Materials science inherently spans disciplines: experimentalists use advanced microscopy to uncover micro- and nanoscale structure, while theorists and computational scientists develop models that link processing, structure, and properties. Bridging these domains is essential for inverse material design where you start from desired performance and work backwards to optimal microstructures and manufacturing routes. Integrating high-resolution imaging with predictive simulations and data-driven optimization accelerates discovery and deepens understanding of process-structure-property relationships. The differentiable physics framework evoxels is based on a fully Pythonic, unified voxel-based approach that integrates segmented 3D microscopy data, physical simulations, inverse modeling, and machine learning.

One of the main computational bottlenecks when working with kernel based learning is dealing with the large and typically dense kernel matrix. Techniques dealing with fast approximations of the matrix vector product for these kernel matrices typically deteriorate in their performance if the feature vectors reside in higher-dimensional feature spaces. We here present a technique based on the non-equispaced fast Fourier transform (NFFT) with rigorous error analysis. We show that this approach is also well suited to allow the approximation of the matrix that arises when the kernel is differentiated with respect to the kernel hyperparameters; a problem often found in the training phase of methods such as Gaussian processes. We also provide an error analysis for this case. We illustrate the performance of the additive kernel scheme with fast matrix vector products on a number of data sets.

As more enterprise firms and their customers start to question the use of data in analytics, research and artificial intelligence tools, the Institute for Operations Research and the Management Sciences (INFORMS) is offering an 18-point set of guidelines to ensure ethics in quantitative decision-making. Based in Catonsville, Md., INFORMS was established in 1995 following a merger between the Operations Research Society of America and The Institute of Management Sciences. Its ethics guidelines, which are available as a foldable printout, are grouped into three broad categories where operations research and analytics are likely to have the greatest impact. These include society, business organizations themselves and those working directly in professional roles involving quantitative decision-making. "We aspire to be . . . Questioning of whether there are more effective and efficient ways to reach a goal," one of the guidelines says, for example, as well as "realistic in our claims of achievable results, and in acknowledging when the best course of action may be to terminate a project."