Evolution of honesty in higher-order social networks

Sender-receiver games are simple models of information transmission that provide a formalism to study the evolution of honest signaling and deception between a sender and a receiver. In many practical scenarios, lies often affect groups of receivers, which inevitably entangles the payoffs of individuals to the payoffs of other agents in their group, and this makes the formalism of pairwise sender-receiver games inapt for where it might be useful the most. We therefore introduce group interactions among receivers and study how their interconnectedness in higher-order social networks affects the evolution of lying. We observe a number of counterintuitive results that are rooted in the complexity of the underlying evolutionary dynamics, which has thus far remained hidden in the realm of pairwise interactions. We find conditions for honesty to persist even when there is a temptation to lie, and we observe the prevalence of moral strategy profiles even when lies favor the receiver at a cost to the sender. We confirm the robustness of our results by further performing simulations on hypergraphs created from real-world data using the SocioPatterns database. Altogether, our results provide persuasive evidence that moral behavior may evolve on higher-order social networks, at least as long as individuals interact in groups that are small compared to the size of the network

Experimental Results of Concurrent Learning Adaptive Controllers

Commonly used Proportional-Integral-Derivative based UAV flight controllers are often seen to provide adequate trajectory-tracking performance only after extensive tuning. The gains of these controllers are tuned to particular platforms, which makes transferring controllers from one UAV to other time-intensive. This paper suggests the use of adaptive controllers in speeding up the process of extracting good control performance from new UAVs. In particular, it is shown that a concurrent learning adaptive controller improves the trajectory tracking performance of a quadrotor with baseline linear controller directly imported from another quadrotors whose inertial characteristics and throttle mapping are very di fferent. Concurrent learning adaptive control uses specifi cally selected and online recorded data concurrently with instantaneous data and is capable of guaranteeing tracking error and weight error convergence without requiring persistency of excitation. Flight-test results are presented on indoor quadrotor platforms operated in MIT's RAVEN environment. These results indicate the feasibility of rapidly developing high-performance UAV controllers by using adaptive control to augment a controller transferred from another UAV with similar control assignment structure.United States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant N000141110688)National Science Foundation (U.S.). Graduate Research Fellowship Program (Grant 0645960)Boeing Scientific Research Laboratorie

Distribution of Contact Pressure and Stresses under Skirted Footings

Skirted footings posses many novel characteristics which render them eminently suitable for construction of structures in situations involving heavy loads and poor soil conditions with promise of economy. The results of the present investigations will help considerably to understand a detailed picture of the complex phenomenon of contact pressure distribution and vertical stress distribution in soil under skirted footings

First hospital outbreak of the globally emerging Candida auris in a European hospital

Background: Candida auris is a globally emerging multidrug resistant fungal pathogen causing nosocomial transmission. We report an ongoing outbreak of C. auris in a London cardio-thoracic center between April 2015 and July 2016. This is the first report of C. auris in Europe and the largest outbreak so far. We describe the identification, investigation and implementation of control measures. Methods: Data on C. auris case demographics, environmental screening, implementation of infection prevention/control measures, and antifungal susceptibility of patient isolates were prospectively recorded then analysed retrospectively. Speciation of C. auris was performed by MALDI-TOF and typing of outbreak isolates performed by amplified fragment length polymorphism (AFLP). Results: This report describes an ongoing outbreak of 50 C. auris cases over the first 16 month (April 2015 to July 2016) within a single Hospital Trust in London. A total of 44 % (n = 22/50) patients developed possible or proven C. auris infection with a candidaemia rate of 18 % (n = 9/50). Environmental sampling showed persistent presence of the yeast around bed space areas. Implementation of strict infection and prevention control measures included: isolation of cases and their contacts, wearing of personal protective clothing by health care workers, screening of patients on affected wards, skin decontamination with chlorhexidine, environmental cleaning with chorine based reagents and hydrogen peroxide vapour. Genotyping with AFLP demonstrated that C. auris isolates from the same geographic region clustered. Conclusion: This ongoing outbreak with genotypically closely related C. auris highlights the importance of appropriate species identification and rapid detection of cases in order to contain hospital acquired transmission

Final Technology Review - Pitch Modulated Vibrato Function

Final Technology Review Written ReportArchitecture & Allied Art

Bayesian Nonparametric Adaptive Control using Gaussian Processes

This technical report is a preprint of an article submitted to a journal.Most current Model Reference Adaptive Control (MRAC) methods rely on parametric adaptive elements, in which the number of parameters of the adaptive element are fixed a priori, often through expert judgment. An example of such an adaptive element are Radial Basis Function Networks (RBFNs), with RBF centers pre-allocated based on the expected operating domain. If the system operates outside of the expected operating domain, this adaptive element can become non-effective in capturing and canceling the uncertainty, thus rendering the adaptive controller only semi-global in nature. This paper investigates a Gaussian Process (GP) based Bayesian MRAC architecture (GP-MRAC), which leverages the power and flexibility of GP Bayesian nonparametric models of uncertainty. GP-MRAC does not require the centers to be preallocated, can inherently handle measurement noise, and enables MRAC to handle a broader set of uncertainties, including those that are defined as distributions over functions. We use stochastic stability arguments to show that GP-MRAC guarantees good closed loop performance with no prior domain knowledge of the uncertainty. Online implementable GP inference methods are compared in numerical simulations against RBFN-MRAC with preallocated centers and are shown to provide better tracking and improved long-term learning.This research was supported in part by ONR MURI Grant N000141110688 and NSF grant ECS #0846750

Accuracy of impressions with different impression materials in angulated implants

Purpose: To evaluate the dimensional accuracy of the resultant (duplicative) casts made from two different impression materials (polyvinyl siloxane and polyether) in parallel and angulated implants.Materials and Methods: Three definitive master casts (control groups) were fabricated in dental stone with three implants, placed at equi-distance. In first group (control), all three implants were placed parallel to each other and perpendicular to the plane of the cast. In the second and third group (control), all three implants were placed at 10° and 15° angulation respectively to the long axis of the cast, tilting towards the centre. Impressions were made with polyvinyl siloxane and polyether impression materials in a special tray, using a open tray impression technique from the master casts. These impressions were poured to obtain test casts. Three reference distances were evaluated on each test cast by using a profile projector and compared with control groups to determine the effect of combined interaction of implant angulation and impression materials on the accuracy of implant resultant cast.Results: Statistical analysis revealed no significant difference in dimensional accuracy of the resultant casts made from two different impression materials (polyvinyl siloxane and polyether) by closed tray impression technique in parallel and angulated implants.Conclusion: On the basis of the results of this study, the use of both the impression materials i.e., polyether and polyvinyl siloxane impression is recommended for impression making in parallel as well as angulated implants.Key words: Angulated implants, implant impression, impression accuracy, impression materia

Experimental Validation of Plant Peroxisomal Targeting Prediction Algorithms by Systematic Comparison of In Vivo Import Efficiency and In Vitro PTS1 Binding Affinity

Most peroxisomal matrix proteins possess a C-terminal targeting signal type 1 (PTS1). Accurate prediction of functional PTS1 sequences and their relative strength by computational methods is essential for determination of peroxisomal proteomes in silico but has proved challenging due to high levels of sequence variability of non-canonical targeting signals, particularly in higher plants, and low levels of availability of experimentally validated non-canonical examples. In this study, in silico predictions were compared with in vivo targeting analyses and in vitro thermodynamic binding of mutated variants within the context of one model targeting sequence. There was broad agreement between the methods for entire PTS1 domains and position-specific single amino acid residues, including residues upstream of the PTS1 tripeptide. The hierarchy Leu>Met>Ile>Val at the C-terminal position was determined for all methods but both experimental approaches suggest that Tyr is underweighted in the prediction algorithm due to the absence of this residue in the positive training dataset. A combination of methods better defines the score range that discriminates a functional PTS1. In vitro binding to the PEX5 receptor could discriminate among strong targeting signals while in vivo targeting assays were more sensitive, allowing detection of weak functional import signals that were below the limit of detection in the binding assay. Together, the data provide a comprehensive assessment of the factors driving PTS1 efficacy and provide a framework for the more quantitative assessment of the protein import pathway in higher plants