The Functional Perspective on Advanced Logic Programming

The basics of logic programming, as embodied by Prolog, are generally well-known in the programming language community. However, more advanced techniques, such as tabling, answer subsumption and probabilistic logic programming fail to attract the attention of a larger audience. The cause for the community\u27s seemingly limited interest lies with the presentation of these features: the literature frequently focuses on implementations and examples that do little to aid the understanding of non-experts in the field. The key point is that many of these advanced logic programming features can be characterised in more generally known, more accessible terms. In my research I try to reconcile these advanced concepts from logic programming (Tabling, Answer subsumption and probabilistic programming) with concepts from functional programming (effects, monads and applicative functors)

Tabling with Sound Answer Subsumption

Tabling is a powerful resolution mechanism for logic programs that captures their least fixed point semantics more faithfully than plain Prolog. In many tabling applications, we are not interested in the set of all answers to a goal, but only require an aggregation of those answers. Several works have studied efficient techniques, such as lattice-based answer subsumption and mode-directed tabling, to do so for various forms of aggregation. While much attention has been paid to expressivity and efficient implementation of the different approaches, soundness has not been considered. This paper shows that the different implementations indeed fail to produce least fixed points for some programs. As a remedy, we provide a formal framework that generalises the existing approaches and we establish a soundness criterion that explains for which programs the approach is sound. This article is under consideration for acceptance in TPLP.Comment: Paper presented at the 32nd International Conference on Logic Programming (ICLP 2016), New York City, USA, 16-21 October 2016, 15 pages, LaTeX, 0 PDF figure

Disjunctive Delimited Control

Delimited control is a powerful mechanism for programming language extension which has been recently proposed for Prolog (and implemented in SWI-Prolog). By manipulating the control flow of a program from inside the language, it enables the implementation of powerful features, such as tabling, without modifying the internals of the Prolog engine. However, its current formulation is inadequate: it does not capture Prolog's unique non-deterministic nature which allows multiple ways to satisfy a goal. This paper fully embraces Prolog's non-determinism with a novel interface for disjunctive delimited control, which gives the programmer not only control over the sequential (conjunctive) control flow, but also over the non-deterministic control flow. We provide a meta-interpreter that conservatively extends Prolog with delimited control and show that it enables a range of typical Prolog features and extensions, now at the library level: findall, cut, branch-and-bound optimisation, probabilistic programming, . . .Comment: New version of paper is available at: arXiv:2108.0297

Fitness cost associated with cell phenotypic switching drives population diversification dynamics and controllability

Isogenic cell populations can cope with stress conditions by switching to alternative phenotypes. Even if it can lead to increased fitness in a natural context, this feature is typically unwanted for a range of applications (e.g., bioproduction, synthetic biology, and biomedicine) where it tends to make cellular response unpredictable. However, little is known about the diversification profiles that can be adopted by a cell population. Here, we characterize the diversification dynamics for various systems (bacteria and yeast) and for different phenotypes (utilization of alternative carbon sources, general stress response and more complex development patterns). Our results suggest that the diversification dynamics and the fitness cost associated with cell switching are coupled. To quantify the contribution of the switching cost on population dynamics, we design a stochastic model that let us reproduce the dynamics observed experimentally and identify three diversification regimes, i.e., constrained (at low switching cost), dispersed (at medium and high switching cost), and bursty (for very high switching cost). Furthermore, we use a cell-machine interface called Segregostat to demonstrate that different levels of control can be applied to these diversification regimes, enabling applications involving more precise cellular responses

Development of a GEM-TPC prototype

The use of GEM foils for the amplification stage of a TPC instead of a con- ventional MWPC allows one to bypass the necessity of gating, as the backdrift is suppressed thanks to the asymmetric field configuration. This way, a novel continuously running TPC, which represents one option for the PANDA central tracker, can be realized. A medium sized prototype with a diameter of 300 mm and a length of 600 mm will be tested inside the FOPI spectrometer at GSI using a carbon or lithium beam at intermediate energies (E = 1-3AGeV). This detector test under realistic experimental conditions should allow us to verify the spatial resolution for single tracks and the reconstruction capability for displaced vertexes. A series of physics measurement implying pion beams is scheduled with the FOPI spectrometer together with the GEM-TPC as well.Comment: 5 pages, 4 figures, Proceedings for 11th ICATTP conference in como (italy

Prevention of infections with highly resistant microorganisms:Maximizing transparency by using outcome indicators

In the Netherlands the quality of health care is supervised by the Health Care Inspectorate. Since 2013 the Health Care Inspectorate has been specifically checking hospital practices for reducing transmission of highly resistant microorganisms. Its mode of operation, using process indicators, has been criticised. Here, it is proposed that this quality control be based on relevant outcome parameters of infection prevention strategies. This would also maximise transparency regarding the occurrence of infections caused by highly resistant microorganisms in Dutch hospitals.</p

Prevention of infections with highly resistant microorganisms:Maximizing transparency by using outcome indicators

In the Netherlands the quality of health care is supervised by the Health Care Inspectorate. Since 2013 the Health Care Inspectorate has been specifically checking hospital practices for reducing transmission of highly resistant microorganisms. Its mode of operation, using process indicators, has been criticised. Here, it is proposed that this quality control be based on relevant outcome parameters of infection prevention strategies. This would also maximise transparency regarding the occurrence of infections caused by highly resistant microorganisms in Dutch hospitals.</p

Prevention of infections with highly resistant microorganisms:Maximizing transparency by using outcome indicators

In the Netherlands the quality of health care is supervised by the Health Care Inspectorate. Since 2013 the Health Care Inspectorate has been specifically checking hospital practices for reducing transmission of highly resistant microorganisms. Its mode of operation, using process indicators, has been criticised. Here, it is proposed that this quality control be based on relevant outcome parameters of infection prevention strategies. This would also maximise transparency regarding the occurrence of infections caused by highly resistant microorganisms in Dutch hospitals.</p