Computational cancer biology: education is a natural key to many locks

Background: Oncology is a field that profits tremendously from the genomic data generated by high-throughput technologies, including next-generation sequencing. However, in order to exploit, integrate, visualize and interpret such high-dimensional data efficiently, non-trivial computational and statistical analysis methods are required that need to be developed in a problem-directed manner.

Discussion: For this reason, computational cancer biology aims to fill this gap. Unfortunately, computational cancer biology is not yet fully recognized as a coequal field in oncology, leading to a delay in its maturation and, as an immediate consequence, an under-exploration of high-throughput data for translational research.

Summary: Here we argue that this imbalance, favoring 'wet lab-based activities', will be naturally rectified over time, if the next generation of scientists receives an academic education that provides a fair and competent introduction to computational biology and its manifold capabilities. Furthermore, we discuss a number of local educational provisions that can be implemented on university level to help in facilitating the process of harmonization.

Dynamic Modeling and Interaction of Hybrid Natural Gas and Electricity Supply System in Microgrid

Natural gas (NG) network and electric network are becoming tightly integrated by microturbines in the microgrid. Interactions between these two networks are not well captured by the traditional microturbine (MT) models. To address this issue, two improved models for single-shaft MT and split-shaft MT are proposed in this paper. In addition, dynamic models of the hybrid natural gas and electricity system (HGES) are developed for the analysis of their interactions. Dynamic behaviors of natural gas in pipes are described by partial differential equations (PDEs), while the electric network is described by differential algebraic equations (DAEs). So the overall network is a typical two-time scale dynamic system. Numerical studies indicate that the two-time scale algorithm is faster and can capture the interactions between the two networks. The results also show the HGES with a single-shaft MT is a weakly coupled system in which disturbances in the two networks mainly influence the dc link voltage of the MT, while the split-shaft MT is a strongly coupled system where the impact of an event will affect both networks.

Injurious tail biting in pigs: How can it be controlled in existing systems without tail docking?

Tail biting is a serious animal welfare and economic problem in pig production. Tail docking, which reduces but does not eliminate tail biting, remains widespread. However, in the EU tail docking may not be used routinely, and some 'alternative' forms of pig production and certain countries do not allow tail docking at all. Against this background, using a novel approach focusing on research where tail injuries were quantified, we review the measures that can be used to control tail biting in pigs without tail docking. Using this strict criterion, there was good evidence that manipulable substrates and feeder space affect damaging tail biting. Only epidemiological evidence was available for effects of temperature and season, and the effect of stocking density was unclear. Studies suggest that group size has little effect, and the effects of nutrition, disease and breed require further investigation. The review identifies a number of knowledge gaps and promising avenues for future research into prevention and mitigation. We illustrate the diversity of hypotheses concerning how different proposed risk factors might increase tail biting through their effect on each other or on the proposed underlying processes of tail biting. A quantitative comparison of the efficacy of different methods of provision of manipulable materials, and a review of current practices in countries and assurance schemes where tail docking is banned, both suggest that daily provision of small quantities of destructible, manipulable natural materials can be of considerable benefit. Further comparative research is needed into materials, such as ropes, which are compatible with slatted floors. Also, materials which double as fuel for anaerobic digesters could be utilised. As well as optimising housing and management to reduce risk, it is important to detect and treat tail biting as soon as it occurs. Early warning signs before the first bloody tails appear, such as pigs holding their tails tucked under, could in future be automatically detected using precision livestock farming methods enabling earlier reaction and prevention of tail damage. However, there is a lack of scientific studies on how best to respond to outbreaks: the effectiveness of, for example, removing biters and/or bitten pigs, increasing enrichment, or applying substances to tails should be investigated. Finally, some breeding companies are exploring options for reducing the genetic propensity to tail bite. If these various approaches to reduce tail biting are implemented we propose that the need for tail docking will be reduced. © 2014 The Animal Consortium.

Optimal day-ahead scheduling of integrated urban energy systems

An optimal day-ahead scheduling method (ODSM) for the integrated urban energy system (IUES) is introduced, which considers the reconfigurable capability of an electric distribution network. The hourly topology of a distribution network, a natural gas network, the energy centers including the combined heat and power (CHP) units, different energy conversion devices and demand responsive loads (DRLs), are optimized to minimize the day-ahead operation cost of the IUES. The hourly reconfigurable capability of the electric distribution network utilizing remotely controlled switches (RCSs) is explored and discussed. The operational constraints from the unbalanced three-phase electric distribution network, the natural gas network, and the energy centers are considered. The interactions between the electric distribution network and the natural gas network take place through conversion of energy among different energy vectors in the energy centers. An energy conversion analysis model for the energy center was developed based on the energy hub model. A hybrid optimization method based on genetic algorithm (GA) and a nonlinear interior point method (IPM) is utilized to solve the ODSM model. Numerical studies demonstrate that the proposed ODSM is able to provide the IUES with an effective and economical day-ahead scheduling scheme and reduce the operational cost of the IUES.