GC Insights: Identifying conditions that sculpted bedforms – human insights to building an effective AI (artificial intelligence)

Insights from a geoscience communication activity, verified using preliminary investigations with an artificial neural network, illustrate that observation of humans' abilities can help design an effective artificial intelligence or “AI”. Even given only one set of “training” examples, survey participants could visually recognize which flow conditions created bedforms (e.g. sand dunes and riverbed ripples) from their shapes, but an interpreter's geoscience expertise does not help. Together, these observations were interpreted as indicating that a machine learning algorithm might be trained successfully from limited data, particularly if it is “helped” by pre-processing bedforms into a simple shape familiar from childhood play.

COMPARISON OF TWO DATA ASSIMILATION METHODS USED TO ACCOUNT FOR OPEN BOUNDARIES IN SEA AREA HYDROTHERMODYNAMICS MODELING

The problems of modeling hydrothermodynamics of particular sea and coastal areas are of current interest, since the results of this modeling are often used in many applications. One of the methods allowing to take into account open boundaries and bring the simulation results closer to real data is the variational assimilation of observational data. In this paper the following approach is considered: it is supposed that there are observational data at a certain moment in time; the problem is considered as an inverse problem, in which the functions of fluxes across the open boundary are treated as additional unknowns. Comparison of methods for reconstructing unknown functions in boundary conditions at an open boundary using sea level and velocity observational data in a number of numerical experiments for a region of a simple shape is carried out.

A Sufficient Condition for Convex Hull Property in General Convex Spatio-Temporal Corridors

Motion planning is one of the key modules in autonomous driving systems to generate trajectories for self-driving vehicles to follow. A common motion planning approach is to generate trajectories within semantic safe corridors. The trajectories are generated by optimizing parametric curves (e.g. Bezier curves) according to an objective function. To guarantee safety, the curves are required to satisfy the convex hull property, and be contained within the safety corridors. The convex hull property however does not necessary hold for time-dependent corridors, and depends on the shape of corridors. The existing approaches only support simple shape corridors, which is restrictive in real-world, complex scenarios. In this paper, we provide a sufficient condition for general convex, spatio-temporal corridors with theoretical proof of guaranteed convex hull property. The theorem allows for using more complicated shapes to generate spatio-temporal corridors and minimizing the uncovered search space to $O(\frac{1}{n^2})$ compared to $O(1)$ of trapezoidal corridors, which can improve the optimality of the solution. Simulation results show that using general convex corridors yields less harsh brakes, hence improving the overall smoothness of the resulting trajectories.

Image classification and cognition using contour curvature statistics

Although the higher order mechanisms behind object representation and classification in the visual system are still not well understood, there are hints that simple shape primitives such as “curviness” might activate neural activation and guide this process. Drawing on elementary invariance principles, we propose that a statistical geometric object, the probability distribution of the normalized contour curvatures (NCC) in the intensity field of a planar image, has the potential to represent and classify categories of objects. We show that NCC is sufficient for discriminating between cognitive categories such as animacy, size and type, and demonstrate the robustness of this metric to variation in illumination and viewpoint, consistent with neurobiological constraints and psychological experiments. A generative model for producing artificial images with the observed NCC distributions highlights the key features that our metric captures and just as importantly, those that it does not. More broadly, our study points to the need for statistical geometric approaches to cognition that build in both the statistics and the natural invariances of the sensory world.

Structural Performance of R-Type Steel Damper Used in Reinforced Concrete Members

This study proposes a steel damper with a simple shape and excellent energy dissipation capacity. The proposed damper has a rectangular shape (R-type) and has an energy dissipation part and a load transmission part. The energy dissipation part dissipates external energy through the yielding of the steel material; it comprises a vertical member and upper and lower horizontal members. This study performed two-phase experiments to verify the structural performance of the proposed damper. The Phase I test was performed to evaluate the load history characteristics and energy dissipation capacity of the damper and the Phase II test was performed to confirm the structural performance of reinforced concrete members with the proposed damper. The experimental results showed that the proposed R-type steel damper had high-energy dissipation performance despite having a simple shape.

Toward a Mechanistic Understanding of Bacterial Rod Shape Formation and Regulation

One of the most common bacterial shapes is a rod, yet we have a limited understanding of how this simple shape is constructed. While only six proteins are required for rod shape, we are just beginning to understand how they self-organize to build the micron-sized enveloping structures that define bacterial shape out of nanometer-sized glycan strains. Here, we detail and summarize the insights gained over the last 20 years into this complex problem that have been achieved with a wide variety of different approaches. We also explain and compare both current and past models of rod shape formation and maintenance and then highlight recent insights into how the Rod complex might be regulated. Expected final online publication date for the Annual Review of Cell and Developmental Biology, Volume 37 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The selection of the main axis and the forming plane in automatic profiling and stamping lines

The article defines the main axis and the profiling plane in automatic profiling and stamping lines. Specific recommendations are given for choosing the position of the main axis and the profiling plane, depending on the configuration of the manufactured parts of the roll-formed section. Under the general name of profiling in the practice of stamping works, it is meant to obtain rigid and light profiles of large length and various configurations from sheet blanks. Profiling is carried out in four ways: in dies on crank presses, in dies on special bending presses, on universal bending machines (edging machines), on profiling roller machines. The first method, profiling on crank presses, is used for complex semi-closed and open profiles of relatively small length, if there are no special bending presses or profiling machines. The second method, profiling on special bending presses, is used for open and semiclosed profiles up to 5 mm long. The advantage of such presses is the possibility of using simple, and therefore cheap, tools in the manufacture. The third method, profiling on universal bending machines (edging machines), is used for bending parts (profiles of a simple shape in straight lines with different coupling radii determined by the radius of the machine ruler, for which the latter has a set of rulers). Bending machines allow bending materials of small thickness. Low productivity and the need for physical labor costs limit the use of these machines. The fourth method, profiling on roller machines, is used for open, semi-closed and closed profiles. The essence of the profiling process is to gradually change the profile drawing of a flat belt to a given profile when it is moved sequentially through several pairs of shaped rollers arranged sequentially one after the other in the same plane and rotating at the same speed. The article describes in detail the fourth method; the advantages and disadvantages are noted.

Microstructural Prediction of Heat Treated Steel Forgings for Severe Applications

An in-house 2D finite volume model, specific for components of simple shape, was developed and applied to predict the thermal and microstructural evolution during heat treatment of steel forgings. The results of the thermal metallurgical modelling, including hardness profiles through the thickness, were compared with the experimental ones. Moreover, the 3D FEM software Deform-HT, able to calculate the thermal and microstructural evolution and the stress field during quenching, was specialized for the cases of interest. Examples of optimal heat treatment to develop the target microstructure and strength and reduce the risk of quenching cracks are discussed.