Spatiotemporal insights of phytoplankton dynamics in a northern, rural-urban lake using a 3D water quality model.

Lake St. Charles, located north of Quebec City, Canada, is a shallow fluvial lake with two distinct basins bridging rural and urban landscapes. Mainly used as a source of drinking water for 300,000 residents, the lake has faced a steady degradation in water quality due to urbanization and the discharge of domestic wastewater. This study introduces a 3D hydrodynamics and water quality model using the Environmental Fluid Dynamics Code to enhance our understanding of algal bloom dynamics in Lake St. Charles. More specifically, we ran simulations for eight years (i.e., a three-year period for calibration, 2015 to 2017; and a five-year period for validation, 2018 to 2022) to reproduce the complex circulation patterns and dynamics of water quality within the system. The simulation results for chlorophyll-a demonstrate seasonal fluctuations in phytoplankton biomass, closely aligning with in situ observations and achieving Relative Root Mean Square Error (RRMSE) values below 50%. (i) In spring, runoff from snowmelt brought phosphorus into the lake, triggering primary production. Diatom growth was initially predominant in the shallow southern basin, then spread to the deeper northern basin due to favorable environmental conditions, including flow- and wind-induced currents, warmer water temperatures and nutrient availability. (ii) In summer, warm water temperatures stimulated biological activity, leading to the growth of cyanobacteria at the expense of diatoms, as well as a drop in phosphorus. (iii) The cyanobacteria persisted into the fall but began to decline in mid-November. (iv) Winter conditions, including the presence of an ice cover, limited the input of phosphorus and minimized phytoplankton production, but diatoms were observed in low concentrations near Des Hurons River inflow. Overall, during the open-water period, the lake-maintained chlorophyll-a concentrations indicative of mesotrophic conditions, with occasional periods when the biomass increased above the eutrophic threshold. Temperature, nutrient levels, and the fluvial dynamics of the lake are the primary factors influencing phytoplankton formation and distribution in lake St. Charles.

Outcomes of COVID-19 in 24 hospitalized liver transplant recipients: an observational study.

BACKGROUND: Although liver transplant (LT) recipients are considered a population at risk of severe features of coronavirus disease 2019 (COVID-19), data in this regard are scarce and controversial. In this study, we reported the outcome of 24 cases of LT recipients who were hospitalized due to COVID-19 and investigated the role-playing factors in the severity of the disease. METHODS: In this single-center, analytic case-series study, eligible patients were among LT recipients who were hospitalized due to the diagnosis of COVID-19 based on positive results of polymerase chain reaction. Participants were categorized as severe COVID-19 if they were admitted to the intensive care unit, experienced respiratory failure demanding mechanical ventilation, or eventually died. Demographic and clinical data, COVID-19 symptoms and specific treatments, laboratory biomarkers, and immunosuppressive regimens and their alteration during the admission were recorded. Analysis was done using SPSS software. RESULTS: Twenty-four hospitalized LT patients were included, of which nine had severe and fifteen had non-severe COVID-19. Out of 9 patients with severe COVID-19, four sadly died. The analysis and comparison between the two groups revealed longer hospital stays (P = 0.02), lower lymphocyte counts (P = 0.002), and higher levels of C-reactive protein (CRP) (P = 0.006) in patients with severe COVID-19. Patients with non-severe COVID-19 had higher doses of tacrolimus and mycophenolate in their baseline immunosuppressive regimen (both P = 0.02). CONCLUSION: Lymphopenia and high CRP levels are associated with more severe forms of COVID-19 in LT patients. Mycophenolate may have protective properties against severe COVID-19. The role of severity indicators in LT patients with COVID-19 needs to be systematically recognized.

The role of cognitive emotion regulation strategies in predicting the resilience, symptom severity, and quality of life of patients with irritable bowel syndrome.

BACKGROUND: Psychosocial stressors contribute to the development of irritable bowel syndrome (IBS) and exacerbate the symptoms. The capability to cope with stress is an essential element in the management of IBS. This study assessed nine cognitive emotion regulation strategies (CERS) and their role in predicting symptom severity, quality of life (QOL), and resilience in IBS subjects. METHODS: The scores regarding nine subscales of CERS were obtained by cognitive emotion regulation questionnaire (CERQ) and compared between study patients based on the severity and subtypes of IBS using one-way ANOVA. To evaluate the predictive role of CERS, logistic regression was performed. The correlation between CERS and the QOL was assessed by Pearson correlation analysis. The score of resilience was measured by Connor-Davidson Resilience Scale (CD-RISC). RESULTS: We recruited 100 patients diagnosed with IBS based on ROME IV criteria. Among nine subscales of CERS, patients with more severe symptoms scored higher in catastrophizing (p < 0.001) and blaming others (p = 0.015) while lower in positive reappraisal (p = 0.028). Blaming others was the only predictor of resilience and severity of IBS in our patients (odds ratio (OR): -2.103, p=0.028, and OR:1.715, p = 0.049, respectively). We observed significant negative correlations between the quality of life and rumination (r= -0.202, p=0.044), self-blame (r= -0.241, p=0.016), catastrophizing (r= -0.342, p<0.001), and blaming others (r= -0.219, p=0.028). CONCLUSION: Maladaptive strategies are more common in IBS patients with more severe symptoms and have negative correlations with the QOL. Blaming others has the potential to predict the resilience and severity of symptoms in IBS patients.

Investigation about the correlation between the severity of metabolic-associated fatty liver disease and adherence to the Mediterranean diet.

BACKGROUND: Metabolic-associated fatty liver disease (MAFLD) is defined by fatty liver combined with a disturbed metabolic state. Mediterranean diet (MedDiet) contains anti-inflammatory, anti-oxidative, and anti-fibrotic components and is seemingly beneficial in the management of MAFLD. We aimed to evaluate the correlation between adherence to MedDiet and the severity of MAFLD. MATERIALS AND METHODS: Totally 101 adult patients diagnosed with MAFLD were enrolled in this cross-sectional study. Persian version of Mediterranean Diet Adherence Screener (MEDAS), demographics, clinical, laboratory, and FibroScan findings were collected. Correlation and regression analyses were performed. RESULTS: The mean of participants' age was 49.37 ± 12.14 (51.48 % male subjects). Six patients (5 diabetic and 1 pre-diabetic) had advanced fibrosis. Overall, 48.5 % had good adherence to MedDiet [the least MEDAS-1 (15.8 %) and the highest MEDAS-13 (99 %)]. The adherence score was significantly higher in married, female, non-smoker, and diabetic subjects, and patients with hypertension. Adherence to MedDiet had insignificant correlations with hepatic fibrosis (P = 0.888), steatosis (P = 0.208), waist-to-height ratio (P = 0.853), and FIB-4 score (P = 0.919). Vitamin D level had just significant inverse associations with steatosis score (r = -0.21, P = 0.037) and no significant association was found with fibrosis score (r = -0.036, P = 0.717) and MedDiet adherence (r = 0.055, P = 0.581). According to the multiple regression analyses, less fruit intake, lower platelet count and DM had significant positive correlations with MAFLD severity (P < 0.001). CONCLUSION: Adherence to Mediterranean diet, particularly a higher fruit intake, is associated with a lower severity of MAFLD. Dietary modification based on taste, economic state, and culture should be deliberated in different geographic areas along with nutritional education.

A 3D numerical modeling of the links between hydrodynamics, dissolved oxygen, and water temperature of a northern rural-urban shallow lake with two distinct basins.

A 3D hydrodynamic model (EFDC) was applied to simulate dissolved oxygen (DO) and temperature (T) (two crucial parameters impacting water quality) throughout Lake St. Charles, a rural-urban shallow lake located North of Quebec City, Canada. Model outputs of T and DO corroborate observations at five monitoring stations within the lake. Simulated results indicated annual cycles of turnovers and stratifications and different behaviors for the deep and shallow basins. For the simulated years, the deep basin was stratified in summer and winter, while the shallow basin was mostly mixed throughout the year. The lake heat budget indicates that during summer with a long retention time, the thermal structure of the lake is principally controlled by net radiation, latent, and sensible heat fluxes. For the rest of the year, the inflow (from the main tributary, the Des Hurons River) and outflow are the main drivers of the lake's thermal structure.

JRDB: A Dataset and Benchmark of Egocentric Robot Visual Perception of Humans in Built Environments.

We present JRDB, a novel egocentric dataset collected from our social mobile manipulator JackRabbot. The dataset includes 64 minutes of annotated multimodal sensor data including stereo cylindrical 360 ° RGB video at 15 fps, 3D point clouds from two 16 planar rays Velodyne LiDARs, line 3D point clouds from two Sick Lidars, audio signal, RGB-D video at 30 fps, 360 ° spherical image from a fisheye camera and encoder values from the robot's wheels. Our dataset incorporates data from traditionally underrepresented scenes such as indoor environments and pedestrian areas, all from the ego-perspective of the robot, both stationary and navigating. The dataset has been annotated with over 2.4 million bounding boxes spread over five individual cameras and 1.8 million associated 3D cuboids around all people in the scenes totaling over 3500 time consistent trajectories. Together with our dataset and the annotations, we launch a benchmark and metrics for 2D and 3D person detection and tracking. With this dataset, which we plan on extending with further types of annotation in the future, we hope to provide a new source of data and a test-bench for research in the areas of egocentric robot vision, autonomous navigation, and all perceptual tasks around social robotics in human environments.

Impacts of Varying Dam Outflow Elevations on Water Temperature, Dissolved Oxygen, and Nutrient Distributions in a Large Prairie Reservoir.

Dam operations are known to have significant impacts on reservoir hydrodynamics and solute transport processes. The Gardiner Dam, one of the structures that forms the Lake Diefenbaker reservoir located in the Canadian Prairies, is managed for hydropower generation and agricultural irrigation and is known to have widely altering temperature regimes and nutrient circulations. This study applies the hydrodynamic and nutrient CE-QUAL-W2 model to explore how various withdrawal depths (5, 15, 25, 35, 45, and 55 m) influence the concentrations and distribution of nutrients, temperature, and dissolved oxygen (DO) within the Lake Diefenbaker reservoir. As expected, the highest dissolved nutrient (phosphate, P O 4 3 - - P and nitrate, N O 3 - - N ) concentrations were associated with hypoxic depth horizons in both studied years. During summer high flow period spillway operations impact the distribution of nutrients, water temperatures, and DO as increased epilimnion flow velocities route the incoming water through the surface of the reservoir and reduce mixing and surface warming. This reduces reservoir concentrations but can lead to increased outflow nitrogen (N) and phosphorus (P) concentrations. Lower withdrawal elevations pull warmer surface water deeper within the reservoir and decrease reservoir DO during summer stratification. During fall turnover low outflow elevations increase water column mixing and draws warmer water deeper, leading to slightly higher temperatures and nutrient concentrations than shallow withdrawal elevations. The 15 m depth (540 m above sea level) outflow generally provided the best compromise for overall reservoir and outflow nutrient reduction.

CE-QUAL-W2 model of dam outflow elevation impact on temperature, dissolved oxygen and nutrients in a reservoir.

Dams are typically designed to serve as flood protection, provide water for irrigation, human and animal consumption, and harness hydropower. Despite these benefits, dam operations can have adverse effects on in-reservoir and downstream water temperature regimes, biogeochemical cycling and aquatic ecosystems. We present a water quality dataset of water withdrawal scenarios generated after implementing the 2D hydrodynamic and water quality model, CE-QUAL-W2. The scenarios explore how six water extraction scenarios, starting at 5 m above the reservoir bottom at the dam and increasing upward at 10 m intervals to 55 m, influence water quality in Lake Diefenbaker reservoir, Saskatchewan, Canada. The model simulates daily water temperature, dissolved oxygen, total phosphorus, phosphate as phosphorus, labile phosphorus, total nitrogen, nitrate as nitrogen, labile nitrogen, and ammonium at 87 horizontal segments and at 60 water depths during the 2011-2013 period. This dataset intends to facilitate a broader investigation of in-reservoir nutrient dynamics under dam operations, and to extend the understanding of reservoir nutrient dynamics globally.

Sedimentation and erosion in Lake Diefenbaker, Canada: solutions for shoreline retreat monitoring.

This study looks into sedimentation and erosion rates in Lake Diefenbaker, a prairie reservoir, in Saskatchewan, Canada, which has been in operation since 1968. First, we looked at the historical data in all different formats over the last 70 years, which includes data from more than 20 years before the formation of the lake. The field observations indicate high rates of shoreline erosion, especially in the upstream portion as a potential region for shoreline retreat. Because of the great importance of this waterbody to the province, monitoring sedimentation and erosion rates is necessary for maintaining the quality of water especially after severe floods which are more common due to climate change effects. Second, we used Google Maps Elevation API, a new tool from Google that provides elevation data for cross sections drawn between two points, by drawing 24 cross sections in the upstream area extending 250 m from each bank. This feature from Google can be used as an easy and fast monitoring tool, is free of charge, and provides excellent control capabilities for monitoring changes in cross-sectional profiles.

Sediment plume model-a comparison between use of measured turbidity data and satellite images for model calibration.

In this study, we built a two-dimensional sediment transport model of Lake Diefenbaker, Saskatchewan, Canada. It was calibrated by using measured turbidity data from stations along the reservoir and satellite images based on a flood event in 2013. In June 2013, there was heavy rainfall for two consecutive days on the frozen and snow-covered ground in the higher elevations of western Alberta, Canada. The runoff from the rainfall and the melted snow caused one of the largest recorded inflows to the headwaters of the South Saskatchewan River and Lake Diefenbaker downstream. An estimated discharge peak of over 5200 m3/s arrived at the reservoir inlet with a thick sediment front within a few days. The sediment plume moved quickly through the entire reservoir and remained visible from satellite images for over 2 weeks along most of the reservoir, leading to concerns regarding water quality. The aims of this study are to compare, quantitatively and qualitatively, the efficacy of using turbidity data and satellite images for sediment transport model calibration and to determine how accurately a sediment transport model can simulate sediment transport based on each of them. Both turbidity data and satellite images were very useful for calibrating the sediment transport model quantitatively and qualitatively. Model predictions and turbidity measurements show that the flood water and suspended sediments entered upstream fairly well mixed and moved downstream as overflow with a sharp gradient at the plume front. The model results suggest that the settling and resuspension rates of sediment are directly proportional to flow characteristics and that the use of constant coefficients leads to model underestimation or overestimation unless more data on sediment formation become available. Hence, this study reiterates the significance of the availability of data on sediment distribution and characteristics for building a robust and reliable sediment transport model.

The effect of lumbar support on the ultrasound measurements of trunk muscles: a single-blinded randomized controlled trial.

OBJECTIVES: To evaluate the effect of lumbopelvic belts on the thickness of lateral abdominal muscles and the cross-sectional area (CSA) of lumbar multifidus (LM) muscles. DESIGN: A single-blinded randomized controlled trial. SETTING: An academic and tertiary care referral spine and sports medicine center. PARTICIPANTS: Sixty healthy volunteers with no history of low back pain in the previous year. METHODS: The subjects were allocated into belt and control groups. Lumbar belts were given to the subjects in the belt group, and they were asked to use the belts during the study period except during sleeping hours. The subjects were assessed at baseline and at 4 and 8 weeks. MAIN OUTCOME MEASURES: The thickness of lateral abdominal muscles and the CSA of the LM muscles were measured by ultrasound with the patient in the hook-lying position on an examination table. RESULTS: The thickness of lateral abdominal muscles and the CSA of LM muscles on both sides decreased significantly among healthy subjects in the belt group after 8 weeks. CONCLUSION: The results of this study show that lumbopelvic belts might influence the ultrasonographic measurements of lateral abdominal and LM muscles and thereby spine stability.

Classification of English vowels using speech evoked potentials.

The objective of this study is to investigate whether Speech Evoked Potentials (SpEPs), which are auditory brainstem responses to speech stimuli, contain information that can be used to distinguish different speech stimuli. Previous studies on brainstem SpEPs show that they contain valuable information about auditory neural processing. As such, SpEPs may be useful for the diagnosis of central auditory processing disorders and language disability, particularly in children. In this work, we examine the spectral amplitude information of both the Envelope Following Response, which is dominated by spectral components at the fundamental (F0) and its harmonics, and Frequency Following Response, which is dominated by spectral components in the region of the first formant (F1), of SpEPs in response to the five English language vowels (\a\,\e\,\ae\,\i\,\u\). Using spectral amplitude features, a classification accuracy of 78.3% is obtained with a linear discriminant analysis classifier. Classification of SpEPs demonstrates that brainstem neural responses in the region of F0 and F1 contain valuable information for discriminating vowels. This result provides an insight into human auditory processing of speech, and may help develop improved methods for objectively assessing central hearing impairment.