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The appropriate transformation and valorisation of biogas offers environmental and economic opportunities in a future with restrictions upon fossil-based fuels and materials. The LCA method was used to quantify and compare the potential environmental impacts of an AD plant incorporating biogas co-generation and upgrading options, namely AD-CHP and AD-RNG. Using an average Anaerobic Digestion facility in Ontario, Canada, modelled after real facilities, as a case study, electricity and steel were identified as potential hotspot input materials carrying a disproportionate environmental burden for biogas production. With a system expansion approach, the biogas was subsequently utilized to produce (1) both heat and electricity using a Combined Heat and Power (CHP) system, or (2) upgraded to renewable natural gas (also called biomethane) through chemical amine scrubbing, respectively.In comparing the biogas co-generation and upgrading options, the AD-CHP alternative resulted in a lesser environmental load, two times lower when compared to the AD-RNG biomethane recovery option. Furthermore, the avoided burden of producing fossil-based electricity, natural gas, and chemical fertilizer was analyzed and compared against their renewable counterparts. Significant reductions in emissions and in the depletion of fossil fuels were achieved, thus confirming the positive efforts of diverting organic waste from landfills to reduce organic waste disposal impacts and improve the management of organic waste. The analysis has provided useful insights to bioenergy project developers, policy makers and the scientific community regarding the processing of source separated organic waste, biogas production, and its upgrading alternatives in a circular economy perspective.

Iodide in the sea-surface plays an important role in the Earth system. It modulates the oxidising capacity of the troposphere and provides iodine to terrestrial ecosystems. However, our understanding of its distribution is limited due to a paucity of observations. Previous efforts to generate global distributions have generally fitted sea-surface iodide observations to relatively simple functions using proxies for iodide such as nitrate and sea-surface temperature. This approach fails to account for coastal influences and variation in the bio-geochemical environment. Here we use a machine learning regression approach (random forest regression) to generate a high-resolution (0.125∘×0.125∘, ∼12.5km×12.5km), monthly dataset of present-day global sea-surface iodide. We use a compilation of iodide observations (1967–2018) that has a 45 % larger sample size than has been used previously as the dependent variable and co-located ancillary parameters (temperature, nitrate, phosphate, salinity, shortwave radiation, topographic depth, mixed layer depth, and chlorophyll a) from global climatologies as the independent variables. We investigate the regression models generated using different combinations of ancillary parameters and select the 10 best-performing models to be included in an ensemble prediction. We then use this ensemble of models, combined with global fields of the ancillary parameters, to predict new high-resolution monthly global sea-surface iodide fields representing the present day. Sea-surface temperature is the most important variable in all 10 models. We estimate a global average sea-surface iodide concentration of 106 nM (with an uncertainty of ∼20 %), which is within the range of previous estimates (60–130 nM). Similar to previous work, higher concentrations are predicted for the tropics than for the extra-tropics. Unlike the previous parameterisations, higher concentrations are also predicted for shallow areas such as coastal regions and the South China Sea. Compared to previous work, the new parameterisation better captures observed variability. The iodide concentrations calculated here are significantly higher (40 % on a global basis) than the commonly used MacDonald et al. (2014) parameterisation, with implications for our understanding of iodine in the atmosphere. We envisage these fields could be used to represent present-day sea-surface iodide concentrations, in applications such as climate and air-quality modelling. The global iodide dataset is made freely available to the community (https://doi.org/10/gfv5v3, Sherwen et al., 2019), and as new observations are made, we will update the global dataset through a “living data” model.

Strategic documents are artifacts that can reveal evidence of an institution's teaching culture and, ideally, can influence how teaching is valued, rewarded, and resourced. This paper describes how an Institutional Teaching Culture framework based on six well-researched levers was applied to analyze strategic documents for indicators of teaching culture. Analyses conducted at five Canadian universities identified strengths and gaps within and across documents which, in turn, helped guide conversations about enhancing representations of institutional teaching culture. The authors share insights about our use of this analysis framework and offer recommendations to institutions invested in understanding and fostering robust teaching cultures.

Abstract The spread of invasive species often follows a jump-dispersal pattern. While jumps are typically fostered by humans, local dispersal can occur due to the specific traits of a species, which are often poorly understood. This holds true for small hive beetles (Aethina tumida), which are parasites of social bee colonies native to sub-Saharan Africa. They have become a widespread invasive species. In 2017, a mark-release-recapture experiment was conducted in six replicates (A–F) using laboratory reared, dye-fed adults (N = 15,690). Honey bee colonies were used to attract flying small hive beetles at fixed spatial intervals from a central release point. Small hive beetles were recaptured (N = 770) at a maximum distance of 3.2 km after 24 h and 12 km after 1 week. Most small hive beetles were collected closest to the release point at 0 m (76%, replicate A) and 50 m (52%, replicates B to F). Temperature and wind deviation had significant effects on dispersal, with more small hive beetles being recaptured when temperatures were high (GLMM: slope = 0.99, SE = 0.17, Z = 5.72, P

Abstract Introduction Although prostate magnetic resonance imaging (MRI) is commonly used in the diagnosis, staging and active surveillance of prostate cancer, little is known about patient perspectives on MRI. Methods We performed a qualitative study consisting of in‐depth, semi‐structured interviews of patients with low‐ and intermediate‐risk prostate cancer managed with active surveillance. Interviews focused on experiences with and knowledge of prostate MRI and MRI‐ultrasound fusion biopsy during active surveillance. We purposively sampled patients who received prostate MRI as part of their clinical care, conducted interviews until reaching thematic saturation and performed conventional content analysis to analyse data. Results Twenty patients aged 51–79 years (mean = 68 years) participated in the study. At diagnosis, 17 (85%) had a Gleason grade group 1, and three (15%) had a grade group 2 tumour. Overall, participants viewed prostate MRI as a valuable tool that accurately localizes and monitors prostate cancer over time, and they considered prostate MRI central to active surveillance monitoring. We identified five thematic categories related to MRI use: (1) the experiential aspects of undergoing an MRI scan; (2) the experience of visualizing one's own prostate and prostate cancer; (3) adequacy of provider explanations of MRI results; (4) confidence in prostate MRI in decision‐making; and (5) the role of prostate MRI in longitudinal follow‐up, including an interest in using MRI to modify the timing of, or replace, prostate biopsy. Conclusion Patients value prostate MRI as a tool that enhances their confidence in the initial diagnosis and monitoring of prostate cancer. This work can inform future studies to optimize patient experience, education and counselling during active surveillance for prostate cancer.

The Norway lobster (Nephrops norvegicus) is one of the most important decapod crustacean seafood species in the Adriatic Sea. Previous research has identified significant differences in growth rates and maturation timing of Nephrops in the Pomo/Jabuka Pits area compared to other subpopulations in Adriatic fishing grounds. Here, we use 1,623 genome-wide single nucleotide polymorphisms (SNPs) to investigate whether the Pomo Pits subpopulation is genetically different from other sites in the Adriatic and neighbouring seas. We found no genetic differentiation among all sampled Adriatic sites, suggesting high gene flow between Pomo Pits Nephrops and those of surrounding areas. We also found genetic homogeneity between the Adriatic sites and single-site samples from the Aegean and Tyrrhenian Seas. However, we detected distinct genetic differentiation between all Mediterranean sites and an Atlantic site in western Scotland, which provides evidence for a phylogenetic break between the Atlantic and the Mediterranean. Our results indicate that Pomo Pits Nephrops are not genetically different from others sampled in the Adriatic and that key biological parameters in Pomo Pits Nephrops could be driven by spatial variation in fishing pressure and/or environmental factors rather than geographic isolation.

Objective: Negative psychological beliefs like fear avoidance and catastrophizing can interfere with exercise engagement in people with knee osteoarthritis (OA). Mindfulness, when integrated with exercise, could potentially address both psychological and physical impairments. Our objectives were to optimize and assess the feasibility of a novel telehealth, group-based mindful exercise intervention for people with knee OA. Methods: We conducted a decentralized randomized controlled trial where participants (n ​= ​40) with symptomatic knee OA were randomized into mindful exercise (n ​= ​21) or exercise-only (n ​= ​19) groups. Both groups received supervised group-based interventions weekly for 8-weeks via Zoom. Primary outcomes were safety, fidelity, and feasibility of the mindful exercise intervention. Participants completed patient-reported outcomes (PRO) for pain, function, and psychological measures at baseline, week-8, and week-14. Results: Participants were from 21 US states; >90% identified as having White race, 16% were from rural areas, and approximately 40% had an annual income < $50,000. At 8-weeks, mindful exercise and exercise groups had retention rates of 86% (18/21) and 100% (19/19), and attendance was 54% (11.4/21) and 68% (13/19) respectively. There were no adverse events in the mindful exercise group and four in the exercise group related to exacerbation of knee pain. Preliminary findings showed numerically larger improvements in several PROs for the mindful exercise group. Conclusion: An 8-week telehealth, group-based, mindful exercise intervention was safe for people with knee OA. Our decentralized approach was feasible in terms of recruitment and retention. Further refinement is needed to improve intervention attendance and participant diversity.

Abstract Background Little research has investigated predictors of specialty substance use treatment gaps among Black adults. This study examined differential odds of experiencing self-reported, past-year treatment gaps among Black adults with respect to sexual minority status and health insurance coverage, accounting for social cofactors. Method This cross-sectional study comprised 36,098 Black Americans aged 18 and older who completed the 2015–2019 National Survey on Drug Use and Health (NSDUH) and provided responses for all selected survey items. Design-based multivariable logistic regression models were used to examine predictors of drug and alcohol treatment gaps. Results Sexual minority Black adults reported greater odds of experiencing treatment gaps to specialty treatment (i.e., inpatient hospital, inpatient/outpatient rehabilitation facility, or mental health center) compared to Black heterosexuals in adjusted models (Gay or lesbian: AOR = 2.01, 95% CI = 1.39–2.89; Bisexual: AOR = 2.35, 95% CI = 1.77–3.12), with bisexual Black women experiencing the greatest odds (AOR = 3.10, 95% CI = 2.33–4.14). Black adults with no health insurance were significantly more likely to report substance use treatment gaps relative to their peers with health insurance coverage (AOR = 50, 95% CI = 1.26–1.78). Conclusion The results suggest a critical need for more investigations into patterns of specialty substance use treatment gaps within Black populations and for developing sexual identity-affirming mechanisms for closing the disparity gap, particularly for Black sexual minorities and those who lack health insurance coverage.

Abstract Populations of anadromous brown trout, also known as sea trout, have suffered recent marked declines in abundance due to multiple factors, including climate change and human activities. While much is known about their freshwater phase, less is known about the species' marine feeding migrations. This situation is hindering the effective management and conservation of anadromous trout in the marine environment. Using a panel of 95 single nucleotide polymorphism markers we developed a genetic baseline, which demonstrated strong regional structuring of genetic diversity in trout populations around the English Channel and adjacent waters. Extensive baseline testing showed this structuring allowed high‐confidence assignment of known‐origin individuals to region of origin. This study presents new data on the movements of anadromous trout in the English Channel and southern North Sea. Assignment of anadromous trout sampled from 12 marine and estuarine localities highlighted contrasting results for these areas. The majority of these fisheries are composed predominately of stocks local to the sampling location. However, there were multiple cases of long‐distance movements of anadromous trout, with several individuals originating from rivers in northeast England being caught in the English Channel and southern North Sea, in some cases more than 1000 km from their natal region. These results have implications for the management of sea trout in inshore waters around the English Channel and southern North Sea.

Effusion cooling is often regarded as one of the critical techniques to protect solid surfaces from exposure to extremely hot environments, such as inside a combustion chamber where temperature can well exceed the metal melting point. Designing such efficient cooling features relies on thorough understanding of the underlying flow physics for the given engineering scenarios, where physical testing may not be feasible or even possible. Inevitably, under these circumstances, modelling and numerical simulation become the primary predictive tools. This review aims to give a broad coverage of the numerical methods for effusion cooling, ranging from the empirical models (often based on first principles and conservation laws) for solving the Reynolds-Averaged Navier–Stokes (RANS) equations to higher-fidelity methods such as Large-Eddy Simulation (LES) and hybrid RANS-LES, including Detached-Eddy Simulation (DES). We also highlight the latest progress in machine learning-aided and data-driven RANS approaches, which have gained a lot of momentum recently. They, in turn, take advantage of the higher-fidelity eddy-resolving datasets performed by, for example, LES or DES. The main examples of this review are focused on the applications primarily related to internal flows of gas turbine engines.

Abstract Introduction High-intensity gait training is widely recognized as an effective rehabilitation approach after stroke. Soft robotic exosuits that enhance post-stroke gait mechanics have the potential to improve the rehabilitative outcomes achieved by high-intensity gait training. The objective of this development-of-concept pilot crossover study was to evaluate the outcomes achieved by high-intensity gait training with versus without soft robotic exosuits. Methods In this 2-arm pilot crossover study, four individuals post-stroke completed twelve visits of speed-based, high-intensity gait training: six consecutive visits of Robotic Exosuit Augmented Locomotion (REAL) gait training and six consecutive visits without the exosuit (CONTROL). The intervention arms were counterbalanced across study participants and separated by 6 + weeks of washout. Walking function was evaluated before and after each intervention using 6-minute walk test (6MWT) distance and 10-m walk test (10mWT) speed. Moreover, 10mWT speeds were evaluated before each training visit, with the time-course of change in walking speed computed for each intervention arm. For each participant, changes in each outcome were compared to minimal clinically-important difference (MCID) thresholds. Secondary analyses focused on changes in propulsion mechanics and associated biomechanical metrics. Results Large between-group effects were observed for 6MWT distance (d = 1.41) and 10mWT speed (d = 1.14). REAL gait training resulted in an average pre-post change of 68 ± 27 m (p = 0.015) in 6MWT distance, compared to a pre-post change of 30 ± 16 m (p = 0.035) after CONTROL gait training. Similarly, REAL training resulted in a pre-post change of 0.08 ± 0.03 m/s (p = 0.012) in 10mWT speed, compared to a pre-post change of 0.01 ± 06 m/s (p = 0.76) after CONTROL. For both outcomes, 3 of 4 (75%) study participants surpassed MCIDs after REAL training, whereas 1 of 4 (25%) surpassed MCIDs after CONTROL training. Across the training visits, REAL training resulted in a 1.67 faster rate of improvement in walking speed. Similar patterns of improvement were observed for the secondary gait biomechanical outcomes, with REAL training resulting in significantly improved paretic propulsion for 3 of 4 study participants (p

Beta-phase gallium oxide (β-Ga2O3) is a cutting-edge ultrawide bandgap (UWBG) semiconductor, featuring a bandgap energy of around 4.8 eV and a highly critical electric field strength of about 8 MV/cm. These properties make it highly suitable for next-generation power electronics and deep ultraviolet optoelectronics. Key advantages of β-Ga2O3 include the availability of large-size single-crystal bulk native substrates produced from melt and the precise control of n-type doping during both bulk growth and thin-film epitaxy. A comprehensive understanding of the fundamental growth processes, control parameters, and underlying mechanisms is essential to enable scalable manufacturing of high-performance epitaxial structures. This review highlights recent advancements in the epitaxial growth of β-Ga2O3 through various techniques, including Molecular Beam Epitaxy (MBE), Metal-Organic Chemical Vapor Deposition (MOCVD), Hydride Vapor Phase Epitaxy (HVPE), Mist Chemical Vapor Deposition (Mist CVD), Pulsed Laser Deposition (PLD), and Low-Pressure Chemical Vapor Deposition (LPCVD). This review concentrates on the progress of Ga2O3 growth in achieving high growth rates, low defect densities, excellent crystalline quality, and high carrier mobilities through different approaches. It aims to advance the development of device-grade epitaxial Ga2O3 thin films and serves as a crucial resource for researchers and engineers focused on UWBG semiconductors and the future of power electronics.

Teachers’ personal beliefs and understanding about science topics play a vital role in students learning. This is especially relevant for the teaching of climate change which is a scientifically complicated topic that can also be influenced by personal and political views. Semi-structured interviews were conducted with thirteen Pakistani chemistry teachers (grades 10 & 12) to understand their knowledge about the science of climate change as well as their beliefs and practices related to the teaching of climate change. We found that teachers believe it is important to teach climate change in schools. They report that they teach climate change with relevant topics and do not face any obstacles doing so. No consensus was found regarding the appropriate grade levels and disciplines in which climate change should be taught. We also found that teachers have insufficient scientific knowledge about climate change (e.g., they think that any change in environment is climate change and climate change is related to pollution and ozone layer depletion). Our results suggest that there is a need to include climate change in in-service refresher courses and preservice teacher training programs, so the teachers have better understanding of the science of climate change. Further, there should be more climate change content in high school chemistry and biology.

Abstract Pests and pathogens are a continuous threat to the health of Western honey bee Apis mellifera L. Monitoring honey bee colonies for arthropod pests, disease‐causing bacteria and fungi, and early detection of new invasions is essential to maintain the pollination services provided by honey bees. We investigated the feasibility of using eDNA metabarcoding to detect pests and pathogens in bee hives and across their foraging environment. We sampled 13 sources for eDNA within and outside hives from our test apiary to determine where the most informative eDNA could be obtained, with most sources sampled thrice. This resulted in 61 samples, 20 negative controls, and three positive controls. Furthermore, we compared two eDNA collection techniques—wiping surfaces with moistened forensic swabs and using a spray/wash technique that aggregated surface eDNA into a container, before collecting the eDNA on a filter. We used DNA metabarcoding with universal primer sets to target arthropod, bacterial, and fungal communities. Our results showed that most sources yielded sufficient eDNA and that results of the swab and spray/wash methods were similar when they could be applied to the same surface. We detected DNA from honey bee bacterial symbionts, mycotoxin‐producing fungi and Brachymyrmex sp. rover ants. Common pests and pathogens of concern to honey bees (i.e., [small hive beetle (Aethina tumida), Varroa destructor, and Melissococcus plutonius]) were detected. This matched our visual observations of clinical signs of these pests and pathogens in the hives we tested. DNA from some species was source specific, which has implications for using eDNA as a monitoring tool. Collectively, our data show that eDNA metabarcoding can accurately detect DNA from arthropods and microbes honey bees contact and can be used as a comprehensive molecular predictor tool for colony health surveys.