Density-functional theory and the v-representability problem for model strongly correlated electron systems

Inspired by earlier work on the band-gap problem in insulators, we reexamine the treatment of strongly correlated Hubbard-type models within density-functional theory. In contrast to previous studies, the density is fully parametrized by occupation numbers and overlap of orbitals centered at neighboring atomic sites, as is the local potential by the hopping matrix. This corresponds to a good formal agreement between density-functional theory in real space and second quantization. It is shown that density-functional theory is formally applicable to such systems and the theoretical framework is provided. The question of noninteracting v representability is studied numerically for finite one-dimensional clusters, for which exact results are available, and qualitatively for infinite systems. This leads to the conclusion that the electron density corresponding to interacting systems of the type studied here is in fact not noninteracting v representable because the Kohn-Sham electrons are unable to reproduce the correlation-induced localization correctly.Comment: 9 pages including 1 figur

Some considerations in the selection of aircraft for earth resource observations

Comparison of logistics problems and cost aspects in selection of aircraft for earth resources survey

Algorithms: What, How, and Particularly Why?

In May 2019 the LSE launched its future strategy LSE 2030, with the following opening statement: “Our strategy lays out the guiding principles and commitments that will help us shape the world’s future…” That is what a good teacher tells their students: that they not only are the future, but that they have the capacity and responsibility to shape the future. In the context of Big Data Ethics this is aptly phrased by Richards & King: “We are building a new digital society, and the values we build or fail to build into our new digital structures will define us.” Algorithms are an integral part of our digital society. The ever growing availability of data in combination with incredible computing power led to today’s success of algorithms. There is, however, also reason for cautiousness and concern. To mention just a few threats:• Decisions based on algorithms and profiles without the one who decides being able to provide an adequate explanation. For instance, people do not get a loan because the algorithm decided so based on the data related to the applicant. Or, parents are visited by social workers because the algorithm determined there is a risk of school drop out of their kids;• The use of biometric data which indelibly connects the individual to their data profiles such as the use of facial recognition software to connect physical appearance to online information;• Mass surveillance by both government and business.Given what algorithms can and might do, we as a society in general, and lawyers in particular, have a responsibility to decide how we want to shape the world we live in. What algorithms we do allow and what not, and in case we allow algorithms, under what conditions

Biomarker signatures in pathophysiology and therapeutic interventions in inflammatory bowel diseases:a multimodal approach

Inflammatory bowel disease (IBD) is a term mainly used to describe two diseases: Crohn’s disease (CD) and ulcerative colitis (UC). These are complex diseases of the gastrointestinal tract, characterised by a relapse-remitting disease course. Hence, IBD is difficult to predict and to adequately treat. Since IBD is a complex, heterogeneous and unpredictable disease, there is an urgent need for biomarkers, which are objectively measured parameters of (ab)normal biological processes or -systems, which may help to (early) diagnose and classify IBD, to assess disease activity and disease complications, and to accurately predict how a patients’ disease course will develop and/or how a patient will respond to a particular treatment. The findings presented in this thesis represent a number of newly identified biomarkers for multiple disease outcomes in patients with IBD. These outcomes included, but were not limited to, diagnosis and classification (Part I), disease activity and complications (Part II and III), and modulation by and prediction of treatment effects (Part IV). This thesis adopted a multimodal approach by exploring biomarkers from different biological perspectives and by performing laboratory-, clinical- and computational research (and combinations thereof). We demonstrated that immune system components (Part I), inflammation, permeability and fibrosis (Part II), and oxidative stress (Part III) provide excellent resources for biomarker discovery and application. The work presented in this thesis sheds light on the establishment of a “systems biology” approach, studying the interplay between multiple disease processes to establish personalised medicine for patients with IBD, thereby improving outcomes of patients with IBD