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River flows and associated suspended sediment (SS) transport are intermittent processes possessing fluctuations over a large range of time scales and space, making it challenging to develop predictive models that are applicable across timescales and rivers. A concept of “effective timescales of connectivity” has been used to define the timeframe over which sediment (dis)connectivity occurs, whereby parts of the catchment are “switched on and off” as a response of events with varying frequency-magnitude relationships and antecedent soil moisture. These concepts provide excellent frameworks to understand temporal variability and identify relevant timescales for sediment transport, but do not help in the knowledge of mechanisms for temporal variability in SS transport. The complexity and scale dependency of processes driving SS transport stress the need to detect how sediment generation, storage, and transport are linked across different timescales. Furthermore, the mechanisms that produce travel time distributions over many orders of magnitude are not known precisely. To this end, in this study we have considered SS transport as a fractal system. By approaching SS transport dynamics as a fractal system, it is assumed that patterns of variation in SS transport exist over different timescales, while linkages across those temporal scales are expressed as fractal power-laws.This work aims to defines the link between (i) sediment transport and deposition and (ii) fractal geometry and fractal storage time distributions in streams.Here, we present case study where fractals are used to describe and predict patterns over different spatial or temporal scales of dynamics in SSCs. We have considered in these studies the statistics and the dynamics of streamflow, SSCs and associated grain size distribution at event based by considering respectively their probability distribution function and Fourier power spectra.We set up a natural experiment site of a first-order mixed bedrock and alluvial stream channel by using LISST instrument coupling with LIDAR remote sensing measurement. Here we obtain high-resolution observations of streambed topography and continuously long-term measurements of suspended sediment in natural experimental site located in an agricultural watershed of a Chianti area (Florence, Italy).The LISST is a submersible laser diffraction particle size analyzer for measuring suspended particle size (range from 2.50 µm to 500 µm), its volume concentration at different time step and depth. We set up at time interval equal to 5 minutes of sample rate.Preliminary results obtained indicate large fluctuations with heavy tails, and long-range properties, characterized by extreme events much more frequent than what is found for a Gaussian process.Hence, insights into the degree of fractal power of a SS transport system may provide a useful basis to evaluate and develop the most appropriate predictive models and management strategies.

The oceans play an important role in the carbon cycle by exchanging CO2 with the atmosphere. These exchanges correspond to the biological pump, where the ocean can be sink or source of atmospheric CO2. Our hypothesis is that CO2 concentration, either atmospheric or oceanic, are chemical tracers being strongly influence by turbulence: we thus study separately their dynamics, and also their difference which is giving indication of the direction of the air-sea CO2 flux. For this we use a publicly available data set of pCO2 simultaneous measurements at high frequency (typically 3 hours time step) at 40 difference places around the globe, from surface buoys (Sutton et al. 2019). We consider here the scaling properties of these quantities in order to characterize their multi-scale fluctuations, which are considered in the framework of passive or active scalars in turbulence. For each site, this is done by analyzing temperature, salinity, oceanic (pCO2sw), atmospheric (pCO2air) pCO2 and their difference $\delta = pCO2sw - pCO2air$. Power spectral density are estimated in Fourier space and using Hilbert spectral analysis, with adapted methodologies to take into account the missing data problem. Spectral slopes are recorded and are interpreted in relation with the local climatology, depth and other factors.

Diatoms have high productivity and are highly influenced by turbulent conditions. We consider here diatoms of the species Pseudo-nitzschia, which are chain forming. The objective of this work was to show how the turbulent environment affects the growth and the chain forming of these species. For this, cultures of the species Pseudo-nitzschia multiseries and Pseudo-nitzschia fraudulenta were performed in the laboratory and submitted to stationary turbulent conditions, using the Agiturb system developed in the LOG at Wimereux (Le Quiniou et al. 2022). In the Agiturb system, the turbulent flow is produced using four contra-rotating agitators that are placed under a cubic tank, generating a statistically stationary, spatially inhomogeneous flow with compression and stretching. The injection of the energy in the flow is produced by 4 stirring bars activated by 4 magnetic stirrers situated at symmetric positions. The cubic tank is almost half-full with 15 liters of sea water. For each experiment, the magnitude of the rotation rate of each agitator was identical, with two agitators rotating clockwise and two anti-clockwise, the same directions being along the diagonal. Different values of the rotation rate were chosen to reach different turbulence levels, characterized by the microscale Reynolds number Rλ going from 130 to 360. These Reynolds numbers correspond to typical values found in the ocean, from the epicontinental zone, to coastal, surf zones and even storm conditions. In the experiments, all the other parameters that affect the diatoms’ proliferation were kept the same. Formation and growth of the chains were assessed through microscopy. P. fraudulenta displayed higher growth than P. multiseries in all turbulence levels except from the control condition (Rλ=0) where the growth was approximately the same. The level of turbulence that was more beneficial for the growth of P. multiseries was the agitated (Rλ= 240) whereas for P. fraudulenta it was for a smaller Reynolds number (Rλ = 160). The chain length were also considered in relation with turbulence level, by considering the probability density of single chains, small chains (2 or 3 cells) and long chains (more than 4 cells). The result was that the predominant form of the cells for both species was the single cells. However, P. multiseries presented higher variations in chain forming throughout the whole experiment than P. fraudulenta. Within this approach, the optimal turbulence level, for growth as well as chain formation, can be assessed for each phytoplankton species.

Bulk ice-microphysical models parameterize the dynamic evolution of ice particles from advection, collection, and sedimentation through a cloud layer to the surface. Frozen hydrometeors can grow to acquire a multitude of shapes and sizes, which influence the distribution of mass within cloud systems. Aggregates, defined herein as the collection of ice particles, have a variety of formations based on initial ice particle size, shape, falling orientation, and the number of particles that collect. This work focuses on using the Ice Particle and Aggregate Simulator (IPAS) as a statistical tool to repetitively collect ice crystals of identical properties to derive bulk aggregate characteristics. A database of 9 744 000 aggregates is generated with resulting properties analyzed. After 150 single ice crystals (monomers) collect, the most extreme aggregate aspect ratio calculations asymptote toward and ϕca ≈ 0.50 for aggregates composed of quasi-horizontally oriented and randomly oriented monomers, respectively. The results presented are largely consistent with both a previous theoretical study and estimates derived from ground-based observations from two different geographic locations. Particle falling orientation highly influences newly formed aggregate aspect ratios from the collection of particles with extreme aspect ratios; quasi-horizontally oriented particles can produce aggregate aspect ratios an order of magnitude more extreme than randomly oriented particles but can also produce near-spherical aggregates as the number of monomers comprising the aggregate reach approximately 100. Finally, a majority of collections result in aggregates that are closer to prolate than oblate spheroids.

The Ice Particle and Aggregate Simulator (IPAS) is used to theoretically represent the aggregation process of ice crystals. Aggregates have a variety of formations based on initial ice particle size, shape, and falling orientation, all of which influence water phase partitioning. Aggregate dimensional properties and density changes are calculated for monomer–monomer (MON–MON), monomer–aggregate (MON–AGG), and aggregate–aggregate (AGG–AGG) collection to be used by ice-microphysical models for improvement in aggregation parameterizations. Aggregates are chosen from a database of 9 744 000 preformed combinations to be further collected (see Part II). AGG–AGG collection results in more extreme and a smaller range of aggregate aspect ratios than MON–AGG collection. A majority of aggregates are closer to prolate than oblate spheroids, regardless of collection type, except for quasi-horizontally oriented particles that have extreme aspect ratios to begin with. MON–AGG collection frequently results in an increase in density upon collection, whereas MON–MON and AGG–AGG collection almost always result in particle density decreases, with extreme reductions near 99% for MON–MON collection. MON–MON collection results in the greatest decreases in density but then quickly becomes unaffected by the addition of more monomers due to inherent size differences between monomers and aggregates. Finally, a holistic analysis to in situ observations of cloud particle images is presented. IPAS 2D aspect ratios surround a median value of 0.6 and closely follow that of previous studies while varying by no more than ≈12% on average from observed aggregates.

A vast amount of ice crystal imagery exists from a variety of field campaign initiatives that can be utilized for cloud microphysical research. Here, nine convolutional neural networks are used to classify particles into nine regimes on over 10 million images from the Cloud Particle Imager probe, including liquid and frozen states and particles with evidence of riming. A transfer learning approach proves that the Visual Geometry Group (VGG-16) network best classifies imagery with respect to multiple performance metrics. Classification accuracies on a validation dataset reach 97% and surpass traditional automated classification. Furthermore, after initial model training and preprocessing, 10 000 images can be classified in approximately 35 s using 20 central processing unit cores and two graphics processing units, which reaches real-time classification capabilities. Statistical analysis of the classified images indicates that a large portion (57%) of the dataset is unusable, meaning the images are too blurry or represent indistinguishable small fragments. In addition, 19% of the dataset is classified as liquid drops. After removal of fragments, blurry images, and cloud drops, 38% of the remaining ice particles are largely intersecting the image border (≥10% cutoff) and therefore are considered unusable because of the inability to properly classify and dimensionalize. After this filtering, an unprecedented database of 1 560 364 images across all campaigns is available for parameter extraction and bulk statistics on specific particle types in a wide variety of storm systems, which can act to improve the current state of microphysical parameterizations.

The 7 January 2020 M 6.4 Puerto Rico earthquake, the mainshock of an extended earthquake sequence, triggered significant ground failure. In this study, we detail the ground failure that occurred based largely on a postearthquake field reconnaissance campaign that we conducted. We documented more than 300 landslides, mainly rock falls that were concentrated in areas where peak ground acceleration (PGA) exceeded 30%g; sparse smaller landslides occurred in highly susceptible areas more than 50 km from the epicenter and at PGA values

Primary immunodeficiency diseases (PIDs) are a rapidly growing, heterogeneous group of genetically determined diseases characterized by defects in the immune system. While individually rare, collectively PIDs affect between 1/1,000 and 1/5,000 people worldwide. The clinical manifestations of PIDs vary from susceptibility to infections to autoimmunity and bone marrow failure. Our understanding of the human immune response has advanced by investigation and discovery of genetic mechanisms of PIDs. Studying patients with isolated genetic variants in proteins that participate in complex signaling pathways has led to an enhanced understanding of host response to infection, and mechanisms of autoimmunity and autoinflammation. Identifying genetic mechanisms of PIDs not only furthers immunological knowledge but also benefits patients by dictating targeted therapies or hematopoietic stem cell transplantation. Here, we highlight several of these areas in the field of primary immunodeficiency, with a focus on the most recent advances.

5-(2-Aminopropyl)benzofuran (5-APB) and 6-(2-aminopropyl)benzofuran (6-APB) are benzofuran analogues of amphetamine and belong to the category of new psychoactive substances. Despite already published fatal 5- and 6-APB intoxication after consumption of both substances in most cases, no sensitive method for the simultaneous detection and quantification of these new psychoactive compounds in human blood samples has yet been developed. Therefore, an easy and fast sample preparation and specific high-performance liquid chromatography and tandem mass spectrometry methods for the determination of both substances in blood were established and validated. In a fatal intoxication in 2017 at the Institute of Forensic and Traffic Medicine in Heidelberg, Germany, concentrations of 850 (5-APB) and 300 ng/mL (6-APB) were determined in peripheral blood. Besides, other body fluids (central blood, urine and bile), hair and various tissues were examined to verify the presence of both compounds and to gain first insights into their distribution. In this publication, we show a method for the simultaneous determination of 5- and 6-APB in human samples by a chromatographic method and to investigate their distribution in the human body.

Osteoarthritis (OA) is a serious consequence of focal osteochondral defects. Gene transfer of human transforming growth factor beta (hTGF-β) with recombinant adeno-associated virus (rAAV) vectors offers a strategy to improve osteochondral repair. However, the long-term in vivo effects of such rAAV-mediated TGF-β overexpression including its potential benefits on OA development remain unknown.Focal osteochondral defects in minipig knees received rAAV-lacZ (control) or rAAV-hTGF-β in vivo. After one year, osteochondral repair and perifocal OA were visualized using validated macroscopic scoring, ultra-high-field MRI at 9.4 Tesla, and micro-CT. A quantitative estimation of the cellular densities and a validated semi-quantitative scoring of histological and immunohistological parameters completed the analysis of microarchitectural parameters.Direct rAAV-hTGF-β application induced and maintained significantly improved defect filling and safranin O staining intensity and overall cartilage repair at one year in vivo. In addition, rAAV-hTGF-β led to significantly higher chondrocyte densities within the cartilaginous repair tissue without affecting chondrocyte hypertrophy and minimized subarticular trabecular separation. Of note, rAAV-hTGF-β significantly improved the adjacent cartilage structure and chondrocyte density and reduced overall perifocal OA development after one year in vivo.rAAV-hTGF-β treatment improves long-term osteochondral repair and delays the progression of perifocal OA in a translational model. These findings have considerable potential for targeted molecular approaches to treat focal osteochondral defects.

A novel methodology for modeling ice–ice aggregation is presented. This methodology combines a modified hydrodynamic collection algorithm with bulk aggregate characteristic information from an offline simulator that collects ice particles, namely, the Ice Particle and Aggregate Simulator, and has been implemented into the Adaptive Habit Microphysics scheme in the Weather Research and Forecasting Model. Aggregates, or snow, are formed via collection of cloud ice particles, where initial ice characteristics and the resulting geometry determine aggregate characteristics. Upon implementation, idealized squall-line simulations are performed to examine the new methodology in comparison with commonly used bulk microphysics schemes. It is found that the adaptive habit aggregation parameterization develops snow and reduces ice mass and number concentrations compared to other schemes. The development of aggregates through the new methodology cascades into other interesting effects, including enhancements in ice and snow growth, as well as homogeneous freezing. Further microphysical analyses reveal varying sensitivities, where snow processes are most sensitive to the new parameterization, followed by ice, then cloud, rain, and graupel processes. Further, the new scheme results in enhancements in surface precipitation due to the persistence of snow at lower altitudes. This persistence is a result of shape-dependent melting and sublimation, increasing the residence time. Moreover, these low-level enhancements are reflected in increases in radar reflectivity at the surface and its spatial distribution. Finally, the ability to predict snow shape and density allows for the simulation of polarimetric radar quantities, resulting in signature enhancements compared to schemes that do not consider spatial and temporal variations in snow shape and density.

Summary Genetic testing has increased the number of variants identified in disease genes, but the diagnostic utility is limited by lack of understanding variant function. CARD11 encodes an adaptor protein that expresses dominant-negative and gain-of-function variants associated with distinct immunodeficiencies. Here, we used a “cloning-free” saturation genome editing approach in a diploid cell line to simultaneously score 2,542 variants for decreased or increased function in the region of CARD11 associated with immunodeficiency. We also described an exon-skipping mechanism for CARD11 dominant-negative activity. The classification of reported clinical variants was sensitive (94.6%) and specific (88.9%), which rendered the data immediately useful for interpretation of seven coding and splicing variants implicated in immunodeficiency found in our clinic. This approach is generalizable for variant interpretation in many other clinically actionable genes, in any relevant cell type.

Although online lectures have become increasingly popular, their effectiveness at promoting learning can be attenuated by mind wandering (shifts in attention away from the task at hand towards unrelated thoughts). We investigated whether taking tests on to-be-studied information, also known as pretesting, could mitigate this problem and promote learning. In two experiments, participants viewed a 26-min video-recorded online lecture that was paired with a pretest activity (answering questions about the lecture) or a control activity (solving algebra problems), and with multiple probes to measure attention. Taking pretests reduced mind wandering and improved performance on a subsequent final test compared to the control condition. This result occurred regardless of whether pretests were interspersed throughout the lecture (Experiment 1) or were administered at the very beginning of the lecture (Experiment 2). These findings demonstrate that online lectures can be proactively structured to reduce mind wandering and improve learning via the incorporation of pretests.

Detailed information about landslide occurrence is the foundation for advancing process understanding, susceptibility mapping, and risk reduction. Despite the recent revolution in digital elevation data and remote sensing technologies, landslide mapping remains resource intensive. Consequently, a modern, comprehensive map of landslide occurrence across the United States (USA) has not been compiled. As a first step toward this goal, we present a national-scale compilation of existing, publicly available landslide inventories. This geodatabase can be downloaded in its entirety or viewed through an online, searchable map, with parsimonious attributes and direct links to the contributing sources with additional details. The mapped spatial pattern and concentration of landslides are consistent with prior characterization of susceptibility within the conterminous USA, with some notable exceptions on the West Coast. Although the database is evolving and known to be incomplete in many regions, it confirms that landslides do occur across the country, thus highlighting the importance of our national-scale assessment. The map illustrates regions where high-quality mapping has occurred and, in contrast, where additional resources could improve confidence in landslide characterization. For example, borders between states and other jurisdictions are quite apparent, indicating the variation in approaches to data collection by different agencies and disparity between the resources dedicated to landslide characterization. Further investigations are needed to better assess susceptibility and to determine whether regions with high relief and steep topography, but without mapped landslides, require further landslide inventory mapping. Overall, this map provides a new resource for accessing information about known landslides across the USA.

Octamethylcyclotetrasiloxane (D4) is a high production volume chemical that has been subject to thorough toxicological investigations. Animal studies with the substance were conducted with either Fischer 344 or Sprague Dawley CD rats. While the pharmacokinetic fate of D4 in Fischer rats is well understood, little information exists on Sprague Dawley CD rats, where reproductive effects have been demonstrated. The objective of this study was to explore the pharmacokinetic behavior in both rats, and to identify potential strain-specific differences. Fischer and Sprague Dawley CD rats were exposed for six hours to 700 ppm of

Plankton species live in a turbulent flow and are fully adapted to it. They have specific behaviour and responses related to turbulence characteristics and intensities, that are still largely unknown. Turbulence systems in the laboratory are needed to perform controled experiments with different zooplankton and phytoplankton species. Here we present the Agiturb turbulence generation system and some first results using different plankton species. In the Agiturb system, the turbulent flow is produced using four contra-rotating agitators that are place under a cubic tank. The model for such flow is the so-called “four-roll mill” proposed by G.I. Taylor in 1934 to generate a statistically stationary, spatially inhomogeneous flow with compression and stretching. In our experiment, the flow close to the agitators is a free flow similar to the four-roll mill, without the cylindrical rolls. The injection of the energy in the flow is produced by 4 stirring bars activated by 4 magnetic stirrers situated at symmetric positions, the centers being placed at one-fourth of the width of the tank. The cubic tank is almost half-full with 15 liters of sea water. For each experiment, the magnitude of the rotation rate of each agitator was identical, with two agitators rotating clockwise and two anti-clockwise, the same directions being along the diagonal. Different values of the rotation rate were chosen to reach different turbulence levels, characterized by the microscale Reynolds number Rλ going from 130 to 360. We present the result of two different experiments: the first one is a record, using a high speed camera in the infrared, of copepods trajectories, at different turbulent intensities, in order to see an optimal Reynolds number for copepods swimming activities (Acartia tonsa). The second one is a systematic study of the proliferation of diatoms under different turbulent intensities (Pseudo-nitzschia). In both cases different rotation rates of the system are considered, and an optimal turbulence level has been found, with maximum swimming activity for copepods and maximum growth rate for diatoms.

Turbulence theory essentially describes energy and enstrophy flows crossing scales or a balance between input and output. A famous example is the Richardson-Kolmogorov forward energy cascade picture for three-dimensional homogeneous and isotropic turbulence. However, due to the complexity of turbulent systems, and the lack of an efficient method to describe the cascade quantitatively, the factual cascade features for most fluids are still unknown. In this work, an improved Filter-Space-Technique (FST) is proposed to extract the energy flux ΠE, and enstrophy flux ΠΩ between different scales for the ocean surface wind field which was remotely sensed by the China-France Oceanography Satellite (CFOSAT). With the improved FST method, ΠE and ΠΩ can be calculated for databases which contain gaps or with irregular boundary conditions. Moreover, the local information of the fluxes are preserved. A case study of the typhoon Maysak (2020) shows both inverse and forward cascades for the energy and enstrophy around the center of the typhoon, indicating a rich dynamical pattern. The global views of ΠE and ΠΩ for the wind field are studied for scales from 12.5 to 500 km. The results show that both ΠE and ΠΩ are hemispherically symmetric, with evident spatial and temporal variations for all the scales. More precisely, positive and negative ΠE are found for the scales less and above 60 km, respectively. As for ΠΩ, the transition scale is around 150 km, forward and backward cascades are corresponding to the scales below and above this scale. In the physical space, stronger fluxes are occurring in midlatitudes than the ones in tropical regions, excepts for a narrow region around 10oN, where strong fluxes are observed. In the temporal space, the fluxes in winter are stronger than the ones in summer. Our study provides an improved approach to derive the local energy and enstrophy fluxes with complex field observed data. The results presented in this work contribute to the fundamental understanding of ocean surface atmospheric motions in their multiscale dynamics, and also provide a benchmark for atmospheric models. Ref. Alexakis, A., & Biferale, L. (2018). Cascades and transitions in turbulent flows. Phys. Rep., 767, 1-101.Dong, S., Huang, Y.X., Yuan, X., Lozano-Durán, A. (2020). The coherent structure of the kinetic energy transfer in shear turbulence. J. Fluid Mech., 892, A22.Frisch, U., Kolmogorov, A. N. (1995). Turbulence: the legacy of AN Kolmogorov. Cambridge University Press.Gao, Y. , Schmitt, F.G., Hu, J.Y. & Huang, Y.X. (2021) Scaling analysis of the China France Oceanography Satellite along-track wind and wave data. J. Geophys. Res. Oceans, 126:e2020JC017119

International audience; We study the statistical properties of scalar fields undergoing reversible chemical reactions in a turbulent environment by means of numerical simulations. To produce strong chemical fluctuations in a wide region of the domain, an original flow configuration has been proposed, where the species are supplied from buffer boundaries with adjustable thickness, while the flow is developed homogeneous and isotropic turbulence in a periodic domain. With the presence of the mean scalar gradient in the bulk region, the strength of turbulent advection is comparable with the chemical source, which is quantified by the Damköhler number. Our analysis focuses on the global and spatial properties of the reactive scalars in their statistically steady regime. We show how for the case of a second-order reaction such features can be connected to the properties of a non-reactive scalar field advected in the same system. Analytical predictions of the scalar moments in the fast reaction regime agree satisfactorily with the direct numerical simulation results. In comparison with the existing results of the isotropic turbulence case, we conclude that the scalar correlation is jointly determined by both the chemical source and the flow configuration. Moreover, the chemical reaction also plays an important role in determining the scalar energy spectra.

International audience