Search

Wave breaking is the main mechanism that dissipates energy input into ocean waves by wind and transferred across the spectrum by nonlinearity. It determines the properties of a sea state and plays a crucial role in ocean-atmosphere interaction, ocean pollution, and rogue waves. Owing to its turbulent nature, wave breaking remains too computationally demanding to solve using direct numerical simulations except in simple, short-duration circumstances. To overcome this challenge, we present a blended machine learning framework in which a physics-based nonlinear evolution model for deep-water, non-breaking waves and a recurrent neural network are combined to predict the evolution of breaking waves. We use wave tank measurements rather than simulations to provide training data and use a long short-term memory neural network to apply a finite-domain correction to the evolution model. Our blended machine learning framework gives excellent predictions of breaking and its effects on wave evolution, including for external data.

Wave breaking is the main mechanism that dissipates energy input into ocean waves by wind and transferred across the spectrum by nonlinearity. It determines the properties of a sea state and plays a crucial role in ocean-atmosphere interaction, ocean pollution, and rogue waves. Owing to its turbulent nature, wave breaking remains too computationally demanding to solve using direct numerical simulations except in simple, short-duration circumstances. To overcome this challenge, we present a blended machine learning framework in which a physics-based nonlinear evolution model for deep-water, non-breaking waves and a recurrent neural network are combined to predict the evolution of breaking waves. We use wave tank measurements rather than simulations to provide training data and use a long short-term memory neural network to apply a finite-domain correction to the evolution model. Our blended machine learning framework gives excellent predictions of breaking and its effects on wave evolution, including for external data., Environmental Fluid Mechanics

Wave breaking is the main mechanism that dissipates energy input into ocean waves by wind and transferred across the spectrum by nonlinearity. It determines the properties of a sea state and plays a crucial role in ocean-atmosphere interaction, ocean pollution, and rogue waves. Owing to its turbulent nature, wave breaking remains too computationally demanding to solve using direct numerical simulations except in simple, short-duration circumstances. To overcome this challenge, we present a blended machine learning framework in which a physics-based nonlinear evolution model for deep-water, non-breaking waves and a recurrent neural network are combined to predict the evolution of breaking waves. We use wave tank measurements rather than simulations to provide training data and use a long short-term memory neural network to apply a finite-domain correction to the evolution model. Our blended machine learning framework gives excellent predictions of breaking and its effects on wave evolution, including for external data., Environmental Fluid Mechanics

Cancer-associated fibroblasts (CAF) are major contributors to pancreatic ductal adenocarcinoma (PDAC) progression through protumor signaling and the generation of fibrosis, the latter of which creates a physical barrier to drugs. CAF inhibition is thus an ideal component of any therapeutic approach for PDAC. SLC7A11 is a cystine transporter that has been identified as a potential therapeutic target in PDAC cells. However, no prior study has evaluated the role of SLC7A11 in PDAC tumor stroma and its prognostic significance. Here we show that high expression of SLC7A11 in human PDAC tumor stroma, but not tumor cells, is independently prognostic of poorer overall survival. Orthogonal approaches showed that PDAC-derived CAFs are highly dependent on SLC7A11 for cystine uptake and glutathione synthesis and that SLC7A11 inhibition significantly decreases CAF proliferation, reduces their resistance to oxidative stress, and inhibits their ability to remodel collagen and support PDAC cell growth. Importantly, specific ablation of SLC7A11 from the tumor compartment of transgenic mouse PDAC tumors did not affect tumor growth, suggesting the stroma can substantially influence PDAC tumor response to SLC7A11 inhibition. In a mouse orthotopic PDAC model utilizing human PDAC cells and CAFs, stable knockdown of SLC7A11 was required in both cell types to reduce tumor growth, metastatic spread, and intratumoral fibrosis, demonstrating the importance of targeting SLC7A11 in both compartments. Finally, treatment with a nanoparticle genesilencing drug against SLC7A11, developed by our laboratory, reduced PDAC tumor growth, incidence of metastases, CAF activation, and fibrosis in orthotopic PDAC tumors. Overall, these findings identify an important role of SLC7A11 in PDAC-derived CAFs in supporting tumor growth. Significance: this study demonstrates that SLC7A11 in PDAC stromal cells is important for the tumor-promoting activity of CAFs and validates a clinically translatable nanomedicine, NHMRC Project Grant; Avner Innovation Grant; NHMRC CDF-I; NHMRC Ideas Grant ; Cancer-Institute NSW ECF/CDFs ; Cancer Institute NSW Innovation Grant; Cancer Institute NSW The Professor Rob Sutherland AO Make a Difference Award; Cancer Australia/Cancer Council; Cancer Australia/Kids Cancer Project; Cure Cancer Australia; Tour de Cure PhD Support Scholarship; Tour de Cure Established Research Grant; Tour de Cure Pioneering Research Grant; UNSW Interlude Grant Scheme; Cancer Research UK Core Funding and Grand Challenge Grants; NHMRC CDF-II; NHMRC Senior Research Fellowship; Suttons, Cancer Council NSW; Avner Grant from PanKind; Australian Pancreatic Cancer Foundation; Translational Cancer Research Network and Australian Postgraduate Award Scholarships; Australian Government Research Training Program Scholarship; UNSW Sydney Scientia PhD Scholarship; Pancreatic Cancer UK Future Leaders Academy; Len Ainsworth Pancreatic Cancer Fellowship

Numerical lake models are useful tools to study hydrodynamics in lakes, and are increasingly applied to extreme weather events. However, little is known about the accuracy of such models during these short-term events. We used high-frequency data from three lakes to test the performance of three one-dimensional (1D) hydrodynamic models (Simstrat, GOTM, GLM) during storms and heatwaves. Models reproduced the overall direction and magnitude of changes during the extreme events, with accurate timing and little bias. Changes in volume-averaged and surface temperatures and Schmidt stability were simulated more accurately than changes in bottom temperature, maximum buoyancy frequency, or mixed layer depth. However, in most cases the model error was higher (30-100%) during extreme events compared to reference periods. As a consequence, while 1D lake models can be used to study effects of extreme weather events, the increased uncertainty in the simulations should be taken into account when interpreting results.

Numerical lake models are useful tools to study hydrodynamics in lakes, and are increasingly applied to extreme weather events. However, little is known about the accuracy of such models during these short-term events. We used high-frequency data from three lakes to test the performance of three one-dimensional (1D) hydrodynamic models (Simstrat, GOTM, GLM) during storms and heatwaves. Models reproduced the overall direction and magnitude of changes during the extreme events, with accurate timing and little bias. Changes in volume-averaged and surface temperatures and Schmidt stability were simulated more accurately than changes in bottom temperature, maximum buoyancy frequency, or mixed layer depth. However, in most cases the model error was higher (30-100%) during extreme events compared to reference periods. As a consequence, while 1D lake models can be used to study effects of extreme weather events, the increased uncertainty in the simulations should be taken into account when interpreting results.

Numerical lake models are useful tools to study hydrodynamics in lakes, and are increasingly applied to extreme weather events. However, little is known about the accuracy of such models during these short-term events. We used high-frequency data from three lakes to test the performance of three one-dimensional (1D) hydrodynamic models (Simstrat, GOTM, GLM) during storms and heatwaves. Models reproduced the overall direction and magnitude of changes during the extreme events, with accurate timing and little bias. Changes in volume-averaged and surface temperatures and Schmidt stability were simulated more accurately than changes in bottom temperature, maximum buoyancy frequency, or mixed layer depth. However, in most cases the model error was higher (30-100%) during extreme events compared to reference periods. As a consequence, while 1D lake models can be used to study effects of extreme weather events, the increased uncertainty in the simulations should be taken into account when interpreting results.

Numerical lake models are useful tools to study hydrodynamics in lakes, and are increasingly applied to extreme weather events. However, little is known about the accuracy of such models during these short-term events. We used high-frequency data from three lakes to test the performance of three one-dimensional (1D) hydrodynamic models (Simstrat, GOTM, GLM) during storms and heatwaves. Models reproduced the overall direction and magnitude of changes during the extreme events, with accurate timing and little bias. Changes in volume-averaged and surface temperatures and Schmidt stability were simulated more accurately than changes in bottom temperature, maximum buoyancy frequency, or mixed layer depth. However, in most cases the model error was higher (30-100%) during extreme events compared to reference periods. As a consequence, while 1D lake models can be used to study effects of extreme weather events, the increased uncertainty in the simulations should be taken into account when interpreting results.

Numerical lake models are useful tools to study hydrodynamics in lakes, and are increasingly applied to extreme weather events. However, little is known about the accuracy of such models during these short-term events. We used high-frequency data from three lakes to test the performance of three one-dimensional (1D) hydrodynamic models (Simstrat, GOTM, GLM) during storms and heatwaves. Models reproduced the overall direction and magnitude of changes during the extreme events, with accurate timing and little bias. Changes in volume-averaged and surface temperatures and Schmidt stability were simulated more accurately than changes in bottom temperature, maximum buoyancy frequency, or mixed layer depth. However, in most cases the model error was higher (30-100%) during extreme events compared to reference periods. As a consequence, while 1D lake models can be used to study effects of extreme weather events, the increased uncertainty in the simulations should be taken into account when interpreting results.

We propose a pump-probe differential Lidar technique to remotely map the ability of the atmosphere to undergo particle condensation, which depends on the concentration of both pre-existing nanoparticles and condensable species or their precursors. Besides its interest for improving short-time, local weather forecast, this technique could provide information on atmospheric parameters such as the concentration of condensable species and physical parameters including the temperature and relative humidity.

We characterized the white-light supercontinuum emission by a sub-petawatt laser system in the atmosphere via light detection and ranging measurements. As much as 1J of supercontinuum is generated in the atmosphere, corresponding to a conversion efficiency of 30%. This generation occurs at altitudes below 100m. The high initial beam intensity results in the saturation of the number of self-guided filaments. Therefore, the "photon bath” surrounding the filaments strongly contributes to the white-light generation. These finding is well reproduced by numerical simulations based on the experimental parameters.

We propose the impingement of non-uniform wavefront curvature as a simple way to improve the longitudinal homogeneity of the plasma density along filaments generated by ultrashort laser pulses. We characterize multiple filamentation of a multiterawatt beam with different wavefront curvatures applied to specific regions in the transverse beam profile. In adequate conditions, the filamenting region is more homogeneously ionized, in the longitudinal direction, than in the case of uniform focusing. Moreover, the ionization maximum is located between the middle and the two thirds of the filaments in all investigated chirps and focus configurations

We experimentally and numerically characterize multiple filamentation of laser pulses with incident intensities of a few TW/cm2. Propagating 100TW laser pulses over 42m in air, we observe a new propagation regime where the filament density saturates. As also evidenced by numerical simulations in the same intensity range, the total number of filaments is governed by geometric constraints and mutual interactions among filaments rather than by the available power in the beam

© The Author(s) 2017. The influence of aerosols on climate is highly dependent on the particle size distribution, concentration, and composition. In particular, the latter influences their ability to act as cloud condensation nuclei, whereby they impact cloud coverage and precipitation. Here, we simultaneously measured the concentration of aerosols from sea spray over the North Atlantic on board the exhaust-free solar-powered vessel "PlanetSolar", and the sea surface physico-chemical parameters. We identified organic-bearing particles based on individual particle fluorescence spectra. Organic-bearing aerosols display specific spatio-temporal distributions as compared to total aerosols. We propose an empirical parameterization of the organic-bearing particle concentration, with a dependence on water salinity and sea-surface temperature only. We also show that a very rich mixture of organic aerosols is emitted from the sea surface. Such data will certainly contribute to providing further insight into the influence of aerosols on cloud formation, and be used as input for the improved modeling of aerosols and their role in global climate processes.

© The Author(s) 2017. The influence of aerosols on climate is highly dependent on the particle size distribution, concentration, and composition. In particular, the latter influences their ability to act as cloud condensation nuclei, whereby they impact cloud coverage and precipitation. Here, we simultaneously measured the concentration of aerosols from sea spray over the North Atlantic on board the exhaust-free solar-powered vessel "PlanetSolar", and the sea surface physico-chemical parameters. We identified organic-bearing particles based on individual particle fluorescence spectra. Organic-bearing aerosols display specific spatio-temporal distributions as compared to total aerosols. We propose an empirical parameterization of the organic-bearing particle concentration, with a dependence on water salinity and sea-surface temperature only. We also show that a very rich mixture of organic aerosols is emitted from the sea surface. Such data will certainly contribute to providing further insight into the influence of aerosols on cloud formation, and be used as input for the improved modeling of aerosols and their role in global climate processes.

Using 100 TW laser pulses, we demonstrate that laser-induced nanometric particle generation in air increases much faster than the beam-averaged incident intensity. This increase is due to a contribution from the photon bath, which adds up with the previously identified one from the filaments and becomes dominant above 550 GW/cm2. It appears related to ozone formation via multiphoton dissociation of the oxygen molecules and demonstrates the critical need for further increasing the laser energy in view of macroscopic effects in laser-induced condensation.

We experimentally measured the supercontinuum generation by 3 J, 30 fs laser pulses and measured white-light generation at the unprecedented level of 1 J. Such high energy is allowed by a strong contribution to the continuum by the photon bath, as compared to the self-guided filaments. This contribution due to the recently observed congestion of the filament number density in the beam profile at very high intensity, also results in a wider broadening for positively chirped pulses rather than for negatively chirped ones, similarly to broadening in hollow-core fibers.

As a contribution to the ongoing controversy about the role of higher-order Kerr effect (HOKE) in laser filamentation, we first provide thorough details about the protocol that has been employed to infer the HOKE indices from the experiment. Next, we discuss potential sources of artifact in the experimental measurements of these terms and show that neither the value of the observed birefringence, nor its inversion, nor the intensity at which it is observed, appear to be flawed. Furthermore, we argue that, independently on our values, the principle of including HOKE is straightforward. Due to the different temporal and spectral dynamics, the respective efficiency of defocusing by the plasma and by the HOKE is expected to depend substantially on both incident wavelength and pulse duration. The discussion should therefore focus on defining the conditions where each filamentation regime dominates. © 2011 Pleiades Publishing, Ltd.

We experimentally and numerically characterize multiple filamentation of laser pulses with incident intensities of a few TW/cm2. Propagating 100 TW laser pulses over 42 m in air, we observe a new propagation regime where the filament density saturates. As also evidenced by numerical simulations in the same intensity range, the total number of filaments is governed by geometric constraints and mutual interactions among filaments rather than by the available power in the beam.

Based on numerical simulations, we show that higher-order nonlinear indices (up to n8 and n10, respectively) of air and argon have a dominant contribution to both focusing and defocusing in the self-guiding of ultrashort laser pulses over most of the spectrum. Plasma generation and filamentation are therefore decoupled. As a consequence, ultraviolet wavelength may not be the optimal wavelength for applications requiring to maximize ionization. © 2010 The American Physical Society.

Lightning research needs on-demand lightning strikes, because of the random character of natural lightning. Lasers have been proposed as alternatives to the current technique using rocket-pulled wires, because they would expectedly provide more flexibility. However, high-energy, nanosecond lasers cannot provide long connected plasma channels. In contrast, we recently reported the triggering of electric events in thunderclouds using ultrashort laser pulses. Further improvements of the laser pulse sequence and experimental geometry are discussed.

We investigated the possibility to trigger real-scale lightning using ionized filaments generated by ultrashort laser pulses in the atmosphere. Under conditions of high electric field during two thunderstorms, we observed a statistically significant number of electric events synchronized with the laser pulses, at the location of the filaments. This observation suggests that corona discharges may have been triggered by filaments.

The Teramobile laser facility was used to realize the first mobile source of high-power THz pulses. The source is based on a tilted-pulse-front pumping THz generation scheme optimized for application of terawatt laser pulses. Generation of 50-μJ single-cycle electromagnetic pulses centered at 0.19 THz with a repetition rate of 10Hz was obtained for incoming 700-fs 120-mJ near-infrared laser pulses. The corresponding laser-to-THz photon conversion efficiency is approximately 100%

We propose a pump-probe differential Lidar technique to remotely map the ability of the atmosphere to undergo particle condensation, which depends on the concentration of both pre-existing nanoparticles and condensable species or their precursors. Besides its interest for improving short-time, local weather forecast, this technique could provide information on atmospheric parameters such as the concentration of condensable species and physical parameters including the temperature and relative humidity.

We characterized the white-light supercontinuum emission by a sub-petawatt laser system in the atmosphere via light detection and ranging measurements. As much as 1J of supercontinuum is generated in the atmosphere, corresponding to a conversion efficiency of 30%. This generation occurs at altitudes below 100m. The high initial beam intensity results in the saturation of the number of self-guided filaments. Therefore, the "photon bath” surrounding the filaments strongly contributes to the white-light generation. These finding is well reproduced by numerical simulations based on the experimental parameters.

We experimentally and numerically characterize multiple filamentation of laser pulses with incident intensities of a few TW/cm2. Propagating 100TW laser pulses over 42m in air, we observe a new propagation regime where the filament density saturates. As also evidenced by numerical simulations in the same intensity range, the total number of filaments is governed by geometric constraints and mutual interactions among filaments rather than by the available power in the beam

We propose the impingement of non-uniform wavefront curvature as a simple way to improve the longitudinal homogeneity of the plasma density along filaments generated by ultrashort laser pulses. We characterize multiple filamentation of a multiterawatt beam with different wavefront curvatures applied to specific regions in the transverse beam profile. In adequate conditions, the filamenting region is more homogeneously ionized, in the longitudinal direction, than in the case of uniform focusing. Moreover, the ionization maximum is located between the middle and the two thirds of the filaments in all investigated chirps and focus configurations