Natural Selection at Work: An Accelerated Evolutionary Computing Approach to Predictive Model Selection

We implement genetic algorithm based predictive model building as an alternative to the traditional stepwise regression. We then employ the Information Complexity Measure (ICOMP) as a measure of model fitness instead of the commonly used measure of R-square. Furthermore, we propose some modifications to the genetic algorithm to increase the overall efficiency

Quantitative analysis of regulatory flexibility under changing environmental conditions

The circadian clock controls 24-h rhythms in many biological processes, allowing appropriate timing of biological rhythms relative to dawn and dusk. Known clock circuits include multiple, interlocked feedback loops. Theory suggested that multiple loops contribute the flexibility for molecular rhythms to track multiple phases of the external cycle. Clear dawn- and dusk-tracking rhythms illustrate the flexibility of timing in Ipomoea nil. Molecular clock components in Arabidopsis thaliana showed complex, photoperiod-dependent regulation, which was analysed by comparison with three contrasting models. A simple, quantitative measure, Dusk Sensitivity, was introduced to compare the behaviour of clock models with varying loop complexity. Evening-expressed clock genes showed photoperiod-dependent dusk sensitivity, as predicted by the three-loop model, whereas the one- and two-loop models tracked dawn and dusk, respectively. Output genes for starch degradation achieved dusk-tracking expression through light regulation, rather than a dusk-tracking rhythm. Model analysis predicted which biochemical processes could be manipulated to extend dusk tracking. Our results reveal how an operating principle of biological regulators applies specifically to the plant circadian clock

The power of physical representations

Commonsense reasoning about the physical world, as exemplified by "Iron sinks in water" or "If a ball is dropped it gains speed," will be indispensable in future programs. We argue that to make such predictions (namely, envisioning), programs should use abstract entities (such as the gravitational field), principles (such as the principle of superposition), and laws (such as the conservation of energy) of physics for representation and reasoning. These arguments are in accord with a recent study in physics instruction where expert problem solving is related to the construction of physical representations that contain fictitious, imagined entities such as forces and momenta (Larkin 1983). We give several examples showing the power of physical representations

Geometric computing and uniform grid technique

If computational geometry should play an important role in the professional environment (e.g. graphics and robotics), the data structures it advocates should be readily implemented and the algorithms efficient. In the paper, the uniform grid and a diverse set of geometric algorithms that are all based on it, are reviewed. The technique, invented by the second author, is a flat, and thus non-hierarchical, grid whose resolution adapts to the data. It is especially suitable for telling efficiently which pairs of a large number of short edges intersect. Several of the algorithms presented here exist as working programs (among which is a visible surface program for polyhedra) and can handle large data sets (i.e. many thousands of geometric objects). Furthermore, the uniform grid is appropriate for parallel processing; the parallel implementation presented gives very good speed-up results. © 1989

Ecology & computer audition: applications of audio technology to monitor organisms and environment

Among the 17 Sustainable Development Goals (SDGs) proposed within the 2030 Agenda and adopted by all the United Nations member states, the 13th SDG is a call for action to combat climate change. Moreover, SDGs 14 and 15 claim the protection and conservation of life below water and life on land, respectively. In this work, we provide a literature-founded overview of application areas, in which computer audition – a powerful but in this context so far hardly considered technology, combining audio signal processing and machine intelligence – is employed to monitor our ecosystem with the potential to identify ecologically critical processes or states. We distinguish between applications related to organisms, such as species richness analysis and plant health monitoring, and applications related to the environment, such as melting ice monitoring or wildfire detection. This work positions computer audition in relation to alternative approaches by discussing methodological strengths and limitations, as well as ethical aspects. We conclude with an urgent call to action to the research community for a greater involvement of audio intelligence methodology in future ecosystem monitoring approaches

Primary coronary artery bypass surgery in the presence of decreasing preoperative renal function: effect on short-term outcomes

Background: This study evaluated the impact of decreasing renal function on short-term outcomes in patients undergoing primary coronary artery bypass grafting (CABG). Methods: The study period was from February 1999 to February 2009. Data on 4050 patients undergoing primary CABG were prospectively collected and analyzed retrospectively. The study population was divided into 3 groups: the CABG:N group, patients with preoperative serum creatinine levels 2 mg/dL (n = 87); and the CABG:D group, patients on dialysis (n = 16). Results: The significant differences between the groups (CABG:D > CABG:RF > CABG:N) in short-term outcomes were with respect to blood product use (P < .001), postoperative acute myocardial infarction (P < .001), pulmonary complications (P .001), infection (P < .001), and death (P < .001). The risk of short-term death (30 days) in the CABG:D group (4/16, 25%) was 25 times greater than that in the CABG:N group (38/3947, 0.96%). Conclusion: CABG in the presence of renal failure is associated with significant morbidity and mortality

MPV17 Loss Causes Deoxynucleotide Insufficiency and Slow DNA Replication in Mitochondria

MPV17 is a mitochondrial inner membrane protein whose dysfunction causes mitochondrial DNA abnormalities and disease by an unknown mechanism. Perturbations of deoxynucleoside triphosphate (dNTP) pools are a recognized cause of mitochondrial genomic instability; therefore, we determined DNA copy number and dNTP levels in mitochondria of two models of MPV17 deficiency. In Mpv17 ablated mice, liver mitochondria showed substantial decreases in the levels of dGTP and dTTP and severe mitochondrial DNA depletion, whereas the dNTP pool was not significantly altered in kidney and brain mitochondria that had near normal levels of DNA. The shortage of mitochondrial dNTPs in Mpv17-/- liver slows the DNA replication in the organelle, as evidenced by the elevated level of replication intermediates. Quiescent fibroblasts of MPV17-mutant patients recapitulate key features of the primary affected tissue of the Mpv17-/- mice, displaying virtual absence of the protein, decreased dNTP levels and mitochondrial DNA depletion. Notably, the mitochondrial DNA loss in the patients’ quiescent fibroblasts was prevented and rescued by deoxynucleoside supplementation. Thus, our study establishes dNTP insufficiency in the mitochondria as the cause of mitochondrial DNA depletion in MPV17 deficiency, and identifies deoxynucleoside supplementation as a potential therapeutic strategy for MPV17-related disease. Moreover, changes in the expression of factors involved in mitochondrial deoxynucleotide homeostasis indicate a remodeling of nucleotide metabolism in MPV17 disease models, which suggests mitochondria lacking functional MPV17 have a restricted purine mitochondrial salvage pathway