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Lentic waters are biogeochemical reactors, producing and receiving carbon (C) originally fixed by the terrestrial and aquatic biosphere, which is then buried in sediments or respired back to the atmosphere in the forms of carbon dioxide (CO2) and one of the more potent greenhouse gas (GHG) methane (CH4). Additionally, lakes serve as archives of terrestrial and aquatic carbon processes within their sediments, enabling the reconstruction of historical changes spanning thousands of years. These changes encompass alterations in land cover, indicated by pollen records, soil carbon erosion and shifts in lake productivity resulting from changes in land use and climate. Both the burial of C in lakes and the emissions of GHGs are recognised as important components of Earth's climate system, yet they remain poorly understood and constrained due to inadequate quantities and qualities of observations. In the case of GHG emissions from lakes, observations are often sporadic, failing to capture the significant spatial and temporal variations in emissions across diverse lentic systems. To address this challenge, process-based models that incorporate the interconnected biogeochemical processes occurring within lakes and their watersheds would arguably be the best tool to extrapolate from site-level observations to regional and finally global scales, to quantify the anthropogenic impact on these fluxes and to reconstruct long-term shifts in emissions and burial due to changes in land cover and climate. However, the development and evaluation of such models is hampered by the lack of observations in sufficient quality. In this project, we bring together a unique consortium of specialists in aquatic ecology, biogeochemistry, palynology, sedimentology and modelling of terrestrial and aquatic biogeochemistry. This project will put forth a national programme of systematic, long-term observations of lake GHG and C cycling processes of unmet detail, consistency and quality. First, at 40 pilot sites spanning typological and environmental gradients, there will be a comprehensive data acquisition endeavour to evaluate biological processes and mesological factors influencing the sequestration or recycling of organic carbon. This effort will be complemented with a synthesis of existing data (WP1). Second, based on well-dated sediment records, which include both newly-acquired and synthesised existing data, variability of lake C burial and their climate and land-use controls will be reconstructed over the past 150 years (WP2). For 15 of these pilot sites, reconstruction will go back until the mid-Holocene (5,000 years BP), allowing us to shed light on the anthropogenic perturbation of the C cycle in this earlier part of human history, which is commonly excluded from this type of research due to lack of information. The activities of these first two WPs will result in an open-source national database, guaranteeing valorisation of our research far beyond this project. In WP3, we will use the land surface model (LSM) ORCHIDEE C-lateral to assess C cycling in the terrestrial biosphere and the mobilisation of biospheric C into lakes, which is possible due to an explicit representation of soil C leaching and erosion processes and a downscaling scheme permitting us to assess C exports from watersheds at sub-grid scale. While LSMs are used to assess evolution of biospheric C budgets from the beginning of the Industrial Period, we will use it to hindcast the evolution since the mid-Holocene, using lake sediment records for model validation. Moreover, we will develop a new process-based lake C model supported by the database established in WPs 1 and 2, which we will couple to ORCHIDEE C-lateral to simulate lake C burial and GHG emissions in response to climate and processes in the lake watershed. This model set-up will first be used to better constrain contemporary large-scale lake GHG emissions and to disentangle the anthropogenic perturbation of these fluxes from the natural background flux. These estimates will be revolutionary, as they will allow attributing part of lake GHG emissions to anthropogenic emissions for national GHG budget reporting. Then, these models will be emulated to reconstruct evolution of lake GHG budgets and C budgets of the whole lake watershed since the mid-Holocene. While simulations will first be performed at the scales of France and Europe, the development of international partnerships to implement observations from other biomes (WP4) will finally support simulations at the global scale.

Abstract Robotic locomotion in unstructured terrain demands an agile, adaptive, and energy-efficient architecture. To traverse such terrains, legged robots use rigid electromagnetic motors and sensorized drivetrains to adapt to the environment actively. These systems struggle to compete with animals that excel through their agile and effortless motion in natural environments. We propose a bio-inspired musculoskeletal leg architecture driven by antagonistic pairs of electrohydraulic artificial muscles. Our leg is mounted on a boom arm and can adaptively hop on varying terrain in an energy-efficient yet agile manner. It can also detect obstacles through capacitive self-sensing. The leg performs powerful and agile gait motions beyond 5 Hz and high jumps up to 40 % of the leg height. Our leg’s tunable stiffness and inherent adaptability allow it to hop over grass, sand, gravel, pebbles, and large rocks using only open-loop force control. The electrohydraulic leg features a low cost of transport (0.73), and while squatting, it consumes only a fraction of the energy (1.2 %) compared to its conventional electromagnetic counterpart. Its agile, adaptive, and energy-efficient properties would open a roadmap toward a new class of musculoskeletal robots for versatile locomotion and operation in unstructured natural environments.

# Background Chlorhexidine gluconate (CHG) bathing has proven to reduce central line--associated bloodstream infections (CLABSI) in hospitalized patients. The aim of this study is to evaluate whether the implementation of a compliance monitoring process for CHG bathing and strict hand hygiene as part of the traditional CLABSI prevention bundle will reduce the overall hospital CLABSI standardized infection ratio (SIR). # Methods A quasi-experimental study was conducted in intensive care and non-intensive care inpatient hospital units in an urban 361-bed teaching hospital in Western Pennsylvania. The pre-intervention period consisted of January--August 2021, the intervention period consisted of September--November 2021, and the post-intervention and sustainability period consisted of December 2021--June 2022. A compliance monitoring process for the initiation of a daily bath using a 4% CHG solution and strict hand hygiene surveillance was implemented as part of the standard CLABSI prevention bundle (which includes standardized insertion checklists and processes, daily necessity assessment, dressing change and integrity standards, five moments hand hygiene standards, CHG disk \[Biopatch\], end caps \[Curos\], and care of tubing). # Outcomes A statistically significant increase in hand hygiene (p=\

Uranium (U) is a radiologically and chemically toxic element that occurs naturally in water, soil, and rock at generally low levels. However, anthropogenic uranium can also leach into groundwater sources due to mining, ore refining, and improper nuclear waste management. Over the last few decades, various methods for measuring uranium have emerged; however, most of these techniques require skilled scientists to run samples on expensive instrumentation for detection or require the pretreatment of samples in complex procedures. In this work, a Schiff base ligand (P1) is used to develop a simple spectrophotometric method for measuring the concentration of uranium (VI) with an accurate and affordable light-emitting diode (LED) spectrophotometer. A test for a higher-order polynomial relationship was used to objectively determine the calibration data's linearity. This test was done with a Python program on a Raspberry Pi computer that captured the spectrophotometer's calibration and sample measurement data.

Interactions between predators and their prey are important in shaping planktonic ecosystems. However, these interactions are difficult to assess in situ at the spatial scales relevant to the organisms. This work presents high spatial resolution observations of the nighttime vertical distributions of individual zooplankton, chlorophyll-a fluorescence, and marine snow in stratified coastal waters of the Southern California Bight. Data were obtained using a planar laser imaging fluorometer (PLIF) augmented with a shadowgraph zooplankton imaging system (O-Cam) mounted along with ancillary sensors on a free-descent platform. Fluorometer and PLIF sensors detected two well-defined and distinct peaks: the subsurface chlorophyll maximum (SCM) and a fluorescent particle maximum (FPM) dominated by large marine snow. The O-Cam imaging system allows reliable estimates of concentrations of crustacean and gelatinous zooplankton groups; we found that grazers and their predators had well-structured nighttime distributions in and around the SCM and FPM in ways that suggested potential predator avoidance at the peak of the SCM and immediately above the FPM (where predatory hydromedusae, and to some degree euphausiids, were primarily located). Calanoid copepods were found above the SCM while cyclopoids were associated with the FPM. The locations of predator and grazer concentration peaks suggest that their dynamics may control the vertical gradients defining the SCM and FPM.

Interactions between predators and their prey are important in shaping planktonic ecosystems. However, these interactions are difficult to assess in situ at the spatial scales relevant to the organisms. This work presents high spatial resolution observations of the nighttime vertical distributions of individual zooplankton, chlorophyll-a fluorescence, and marine snow in stratified coastal waters of the Southern California Bight. Data were obtained using a planar laser imaging fluorometer (PLIF) augmented with a shadowgraph zooplankton imaging system (O-Cam) mounted along with ancillary sensors on a free-descent platform. Fluorometer and PLIF sensors detected two well-defined and distinct peaks: the subsurface chlorophyll maximum (SCM) and a fluorescent particle maximum (FPM) dominated by large marine snow. The O-Cam imaging system allows reliable estimates of concentrations of crustacean and gelatinous zooplankton groups; we found that grazers and their predators had well-structured nighttime distributions in and around the SCM and FPM in ways that suggested potential predator avoidance at the peak of the SCM and immediately above the FPM (where predatory hydromedusae, and to some degree euphausiids, were primarily located). Calanoid copepods were found above the SCM while cyclopoids were associated with the FPM. The locations of predator and grazer concentration peaks suggest that their dynamics may control the vertical gradients defining the SCM and FPM.

Methane metabolism is considered of secondary importance in most lake food webs. Here the authors quantify the contribution of methanotrophs to C cycling in six lakes, finding evidence of a large role of methanotrophs due to their higher specific activity and larger cell size.

There are 25 million displaced children worldwide, and those receiving schooling are often educated in overcrowded classrooms. Montessori is a child-centred educational method that provides an alternative model to traditional educational approaches. In this model, students are able to direct their own learning and develop at their own pace, working with materials rather than in supervised groups or with direct teacher instruction. Because most children are working alone, teachers have more time to work one-on-one with children even when student-teacher ratios are quite large. This gives teachers increased opportunity to tailor their teaching to the specific needs and strengths of each student. We conducted an evaluation of Montessori classroom conversion for displaced students on the Thai-Myanmar border. We administered the Ages and Stages Questionnaire (ASQ) to 66 children before and after classroom conversion and across treatment and control classroom conditions. We then conducted difference in difference testing. All domains showed meaningful improvements in ASQ scores, with the Montessori students gaining 18 points relative to the traditional students (p = 0.33). However, only the personal-social domain of the ASQ was statistically significant (8.8 point gain for the Montessori students relative to the control, p < 0.05) in our underpowered sample.

Objective: We conducted a systematic review to answer the following research question: “What logics or rationales have structured interventions aimed at preventing suicidal behaviors among AI/AN populations?” Method: Our screening and searching process yielded 32 publications that overlapped considerably in terms of suicide prevention strategies, logics, and rationales. Results: Regarding suicide prevention strategies, most studies featured interventions that sought to promote connectedness, create protective environments, identify and support people at risk, and teach coping and problem-solving skills, while others strengthened access and delivery of suicide care, lessened harms and prevented future risk, and strengthened economic support. The rationales justifying these suicide prevention strategies varied from strategy to strategy. Discussion: While most program developers related their choice of suicide prevention strategy to distress at the individual level, each and every developer foregrounded their efforts in collectivist-attitudes, social relations, non-professional services, and community-driven projects rooted in decolonization efforts. This focus may reflect a need to honor Indigenous assumptions about suicide in community-based prevention programs. Conclusion: Altogether, our analysis points to a multi-level ecosystem of interventions that incorporates individual-centered rationales and interventions so long as they also consider systems, contexts, and a collectivist mentality.

The aerobic oxidation of methane (CH4) by methanotrophic bacteria (MOB) is the major sink of this highly potent greenhouse gas in freshwater environments. Yet, CH4 oxidation is one of the largest uncertain components in predicting the current and future CH4 emissions from these systems. While stable carbon isotopic mass balance is a powerful approach to estimate the extent of CH4 oxidation in situ, its applicability is constrained by the need of a reliable isotopic fractionation factor (αox), which depicts the slower reaction of the heavier stable isotope (13C) during CH4 oxidation. Here we explored the natural variability and the controls of αox across the water column of six temperate lakes using experimental incubation of unamended water samples at different temperatures. We found a large variability of αox (1.004–1.038) with a systematic increase from the surface to the deep layers of lake water columns. Moreover, αox was strongly positively coupled to the abundance of MOB in the γ-proteobacteria class (γ-MOB), which in turn correlated to the concentrations of oxygen and CH4, and to the rates of CH4 oxidation. To enable the applicability in future isotopic mass balance studies, we further developed a general model to predict αox using routinely measured limnological variables. By applying this model to δ13C-CH4 profiles obtained from the study lakes, we show that using a constant αox value in isotopic mass balances can largely misrepresent and undermine patterns of the extent of CH4 oxidation in lakes. Our αox model thus contributes towards more reliable estimations of stable carbon isotope-based quantification of CH4 oxidation and may help to elucidate large scale patterns and drivers of the oxidation-driven mitigation of CH4 emission from lakes.

Uranium (U) is a radiologically and chemically toxic element that occurs naturally in water, soil, and rock at generally low levels. However, anthropogenic uranium can also leach into groundwater sources due to mining, ore refining, and improper nuclear waste management. Over the last few decades, various methods for measuring uranium have emerged; however, most of these techniques require skilled scientists to run samples on expensive instrumentation for detection or require the pretreatment of samples in complex procedures. In this work, a Schiff base ligand (P1) is used to develop a simple spectrophotometric method for measuring the concentration of uranium (VI) with an accurate and affordable light-emitting diode (LED) spectrophotometer. A test for a higher-order polynomial relationship was used to objectively determine the calibration data's linearity. This test was done with a Python program on a Raspberry Pi computer that captured the spectrophotometer's calibration and sample measurement data. [ABSTRACT FROM AUTHOR]

Headspace analysis of CO2 frequently has been used to quantify the concentration of CO2 in fresh water. According to basic chemical theory, not considering chemical equilibration of the carbonate system in the sample vials will result in a systematic error. By analysing the potential error for different types of water and experimental conditions, we show that the error incurred by headspace analysis of CO2 is less than 5 % for typical samples from boreal systems which have low alkalinity (< 900 µmol L−1), with pH < 7.5, and high pCO2 (> 1000 µatm). However, the simple headspace calculation can lead to high error (up to −300 %) or even impossibly negative values in highly undersaturated samples equilibrated with ambient air, unless the shift in carbonate equilibrium is explicitly considered. The precision of the method can be improved by lowering the headspace ratio and/or the equilibration temperature. We provide a convenient and direct method implemented in an R script or a JMP add-in to correct CO2 headspace results using separately measured alkalinity.