Research Data Management (RDM) receives more and more attention as a core component of scientific work. This importance equally stems from the scientific work with everincreasing amounts of data, the value of this data for subsequent use, and the formal requirements of funding agencies. While these requirements are widely accepted among the researchers, the individual acceptance depends on many...

The ability to predict the spatial distribution of tree root system variables (e.g., Root Area (RA), maximum diameter, number roots in diameter classes, density fine roots, etc.) under different environmental conditions is relevant several scientific disciplines and engineering practice. In this work, three well known analytical models from literature are assembled into a unique framework calle...

We propose a tomographic protocol for estimating any $k$-body reduced density matrix ($k$-RDM) of an $n$-mode fermionic state, ubiquitous step in near-term quantum algorithms simulating many-body physics, chemistry, and materials. Our approach extends the framework classical shadows, randomized to learning collection quantum-state properties, setting. sampling uses measurement settings generate...

Correlation-driven phenomena in molecular periodic systems are challenging to predict computationally not only because such periodically infinite but also they typically strongly correlated. Here we generalize the variational two-electron reduced density matrix (2-RDM) theory compute energies and properties of correlated systems. The 2-RDM unit cell is directly computed subject necessary $N$-re...

Data mining (DM) has emerged as one of the key features of many applications on information system. While Data Analysis (DA) represents a significant advance in the type of analytical tools currently available, there are limitations to its capability. In order to address one of the limitations on the DA capabilities of identifying a causal relationship, we propose an integrated approach, called...

Recently, an approximate theoretical framework was introduced, called local reduced density matrix functional theory (local-RDMFT), where functionals of the one-body reduced density matrix (1-RDM) are minimized under the additional condition that the optimal orbitals satisfy a single electron Schrödinger equation with a local potential. In the present work, we focus on the character of these op...

How do we study long-term policy challenges where the outcomes are difacult to anticipate far into the future? After a brief overview of the broad classes of methods used to inform long-term policy decisions, this article will review in more depth three analytic methods—statistical methods, robust decisionmaking, and adaptive agent-based models—that provide innovative examples. The article cons...

The Bandwidth Allocation Models (MAM, RDM, G-RDM and AllocTC-Sharing) are management alternatives currently available which propose different resource (bandwidth) allocation strategies in multiservice networks. The BAM adoption by a network is typically a management choice and configuration task executed by the network operations and management system setup in a static or nearly static way. Thi...

This study evaluated rituximab-conjugated, doxorubicin-loaded microbubbles (RDMs) in combination with ultrasound as molecular imaging agents for early diagnosis of B cell lymphomas, and as a targeted drug delivery system. Rituximab, a monoclonal CD20 antibody, was attached to the surfaces of doxorubicin-loaded microbubbles. RDM binding to B cell lymphoma cells was assessed using immunofluoresce...