability of the luminescence signal to be reset due to sunlight exposure during transport or rest), and the likelihood of partial bleaching. Identification of model parameters that best reproduce natural observations allowed estimating transit time of sediments between 2.1 and 10.3 Kyr (mean of 6.9 2.9 Kyr), corresponding to mean virtual transit velocity of 20–95 m.yr−1(mean of 46 28 m.yr−1). Our study illustrates the potential of the combined single‐grain luminescence and modeling approach to quantify sediment transfer in fluvial systems.

An All-Optical System for Transit Time Estimation in Fluids Using Single Source and Detector

An All-Optical System for Transit Time Estimation in Fluids Using Single Source and Detector