Thermal effects on cephalopod energy metabolism - A case study for Sepia officinalis

Cephalopods are the largest, most active invertebrates and there is considerable evidence for their convergent evolution with fishes. However, most active cephalopods display standard and active metabolic rates that are several-fold higher than comparably sized fishes. Shifting habitat temperatures due to climate change will therefore affect a cephalopods energy metabolism much more than that of a fish. Prediction of the probable outcome of cephalopod-fish competition thus requires quantitative information concerning whole animal energetics and corresponding efficiencies. Migrating cephalopods such as squid and cuttlefish grow rapidly to maturity, carry few food reserves and have little overlap of generations. This "live fast, die young" life history strategy means that they require niches capable of sustaining high power requirements and rapid growth. This presentation aims to draw a bottom-up picture of the cellular basis of energy metabolism of the cuttlefish Sepia officinalis, from its molecular basis to whole animal energetics based on laboratory experiments and field data. We assessed the proportionality of standard vs active metabolic rate and the daily energetic requirements using field tracking data in combination with lab based respirometry and video analysis. Effects of environmental temperature on mitochondrial energy coupling were investigated in whole animals using in vivo 31P-NMR spectroscopy. As efficient energy turnover needs sufficient oxygen supply, also thermal effects on the blood oxygen-binding capacities of the respiratory pigment haemocyanin and the differential expression of its isoforms were investigated.Supported by NERC grant NERC/A/S/2002/00812

Preentry communication design elements for outer planets atmospheric entry probe

Four related tasks are discussed for data transmission from a probe prior to entering the atmosphere of Jupiter to an orbiting spacecraft in a trajectory past the planet: (1) link analysis and design; (2) system conceptual design; (3) Doppler measurement analysis; and (4) an electronically despun antenna. For tasks 1, 3, and 4, an analytical approach was developed and combined with computational capability available to produce quantitative results corresponding to requirements and constraints given by NASA, ARC. One constraint having a major impact on the numerical results of the link analysis was the assumption of a nonsteerable antenna on a spinning orbiter. Other constraints included the interplanetary trajectory and the approach trajectory. Because the Jupiter Orbiter Probe (JOP) program is currently in a state of evolution, all requirements and constraints applied during this study are subject to change. However, the relationships of parameters as developed will remain valid and will aid in planning Jupiter missions

Is Bigger Always Better? Lessons Learnt from the Evolution of Deep Learning Architectures for Image Classification

There exist numerous scientific contributions to the design of deep learning networks. However, using the right architecture that is suited for a given business problem with all constraints such as memory and inference time requirements can be cumbersome. We reflect on the evolution of the state-of-the-art architectures for convolutional neural networks(CNN) for the case of image classification. We compare architectures regarding classification results, model size, and inference time to discuss the choices of designs for CNN architectures. To maintain scientific comprehensibility, the established ILSVRC benchmark is used as a basis for model selection and benchmark data. The quantitative comparison shows that while the model size and the required inference time correlate with result accuracy across all architectures, there are major trade-offs between those factors. The qualitative analysis further depicts that published models always build on previous research and adopt improved components in either evolutionary or revolutionary ways. Finally, we discuss design and result improvement during the evolution of CNN architectures. Further, we derive practical implications for designing deep learning network

CASSIOPE: An expert system for conserved regions searches

<p>Abstract</p> <p>Background</p> <p>Understanding genome evolution provides insight into biological mechanisms. For many years comparative genomics and analysis of conserved chromosomal regions have helped to unravel the mechanisms involved in genome evolution and their implications for the study of biological systems. Detection of conserved regions (descending from a common ancestor) not only helps clarify genome evolution but also makes it possible to identify quantitative trait loci (QTLs) and investigate gene function.</p> <p>The identification and comparison of conserved regions on a genome scale is computationally intensive, making process automation essential. Three key requirements are necessary: consideration of phylogeny to identify orthologs between multiple species, frequent updating of the annotation and panel of compared genomes and computation of statistical tests to assess the significance of identified conserved gene clusters.</p> <p>Results</p> <p>We developed a modular system superimposed on a multi-agent framework, called CASSIOPE (Clever Agent System for Synteny Inheritance and Other Phenomena in Evolution). CASSIOPE automatically identifies statistically significant conserved regions between multiple genomes based on automated phylogenies and statistical testing. Conserved regions were searched for in 19 species and 1,561 hits were found. To our knowledge, CASSIOPE is the first system to date that integrates evolutionary biology-based concepts and fulfills all three key requirements stated above. All results are available at <url>http://194.57.197.245/cassiopeWeb/displayCluster?clusterId=1</url></p> <p>Conclusion</p> <p>CASSIOPE makes it possible to study conserved regions from a chosen query genetic region and to infer conserved gene clusters based on phylogenies and statistical tests assessing the significance of these conserved regions.</p> <p><b>Source code </b>is freely available, please contact: <email>[email protected]</email></p

Agent-based simulation of open source evolution

We present an agent-based simulation model developed to study how size, complexity and effort relate to each other in the development of open source software (OSS). In the model, many developer agents generate, extend, and re-factor code modules independently and in parallel. This accords with empirical observations of OSS development. To our knowledge, this is the first model of OSS evolution that includes the complexity of software modules as a limiting factor in productivity, the fitness of the software to its requirements, and the motivation of developers. Validation of the model was done by comparing the simulated results against four measures of software evolution (system size, proportion of highly complex modules, level of complexity control work, and distribution of changes) for four large OSS systems. The simulated results resembled the observed data, except for system size: three of the OSS systems showed alternating patterns of super-linear and sub-linear growth, while the simulations produced only super-linear growth. However, the fidelity of the model for the other measures suggests that developer motivation and the limiting effect of complexity on productivity have a significant effect on the development of OSS systems and should be considered in any model of OSS development

The impact of using pair programming on system evolution a simulation-based study

In this paper we investigate the impact of pair--programming on the long term evolution of software systems. We use system dynamics to build simulation models which predict the trend in system growth with and without pair programming. Initial results suggest that the extra effort needed for two people to code together may generate sufficient benefit to justify pair programming.Peer reviewe

Analysing how constraints impact architectural decision-making

Architectural design projects are characterised by a high number of constraints. Along with planning, energy performance and fire safety regulations, current designers have to face constraining factors related to budget, acoustics, orientation, wind turbulence, accessibility for the disabled, and so forth. These constraints steer the design process implicitly and explicitly in certain directions as soon as architectural designers aim at satisfying design briefs. We aim in this article at analysing the impact of such constraints on the design process. At this end, we have studied four design sessions in a particular (student) design use case. In analysing these four sessions, we used linkography as a method, because this appeared to be one of the better options to obtain a more quantitative assessment of the design process. The linkography method was combined with an interview of the student design team, in order to check the correctness of our conclusions

Software Sustainability: The Modern Tower of Babel

<p>The aim of this paper is to explore the emerging definitions of software sustainability from the field of software engineering in order to contribute to the question, what is software sustainability?</p