Related papers: Data mining the EXFOR database using network theor…
Networks represent relationships between entities in many complex systems, spanning from online social interactions to biological cell development and brain connectivity. In many cases, relationships between entities are unambiguously…
Particle- and agent-based systems are a ubiquitous modeling tool in many disciplines. We consider the fundamental problem of inferring interaction kernels from observations of agent-based dynamical systems given observations of…
Quantifying inherent neutron sources in matter, particularly $(\alpha, n)$ reactions and spontaneous fission, is important in nuclear engineering and other fields. The SOURCES code is a common tool for calculating the yield and spectrum of…
Background: Single-crystal chemical vapor deposited (sCVD) diamond detectors offer a unique method to study cross sections of reactions on carbon since they can be used as active targets. Previous studies analyzing neutrons on carbon using…
Many complex networks display a mesoscopic structure with groups of nodes sharing many links with the other nodes in their group and comparatively few with nodes of different groups. This feature is known as community structure and encodes…
Social media and social networks have already woven themselves into the very fabric of everyday life. This results in a dramatic increase of social data capturing various relations between the users and their associated artifacts, both in…
RNA-KG is a recently developed knowledge graph that integrates the interactions involving coding and non-coding RNA molecules extracted from public data sources. It can be used to support the classification of new molecules, identify new…
We describe evaluation methods that make use of experimental data, and nuclear model calculations, to develop an ENDF-formatted data library for the reaction p + Li7 for incident protons with energies up to 150 MeV. The important…
Classification, which involves finding rules that partition a given data set into disjoint groups, is one class of data mining problems. Approaches proposed so far for mining classification rules for large databases are mainly decision tree…
Graphs are essential for modeling complex relationships and capturing structured interactions in data. Graph Neural Networks (GNNs) are particularly effective when such relational structure is explicitly available, but many real-world…
We describe a new web based data resource being developed to provide access to accurate and validated cross sections of low energy neutrino and antineutrino interactions. The proposed content of this database are outlined which cover total…
I review the main features of the nuclear response extracted from electron scattering data. The emerging picture clearly shows that the shell model does not provide a fully quantitative description of nuclear dynamics. On the other hand,…
The nuclear reactions in a plasma system with energy distribution deviated from Maxwellian are proved to have some unique characteristics including those in their product energy spectrum. Based on this, a new nuclear diagnostic scheme for…
The low energy part of the reactor neutrino spectra has not been experimentally measured. Its uncertainties limit the sensitivities in certain reactor neutrino experiments. The origin of these uncertainties are discussed, and the effects on…
The importance of databases of reliable and accurate data in chemistry has substantially increased in the past two decades. Their main usage is to parametrize electronic structure theory methods, and to assess their capabilities and…
We show how neutrino data can be used in order to constrain the free parameters of possible extensions to the standard model of elementary particles (SM). For definiteness, we focus in the recently proposed unparticle scenario. We show that…
Exchangeable models for countable vertex-labeled graphs cannot replicate the large sample behaviors of sparsity and power law degree distribution observed in many network datasets. Out of this mathematical impossibility emerges the question…
A detailed algorithmic explanation is required for how a network of chemical reactions can generate the sophisticated behavior displayed by living cells. Though several previous works have shown that reaction networks are computationally…
Reactions between atomic nuclei are measured in great detail in terrestrial laboratory experiments; transferring and extrapolating this knowledge to how the same reactions act within cosmic environments presents major challenges.…
We introduce and study a class of exchangeable random graph ensembles. They can be used as statistical null models for empirical networks, and as a tool for theoretical investigations. We provide general theorems that carachterize the…