Turing learning: : A metric-free approach to inferring behavior and its application to swarms

We propose Turing Learning, a novel system identification method for inferring the behavior of natural or artificial systems. Turing Learning simultaneously optimizes two populations of computer programs, one representing models of the behavior of the system under investigation, and the other representing classifiers. By observing the behavior of the system as well as the behaviors produced by the models, two sets of data samples are obtained. The classifiers are rewarded for discriminating between these two sets, that is, for correctly categorizing data samples as either genuine or counterfeit. Conversely, the models are rewarded for 'tricking' the classifiers into categorizing their data samples as genuine. Unlike other methods for system identification, Turing Learning does not require predefined metrics to quantify the difference between the system and its models. We present two case studies with swarms of simulated robots and prove that the underlying behaviors cannot be inferred by a metric-based system identification method. By contrast, Turing Learning infers the behaviors with high accuracy. It also produces a useful by-product - the classifiers - that can be used to detect abnormal behavior in the swarm. Moreover, we show that Turing Learning also successfully infers the behavior of physical robot swarms. The results show that collective behaviors can be directly inferred from motion trajectories of individuals in the swarm, which may have significant implications for the study of animal collectives. Furthermore, Turing Learning could prove useful whenever a behavior is not easily characterizable using metrics, making it suitable for a wide range of applications.Comment: camera-ready versio

The liquid-glass-jamming transition in disordered ionic nanoemulsions

In quenched disordered out-of-equilibrium many-body colloidal systems, there are important distinctions between the glass transition, which is related to the onset of nonergodicity and loss of low-frequency relaxations caused by crowding, and the jamming transition, which is related to the dramatic increase in elasticity of the system caused by the deformation of constituent objects. For softer repulsive interaction potentials, these two transitions become increasingly smeared together, so measuring a clear distinction between where the glass ends and where jamming begins becomes very difficult or even impossible. Here, we investigate droplet dynamics in concentrated silicone oil-in-water nanoemulsions using light scattering. For zero or low NaCl electrolyte concentrations, interfacial repulsions are soft and longer in range, this transition sets in at lower concentrations, and the glass and the jamming regimes are smeared. However, at higher electrolyte concentrations the interactions are stiffer, and the characteristics of the glass-jamming transition resemble more closely the situation of disordered elastic spheres having sharp interfaces, so the glass and jamming regimes can be distinguished more clearly

The deuteron: structure and form factors

A brief review of the history of the discovery of the deuteron in provided. The current status of both experiment and theory for the elastic electron scattering is then presented.Comment: 80 pages, 33 figures, submited to Advances in Nuclear Physic

Peripheral arterial disease: A high risk – but neglected – disease population

Peripheral arterial disease (PAD) is a common, progressive manifestation of atherothrombotic vascular disease, which should be managed no different to cardiac disease. Indeed, there is growing evidence that PAD patients are a high risk group, although still relatively under-detected and under treated. This is despite the fact that PAD patients are an increased mortality rate comparable to those with pre-existing or established cardiovascular disease [myocardial infarction, stroke]. With a holistic approach to atherothrombotic vascular disease, our management of PAD can only get better

Intensified surveillance after surgery for colorectal cancer significantly improves survival

<p>Abstract</p> <p>Background</p> <p>Postoperative surveillance after curative resection for colorectal cancer has been demostrated to improve survival. It remains unknown however, whether intensified surveillance provides a significant benefit regarding outcome and survival. This study was aimed at comparing different surveillance strategies regarding their effect on long-term outcome.</p> <p>Methods</p> <p>Between 1990 and 2006, all curative resections for colorectal cancer were selected from our prospective colorectal cancer database. All patients were offered to follow our institution's surveillance programm according to the ASCO guidelines. We defined surveillance as "intensive" in cases where > 70% appointments were attended and the program was completed. As "minimal" we defined surveillance with < 70% of the appointments attended and an incomplete program. As "none" we defined the group which did not take part in any surveillance.</p> <p>Results</p> <p>Out of 1469 patients 858 patients underwent "intensive", 297 "minimal" and 314 "none" surveillance. The three groups were well balanced regarding biographical data and tumor characteristics. The 5-year survival rates were 79% (intensive), 76% (minimal) and 54% (none) (OR 1.480, (95% CI 1.135-1.929); <it>p </it>< 0.0001), respectively. The 10-year survival rates were 65% (intensive), 50% (minimal) and 31% (none) (<it>p </it>< 0.0001), respectively. With a median follow-up of 70 months the median time of survival was 191 months (intensive), 116 months (minimal) and 66 months (none) (<it>p </it>< 0.0001). After recurrence, the 5-year survival rates were 32% (intensive, <it>p </it>= 0.034), 13% (minimal, <it>p </it>= 0.001) and 19% (none, <it>p </it>= 0.614). The median time of survival after recurrence was 31 months (intensive, <it>p </it>< 0.0001), 21 months (minimal, <it>p </it>< 0.0001) and 16 month (none, <it>p </it>< 0.0001) respectively.</p> <p>Conclusion</p> <p>Intensive surveillance after curative resection of colorectal cancer improves survival. In cases of recurrent disease, intensive surveillance has a positive impact on patients' prognosis. Large randomized, multicenter trials are needed to substantiate these results.</p

The correlation between colorectal cancer rates of proliferation and apoptosis and systemic cytokine levels; plus their influence upon survival

Colorectal cancer development is associated with a shift in host immunity with suppression of the cell-mediated immune system (CMI) and a predominance of humoral immunity (HI). Tumour progression is also associated with increased rates of cell proliferation and apoptosis. The aim of this study was to investigate whether these factors correlate and have an influence upon prognosis. Long-term follow-up was performed on 40 patients with colorectal cancer who had levels of tumour necrosis factor (TNF)-α, interferon (IFN)-γ and interleukin (IL)-10 measured from stimulated blood cultures before surgery. Their archived tumour specimens were analysed to determine a Ki-67-derived proliferation index (PI) and a M30-derived apoptosis index (AI). Tumour necrosis factor-α levels negatively correlated to tumour proliferation (ρ=−0.697, P=0.01). Interleukin-10 levels had a positive correlation with tumour proliferation (ρ=0.452, P=0.05) and apoptosis (ρ=0.587, P=0.01). Patient survival correlates to tumour pathological stage (P=0.0038) and vascular invasion (P=0.0014). An AI⩽0.6% and TNF-α levels ⩾8148 pg ml−1 correlate to improved survival (P=0.032, P=0.021). Tumour proliferation and apoptosis correlate to progressive suppression of the CMI-associated cytokine TNF-α and to and higher levels of IL-10. Survival is dependent upon the histological stage of the tumour, vascular invasion, rates of apoptosis and proliferation and systemic immunity which are all interconnected

Computational Analysis of mRNA Expression Profiles Identifies MicroRNA-29a/c as Predictor of Colorectal Cancer Early Recurrence

Colorectal cancer (CRC) is one of the leading malignant cancers with a rapid increase in incidence and mortality. The recurrences of CRC after curative resection are sometimes unavoidable and often take place within the first year after surgery. MicroRNAs may serve as biomarkers to predict early recurrence of CRC, but identifying them from over 1,400 known human microRNAs is challenging and costly. An alternative approach is to analyze existing expression data of messenger RNAs (mRNAs) because generally speaking the expression levels of microRNAs and their target mRNAs are inversely correlated. In this study, we extracted six mRNA expression data of CRC in four studies (GSE12032, GSE17538, GSE4526 and GSE17181) from the gene expression omnibus (GEO). We inferred microRNA expression profiles and performed computational analysis to identify microRNAs associated with CRC recurrence using the IMRE method based on the MicroCosm database that includes 568,071 microRNA-target connections between 711 microRNAs and 20,884 gene targets. Two microRNAs, miR-29a and miR-29c, were disclosed and further meta-analysis of the six mRNA expression datasets showed that these two microRNAs were highly significant based on the Fisher p-value combination (p = 9.14×10−9 for miR-29a and p = 1.14×10−6 for miR-29c). Furthermore, these two microRNAs were experimentally tested in 78 human CRC samples to validate their effect on early recurrence. Our empirical results showed that the two microRNAs were significantly down-regulated (p = 0.007 for miR-29a and p = 0.007 for miR-29c) in the early-recurrence patients. This study shows the feasibility of using mRNA profiles to indicate microRNAs. We also shows miR-29a/c could be potential biomarkers for CRC early recurrence