Would you be impressed: applying principles of magic to chatbot conversations.

A magician's trick and a chatbot conversation have something in common: most of their audiences do not know how they work. Both are also constrained by their own limitations: magicians by the constraints of biology and physics, and dialogue systems by the status of current technology. Magicians and chatbot creators also share a goal: they want to engage their audience. But magicians, unlike the designers of dialogue systems, have centuries of practice in gracefully skirting limitations in order to engage their audience and enhance a sense of awe. In this paper, we look at these practices and identify several key principles of magic and psychology to apply to conversations between chatbots and humans. We formulate a model of communication centered on controlling the user's attention, expectations, decisions, and memory based on examples from the history of magic. We apply these magic principles to real-world conversations between humans and a social robot and evaluate their effectiveness in a Magical conversation setting compared to a Control conversation that does not incorporate magic principles. We find that human evaluators preferred interactions that incorporated magical principles over interactions that did not. In particular, magical interactions increased 1) the personalization of experience, 2) user engagement, and 3) character likability. Firstly, the magical experience was "personalized." According to survey results, the magical conversation demonstrated a statistically significant increase in "emotional connection" and "robot familiarity." Therefore, the personalization of the experience leads to higher levels of perceived impressiveness and emotional connection. Secondly, in the Magical conversation, we find that the human interlocutor is perceived to have statistically-significantly higher engagement levels in four of seven characteristics. Thirdly, participants judged the robot in the magical conversation to have a significantly greater degree of "energeticness,""humorousness," and "interestingness." Finally, evaluation of the conversations with questions intended to measure contribution of the magical principals showed statistically-significant differences for five out of nine principles, indicating a positive contribution of the magical principles to the perceived conversation experience. Overall, our evaluation demonstrates that the psychological principles underlying a magician's showmanship can be applied to the design of conversational systems to achieve more personalized, engaging, and fun interactions.

Application of the Clavien-Dindo classification to a pediatric surgical network.

INTRODUCTION: A comprehensive validated system to evaluate surgical complications is required in our specialty to facilitate comparison and audit. The Clavien-Dindo (CD) classification of post-surgical complications was originally described in an adult general surgical setting in 1992 and has become widely used. We aimed to apply this to a pediatric surgical setting. METHODS: Data were collected on emergency and elective surgical activity together with complications in a prospective audit over a recent 4-month period in three geographical conjoined regional pediatric surgical units (including two major trauma centres). Briefly the CD classification codes complications according to degree of harm and magnitude of intervention required [I - V (death) with III and IV sub-divided according to whether general anesthesia was needed]. Length of stay and mode of admission were recorded. Data are given as median (range). Non-parametric comparison was used, and a p value of <0.05 was regarded as significant. RESULTS: During the period JULY - OCT 2018 (inclusive), there were 1822 admissions (elective, n = 1186: emergency, n = 636) and 1556 operations (elective, n = 1189, and of these 393 were urological). There were 69 patient complications: CDI (n = 7), CD-II (n = 19), CD-IIIa (n = 4), CD-IIIb (n = 28), CD-IV (n = 4), CD-V (n = 7). Deaths were principally in neonates and due to NEC (n = 6) at 2.5 (1-140) days post-operatively. There was a single post-traumatic death in an adolescent. LOS was 9 (0-217) days in CD I-IV. The incidence of any complication was 4.4%, of serious complication (defined as ≥CD III) 2.6% (A = 2.1%, B = 2.0%, and C = 3.2%: p = 0.16), and of death 0.45%. The most frequent complications were wound infection (n = 12) and post-appendicectomy collections/abscess (n = 10). CONCLUSIONS: This appears to be the 1st report of the C-D classification in a general pediatric surgery network and can be considered a benchmark. The risk of death or serious harm is very low in such a practice. TYPE OF STUDY: Prospective Cohort Study. LEVEL OF EVIDENCE: IIb.

Neural field simulator: two-dimensional spatio-temporal dynamics involving finite transmission speed.

Neural Field models (NFM) play an important role in the understanding of neural population dynamics on a mesoscopic spatial and temporal scale. Their numerical simulation is an essential element in the analysis of their spatio-temporal dynamics. The simulation tool described in this work considers scalar spatially homogeneous neural fields taking into account a finite axonal transmission speed and synaptic temporal derivatives of first and second order. A text-based interface offers complete control of field parameters and several approaches are used to accelerate simulations. A graphical output utilizes video hardware acceleration to display running output with reduced computational hindrance compared to simulators that are exclusively software-based. Diverse applications of the tool demonstrate breather oscillations, static and dynamic Turing patterns and activity spreading with finite propagation speed. The simulator is open source to allow tailoring of code and this is presented with an extension use case.

Buckling the equatorial anion plane: octahedral anion distortions in ferroic perovskites and related systems resolved via neutron diffraction.

A framework for describing anion displacements from perfect octahedra in perovskites has been developed for use with neutron diffraction data sets. We describe the distortions as noncoplanar arrangements, or buckling, of oxygen ions in any central plane of the octahedron, ignoring the central cation. Nonplanar distortions of octahedra have been calculated for perovskite structures contained within the Inorganic Crystal Structure Database. We find that antiferroelectric materials have buckling angles larger than ~2° and ferroelectric materials have buckling angles between 0° and 1°. The trend is found as a function of solid solution composition and temperature for common antiferroelectrics. For example, the described method resolves a structural difference between the end members PbTiO(3) and PbZrO(3), which exhibit ferroelectric and antiferroelectric responses, respectively. This technique is applicable to other structures containing anion octahedra, e.g., pyrochlores, spinels, and tungsten bronzes.

Biologically Inspired SNN for Robot Control.

This paper proposes a spiking-neural-network-based robot controller inspired by the control structures of biological systems. Information is routed through the network using facilitating dynamic synapses with short-term plasticity. Learning occurs through long-term synaptic plasticity which is implemented using the temporal difference learning rule to enable the robot to learn to associate the correct movement with the appropriate input conditions. The network self-organizes to provide memories of environments that the robot encounters. A Pioneer robot simulator with laser and sonar proximity sensors is used to verify the performance of the network with a wall-following task, and the results are presented.

The role of clonal interference in the evolutionary dynamics of plasmid-host adaptation.

UNLABELLED: Promiscuous plasmids replicate in a wide range of bacteria and therefore play a key role in the dissemination of various host-beneficial traits, including antibiotic resistance. Despite the medical relevance, little is known about the evolutionary dynamics through which drug resistance plasmids adapt to new hosts and thereby persist in the absence of antibiotics. We previously showed that the incompatibility group P-1 (IncP-1) minireplicon pMS0506 drastically improved its stability in novel host Shewanella oneidensis MR-1 after 1,000 generations under antibiotic selection for the plasmid. The only mutations found were those affecting the N terminus of the plasmid replication initiation protein TrfA1. Our aim in this study was to gain insight into the dynamics of plasmid evolution. Changes in stability and genotype frequencies of pMS0506 were monitored in evolving populations of MR-1 (pMS0506). Genotypes were determined by sequencing trfA1 amplicons from individual clones and by 454 pyrosequencing of whole plasmids from entire populations. Stability of pMS0506 drastically improved by generation 200. Many evolved plasmid genotypes with point mutations as well as in-frame and frameshift deletions and duplications in trfA1 were observed in all lineages with both sequencing methods. Strikingly, multiple genotypes were simultaneously present at high frequencies (>10%) in each population. Their relative abundances changed over time, but after 1,000 generations only one or two genotypes dominated the populations. This suggests that hosts with different plasmid genotypes were competing with each other, thus affecting the evolutionary trajectory. Plasmids can thus rapidly improve their stability, and clonal interference plays a significant role in plasmid-host adaptation dynamics. IMPORTANCE: Promiscuous plasmids play an important role in the spread of antibiotic resistance and many other traits between closely and distantly related bacteria. However, little is known about the dynamics by which these broad-host-range antibiotic resistance plasmids adapt to novel bacteria and thereby become more persistent, even in the absence of antibiotics. In this study, we show that after no more than 200 generations of growth in the presence of antibiotics, a plasmid that was initially poorly maintained in a novel bacterial host evolved to become drastically more persistent in the absence of antibiotics. In each of the evolving populations, an unexpectedly large number of bacterial variants arose with distinct mutations in the plasmid's replication initiation protein. Our results suggest that clonal interference, characterized by competition between variant clones in a population, plays a major role in the evolution of the persistence of drug resistance.

Risk, individual differences, and environment: an Agent-Based Modeling approach to sexual risk-taking.

Risky sexual behaviors, including the decision to have unprotected sex, result from interactions between individuals and their environment. The current study explored the use of Agent-Based Modeling (ABM)-a methodological approach in which computer-generated artificial societies simulate human sexual networks-to assess the influence of heterogeneity of sexual motivation on the risk of contracting HIV. The models successfully simulated some characteristics of human sexual systems, such as the relationship between individual differences in sexual motivation (sexual excitation and inhibition) and sexual risk, but failed to reproduce the scale-free distribution of number of partners observed in the real world. ABM has the potential to inform intervention strategies that target the interaction between an individual and his or her social environment.

Case study on a self-organizing spiking neural network for robot navigation.

This paper presents a Spiking Neural Network (SNN) architecture for mobile robot navigation. The SNN contains 4 layers where dynamic synapses route information to the appropriate neurons in each layer and the neurons are modeled using the Leaky Integrate and Fire (LIF) model. The SNN learns by self-organizing its connectivity as new environmental conditions are experienced and consequently knowledge about its environment is stored in the connectivity. Also a novel feature of the proposed SNN architecture is that it uses working memory, where present and previous sensor states are stored. Results are presented for a wall following application.

Efficacy of pyrantel pamoate and ivermectin paste formulations against naturally acquired Oxyuris equi infections in horses.

In recent years, numerous veterinary practitioners have reported anecdotal episodes in which anthelmintic treatment did not appear to deliver the expected efficacy against equine pinworms (Oxyuris equi). Anthelmintic resistance has not been demonstrated formally in equine pinworms, so a clinical study was designed to evaluate the efficacy of paste formulations of pyrantel pamoate or ivermectin against naturally acquired infections with O. equi. Twenty-one horses (>4 months to 15 years of age) with patent, naturally acquired pinworm infections were blocked by source of origin and allocated randomly to one of three treatment groups: horses (n=7) assigned to Group 1 were treated orally with pyrantel pamoate paste at a dosage of 13.2 mg/kg (2x label dosage), Group 2 horses (n=7) were untreated controls, and horses (n=7) assigned to Group 3 were treated orally with ivermectin paste at a dosage of 200 microg/kg. Fourteen days after treatment, horses were euthanatized, necropsied, and large intestinal contents were processed for recovery of adult pinworms. In addition, duplicate 1% aliquots of intestinal contents from the cecum, ventral colon, dorsal colon, and small colon were collected, preserved, and examined for recovery and enumeration of fourth-stage larval O. equi. Anthelmintic efficacy against pinworms was evaluated by comparing the post-treatment worm counts of Groups 1 and 3 to those of control animals. Mean numbers of O. equi adults recovered postmortem were significantly decreased by both pyrantel pamoate (P=0.0366) and ivermectin (P=0.0137) treatment, with respective efficacies of 91.2% and 96.0%. In addition, both products demonstrated >99% efficacy against fourth-stage O. equi larvae. The current study demonstrated acceptable adulticidal and larvicidal efficacy of both pyrantel pamoate and ivermectin paste formulations against O. equi and did not support the existence of macrocyclic lactone or pyrimidine resistance in the pinworm populations evaluated.

Efficacy of pyrantel pamoate against a macrocyclic lactone-resistant isolate of Parascaris equorum in horses.

The expanding prevalence of Parascaris equorum populations that are resistant to macrocyclic lactone (ML) anthelmintics makes it desirable to identify dewormers which remain effective. The objective was to evaluate the efficacy of pyrantel pamoate in 14 suckling foals that had been infected orally with approximately 600 larvated eggs of a P. equorum isolate selected for ML resistance (ML-R). Seventy days after inoculation, foals were weaned, housed individually, and fecal samples were examined frequently to detect the onset of patency. Between 73 and 80 days post-inoculation, all 14 foals developed P. equorum egg counts>or=150 eggs per gram (EPG). An initial cohort of eight foals was treated orally with ivermectin paste (200 microg/kg) 84-91 days post-inoculation. Egg counts were reduced by only 47% at 2 weeks after ivermectin treatment, confirming the ML-R status of the isolate. A second cohort of six foals was not treated with ivermectin. Within each cohort, eligible foals were allocated randomly to treated (pyrantel pamoate; n=7) or untreated control (n=7) groups. Treated foals were dosed orally on Day 0 with a paste formulation of pyrantel pamoate at 13.2mg/kg. Mean ascarid egg counts of treated foals were reduced by 96.0% and 98.8% at 1 and 2 weeks post-treatment, respectively. On Day 14, foals were euthanatized and specimens of P. equorum were recovered from the gut contents, preserved in 10% formalin, and counted. Mean numbers of P. equorum adults recovered postmortem were significantly lower (P=0.0031) in foals treated with pyrantel pamoate (X=1.7; range 0-16) compared to control foals (X=63.0; range 0-320). A paste formulation of pyrantel pamoate, at a dosage of 13.2 mg/kg, was 97.3% effective against a ML-R isolate of P. equorum.

An intensive insulinotherapy mobile phone application built on artificial intelligence techniques.

BACKGROUND: Software to help control diabetes is currently an embryonic market with the main activity to date focused mainly on the development of noncomputerized solutions, such as cardboard calculators or computerized solutions that use "flat" computer models, which are applied to each person without taking into account their individual lifestyles. The development of true, mobile device-driven health applications has been hindered by the lack of tools available in the past and the sheer lack of mobile devices on the market. This has now changed, however, with the availability of pocket personal computer handsets. METHOD: This article describes a solution in the form of an intelligent neural network running on mobile devices, allowing people with diabetes access to it regardless of their location. Utilizing an easy to learn and use multipanel user interface, people with diabetes can run the software in real time via an easy to use graphical user interface. The neural network consists of four neurons. The first is glucose. If the user's current glucose level is within the target range, the glucose weight is then multiplied by zero. If the glucose level is high, then there will be a positive value multiplied to the weight, resulting in a positive amount of insulin to be injected. If the user's glucose level is low, then the weights will be multiplied by a negative value, resulting in a decrease in the overall insulin dose. RESULTS: A minifeasibility trial was carried out at a local hospital under a consultant endocrinologist in Belfast. The short study ran for 2 weeks with six patients. The main objectives were to investigate the user interface, test the remote sending of data over a 3G network to a centralized server at the university, and record patient data for further proofing of the neural network. We also received useful feedback regarding the user interface and the feasibility of handing real-world patients a new mobile phone. Results of this short trial confirmed to a large degree that our approach (which also can be known as intensive insulinotherapy) has value and perhaps that our neural network approach has implications for future intelligent insulin pumps. CONCLUSIONS: Currently, there is no software available to tell people with diabetes how much insulin to inject in accordance with their lifestyle and individual inputs, which leads to adjustments in software predictions on the amount of insulin to inject. We have taken initial steps to supplement the knowledge and skills of health care professionals in controlling insulin levels on a daily basis using a mobile device for people who are less able to manage their disease, especially children and young adults.