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BACKGROUND Viscoelastic hemostatic assays, such as ROTEM or TEG, enable prompt diagnosis and accelerate targeted treatment. However, the complex interpretation of the results remains challenging. Visual Clot - a situation awareness-based visualization technology - was developed to assist clinicians in interpreting viscoelastic tests. OBJECTIVE Following a previous high-fidelity simulation study, we analyzed users' perceptions of the technology to identify its strengths and limitations from clinicians' perspectives. METHODS This is a mixed qualitative-quantitative study consisting of interviews and an online survey. After solving coagulation scenarios using Visual Clot in high-fidelity simulations, we interviewed anesthesia personnel about the perceived advantages and disadvantages of the new tool. We used a template approach to identify dominant themes in interview responses. Out of these themes, we then defined five main statements, which were rated on Likert scales in the online questionnaire. RESULTS We interviewed 77 participants and 23 completed the online survey. We identified nine frequently mentioned topics by analyzing interview responses. The most common themes were ``positive design features``, ``intuitive and easy to learn`` and ``lack of a quantitative component ``. In the online survey, 70% of participants agreed that Visual Clot is easy to learn and that a combination of Visual Clot and ROTEM would help manage complex hemostatic situations. CONCLUSIONS A group of anesthesia care providers found Visual Clot well-designed, intuitive and easy to learn. Participants highlighted its usefulness in emergencies, especially for clinicians inexperienced in coagulation management. However, the lack of quantitative information is an area for improvement.

Peripartum metabolism and subsequent reproductive performance of dairy cows are linked, with maladaptation over the transition period associated with poor reproductive success. A herd of seasonal calving, grazing dairy cows was established that differed in their genetic merit for fertility traits. The heifers were produced by a customized mating program to achieve a 10-percentage point divergence in the New Zealand fertility breeding value (FertBV) as follows: +5 FertBV (POS) versus −5% FertBV (NEG), while also limiting divergence in other breeding values, including body weight, body condition score, and milk production. In this study, we aimed to characterize differences in metabolic, mineral, and metabolic stress marker profiles during their first postpartum transition period as primiparous heifers and to examine if animals with longer postpartum anestrous intervals (PPAI; more than 66 d compared with less than 35 d) had greater metabolic dysfunction. Blood was sampled at −21, −14, −7, 0, 4, 7, 10, 14, 17, 21, 28, and 35 d relative to calving in 455 primiparous cows and plasma analyzed. The NEG cows had lower concentrations of both plasma nonesterified fatty acids and β-hydroxybutyrate at d 7 compared with POS cows. Detailed temporal profiling of various metabolic, mineral, and metabolic stress markers was undertaken in a subset of cows (n = 70). Cows were selected retrospectively to create 4 groups in a 2 × 2 factorial design with either a POS or NEG FertBV and either a short (19–35 d) or long (66–131 d) PPAI. The NEG cows tended, on average, to have lower nonesterified fatty acids and β-hydroxybutyrate concentrations compared with POS cows across the transition period. Mean body weight and body condition score was greatest in NEG cows when compared with the POS cows and an interaction with day demonstrated this only occurred precalving. They also had indications of improved liver health precalving, with higher albumin-to-globulin ratios and lower bilirubin concentrations. Concentrations of aspartate aminotransferase were lower, and the Na-to-Cl ratio was greater in cows with a long versus a short PPAI at d 28 and d 35 after calving, potentially because of cows with a short PPAI (19–35 d) returning to estrous during this time. Magnesium concentrations were lower in NEG cows with a short PPAI from d 21 onwards, indicating NEG cows may metabolically respond to estrous differently than POS cows. The NEG-long PPAI cows had greater gamma-glutamyl transferase concentrations from calving until d 28 and lower bilirubin concentrations throughout the transition period. Together, the results demonstrate significant effects of FertBV on peripartum metabolic status. However, most of the markers tested returned to reference intervals within 4 d after calving or remained within those intervals for the whole transition period, indicating relatively minor biological effects of FertBV on transition period adaptation. The profound differences in reproductive performance among the groups was not explained by underlying differences in metabolic responses during the transition period.

BACKGROUND Artificial intelligence (AI) is predicted to play an increasingly important role in perioperative medicine in the very near future. However, little is known about what anesthesiologists know and think about AI in this context. This is important because the successful introduction of new technologies depends on the understanding and cooperation of end users. OBJECTIVE Investigate how much anesthesiologists know about AI, and what they think about the introduction of AI-based technologies into the clinical setting. METHODS In order to better understand what anesthesiologists think of AI, we recruited 21 anesthesiologists from two university hospitals for face-to-face structured interviews. Thematic analysis was applied to statements derived from these interviews, and key themes were determined. Subsequently, a survey of closed questions based on these themes was sent to 70 anesthesiologists from three university hospitals for rating. RESULTS In the interviews, the base level of knowledge of AI was good at 86 of 90 statements (96%), although awareness of potential applications of AI in anesthesia was poor at only 7 of 42 statements (17%). Regarding the implementation of AI in anesthesia, statements were split roughly evenly between pros (46 of 105, 44%) and cons (59 of 105, 56%). Interviewees considered that AI could usefully be used in diverse tasks such as risk stratification, the prediction of vital sign changes, or as a treatment guide. The validity of these themes was probed in a follow-up survey of 70 anesthesiologists with a response rate of 70%, which confirmed an overall positive view of AI in this group. CONCLUSIONS Anesthesiologists hold a range of opinions, both positive and negative, regarding the application of AI in their field of work. Survey-based studies do not always uncover the full breadth of nuance of opinion amongst clinicians. Engagement with specific concerns, both technical and ethical, will prove important as this technology moves from research into the clinic.

Until recently, animal behavior has been studied through close and extensive observation of individual animals and has relied on subjective assessments. Wearable technologies that allow the automation of dairy cow behavior recording currently dominate the precision dairy technology market. Wearable accelerometers provide new opportunities in animal ethology using quantitative measures of dairy cow behavior. Recent research developments indicate that quantitative measures of behavior may provide new objective on-farm measures to assist producers in predicting, diagnosing, and managing disease or injury on farms and allowing producers to monitor cow comfort and estrus behavior. These recent research developments and a large increase in the availability of wearable accelerometers have led to growing interest of both researchers and producers in this technology. This review aimed to summarize the studies that have validated lying behavior derived from accelerometers and to describe the factors that should be considered when using leg-attached accelerometers and neck-worn collars to describe lying behavior (e.g., lying time and lying bouts) in dairy cows for research purposes. Specifically, we describe accelerometer technology, including the instrument properties and methods for recording motion; the raw data output from accelerometers; and methods developed for the transformation of raw data into meaningful and interpretable information. We highlight differences in validation study outcomes for researchers to consider when developing their own experimental methodology for the use of accelerometers to record lying behaviors in dairy cows. Finally, we discuss several factors that may influence the data recorded by accelerometers and highlight gaps in the literature. We conclude that researchers using accelerometers to record lying behaviors in dairy cattle should (1) select an accelerometer device that, based on device attachment and sampling rate, is appropriate to record the behavior of interest; (2) account for cow-, farm-, and management-related factors that could affect the lying behaviors recorded; (3) determine the appropriate editing criteria for the accurate interpretation of their data; (4) support their chosen method of recording, editing, and interpreting the data by referencing an appropriately designed and accurate validation study published in the literature; and (5) report, in detail, their methodology to ensure others can decipher how the data were captured and understand potential limitations of their methodology. We recommend that standardized protocols be developed for collecting, analyzing, and reporting lying behavior data recorded using wearable accelerometers for dairy cattle.

Hypocalcemia is a common metabolic disorder of transition dairy cows that is considered a gateway disease, increasing the risk of other health disorders and reducing cow performance. Clinical milk fever is associated with long periods of recumbency, and it is plausible that cows experiencing non-paretic hypocalcemia may spend more time lying; hence, lying behavior and activity measures may be useful in identifying at-risk cows. The objective of this study was to describe associations among blood calcium (Ca) status at calving and lying behavior and activity measures during the transition period in grazing dairy cows. Blood was sampled on the day of calving (d 0), and d 1, 2, 3, and 4 postcalving, and analyzed for total plasma Ca concentration. Twenty-four multiparous Holstein-Friesian and Holstein-Friesian × Jersey grazing dairy cows were classified, retrospectively, as clinically hypocalcemic (CLIN; blood Ca ≤ 1.4 mmol/L at 1 or more consecutive samplings within 48 h postcalving, but without parturient paresis). These cows were pair-matched (using milk production potential from their estimated breeding value for milk protein, mean body weight at wk -5 and -6 precalving, and, where possible, parity) with 24 cows classified as subclinically hypocalcemic (SUB; blood Ca > 1.4 and < 2.0 mmol/L at 2 consecutive samplings within 48 h postcalving), and 24 cows classified as normocalcemic (NORM; blood Ca ≥ 2.0 mmol/L at 3 consecutive samplings within 72 h postcalving). Lying behavior and activity were monitored using triaxial accelerometers from -21 to +35 d relative to calving. Data were summarized to calculate daily lying time (h/d), daily number of lying bouts (LB; no./d), mean LB duration (min/bout), and the number of steps taken (steps/d). On d 0, the CLIN group were less active and spent approximately 2.6 h longer lying than the SUB and NORM groups, particularly between 0200 and 1400 h. On d 0, the NORM group had fewer LB (16.3/d) than the SUB and CLIN groups (18.2 and 19.2/d, respectively). These differences in behavior were no longer detected 2 d postcalving, and no further differences were observed. The day before calving, the CLIN group spent 1.4 h longer lying down than did the SUB and NORM groups. Further, the relative change in steps from a precalving baseline period (d -14 to -7) until d 0 was positively, linearly associated with blood Ca concentration within 24 h postcalving. Future work should consider daily and temporal changes in behavior in individual cows to determine the potential for these measures to allow early detection of hypocalcemia.

Background: Cognitive ergonomics design of patient monitoring may reduce human factor errors in high-stress environments. Eye-tracking is a suitable tool to gain insight into the visual interaction of healthcare professionals with patient monitors, which may facilitate their further development.Methods: This prospective, randomized, high-fidelity simulation study compared anesthesia personnel's visual attention (fixation count and dwell time) to 15 areas of interest on the patient monitor during critical and non-critical anesthesia scenarios. Furthermore, we examined the extent to which participants' experience influenced visual attention and which vital signs displayed on the patient monitor received the most visual attention. We used mixed zero-inflated Poisson regression and mixed linear models to analyze the results.Results: Analyzing 23 ten-minute scenarios, we found significantly more fixations to the areas of interest on the patient monitor during critical situations (rate ratio of 1.45; 95% CI 1.33 to 1.59; p < 0.001). However, the dwell-time on the areas of interest did not significantly differ between the critical and non-critical scenarios (coefficient of –1.667; 95% CI –4.549 to 1.229; p = 0.27). The professional experience did not significantly influence the visual attention (fixation: rate ratio of 0.88; 95% CI 0.54 to 1.43; p = 0.61 and dwell-time: coefficient of 0.889; 95% CI –1.465 to 3.229; p = 0.27). Regarding vital signs, anesthesia personnel paid the most attention to blood pressure (fixation: mean [SD] of 108 [74.83]; dwell-time: mean [SD] of 27 [15.90] seconds), end-expiratory carbon dioxide (fixation: mean [SD] of 59 [47.39]; dwell-time: mean [SD] of 30 [21.51] seconds), and the electrocardiogram (fixation: mean [SD] of 58 [64.70]; dwell-time: mean [SD] of 15 [14.95] seconds).Conclusions: Critical anesthesia situations increased anesthesia personnel’s visual interaction with the patient monitor. Furthermore, we found that their visual attention focused mainly on a few vital signs. To assist clinicians in critical situations, manufacturers should optimize monitors to convey necessary information as easily and quickly as possible and optimize the visibility of less frequently observed but equally critical vital signs, especially when they are in an abnormal range.

Since 1 April 2015, European dairy milk quotas have been removed resulting in the intensification of dairy production within EU countries. The aim of this study was to evaluate the physical and economic impacts of the initial intensification undertaken within Irish grazing dairy systems. Physical and financial data for 868 seasonal calving dairy farmers with records for each of the years 2013–2017 inclusive were used in this analysis. All analyses were undertaken using a mixed-model framework in PROC MIXED. The overall level of fat plus protein productivity of studied farms increased by 51% during the 5-year period through a combination of increased production per cow, increased operational scale and system intensification. Overall farm net profit was highly variable between years and was greatest in 2017 (€133 836) and least in 2016 (€65 176). When farms were characterized into milk production expansion quartiles, farms in Q1, Q2, Q3 and Q4 increased output by +7, +25, +44 and +86%, respectively. Whereas total farm profit (€/farm) declined for Q1 farms between 2013/2014 and 2016/2017 (€−5257; −7%), the greater expansion undertaken in Q2, Q3 and Q4 resulted in increases of €3046 (+4%), €20 810 (+25%) and €51 604 (+62%), respectively. In all strategies studied, farm profit increased due to a combination of increased revenues, increased pasture utilization and a dilution of per unit production costs. Further investigation of the longer term impacts of expansion is merited, not just in terms of economic indicators, but also in terms of environmental and socio-cultural change.

Precalving feeding level and body condition score (BCS) alter postcalving energy balance and oxidant status of dairy cows. We hypothesized that the reported benefits of a controlled restriction precalving depend on precalving BCS. The objective was to identify alterations in activity and intermediates of the hepatic one-carbon metabolism, transsulfuration, and tricarboxylic acid pathways. Twenty-eight pregnant and nonlactating grazing dairy cows of mixed age and breed (Friesian, Friesian × Jersey) were randomly allocated to 1 of 4 treatment groups in a 2 × 2 factorial design: 2 prepartum BCS categories [4.0 (thin, BCS4) and 5.0 (optimal, BCS5); 10-point scale], by managing cows in late lactation to achieve the 2 groups at dry-off, and 2 levels of energy intake during the 3 wk preceding calving (75 or 125% of estimated requirements), obtained via allowance (m2/cow) of fresh pasture composed of mostly perennial ryegrass and white cover. Average (± standard deviation) age was 6 ± 2, 6 ± 3, 5 ± 1, and 7 ± 3 yr for BCS4 fed 75 and 125%, and BCS5 fed 75 and 125%, respectively. Breed distribution (average ± standard deviation) for the 4 groups was 79 ± 21, 92 ± 11, 87 ± 31, and 74 ± 23% Friesian, and 17 ± 20, 8 ± 11, 13 ± 31, and 25 ± 23% Jersey. Liver tissue was collected by biopsy at -7, 7, and 28 d relative to calving. Tissue was used for 14C radio-labeling assays to measure betaine-homocysteine S-methyltransferase, 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR), and cystathionine-β-synthase (CBS) activity. Liver metabolomics was undertaken using a targeted liquid chromatography with tandem mass spectrometry-based profiling approach. After initial liquid chromatography separation, mass spectra were acquired under both positive and negative ionization, whereas multiple reaction monitoring was used to measure target compound signal response (peak area count). Enzyme activity and metabolite peak area count were normalized with the homogenate protein concentration. Repeated measures analysis of variance via PROC MIXED in SAS (SAS Institute Inc., Cary, NC), with BCS, feeding, and time as fixed effects, and cow as random effect was used. All enzyme activities were affected by time, with betaine-homocysteine S-methyltransferase activity peaking at 7 d, whereas CBS and MTR activity decreased postpartum. Overall, thin cows had greater MTR activity, whereas cows fed 125% requirements had greater CBS activity. An interaction was detected between BCS and feeding for CBS activity, as thin cows fed 125% of requirements had greater overall activity. Compared with liver from BCS4 cows, BCS5 cows had overall greater betaine, glycine, butyrobetaine/acetylcholine, serine, and taurine concentrations. The same metabolites, plus choline and N-N-dimethylglycine, were overall greater in liver of cows fed 75% compared with those fed 125% of requirements. An interaction of BCS and feeding level was detected for the aforementioned metabolites plus methionine, cystathionine, cysteinesulfinate, and hypotaurine, due to greater overall concentrations in BCS5 cows fed 75% of requirements compared with other groups. Overall, differences in hepatic enzyme activity and intermediate metabolites suggest that both BCS and feeding level can alter the internal antioxidant system (e.g., glutathione and taurine) throughout the periparturient period. Further studies are needed to better understand potential mechanisms involved.

In theory, a late winter–early spring calving date in temperate grazing systems best matches pasture supply and herd demand, thereby minimizing the need for nonpasture feeds and maximizing profitability. We used a quantitative case study approach to define the effects of season of calving on biophysical and financial performance in a grazing system without the confounding effects of imported feeds (i.e., milk production directly from grazed pasture). A 2-yr production system experiment was established to quantify the effects of changing onset of seasonal calving (i.e., planned start of calving; PSC) from winter (July in the Southern Hemisphere) to spring (October), summer, (January), or autumn (April) on pasture and animal production and profitability. Eighty Holstein-Friesian cows were randomly allocated to 1 of 4 PSC treatments, each of which had a different PSC [mean calving date of January 10 (JAN), April 10 (APR), July 10 (JUL), or October 10 (OCT)]. Data were analyzed for consistency of treatment response over years using ANOVA procedures with year, PSC treatment, and year × PSC treatment interactions as fixed effects. Collated biological data and financial data extracted from a national economic database were used as fixed variables to model the financial performance for the different treatments. A stochastic risk analysis was undertaken, where historical pasture growth and milk price data were used to estimate the probability distributions for stochastic input variables. Gross farm revenue and operating profit per hectare were modeled under 2 scenarios: (A) milk price did not include a premium for milk supplied during the winter, and (B) milk price included a realistic premium for milk supplied in winter. Annual and seasonal pasture growth did not differ between treatments, but the pasture growth (kg of dry matter/ha) and profile of the JUL treatment best matched the lactation nutrient demand profile. In comparison, profiles for JAN, APR, and OCT calving treatments had periods of greater surplus and deficit due to the time of calving and herd demand relative to the pasture growth profile. As a result, the JAN and OCT treatments conserved more pasture as silage and cows consumed a larger proportion of their annual diet as silage. Although the amount of silage conserved and consumed did not differ between the JUL and APR calving treatments, the timing of the silage consumption was different, with silage making up a greater proportion of the diets in the APR treatment 1 to 90 and 91 to 180 d postcalving and being offered to the JUL calving treatment only 271 to 365 d postcalving. As a result of differences in the quantity and proportion of pasture and pasture silage in the lactating diet, the JUL treatment herd tended to produce greater milk, 4% fat-corrected milk, fat, protein, and lactose yields (kg/cow) than the other PSC treatments, which did not differ from each other. Operating expenses per hectare did not differ materially between calving date scenarios, but operating expenses per kilogram of fat-corrected milk and kilogram of fat and protein were 15 to 20% less in the JUL treatment. With or without a realistic winter milk premium, gross farm revenue and operating profit per hectare were greater in the JUL treatment than in the APR treatment, which had greater revenue and profitability than the remaining 2 calving date treatments. In summary, our results indicate that a PSC in late winter is most profitable in a grazing system not importing feed, with or without a realistic price incentive scheme.

The influence of medical culture and beliefs on the management of colleagues who pose risks of patient harm resulting from clinical errors or inappropriate behaviours is discussed. The importance of an evidence-based approach to the promotion of an ethos that is both conducive to openness and learning and that allows shortcomings to be identified and addressed is emphasised. A culture based on these principles is regarded as being fundamental to the development and maintenance of high standards of professional practice and conduct. Professional and social isolation of individual doctors, particularly of graduates from other countries, poses risks to both the doctors and patients and the mitigation of these risks is discussed. The need to address the mental wellbeing of doctors who are subject to complaints and/or investigations cannot be over-emphasised as there is a significant risk of self-harm in these situations.

Background Inadequate situational awareness accounts for two-thirds of preventable complications in anesthesia. An essential tool for situational awareness in the perioperative setting is the patient monitor. However, the conventional monitor has several weaknesses. Avatar-based patient monitoring may address these shortcomings and promote situation awareness, a prerequisite for good decision making. Objective The spatial distribution of visual attention is a fundamental process for achieving adequate situation awareness and thus a potential quantifiable surrogate for situation awareness. Moreover, measuring visual attention with a head-mounted eye-tracker may provide insights into usage and acceptance of the new avatar-based patient monitoring modality. Methods This prospective eye-tracking study compared anesthesia providers' visual attention on conventional and avatar-based patient monitors during simulated critical anesthesia events. We defined visual attention, measured as fixation count and dwell time, as our primary outcome. We correlated visual attention with the potential confounders: performance in managing simulated critical anesthesia events (task performance), work experience, and profession. We used mixed linear models to analyze the results. Results Fifty-two teams performed 156 simulations. After a manual quality check of the eye-tracking footage, we excluded 57 simulations due to technical problems and quality issues. Participants had a median of 198 (IQR 92.5-317.5) fixations on the patient monitor with a median dwell time of 30.2 (IQR 14.9-51.3) seconds. We found no significant difference in participants' visual attention when using avatar-based patient monitoring or conventional patient monitoring. However, we found that with each percentage point of better task performance, the number of fixations decreased by about 1.39 (coefficient –1.39; 95% CI –2.44 to –0.34; P=.02), and the dwell time diminished by 0.23 seconds (coefficient –0.23; 95% CI: –0.4 to –0.06; P=.01). Conclusions Using eye tracking, we found no significant difference in visual attention when anesthesia providers used avatar-based monitoring or conventional patient monitoring in simulated critical anesthesia events. However, we identified visual attention in conjunction with task performance as a surrogate for situational awareness.

BACKGROUND Inadequate situational awareness accounts for two-thirds of preventable complications in anesthesia. An essential tool for situational awareness in the perioperative setting is the patient monitor. However, the conventional monitor has several weaknesses. Avatar-based patient monitoring may address these shortcomings and promote situation awareness, a prerequisite for good decision making. OBJECTIVE The spatial distribution of visual attention is a fundamental process for achieving adequate situation awareness and thus a potential quantifiable surrogate for situation awareness. Moreover, measuring visual attention with a head-mounted eye-tracker may provide insights into usage and acceptance of the new avatar-based patient monitoring modality. METHODS This prospective eye-tracking study compared anesthesia providers' visual attention on conventional and avatar-based patient monitors during simulated critical anesthesia events. We defined visual attention, measured as fixation count and dwell time, as our primary outcome. We correlated visual attention with the potential confounders: performance in managing simulated critical anesthesia events (task performance), work experience, and profession. We used mixed linear models to analyze the results. RESULTS Fifty-two teams performed 156 simulations. After a manual quality check of the eye-tracking footage, we excluded 57 simulations due to technical problems and quality issues. Participants had a median of 198 (IQR 92.5-317.5) fixations on the patient monitor with a median dwell time of 30.2 (IQR 14.9-51.3) seconds. We found no significant difference in participants' visual attention when using avatar-based patient monitoring or conventional patient monitoring. However, we found that with each percentage point of better task performance, the number of fixations decreased by about 1.39 (coefficient –1.39; 95% CI –2.44 to –0.34; P=.02), and the dwell time diminished by 0.23 seconds (coefficient –0.23; 95% CI: –0.4 to –0.06; P=.01). CONCLUSIONS Using eye tracking, we found no significant difference in visual attention when anesthesia providers used avatar-based monitoring or conventional patient monitoring in simulated critical anesthesia events. However, we identified visual attention in conjunction with task performance as a surrogate for situational awareness.

The fate and transport of nanoparticles (NPs) in streams is critical for understanding their overall environmental impact. Using a unique field-scale stream at the Notre Dame-Linked Experimental Ecosystem Facility, we investigated the impact of biofilms and the presence of dissolved organic matter (DOM) on the transport of titanium dioxide (TiO

Hyporheic zone reaction rates are highest just below the sediment-water interface, in a shallow region called the benthic biolayer. Vertical variability of hyporheic reaction rates leads to unexpec...

Dietary transitions, such as eliminating meat consumption, have been proposed as one way to reduce the climate impact of the global and regional food systems. However, it should be ensured that replacement diets are, indeed, nutritious and that climate benefits are accurately accounted for. This study uses New Zealand food consumption as a case study for exploring the cumulative climate impact of adopting the national dietary guidelines and the substitution of meat from hypothetical diets. The new GWP* metric is used as it was designed to better reflect the climate impacts of the release of methane than the de facto standard 100-year Global Warming Potential metric (GWP100). A transition at age 25 to the hypothetical dietary guideline diet reduces cumulative warming associated with diet by 7 to 9% at the 100th year compared with consuming the average New Zealand diet. The reduction in diet-related cumulative warming from the transition to a hypothetical meat-substituted diet varied between 12% and 15%. This is equivalent to reducing an average individual’s lifetime warming contribution by 2 to 4%. General improvements are achieved for nutrient intakes by adopting the dietary guidelines compared with the average New Zealand diet, however, the substitution of meat items results in characteristic nutrient differences, and these differences must be considered alongside changes in emission profiles.

In low-gradient, macrophyte-rich rivers, we expect that the significant change in macrophyte biomass among seasons will strongly influence both biological activity and hydraulic conditions resulting in significant effects on nutrient dynamics. Understanding seasonal variation will improve modelling of nutrient transport in river networks, including annual estimations of export, which could optimise decision-making and management outcomes. We explored the relationships among seasonal differences in reach-scale nutrient uptake, macrophyte abundance, solute transport and transient storage in the River Gudenå (Denmark), a large macrophyte-rich river. We used the minimal pulse addition technique to measure uptake of ammonium, nitrate, soluble reactive phosphorus, as well as reach-scale metabolism, and surface transient storage in spring, summer, and autumn. We found that riverine uptake changed among seasons and was linked to macrophyte biomass via both biological activity, reflected in reach-scale metabolism, and through physical processes, as solute transport was influenced by longitudinal dispersion. In this macrophyte-rich river, seasonal changes in macrophyte biomass affected contact time between the water and biota, which influenced ammonium and soluble reactive phosphorus uptake. Using stoichiometric scaling of reach-scale metabolism, we found that seasonal variation also influenced the relative contributions of autotrophic and heterotrophic biota in assimilatory uptake. In summary, riverine nutrient uptake was not static, highlighting the importance of seasonality, with significant implications for modelling of nutrient export in river networks. Moreover, current management strategies that remove macrophyte biomass (i.e. weed cutting and dredging) will short-circuit the positive effects of enhanced nutrient uptake resulting from abundant macrophytes in rivers.

Disease susceptibility of dairy cows is greatest during the transition from pregnancy to lactation. Circulating exosomes may provide biomarkers to detect at-risk cows to enhance health and productivity. From 490 cows, animals at high- (n = 20) or low-risk (n = 20) of transition-related diseases were identified using plasma non-esterified fatty acid and β-hydroxybutyrate concentrations and liver triacylglyceride concentrations during the two weeks post-calving. We isolated circulating exosomes from plasma of dairy cows at low-risk (LR-EXO) and high-risk (HR-EXO), and analyzed their proteome profiles to determine markers for metabolic dysfunction. We evaluated the effects of these exosomes on eicosanoid pathway expression by bovine endometrial stromal (bCSC) and epithelial (bEEL) cells. HR-EXO had significantly lower yield of circulating exosomes compared with LR-EXO, and unique proteins were identified in HR-EXO and LR-EXO. Exposure to LR-EXO or HR-EXO differentially regulated eicosanoid gene expression and production in bCSC and bEEL cells. In bCSC, LR-EXO exposure increased PGE2 and PGD2 production, whereas HR-EXO exposure increased PTGS2 gene expression. In bEEL, HR-EXO exposure caused a decrease in PGE2, PGF2α, PGD2, PGFM and TXB2 production. The unique presence of serpin A3-7, coiled-coil domain containing 88A and inhibin/activin β A chain in HR-EXO, indicates potential biomarkers for cows at-risk for metabolic diseases. Our results are in line with the health status of the cow indicating a potential diagnostic role for exosomes in enhancing cows’ health and fertility.

We present a novel seismocardiography (SCG)-based approach for real-time cardio-respiratory activity measurement called the Autocorrelated Differential Algorithm (ADA). Measurements were performed on ten male subjects in the supine position for three 7-minute-long sets each, corresponding to 14,619 heartbeats. The ADA utilized temporal variations, windowing, and autocorrelation to produce physiological measurements corresponding to heart rate (HR), and left ventricular ejection time, and estimations of respiration rate, volume, and phase. The versatility of the ADA was investigated in two contexts: physical exertion and heart rate variability. The accuracy of HR measurements at a sampling frequency of 200 Hz resulted in a correlation coefficient ( $r^{2}$ ) of 0.9808 when compared with a manual annotation of all datasets. Its reproducibility was tested on externally obtained SCG and electrocardiography datasets, which produced an $r^{2}$ of 0.8224. The accuracy and computational time were also characterized by different sampling frequencies to quantify performance. The recommended sampling frequency is 200 Hz corresponding to a computation time of 0.05 s per instantaneous measurement using a standard desktop computer. The ADA delivered real-time SCG measurements with a refresh rate that was dependent on the computational time per measurement, which could be decreased by lowering the sampling frequency. The presented algorithm offers a novel tool toward real-time physiological monitoring in clinical and everyday scenarios.

Turbulence causes rapid mixing of solutes and fine particles between open channel flow and coarse-grained streambeds. Turbulent mixing is known to control hyporheic exchange fluxes and the distribution of vertical mixing rates in the streambed, but it is unclear how turbulent mixing ultimately influences mass transport at the reach scale. We used a particle-tracking model to simulate local- and reach-scale solute transport for a stream with coarse-grained sediments. Simulations were first used to determine profiles of vertical mixing rates that best described solute concentration profiles measured within a coarse granular bed in flume experiments. These vertical mixing profiles were then used to simulate a pulse solute injection to show the effects of turbulent hyporheic exchange on reach-scale solute transport. Experimentally measured concentrations were best described by simulations with a non-monotonic mixing profile, with highest mixing at the sediment-water interface and exponential decay into the bed. Reach-scale simulations show that this enhanced interfacial mixing couples in-stream and hyporheic solute transport. Coupling produces an interval of exponential decay in breakthrough curves and delays the onset of power-law tailing. High streamwise velocities in the hyporheic zone reduced mass recovery in the water column and caused breakthrough curves to exhibit steeper power-law slopes than predictions from mobile-immobile modeling theory. These results demonstrate that transport models must consider the spatial variability of streamwise velocity and vertical mixing for both the stream and the hyporheic zone, and new analytical theory is needed to describe reach-scale transport when high streamwise velocities are present in the hyporheic zone.

The exchange of surface and subsurface waters plays an important role in understanding and predicting large scale transport processes in streams and rivers. Accurately capturing the influence of small-scale features associated with turbulent dispersion on exchange in an upscaled framework is necessary for developing reliable predictive models at the reach scale. In this work, we use high-fidelity direct numerical simulations (DNS) to fully resolve turbulent flow and hyporheic exchange in an open channel. We parameterize a 2D particle tracking model with the average DNS velocity and scalar diffusivity profiles. Breakthrough curves and rate of surface mass loss to the subsurface in both models agree after a sufficient distance downstream from particle injection. Finally we find that the travel time/distance joint pdf contains enough information to parameterize a 1D dual domain coupled Continuous Time Random Walk (ddc-CTRW) model that successfully reproduces the behavior of both the DNS and the 2D particle tracking model, allowing accurate prediction of breakthrough curves. Predicting breakthrough curves with a fully parameterized ddc-CTRW reduces cpu time by orders of magnitude when compared with DNS.

This work elucidates the impacts of model construction choices on turbulence characteristics and solution fidelity in the simulation of coupled freestream and porous turbulent flows. A freestream-porewater interface is modeled numerically as a matrix of regularly spaced spheres submerged in a surrounding flow. Simulations are conducted to solve the continuity and momentum equations via Large Eddy Simulation (LES) using the Control Volume Finite Element Method (CVFEM) on an unstructured, surface-conforming mesh, and simulated flow fields are compared with experimental results. Key parameters are identified, allowing for model creation recommendations. A mesh refinement study is performed, and characteristic required mesh sizes in both the bed and the freestream are identified that achieve a good trade-off between accuracy and efficiency. Additionally, it is shown that similar to wall-bounded flows, the computational domain for a coupled freestream and porous flow must be sufficiently large to capture the relevant largest-sized eddies and to avoid the spanwise locking of flow structures; such structures may affect the flow field in the pores as well as in the freestream. Dimensions of 7.5H × 3.5H × H, where H is the freestream height, are found to give satisfactory comparison with experimental results for the cases studied. Finally, it is found that the wall-adapting local eddy-viscosity (WALE) turbulence closure scheme is better able to model the fluid velocity in the problem domain compared with the Smagorinsky model. Failure to select the proper turbulence closure model or domain size leads to a misrepresentation of the turbulent structures. Because of the strong coupling between the porewater flow and the freestream, these modeling errors propagate in both flow regions.

With the increased use of nanoparticles (NPs) in consumer, food, and pharmaceutical products, their eventual release into streams is inevitable. Critical factors affecting the transport of NPs in streams are the hyporheic exchange between the water column and porous streambed substrate and the interaction with biofilms. In this study, the transport behavior of two titanium dioxide NPs – catalytic- (P90) and food-grade (E171) – was evaluated in four field streams lined with different streambed substrate sizes for varying seasonal biofilm conditions. When biofilm growth was minimal, NP retention in the streams increased with increasing substrate size due to increased hyporheic exchange and subsequent physical and chemical interactions between the NPs and substrate. For all streams, the average mass recovery at the 40 m sampling point for E171 and P90 was 44 ± 8.7% and 16 ± 8.0%, respectively. The greater mobility of E171 was due to the inherent presence of negatively charged surface phosphates that reduced aggregation and decreased its interaction with the substrate. When biofilms were thriving in the streams the average mass recovery at 40 m for both NPs decreased significantly (E171 = 5.8 ± 7.3%, P = 0.0017; P90 = 2.4 ± 0.7%, P = 0.041), and the mass recovery difference between the two NPs became insignificant (P = 0.38).

Inland lakes face unprecedented pressures from climatic and anthropogenic stresses, causing their recession and desiccation globally. Climate change is increasingly blamed for such environmental degradation, but in many regions, direct anthropogenic pressures compound, and sometimes supersede, climatic factors. This study examined a human-environmental system - the terminal Hamun Lakes on the Iran-Afghanistan border - that embodies amplified challenges of inland waters. Satellite and climatic data from 1984 to 2019 were fused, which documented that the Hamun Lakes lost 89% of their surface area between 1999 and 2001 (3809 km