Periodic Flow Research Articles

The potential influence of genome-wide adaptive divergence on conservation translocation outcome in an isolated greater sage-grouse population.

Conservation translocations are an important conservation tool commonly employed to augment declining or reestablish extirpated populations. One goal of augmentation is to increase genetic diversity and reduce the risk of inbreeding depression (i.e., genetic rescue). However, introducing individuals from significantly diverged populations risks disrupting coadapted traits and reducing local fitness (i.e., outbreeding depression). Genetic data are increasingly more accessible for wildlife species and can provide unique insight regarding the presence and retention of introduced genetic variation from augmentation as an indicator of effectiveness and adaptive similarity as an indicator of source and recipient population suitability. We used 2 genetic data sets to evaluate augmentation of isolated populations of greater sage-grouse (Centrocercus urophasianus) in the northwestern region of the species range (Washington, USA) and to retrospectively evaluate adaptive divergence among source and recipient populations. We developed 2 statistical models for microsatellite data to evaluate augmentation outcomes. We used one model to predict genetic diversity after augmentation and compared these predictions with observations of genetic change. We used the second model to quantify the amount of observed reproduction attributed to transplants (proof of population integration). We also characterized genome-wide adaptive divergence among source and recipient populations. Observed genetic diversity (HO=0.65) was higher in the recipient population than predicted had no augmentation occurred (HO=0.58) but less than what was predicted by our model (HO=0.75). The amount of shared genetic variation between the 2 geographically isolated resident populations increased, which is evidence of periodic gene flow previously assumed to be rare. Among candidate adaptive genes associated with elevated fixation index (FST) (143 genes) or local environmental variables (97 and 157 genes for each genotype-environment association method, respectively), we found clusters of genes with related functions that may influence the ability of transplants to use local resources and navigate unfamiliar environments and their reproductive potential, all possible reasons for low genetic retention from augmentation.

Fast fluid–structure interaction simulation method based on deep learning flow field modeling

The rapid acquisition of high-fidelity flow field information is of great significance for engineering applications such as multi-field coupling. Current research in flow field modeling predominantly focuses on low Reynolds numbers and periodic flows, exhibiting weak generalization capabilities and notable issues with temporal inferring error accumulation. Therefore, we establish a reduced order model (ROM) based on Convolutional Auto-Encoder (CAE) and Long Short-Term Memory (LSTM) neural network and propose an unsteady flow field modeling method for the airfoil with a high Reynolds number and strong nonlinear characteristics. The attention mechanism and weak physical constraints are integrated into the model architecture to improve the modeling accuracy. A broadband excitation training strategy is proposed to overcome the error accumulation problem of long-term inferring. With only a small amount of latent codes, the relative error of the flow field reconstructed by CAE can be less than 5‰. By training LSTM with broadband excitation signals, stable dynamic evolution can be achieved in the time dimension. CAE-LSTM can accurately predict the forced response and complex limit cycle behavior of the airfoil in a wide range of amplitude and frequency under subsonic/transonic conditions. The relative errors of predicted variables and integral force are less than 1%. The fluid–structure interaction framework is built by coupling the ROM and motion equations of the structure. CAE-LSTM predicts the time series response of pitch displacement and moment coefficient at different reduced frequencies, which is in good agreement with computational fluid dynamics, and the simulation time savings exceed one order of magnitude.

The effect of the four-tentacled collaboration on the self-propelled performance of squid robot

This study conducts a numerical investigation of the self-propelled performance of a bio-inspired squid robot equipped with four rigid tentacles, exploring three sets of collaborative modes. Leveraging the open-source platform OpenFOAM, we develop a self-propulsion module incorporating the dynamic overset grid technique to manipulate the complex motion of rigid tentacles. The driving system of a single tentacle is simplified into a two-link mechanism, where the phase difference between the links effectively emulates the oscillatory pattern of fish-like locomotion. The interaction of four tentacles gives rise to three distinct driving modes: reverse, homologous, and interlace modes. The results indicate that the homologous mode follows the hydrodynamic characteristics of fish-like waves, the interlace mode can cause the robot to deviate from the initial path, and the reverse mode outperforms the other two modes, exhibiting a higher ultimate cruising speed. Regardless of the propulsion process, the cruising performance of the robot is significantly influenced by the maximum amplitude angle θmax. An increase in θmax also contributes to an elevation in the instantaneous longitudinal force coefficient CFx, with the most pronounced impact observed in the homologous mode. The disparity among the three modes is also evident in the periodic pressure variation and flow field evolution patterns. The vortex distribution during steady-state moments systematically reveals the collaborative effects among the tentacles in different modes on the self-propulsion performance.

Investigating the use of 3-component-2-dimensional particle image velocimetry fields as inflow boundary condition for the direct numerical simulation of turbulent channel flow

Direct numerical simulation (DNS) of turbulent wall-bounded flows requires long streamwise computational domains to establish the correct spatial evolution of large-scale structures with high fidelity. In contrast, experimental measurements can relatively easily capture large-scale structures but struggle to resolve the dissipative flow scales with high fidelity. One methodology to overcome the shortcomings of each approach is by incorporating experimental velocity field measurements into DNS as an inflow boundary condition. This hybrid approach combines the strengths of DNS and experimental measurements, allowing for a reduction in the streamwise computational domain and accelerated development of large-scale structures in turbulent wall-bounded flows. To this end, this paper reports the results of an investigation to establish the impact of limited spatial resolution and limited near-wall experimental inflow data on the DNS of a wall-bounded turbulent shear flow. Specifically, this study investigates the spatial extent required for the DNS of a turbulent channel flow to recover the turbulent velocity fluctuations and energy when experimental inflow data is typically unable to capture fluctuations down to the viscous sub-layer or the smallest viscous scales (i.e. the Kolmogorov scale or their surrogate viscous scale in wall-bounded turbulent shear slows) is used as the inflow to a DNS. A time-resolved numerically generated experimental field is constructed from a periodic channel flow DNS (PCH-DNS) at Reτ=\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Re_{\ au } =$$\\end{document} 550 and 2300, which is subsequently used as the inflow velocity field for an inflow–outflow boundary conditions DNS. The time-resolved experimental inflow field is generated by appropriately filtering the small scales from the PCH-DNS velocity by integrating over a spatial domain that is representative of a particle image velocimetry interrogation window. This study shows that the recovery of small scales requires a longer domain as the spatial resolution at the inflow decreases with all flow scales recovered and their correct scale-dependent energy is re-established once the flow has developed for 3 channel heights.

Mechanism of periodic oscillation in low-Reynolds-number buffet around an airfoil at angle of attack 0

In this study, the low-frequency oscillations found in the compressible low-Reynolds-number regime, defined as low-Reynolds-number buffet, were investigated by numerical calculations and modal analysis. Dynamic mode decomposition (DMD) and compressive sensing methods were employed to extract periodic flow structures. Numerical simulation results showed low-Reynolds-number buffet and Kármán vortex shedding. Low- and high-frequency oscillations [St=O(0.01), O(1.0)] were extracted by DMD and named the buffet mode and vortex shedding mode, respectively. Low-Reynolds-number buffet does not necessarily exhibit supersonic regions or shock wave. Simulation results show that the thickness of the separated shear layer changes significantly under low-Reynolds-number buffet. The change in the thickness of the separated shear layer was confirmed by the buffet mode of DMD results. Two types of compression pressure waves, advecting upstream, were identified. DMD indicated that they resulted from vortex shedding. According to simulation and DMD results, the origin of the shock waves appears to be the condensation of compression pressure waves due to the vortex shedding mode and expansion in the supersonic region due to the buffet mode. The formation of the shock waves seems to be subordinated to the vortex shedding mode and the buffet mode. A feedback model for low-Reynolds-number buffet inherent in separated shear layers, which does not require supersonic regions or shock waves, was proposed. Supersonic regions highly condensed the compression pressure waves, inducing a larger separation region and amplifying the oscillation. The role of supersonic regions in determining oscillation amplitudes was evidenced, although supersonic regions are not essential to the mechanism of low-Reynolds-number buffet.

Analysis of hydraulic losses in the series from 1990 to 2022 at the Retiro small hydroelectric power plant

Hydraulic losses are a crucial variable in hydroelectric ventures as they can cause significant reductions in power generation. This article analyses the impact of hydraulic losses on the Retiro Small Hydroelectric Power Plant (SHPP), investigating their effect on monthly average power and, consequently, the efficiency of electricity generation. This study examines the historical series of load losses at the Retiro SHPP from 1990 to 2022. The calculations are based on flow data available in HidroWeb. The study considered the maximum and minimum flow rates in the historical flow series as constraints for hydropower generation. We used a multivariable function to calculate the efficiency of the hydraulic turbine, relating the turbine flow rate and the net water head. We developed mathematical relationships for head losses that occur in the grid, at the water intake, and due to friction from the intake to the turbine of the Retiro SHPP. The article presents a comparison between the actual monthly average power of the Small Hydroelectric Power Plant (SHPP) and the simulated monthly average power. We normalized the data for turbine flow and load loss to conduct statistical analysis. Kernel probability density was applied to understand the distribution shape of the data. Findings show that average monthly capacity is lowest in September, at approximately 0.81 MW. In March, the highest power occurs, approximately 14.19 MW. During the high flow period, the simulated average power, which accounts for load losses, closely matched the actual average power generated at the Retiro SHPP. In the months from July to October, despite being the period with the lowest head losses, it is the time when there is a greater opportunity to maximize energy generation at the power plant. An inefficient power generation system experiences significant load losses during specific periods of the year. To minimize this effect, it is crucial to understand the behavior of hydraulic losses and consider implementing mitigating measures.

2021–2022年鄱阳湖丰水期水体富营养化指标空间分布数据集

Poyang Lake, the largest lake connected to the Yangtze River, plays an important role in preserving the ecological balance of the Yangtze River Basin. However, due to the escalating effects of climate change and human activities, the eutrophication status of the lake has been increasing year by year, resulting in a gradual deterioration of its ecological function. In order to study the spatio-temporal variation characteristics of eutrophication in Poyang Lake and protect its water resources and environment, we systematically collected water samples from 72 sites across the lake during the peak algae growth periods of the summers from 2021 to 2022. In the laboratory, the determination of eutrophication indicators, including total nitrogen, total phosphorus, permanganate index and chlorophyll-a at sampling sites was conducted in strict accordance with the methods stipulated by national standards and industrial standards. Based on this, we obtained the dataset of spatial distribution of water eutrophication indicators in Poyang Lake during high flow period from 2021 to 2022. This dataset can provide precise insights into the water pollution and eutrophication status, as well as the spatial distribution characteristics of Poyang Lake during high flow season, which has important data supporting significance for the pollution control of Poyang Lake basin and water environment protection of the Yangtze River basin.

Living with hypoxia: Residence and site fidelity by golden perch (Macquaria ambigua) in habitats affected by methane seeps and chronic hypoxia

Abstract We conducted an acoustic telemetry study of native golden perch (Macquaria ambigua) to examine movement behaviour in areas affected by methane seeps and hypoxia in the intermittent Condamine River, Murray‐Darling Basin (MDB), Australia. Fish were collected during periods of no flow and hypoxia (dissolved oxygen [DO] <1 mg/L). Despite these conditions, 38 of 43 fish tagged with acoustic transmitters were detected for >3 months post‐tagging in the study reach and 27 fish were being detected after 14 months. During periods of elevated river flow and relatively high DO, 30 fish moved away from their original tagging locations, with three undertaking movements (>7 km) outside the study reach and not returning. Generalised additive mixed models showed a significant increase in the probability of movement as soon as flow commenced and when water temperatures exceeded 19°C. As flows receded, most fish that had moved exhibited accurate homing behaviour to their original tagging location. The patterns of movement and site fidelity exhibited by golden perch correspond with previous studies of the species in intermittent rivers not affected by methane seeps and severe hypoxia, suggesting that the methane seeps and hypoxia did not inhibit fish movement nor render the affected habitats unsuitable for habitation. Golden perch can survive and remain active in water with much lower DO (<1 mg/L) than previously described for large‐bodied native fishes in the MDB. However, fish condition in the study reach was slightly lower than other regions of the MDB, providing preliminary evidence that fish residing in habitats affected by chronic hypoxia and methane seepage may experience sub‐lethal stress. Our results demonstrate the importance of field‐based data on the behavioural and physiological responses of fish to chronic hypoxia and methane exposure to guide appropriate management responses.

DYNAMIC ASSESSMENT OF CEREBRAL PERFUSION BLOOD FLOW IN THE EARLY POST-STROKE PERIOD ACCORDING TO NON-CONTRAST MRI DATA

HighlightsThe non-contrast perfusion MR sequence pCASL (pseudocontinuous arterial spin labeling) is a technique that allows specialist to quantify and trace the changes in cerebral blood flow in the early post-stroke period. At the same time, there is a change in perfusion indices not only in the ischemic stroke area, but also in visually intact areas of the ipsilateral and contralateral hemispheres of the brain, which indicates the involvement of the blood supply area and the brain as a whole in the pathological process. The obtained data on the dynamics in perfusion, verified by the results of cognitive tests, open up the prospect of a comprehensive study of stroke as a complex brain disease with the possibility of predictive assessment of rehabilitation. Aim. To assess the dynamics of microcirculatory changes in the brain in the early post-stroke period by non-contrast perfusion MRI.Methods. The study included 42 patients with acute ischemic stroke. The patients were examined by 3T MRI using the following sequences: DWI-EPI, 3D FLAIR-SPIR, T2-TSE, T1W 3D-TFE, and pseudocontinuous arterial spin labeling (pCASL) on 1–3 days, 7–10 days and 3 months later after the manifestation of acute ischemic stroke. The cerebral blood flow (CBF) was obtained in 4 supratentorial regions of the brain: in the ischemic stroke and contralateral areas, as well as in a visually intact area of the ipsilateral and contralateral hemispheres (mL/100g/min).Results. In the ischemic stroke area, CBF increased from 19.86±5.69 (mean+Std) to 27.57±4.86 by first to the second examination, which was associated with the infusion therapy, local inflammatory response and compensatory reperfusion. By the 3rd examination CBF decreased to 14.48±3.66 (Student t-test, p<0.05), which reflects cystic and atrophic transformation of the affected area. In visually intact white matter of the ipsilateral and contralateral hemispheres, CBF increased from hypoperfused to normoperfused from the first to the third examination. There was a significant decrease (p<0.001) in tissue blood flow (by 54% for the 1st, 38% for the 2nd, 67% for the 3rd examination) in the ischemia area relative to intact parts of the brain.Conclusion. The pCASL allowed us to assess CBF in the post-stroke period in the ischemic area and in visually intact area, nevertheless, it requires additional pre- and postprocessing of data to obtain quantitative values. At the same time, we observed changes in perfusion in the ischemic stroke area, and in the visually intact areas of the ipsilateral and contralateral hemispheres of the brain, indicating the involvement of the cerebral blood flow and brain as a whole in the pathological process.

Incorporating environmental knowledge embedding and spatial-temporal graph attention networks for inland vessel traffic flow prediction

Accurate prediction of vessel traffic flow is crucial for maritime regulatory authorities and transportation planners. However, existing methods for inland vessel traffic flow prediction often overlook spatial correlation and environmental influences, leading to suboptimal accuracy. To address this issue, we propose an innovative model that incorporates environmental knowledge embedding and a spatial-temporal information extraction module. Our approach involves constructing a vessel traffic knowledge graph, embedding traffic flow through knowledge representation learning. The spatial-temporal information extraction module is leveraged to analyze inherent periodicity and external spatial relationships in vessel traffic flow. Extensive experiments on real-world datasets demonstrate that our approach significantly enhances predictive accuracy. In comparison to the second-ranked model, our approach achieves a decrease of 0.46 in mean absolute error, a decrease of 0.64 in root mean squared error, an increase of 3.06% in accuracy, and an increase of 0.07 in R-squared. Furthermore, our approach excels in upstream, downstream and long-term prediction, and displays robustness in handling noisy data.

Еволюція поглядів на функціональну анатомію міхурово-сечовідного сегмента та етіопатогенетичні особливості міхурово-сечовідного рефлюксу в дітей

Bladder-ureteral reflux is a pathological condition in which there is a periodic and/or permanent retrograde flow of urine from the bladder into the urinary tract due to a malfunction of the anti-reflux mechanism of the vesicoureteral segment. The aim - to study etio-pathological mechanisms of vesicoureteral reflux in children to improve diagnostic and therapeutic tactics. Every year in Ukraine, 3,600-3,700 children with congenital defects of the urinary tract are diagnosed, with 1/3 of the defects occurring in their upper parts. According to statistics, there are 40-50 cases of congenital diseases of the urinary system per 1000 newborns. There are reports that the frequency of vesicoureteral reflux in the general pediatric population exceeds 2%. According to modern data, vesicoureteral reflux accounts for 0.1% to 1.0% of all pathology in the general pediatric population, accounting for 10% of all diseases of the urinary system in hospitalized children. Bladder-ureter is the initial link in the chain of pathological reflux in the urinary tract. The leading importance of the mechanism of the vesicoureteral reflux belongs to the study functional anatomy of the urinary tract as a whole. Bladder-ureteral reflux is most often detected during urination against the background of increased intravesical pressure, but it can occur during any of the stages of the urination cycle. Nephrosclerosis with vesicoureteral reflux is formed in 30-60% of cases, which leads to the development of the terminal stage of chronic renal failure in 25-60% of patients due to a decrease in the functional renal reserve, as an indicator of the compensatory capabilities of the kidneys. Conclusions. Review of literature dataregarding the structure and functional anatomy of the vesicoureteral segment convincingly testifies to the complexity and multi-level organization of its antireflux mechanism. Therefore, any further research in this direction will undoubtedly contribute to a deeper understanding of the normal functioning of this complex anatomical part of the human urinary system, which will allow the development and implementation of the latest physiological treatment methods in the practice of pediatric surgeons. No conflict of interests was declared by the authors.

Evaluation of surface water supply impacts from permit exemptions: A comparison with climate change and demand growth

AbstractMany states in the Eastern U.S. have limited water withdrawal regulations, posing significant risks to water supply management during periods of low flows. While these states require water withdrawal permits, exemptions for grandfathered withdrawals that allow unregulated access to surface water are common. Such permit exemptions present a challenge to water supply management, as full utilization of allowable withdrawals by permit‐exempt users could pose risks to maintaining adequate water supplies for current and projected demand. This study used reported permit exemption data in Virginia to understand the extent, volume, and potential impact of permit‐exempt withdrawals on 30‐ and 90‐day low flows. The permit‐exempt withdrawal values used in this study were obtained from Virginia Department of Environmental Quality. Maximum permit‐exempt withdrawal volumes were significantly higher than projected future demands in permitted users. The impacts of these withdrawals on drought flows were compared with the impacts presented by climate change and demand growth. Widespread reduction in flows was observed with the “dry” future climate change scenario, while impacts were more localized in the exempt users and the demand growth scenarios. The impacts of exempt users exceeded the impact of climate change and demand growth scenarios in many regions during low‐flow periods. Therefore, more comprehensive water planning, policy and research is needed to address the impact of permit exemptions.

Data-driven RANS closures for improving mean field calculation of separated flows

Reynolds-averaged Navier-Stokes (RANS) simulations have found widespread use in engineering applications, yet their accuracy is compromised, especially in complex flows, due to imprecise closure term estimations. Machine learning advancements have opened new avenues for turbulence modeling by extracting features from high-fidelity data to correct RANS closure terms. This method entails establishing a mapping relationship between the mean flow field and the closure term through a designated algorithm. In this study, the k-ω SST model serves as the correction template. Leveraging a neural network algorithm, we enhance the predictive precision in separated flows by forecasting the desired learning target. We formulate linear terms by approximating the high-fidelity closure (from Direct Numerical Simulation) based on the Boussinesq assumption, while residual errors (referred to as nonlinear terms) are introduced into the momentum equation via an appropriate scaling factor. Utilizing data from periodic hills flows encompassing diverse geometries, we train two neural networks, each possessing comparable structures, to predict the linear and nonlinear terms. These networks incorporate features from the minimal integrity basis and mean flow. Through generalization performance tests, the proposed data-driven model demonstrates effective closure term predictions, mitigating significant overfitting concerns. Furthermore, the propagation of the predicted closure term to the mean velocity field exhibits remarkable alignment with the high-fidelity data, thus affirming the validity of the current framework. In contrast to prior studies, we notably trim down the total count of input features to 12, thereby simplifying the task for neural networks and broadening its applications to more intricate scenarios involving separated flows.

Streamflow response to catastrophic windthrow and forest recovery in subalpine spruce forest

Windstorms account for about half of forest disturbances in Europe and are considered as drivers of natural regeneration of plant species, accompanied by significant changes in hydrological and soil moisture conditions. Our study aims to identify the effects of deforestation caused by catastrophic windthrow on streamflow characteristics in conjunction with meteorological and soil moisture data. The research was conducted in the headwater catchment (34.4 km2), in the Western Tatra Mountains, Poland. Streamflow characteristics such as average, high, and low flows, coefficient of variability, as well as flashiness of the streamflow (Richard-Baker Flashiness Index) and drought frequency (Standardised Streamflow Index) were calculated in the pre-event (2007–2013) and post-event (2013–2020) periods. The analysis was carried out for calendar months, seasons of the year, as well as for the growing and non-growing seasons. Wavelet Analysis was applied to track the changes in streamflow time series in relation to meteorological conditions (precipitation, air temperature) and remotely sensed soil wetness in the root zone. Principal Components Analysis was applied in order to identify the major drivers of the observed variability. The results revealed increasing low (+14%), average (+8%), and maximum monthly flows (16%) in the post-event period. The most significant increase in low flows (+47%, p<0.1) occurred during snowmelt. The increase in average (+31%, p<0.1) and high flows (+90%, p<0.05) occurred during mid-winter thaws. The frequency of hydrological droughts decreased by up to 36% in the post-event period, despite similar climatic conditions. The flashiness of streamflow increased during mid-winter thaws and rainfall events. The short-scale periodicity in streamflow increased in the post-event period. The results revealed the presence of 3-month periodicity in the root zone soil wetness associated with long-term soil water storage, which decreased after the catastrophic windthrow. Streamflow in the post-event period became strongly coupled with precipitation and root zone soil wetness at short period bands (∼3–16 days) in hydrologically active season. Short-scale correlation between precipitation and streamflow was decreasing with the gradual succession of vegetation.

A Comparative Analysis of Passenger Flow Forecasting in Trams Using Machine Learning Algorithms

Forecasting tram passenger flow is an important part of the intelligent transportation system since it helps with resource allocation, network design, and frequency setting. Due to varying destinations and departure times, it is difficult to notice large fluctuations, non-linearity, and periodicity of tram passenger flows. In this paper, the first-order difference technique is used to eliminate seasonal structure from the time series data and the performance of different machine learning algorithms on passenger flow forecasting in trams is evaluated. Furthermore, the impact of the Covid-19 pandemic on forecasting success is examined. For this purpose, the tram data of Kayseri Transportation Inc. for the years 2018-2021 are used. Different estimation models including Linear Regression, Support Vector Regression, Random Forest, Artificial Neural Network, Convolutional Neural Network, and LongTerm Short Memory are applied and the time series forecasting performances of the models are evaluated with MAPE and R2 metrics.

Periodic electroosmotic flow of nanofluids with slip-dependent high zeta potential

The time periodic electroosmotic flow of nanofluids is investigated analytically in a hydrophobic microchannel. In this study, we consider the interdependence relationship between the wall electrical potential and slip. According to the non-linear slip-dependent zeta potential, we obtain an analytical solution of electrical potential for arbitrary value of wall electrical potential. Subsequently, we give the analytical integration expression of time periodic electroosmotic velocity of nanofluids. Based on the obtained electrical potential distribution, the oscillating flow velocity and rate are calculated numerically. The flow characteristics are determined by the oscillating frequency of electrical field, the volume fraction of nanoparticles and wall electrical potential. The noteworthy results are that, the oscillating electrical field can result in the oscillation of nanofluids. However, such oscillation is strongly dependent on the electrical field frequency and the flow characteristics are significantly different for various frequencies. Moreover, when the nanoparticles are introduced into the time periodic electroosmotic flow, the oscillation can be restrained. This may be helpful to understand the electrohydrodynamic instability of nanofluids.

The Effects of Wastewater Reuse on Smallmouth Bass (Micropterus dolomieu) Relative Abundance in the Shenandoah River Watershed, USA.

Municipal and industrial wastewater effluent is an important source of water for lotic systems, especially during periods of low flow. The accumulated wastewater effluent flows-expressed as a percentage of total streamflow (ACCWW%)-contain chemical mixtures that pose a risk to aquatic life; fish may be particularly vulnerable when chronically exposed. Although there has been considerable focus on individual-level effects of exposure to chemical mixtures found in wastewater effluent, scaling up to population-level effects remains a challenging component needed to better understand the potential consequences of exposure in wild populations. This may be particularly important under a changing climate in which wastewater reuse could be essential to maintain river flows. We evaluated the effects of chronic exposure to wastewater effluent, as measured by ACCWW%, on the relative abundance of young-of-year (YOY), juvenile, and adult smallmouth bass (Micropterus dolomieu) populations in the Shenandoah River Watershed (USA). We found that increases in ACCWW% in the previous year and during the prespawn period were negatively correlated with the relative abundance of YOY, resulting in an average 41% predicted decrease in abundance (range = 0.5%-94% predicted decrease in abundance). This lagged effect suggests that adult fish reproductive performance may be compromised by chemical exposure during periods of high ACCWW%. No relationships between ACCWW% and juvenile or adult relative abundance were found, suggesting that negative effects of ACCWW% on YOY abundance may be offset due to compensatory mechanisms following higher ACCWW% exposure. Understanding the effects of wastewater effluent exposure at multiple levels of biological organization will help in the development of management strategies aimed at protecting aquatic life. Environ Toxicol Chem 2024;43:1138-1148. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Stimulus type and duration affect magnitude and evolution of flicker-induced hyperemia measured by laser speckle flowgraphy at the optic disc and peripapillary vessels

Neurovascular coupling is a vital mechanism employed by the cerebrovascular system, including the eye, to regulate blood flow in periods of neuronal activation. This study aims to investigate if laser speckle flowgraphy (LSFG) can detect coupling response elicited by flickering light stimuli and how variations in stimulus type and duration can affect the magnitude and evolution of blood flow in the optic nerve head (ONH) and peripapillary vessels. Healthy adults were exposed to two types of 10-Hz flicker stimuli: a photopic negative response-like stimulus (PhNR-S) or a visual evoked potential-like stimulus (VEP-S)—each presented in separate 10- and 60-s epochs. Both PhNR-S and VEP-S significantly increased ONH blood flow (p < 0.001) immediately after flicker cessation, with a trend of 60-s stimuli (PhNR-S = 11.6%; VEP-S = 10.4%) producing a larger response than 10-s stimuli (PhNR-S = 7.5%; VEP-S = 6.2%). Moreover, exposure to 60-s stimuli elicited a significantly prolonged ONH hyperemic response, especially with PhNR-S. Lastly, stimulation with either 60-s stimuli elicited a robust increase in blood flow within the peripapillary arterioles (p < 0.01) and venules (p < 0.01) as well. Flicker stimulation with common visual electrophysiology stimuli (PhNR-S and VEP-S) induced a demonstrable increase in ONH and peripapillary vessel blood flow, which varied with flicker duration. Our results validate that LSFG is a robust method to quantify flicker-induced hyperemic responses and to study neurovascular coupling in humans.

Typology and classification of water quality in an intermittent river in a semi-arid Mediterranean climate.

The typology and classification of rivers are highly relevant concepts in the field of limnology and freshwater ecology. Water body typology systematically categorizes water bodies based on their natural attributes, while water body classification groups them based on specific criteria or purposes for management, regulatory, or administrative reasons. Both concepts play important roles in understanding and managing water resources effectively. This scientific article focuses on the ZAT River in Morocco as a model for studying low-flow and intermittent rivers. The objective is to develop an accurate model for the typology and classification of small, low-flow rivers into homogeneous classes based on natural and anthropogenic factors. The study also investigates the impact of human activities on altering the uniformity and reference nature of the water body. The typology of water bodies is carried out according to the European methodology specified in The European Commission's Water Framework Directive (WFD) in 2000. The classification of water bodies is conducted by assessing their chemical and biological quality using the weighted index (WI), the Iberian Biological Monitoring Working Group (IBMWP) index, and multivariate statistical methods such as principal component analysis (PCA) for confirming water quality assessment. The results indicate the possibility of dividing the basin into four water bodies. Water bodies show homogeneity in terms of chemical quality when human influence is minimal or during periods of high river flow. However, increased human influence and decreased river flows lead to heterogeneity in chemical quality, indicating an unstable state. This study is the first of its kind in arid and semi-arid intermittent rivers, where such an approach could be suggested to determine their typology and classification.

On robust boundary treatments for wall‐modeled LES with high‐order discontinuous finite element methods

SummaryTo robustly and accurately simulate wall‐bounded turbulent flows at high Reynolds numbers, we propose suitable boundary treatments for wall‐modeled large‐eddy simulation (WMLES) coupled with a high‐order flux reconstruction (FR) method. First, we show the need to impose an auxiliary boundary condition on auxiliary variables (solution gradients) that are commonly introduced in high‐order discontinuous finite element methods (DFEMs). Auxiliary boundary conditions are introduced in WMLES, where the grid resolution is too coarse to resolve the inner layer of a turbulent boundary layer. Another boundary treatment to further enhance stability with under‐resolved grids, is the use of a modal filter only in the wall‐normal direction of wall‐adjacent cells to remove the oscillations. A grid convergence study of turbulent channel flow with a high Reynolds number () shows that the present WMLES framework accurately predicts velocity profiles, Reynolds shear stress, and skin friction coefficients at the grid resolutions recommended in the literature. It was confirmed that a small amount of filtering is sufficient to stabilize computation, with negligible influence on prediction accuracy. In addition, non‐equilibrium periodic hill flow with a curved wall, including flow separation, reattachment, and acceleration at a high Reynolds number (), is reported. Considering stability and the prediction accuracy, we recommend a loose auxiliary wall boundary conditions with a less steep velocity gradient for WMLES using high‐order DFEMs.