Agent cognition through micro-simulations: Adaptive and tunable intelligence with NetLogo LevelSpace

We present a method of endowing agents in an agent-based model (ABM) with sophisticated cognitive capabilities and a naturally tunable level of intelligence. Often, ABMs use random behavior or greedy algorithms for maximizing objectives (such as a predator always chasing after the closest prey). However, random behavior is too simplistic in many circumstances and greedy algorithms, as well as classic AI planning techniques, can be brittle in the context of the unpredictable and emergent situations in which agents may find themselves. Our method, called agent-centric Monte Carlo cognition (ACMCC), centers around using a separate agent-based model to represent the agents' cognition. This model is then used by the agents in the primary model to predict the outcomes of their actions, and thus guide their behavior. To that end, we have implemented our method in the NetLogo agent-based modeling platform, using the recently released LevelSpace extension, which we developed to allow NetLogo models to interact with other NetLogo models. As an illustrative example, we extend the Wolf Sheep Predation model (included with NetLogo) by using ACMCC to guide animal behavior, and analyze the impact on agent performance and model dynamics. We find that ACMCC provides a reliable and understandable method of controlling agent intelligence, and has a large impact on agent performance and model dynamics even at low settings.Comment: Model source code available here: https://github.com/qiemem/Wolf-Sheep-Predation-Micro-Sims, In: Unifying Themes in Complex Systems IX. ICCS 2018. Springer Proceedings in Complexity. Springer, Cha

Fabrication of beryllia-coated, fuelled beryllia spheres for in-pile fission product release tests.

Three sees of beryllia-coated, fuelled beryllia spheres were made for fission product release testing in a sweep capsule irradiation rig Results of various pre-irradiation tests are presented and discussed, and a summary of fission gas release results is included, Gas release rates were expected to vary inversely as the beryllia density However, the release rate was lowest for the loading with an intermediate density and was highest for that with the highest density One or more of several structural factors may have changed the behaviour from that expected

Adverse pregnancy and neonatal outcomes associated with <i>Neisseria gonorrhoeae:</i> systematic review and meta-analysis.

ObjectiveTo examine associations between Neisseria gonorrhoeae (NG) infection during pregnancy and the risk of preterm birth, spontaneous abortion, premature rupture of membranes, perinatal mortality, low birth weight and ophthalmia neonatorum.Data sourcesWe searched Medline, EMBASE, the Cochrane Library and Cumulative Index to Nursing and Allied Health Literature for studies published between 1948 and 14 January 2020.MethodsStudies were included if they reported testing for NG during pregnancy and compared pregnancy, perinatal and/or neonatal outcomes between women with and without NG. Two reviewers independently assessed papers for inclusion and extracted data. Risk of bias was assessed using established checklists for each study design. Summary ORs with 95% CIs were generated using random effects models for both crude and, where available, adjusted associations.ResultsWe identified 2593 records and included 30 in meta-analyses. Women with NG were more likely to experience preterm birth (OR 1.55, 95% CI 1.21 to 1.99, n=18 studies); premature rupture of membranes (OR 1.41, 95% CI 1.02 to 1.92, n=9); perinatal mortality (OR 2.16, 95% CI 1.35 to 3.46, n=9); low birth weight (OR 1.66, 95% CI 1.12 to 2.48, n=8) and ophthalmia neonatorum (OR 4.21, 95% CI 1.36 to 13.04, n=6). Summary adjusted ORs were, for preterm birth 1.90 (95% CI 1.14 to 3.19, n=5) and for low birth weight 1.48 (95% CI 0.79 to 2.77, n=4). In studies with a multivariable analysis, age was the variable most commonly adjusted for. NG was more strongly associated with preterm birth in low-income and middle-income countries (OR 2.21, 95% CI 1.40 to 3.48, n=7) than in high-income countries (OR 1.38, 95% CI 1.04 to 1.83, n=11).ConclusionsNG is associated with a number of adverse pregnancy and newborn outcomes. Further research should be done to determine the role of NG in different perinatal mortality outcomes because interventions that reduce mortality will have the greatest impact on reducing the burden of disease in low-income and middle-income countries.Prospero registration numberCRD42016050962

Presymptomatic risk assessment for chronic non-communicable diseases

The prevalence of common chronic non-communicable diseases (CNCDs) far overshadows the prevalence of both monogenic and infectious diseases combined. All CNCDs, also called complex genetic diseases, have a heritable genetic component that can be used for pre-symptomatic risk assessment. Common single nucleotide polymorphisms (SNPs) that tag risk haplotypes across the genome currently account for a non-trivial portion of the germ-line genetic risk and we will likely continue to identify the remaining missing heritability in the form of rare variants, copy number variants and epigenetic modifications. Here, we describe a novel measure for calculating the lifetime risk of a disease, called the genetic composite index (GCI), and demonstrate its predictive value as a clinical classifier. The GCI only considers summary statistics of the effects of genetic variation and hence does not require the results of large-scale studies simultaneously assessing multiple risk factors. Combining GCI scores with environmental risk information provides an additional tool for clinical decision-making. The GCI can be populated with heritable risk information of any type, and thus represents a framework for CNCD pre-symptomatic risk assessment that can be populated as additional risk information is identified through next-generation technologies.Comment: Plos ONE paper. Previous version was withdrawn to be updated by the journal's pdf versio

A Large Web-Based Observer Reliability Study of Early Ischaemic Signs on Computed Tomography. The Acute Cerebral CT Evaluation of Stroke Study (ACCESS)

BACKGROUND: Early signs of ischaemic stroke on computerised tomography (CT) scanning are subtle but CT is the most widely available diagnostic test for stroke. Scoring methods that code for the extent of brain ischaemia may improve stroke diagnosis and quantification of the impact of ischaemia. METHODOLOGY AND PRINCIPAL FINDINGS: We showed CT scans from patients with acute ischaemic stroke (n = 32, with different patient characteristics and ischaemia signs) to doctors in stroke-related specialties world-wide over the web. CT scans were shown twice, randomly and blindly. Observers entered their scan readings, including early ischaemic signs by three scoring methods, into the web database. We compared observers' scorings to a reference standard neuroradiologist using area under receiver operator characteristic curve (AUC) analysis, Cronbach's alpha and logistic regression to determine the effect of scales, patient, scan and observer variables on detection of early ischaemic changes. Amongst 258 readers representing 33 nationalities and six specialties, the AUCs comparing readers with the reference standard detection of ischaemic signs were similar for all scales and both occasions. Being a neuroradiologist, slower scan reading, more pronounced ischaemic signs and later time to CT all improved detection of early ischaemic signs and agreement on the rating scales. Scan quality, stroke severity and number of years of training did not affect agreement. CONCLUSIONS: Large-scale observer reliability studies are possible using web-based tools and inform routine practice. Slower scan reading and use of CT infarct rating scales improve detection of acute ischaemic signs and should be encouraged to improve stroke diagnosis

Complex Evolutionary History of the Aeromonas veronii Group Revealed by Host Interaction and DNA Sequence Data

Aeromonas veronii biovar sobria, Aeromonas veronii biovar veronii, and Aeromonas allosaccharophila are a closely related group of organisms, the Aeromonas veronii Group, that inhabit a wide range of host animals as a symbiont or pathogen. In this study, the ability of various strains to colonize the medicinal leech as a model for beneficial symbiosis and to kill wax worm larvae as a model for virulence was determined. Isolates cultured from the leech out-competed other strains in the leech model, while most strains were virulent in the wax worms. Three housekeeping genes, recA, dnaJ and gyrB, the gene encoding chitinase, chiA, and four loci associated with the type three secretion system, ascV, ascFG, aexT, and aexU were sequenced. The phylogenetic reconstruction failed to produce one consensus tree that was compatible with most of the individual genes. The Approximately Unbiased test and the Genetic Algorithm for Recombination Detection both provided further support for differing evolutionary histories among this group of genes. Two contrasting tests detected recombination within aexU, ascFG, ascV, dnaJ, and gyrB but not in aexT or chiA. Quartet decomposition analysis indicated a complex recent evolutionary history for these strains with a high frequency of horizontal gene transfer between several but not among all strains. In this study we demonstrate that at least for some strains, horizontal gene transfer occurs at a sufficient frequency to blur the signal from vertically inherited genes, despite strains being adapted to distinct niches. Simply increasing the number of genes included in the analysis is unlikely to overcome this challenge in organisms that occupy multiple niches and can exchange DNA between strains specialized to different niches. Instead, the detection of genes critical in the adaptation to specific niches may help to reveal the physiological specialization of these strains

"I am your mother and your father!": In vitro derived gametes and the ethics of solo reproduction

In this paper, we will discuss the prospect of human reproduction achieved with gametes originating from only one person. According to statements by a minority of scientists working on the generation of gametes in vitro, it may become possible to create eggs from men’s non-reproductive cells and sperm from women’s. This would enable, at least in principle, the creation of an embryo from cells obtained from only one individual: ‘solo reproduction’. We will consider what might motivate people to reproduce in this way, and the implications that solo reproduction might have for ethics and policy. We suggest that such an innovation is unlikely to revolutionise reproduction and parenting. Indeed, in some respects it is less revolutionary than in vitro fertilisation as a whole. Furthermore, we show that solo reproduction with in vitro created gametes is not necessarily any more ethically problematic than gamete donation—and probably less so. Where appropriate, we draw parallels with the debate surrounding reproductive cloning. We note that solo reproduction may serve to perpetuate reductive geneticised accounts of reproduction, and that this may indeed be ethically questionable. However, in this it is not unique among other technologies of assisted reproduction, many of which focus on genetic transmission. It is for this reason that a ban on solo reproduction might be inconsistent with continuing to permit other kinds of reproduction that also bear the potential to strengthen attachment to a geneticised account of reproduction. Our claim is that there are at least as good reasons to pursue research towards enabling solo reproduction, and eventually to introduce solo reproduction as an option for fertility treatment, as there are to do so for other infertility related purposes

Robust Multimodal Image Registration Using Deep Recurrent Reinforcement Learning

The crucial components of a conventional image registration method are the choice of the right feature representations and similarity measures. These two components, although elaborately designed, are somewhat handcrafted using human knowledge. To this end, these two components are tackled in an end-to-end manner via reinforcement learning in this work. Specifically, an artificial agent, which is composed of a combined policy and value network, is trained to adjust the moving image toward the right direction. We train this network using an asynchronous reinforcement learning algorithm, where a customized reward function is also leveraged to encourage robust image registration. This trained network is further incorporated with a lookahead inference to improve the registration capability. The advantage of this algorithm is fully demonstrated by our superior performance on clinical MR and CT image pairs to other state-of-the-art medical image registration methods