Evolving collective behavior in an artificial ecology

Collective behavior refers to coordinated group motion, common to many animals. The dynamics of a group can be seen as a distributed model, each “animal” applying the same rule set. This study investigates the use of evolved sensory controllers to produce schooling behavior. A set of artificial creatures “live” in an artificial world with hazards and food. Each creature has a simple artificial neural network brain that controls movement in different situations. A chromosome encodes the network structure and weights, which may be combined using artificial evolution with another chromosome, if a creature should choose to mate. Prey and predators coevolve without an explicit fitness function for schooling to produce sophisticated, nondeterministic, behavior. The work highlights the role of species’ physiology in understanding behavior and the role of the environment in encouraging the development of sensory systems

Factors Influencing Willingness-to-Pay for the Energy Star Label

In the United States, nearly 17 percent of greenhouse gas emissions come from residential energy use. Increases in energy efficiency for the residential sector can generate significant energy savings and emissions reductions. Consumer labels, such as USEPA’s Energy Star, promote conservation by providing consumers with information on energy usage for household appliances. This study examines how the Energy Star label affects consumer preferences for refrigerators. An online survey of a national sample of adults suggest that consumers are, on average, willing to pay an extra $249.82 to$349.30 for a refrigerator that has been awarded the Energy Star label. Furthermore, the results provide evidence that willingness to pay was motivated by both private (energy cost savings) and public (environmental) benefits.Energy Star, willingness-to-pay, eco-label, Consumer/Household Economics, Demand and Price Analysis, Environmental Economics and Policy,

SAFE: Simulation Automation Framework for Experiments

The workflow of a network simulation study requires adherence to best practices in methodology so that results are credible and reproducible by third parties. The opportunities for one to introduce errors start at model description and permeate the process through to the reporting of results. The literature indicates that even publications in respected venues include inadvertent mistakes and poor application of methodology. When experts are liable to fail, it is unreasonable to expect that students would fare any better. This paper presents a system designed to provide guidance for inexperienced users of the popular ns-3 network simulator. SAFE automates the workflow from the initialization of model parameters, to the parallelized execution of experiments, to the processing and persistent storage of output data, and to graphical visualization of results. We discuss the architecture and the implementation of the system in the context of similar contributions in the literature

Novel NDE techniques in the power generation industry

The thesis presented here comprises the work undertaken for research into novel NDE techniques in the power generation industry. This has been undertaken as part of the Engineering Doctorate Scheme run by the Research Centre for Non-Destructive Evaluation (RCNDE), which aims to bridge the technological gap between university research and industrial application. In this case, the scheme consisted of two projects completed in conjunction with RWE npower looking at current NDE problems in steam turbine and steam-raising plant. The first project was concerned with detecting microstructural transformation in steam turbine blades, which can act as a precursor to failure by environmentally assisted cracking. This project, and indeed, this entire thesis is principally based on electromagnetic testing methods. An eddy current technique for mapping the microstructural phases was produced and validated as far as was achievable; this offered a significant time-saving advantage over the previous method, by reducing inspection time from 5 man days to just 1.5. The technique has novelty in producing a 2-dimensional map of the blade surface which highlights areas where microstructural phases differ. The second project focuses on the detection of microstructural damage associated with material creep life expiry. This forms a review of the current state of technology and highlights potentially useful paths for future research in both established and emerging NDE technologies, including Magnetic Barkhausen Noise testing and laser-generated ultrasound. Both projects have provided tangible benefit to the sponsoring company and have pushed forward research in a number of technological applications

A broad‐spectrum synthesis of Tetravinylethylenes

The first general synthesis of compounds of the tetravinylethylene (TVE) family is reported. Ramirez‐type dibromo‐olefination of readily accessible penta‐1,4‐dien‐3‐ones generates 3,3‐dibromo[3]dendralenes, which undergo twofold Negishi, Suzuki–Miyaura or Mizoroki–Heck reactions with a wide variety of olefinic coupling partners. This route delivers a broad range of unsymmetrically substituted tetravinylethylenes with up to three different alkenyl substituents attached to the central C=C bond. The extensive scope of the approach is demonstrated by the preparation of the first higher order oligo‐alkenic through‐conjugated/cross‐conjugated hybrid compounds. An unsymmetrically substituted TVE is shown to undergo a domino electrocyclization–cycloaddition with high site‐selectivity and diastereoselectivity, thereby demonstrating the substantial synthetic potential of substituted TVEs for controlled, rapid structural complexity generation.This work was supported by the Australian Research Counci

Novel NDE techniques in the power generation industry

The thesis presented here comprises the work undertaken for research into novel NDE techniques in the power generation industry. This has been undertaken as part of the Engineering Doctorate Scheme run by the Research Centre for Non-Destructive Evaluation (RCNDE), which aims to bridge the technological gap between university research and industrial application. In this case, the scheme consisted of two projects completed in conjunction with RWE npower looking at current NDE problems in steam turbine and steam-raising plant. The first project was concerned with detecting microstructural transformation in steam turbine blades, which can act as a precursor to failure by environmentally assisted cracking. This project, and indeed, this entire thesis is principally based on electromagnetic testing methods. An eddy current technique for mapping the microstructural phases was produced and validated as far as was achievable; this offered a significant time-saving advantage over the previous method, by reducing inspection time from 5 man days to just 1.5. The technique has novelty in producing a 2-dimensional map of the blade surface which highlights areas where microstructural phases differ. The second project focuses on the detection of microstructural damage associated with material creep life expiry. This forms a review of the current state of technology and highlights potentially useful paths for future research in both established and emerging NDE technologies, including Magnetic Barkhausen Noise testing and laser-generated ultrasound. Both projects have provided tangible benefit to the sponsoring company and have pushed forward research in a number of technological applications

DNA-based Diagnosis of Uncharacterized Inherited Macrothrombocytopenias Using Next-generation Sequencing Technology with a Candidate Gene Array

Inherited macrothrombocytopenias comprise a heterogeneous group of inherited platelet disorders that are characterized by large platelets, thrombocytopenia and bleeding tendencies in affected individuals. Diagnostic platforms have traditionally involved a battery of complex phenotypic tests that often fail to reach a diagnosis. Next-generation sequencing lacks the pre-analytical and analytical shortcoming of these tests and provides an attractive alternate diagnostic approach. Our group has developed a candidate gene array targeting genes known to affect platelet function and tested it in a large cohort of Australasian patients with presumed platelet function disorders, particularly macrothrombocytopenia. This array identified causative variants in a significant portion of patients with uncharacterized platelet disorders, including transcription factor mutations that cannot easily be diagnosed with standard platelet phenotyping procedures. We propose that targeted genotypic screening can identify the genetic basis of platelet function defects and has the potential to be developed into a powerful clinical platform to help clinicians diagnose these rare disorders

Hepatic Xenobiotic Metabolizing Enzyme and Transporter Gene Expression through the Life Stages of the Mouse

Differences in responses to environmental chemicals and drugs between life stages are likely due in part to differences in the expression of xenobiotic metabolizing enzymes and transporters (XMETs). No comprehensive analysis of the mRNA expression of XMETs has been carried out through life stages in any species.Using full-genome arrays, the mRNA expression of all XMETs and their regulatory proteins was examined during fetal (gestation day (GD) 19), neonatal (postnatal day (PND) 7), prepubescent (PND32), middle age (12 months), and old age (18 and 24 months) in the C57BL/6J (C57) mouse liver and compared to adults. Fetal and neonatal life stages exhibited dramatic differences in XMET mRNA expression compared to the relatively minor effects of old age. The total number of XMET probe sets that differed from adults was 636, 500, 84, 5, 43, and 102 for GD19, PND7, PND32, 12 months, 18 months and 24 months, respectively. At all life stages except PND32, under-expressed genes outnumbered over-expressed genes. The altered XMETs included those in all of the major metabolic and transport phases including introduction of reactive or polar groups (Phase I), conjugation (Phase II) and excretion (Phase III). In the fetus and neonate, parallel increases in expression were noted in the dioxin receptor, Nrf2 components and their regulated genes while nuclear receptors and regulated genes were generally down-regulated. Suppression of male-specific XMETs was observed at early (GD19, PND7) and to a lesser extent, later life stages (18 and 24 months). A number of female-specific XMETs exhibited a spike in expression centered at PND7.The analysis revealed dramatic differences in the expression of the XMETs, especially in the fetus and neonate that are partially dependent on gender-dependent factors. XMET expression can be used to predict life stage-specific responses to environmental chemicals and drugs

An analysis of SARS-CoV-2 cell entry genes identifies the intestine and colorectal cancer as susceptible tissues.

SARS-CoV-2 is the causative agent for the COVID-19 pandemic. COVID-19 has necessitated rapid changes in surgical practice and organisation through both the initial peak and ongoing recovery period 1. SARS-CoV-2 infects cells by interacting with the host cell surface protein ACE2 and utilises TMPRSS2 in viral spike protein priming to facilitate cell entry (Fig. 1a) 2. Whilst COVID-19 is predominantly a respiratory disease approximately 15% of patients have concurrent gastrointestinal symptoms 3. SARS-CoV-2 RNA and live virus have been identified in stool from COVID-19 patients and SARS-CoV-2 readily infects intestinal organoids 4-6. Despite these circumstantial data, gastrointestinal transmission has not yet been formally confirmed. Cancers commonly express different genes from the tissue of origin and it is largely unexplored whether tumours can be infected with SARS-CoV-2. We sought to explore the expression of ACE2 and TMPRSS2 in large publicly available normal tissue and pan-cancer expression data sets to understand whether levels of these genes identify susceptible tissues.SJAB is supported by an Advanced Clinician Scientist Fellowship grant from Cancer Research UK C14094/A27178; and core funding from Wellcome and MRC to the Wellcome-MRC Cambridge Stem Cell Institute