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Over the last decade, supercell simulations and observations with ever increasing resolution have provided new insights into the vortex-scale processes of tornado formation. This article incorporates these and other recent findings into the existing three-step model by adding an additional fourth stage. The goal is to provide an updated and clear picture of the physical processes occurring during tornadogenesis. Specifically, we emphasize the importance of the low-level wind shear and mesocyclone for tornado potential, the organization and interaction of relatively small-scale pre-tornadic vertical vorticity maxima, and the transition to a tornado-characteristic flow. Based on these insights, guiding research questions are formulated for the decade ahead.

A growing body of literature argues that digital models do not just help organizational leaders to predict the future. Models can inadvertently produce the very future they purport to describe. In this view,performativityis a side-effect of digital modeling. But digital twins turn such thinking on its head. Digital twins are digital models that are designed to be performative—changes in the model are supposed to produce corresponding changes in the world the model represents. This is what makes digital twins useful. But for decision-makers to act in ways that align the world outside the model with the predictions contained within, they must first believe that the model is a faithful representation. In other words, for a digital twin to become performative, it must first be taken-for-granted as “real”. In this paper, we explore the technological and organizational characteristics that are likely to shape the level of taken-for-grantedness of a digital twin.

Experiments have demonstrated that ion phenomena, such as the lower hybrid resonance, play an important role in helicon source operation. Damping of the slow branch of the bounded whistler wave at the edge of a helicon source (i.e. the Trivelpiece-Gould mode) has been correlated with the creation of energetic electrons, heating of ions at the plasma edge, and anisotropic ion heating. Here we present ion velocity distribution function measurements, electron density and temperature measurements, and magnetic fluctuation measurements on both sides of an$m=|1|$helical antenna in a helicon source as a function of the driving frequency, magnetic field strength, and magnetic field orientation relative to the antenna helicity. Significant electron and ion heating (up to two times larger) occurs on the side of the antenna consistent with the launch of the$m=+1$mode. The electron and ion heating occurs within one electron skin depth of the plasma edge, where slow wave damping is expected. The source parameters for enhanced particle heating are also consistent with lower hybrid resonance effects, which can only occur for Trivelpiece-Gould wave excitation.

The Gram-negative betaproteobacterium Cupriavidus necator is a chemolithotroph that can convert carbon dioxide into biomass. Cupriavidus necator has been engineered to produce a variety of high-value chemicals in the past. However, there is still a lack of a well-characterized toolbox for gene expression and genome engineering. Development and optimization of biosynthetic pathways in metabolically engineered microorganisms necessitates control of gene expression via functional genetic elements such as promoters, ribosome binding sites (RBSs), and codon optimization. In this work, a set of inducible and constitutive promoters were validated and characterized in C. necator, and a library of RBSs was designed and tested to show a 50-fold range of expression for green fluorescent protein (gfp). The effect of codon optimization on gene expression in C. necator was studied by expressing gfp and mCherry genes with varied codon-adaptation indices and was validated by expressing codon-optimized variants of a C12-specific fatty acid thioesterase to produce dodecanoic acid. We discuss further hurdles that will need to be overcome for C. necator to be widely used for biosynthetic processes.

A simulation of a supercell storm produced for a prior study on tornado predictability is reanalyzed for the purpose of examining the fine-scale details of tornadogenesis. It is found that the formation of a tornado-like vortex in the simulation differs from how such vortices have been understood to form in previous numerical simulations. The main difference between the present simulation and past ones is the inclusion of a turbulent boundary layer in the storm’s environment in the present case, whereas prior simulations have used a laminar boundary layer. The turbulent environment contains significant near-surface vertical vorticity (ζ> 0.03 s⁻¹atz= 7.5 m), organized in the form of longitudinal streaks aligned with the southerly ground-relative winds. Theζstreaks are associated with corrugations in the vertical plane in the predominantly horizontal, westward-pointing environmental vortex lines; the vortex-line corrugations are produced by the vertical drafts associated with coherent turbulent structures aligned with the aforementioned southerly ground-relative winds (longitudinal coherent structures in the surface layer such as these are well known to the boundary layer and turbulence communities). Theζstreaks serve as focal points for tornadogenesis, and may actually facilitate tornadogenesis, given how near-surfaceζin the environment can rapidly amplify when subjected to the strong, persistent convergence beneath a supercell updraft.

Sugarcane croplands account for ~70% of global sugar production and ~60% of global ethanol production. Monitoring and predicting gross primary production (GPP) and transpiration (T) in these fields is crucial to improve crop yield estimation and management. While moderate-spatial-resolution (MSR, hundreds of meters) satellite images have been employed in several models to estimate GPP and T, the potential of high-spatial-resolution (HSR, tens of meters) imagery has been considered in only a few publications, and it is underexplored in sugarcane fields. Our study evaluated the efficacy of MSR and HSR satellite images in predicting daily GPP and T for sugarcane plantations at two sites equipped with eddy flux towers: Louisiana, USA (subtropical climate) and Sao Paulo, Brazil (tropical climate). We employed the Vegetation Photosynthesis Model (VPM) and Vegetation Transpiration Model (VTM) with C4 photosynthesis pathway, integrating vegetation index data derived from satellite images and on-ground weather data, to calculate daily GPP and T. The seasonal dynamics of vegetation indices from both MSR images (MODIS sensor, 500 m) and HSR images (Landsat, 30 m; Sentinel-2, 10 m) tracked well with the GPP seasonality from the EC flux towers. The enhanced vegetation index (EVI) from the HSR images had a stronger correlation with the tower-based GPP. Our findings underscored the potential of HSR imagery for estimating GPP and T in smaller sugarcane plantations.

Nanoscale industrial robots have potential as manufacturing platforms and are capable of automatically performing repetitive tasks to handle and produce nanomaterials with consistent precision and accuracy. We demonstrate a DNA industrial nanorobot that fabricates a three-dimensional (3D), optically active chiral structure from optically inactive parts. By making use of externally controlled temperature and ultraviolet (UV) light, our programmable robot, ~100 nanometers in size, grabs different parts, positions and aligns them so that they can be welded, releases the construct, and returns to its original configuration ready for its next operation. Our robot can also self-replicate its 3D structure and functions, surpassing single-step templating (restricted to two dimensions) by using folding to access the third dimension and more degrees of freedom. Our introduction of multiple-axis precise folding and positioning as a tool/technology for nanomanufacturing will open the door to more complex and useful nano- and microdevices.