Communicating qualitative uncertainty in data visualization

Qualitative uncertainty refers to the implicit and underlying issues that are imbued in data, such as the circumstances of its collection, its storage or even biases and assumptions made by its authors. Although such uncertainty can jeopardize the validity of the data analysis, it is often overlooked in visualizations, due to it being indirect and non-quantifiable. In this paper we present two case studies within the digital humanities in which we examined how to integrate uncertainty in our visualization designs. Using these cases as a starting point we propose four considerations for data visualization research in relation to indirect, qualitative uncertainty: (1) we suggest that uncertainty in visualization should be examined within its socio-technological context, (2) we propose the use of interaction design patterns to design for it, (3) we argue for more attention to be paid to the data generation process in the humanities, and (4) we call for the further development of participatory activities specifically catered for understanding qualitative uncertainties. While our findings are grounded in the humanities, we believe that these considerations can be beneficial for other settings where indirect uncertainty plays an equally prevalent role

Survey of Microbial Composition and Mechanisms of Living Stromatolites of the Bahamas and Australia: Developing Criteria to Determine the Biogenicity of Fossil Stromatolites

A stromatolite is typically defined as a laminated and lithified structure that is the result of microbial activity over the course of time. Fossil stromatolites are relatively abundant; however, modern living stromatolites are rare. Two well-studied examples of living stromatolites include those found in the Exuma Cays of the Bahamas and Shark Bay in Australia. Depending on dominant chemical reactions by bacteria and environmental conditions, accretion and lithification of the stromatolite occurs at intervals. Each layer or lamina of a stromatolite represents a former surface mat of bacteria. As long as cyanobacteria (or other phototrophs) colonize the top surface of the stromatolite, growth is likely to continue. Understanding microbial composition and mechanisms of living stromatolites is crucial to determining the biogenicity of fossil stromatolites. Although there is a paucity of fossilized bacteria in fossil stromatolites, their structural features closely resemble those of living stromatolites. A set of criteria from the study of living and fossil stromatolites has been developed to aid determination of the biogenicity of fossil stromatolites. It was concluded that there is now sufficient evidence for the biogenicity of many stromatolites, even as early as 3.5 Ga, so these need to be understood within the biblical framework of earth history. Discernment of genuine stromatolites in the geologic record may help determine boundaries between Creation Week, pre- Flood and Flood strata. In addition, understanding how various living stromatolites form in different environments provides insight into the pre-Flood environments in which fossil stromatolites grew

The mechanism by which potassium causes neurite retraction in lamprey descending neurons in cell culture

Abstract only availableSevere spinal cord injury (SCI) disrupts descending axons from reticulospinal (RS) neurons that project to the spinal cord. In most “higher” vertebrates, including humans, recovery is very minimal due to limited regeneration in the central nervous system, and paralysis is usually permanent below the injury site. In several lower vertebrates, including the lamprey, behavioral recovery is almost complete following SCI due to robust axonal regeneration. To study the cellular and molecular mechanisms that regulate axonal regeneration, neurons are often isolated in cell culture so that the factors that influence neurite outgrowth can be studied under controlled conditions. In our laboratory, we have developed a cell culture system in which neurite outgrowth of RS neurons can be studied (Hong et al., 2002; Ryan et al., 2004). Application of glutamate, an excitatory neurotransmitter, to the growth cones of RS neurons results in neurite retraction, presumably because of depolarization, calcium influx, and an increase in intracellular calcium. Intracellular calcium is thought to be one of the important regulators of the rate and direction of neurite outgrowth. Calcium influx could result from at least two different channels: chemically-gated channels (e.g. NMDA channels); or voltage-gated calcium channels. The purpose of the present study was to determine if calcium influx via voltage-gated calcium channels is sufficient to elicit neurite retraction. First, focal application of a 31 M potassium to growth cones of DiI-labeled RS neurons in culture to open voltage-gated calcium channels significantly reduced neurite growth rates, including neurite retraction, compared to pre-control periods. Second, 2 of Co++ or 300 M Cd++, which block calcium channels, abolished potassium-induced neurite retraction. In conclusion, the results suggest that calcium influx via voltage-gated calcium channels is sufficient to cause neurite retraction. Other experiments will determine if influx through voltage-gated channels is necessary for glutamate to elicit neurite outgrowth. Determination of the factors that regulate neurite outgrowth may provide information about the mechanism by which RS neurons regenerate their axons following spinal cord injury and restore locomotor function.Life Sciences Undergraduate Research Opportunity Progra

Evidence that glutamate induced neurite retraction of reticulospinal neurons is dependent on calcium influx

Abstract only availableLocomotor systems of vertebrates consist of a command system in the brain that activates central pattern generators in the spinal cord to initiate locomotor behavior. Reticulospinal (RS) neurons are the output neural elements of the command system. Following spinal cord injury, axons of RS neurons are severed and must regenerate to restore behavioral functions below the lesion. In higher vertebrates, such as birds and mammals, axonal regeneration is very limited, and spinal cord injury usually results in permanent paralysis below the lesion. In contrast, in the lamprey and a few other lower vertebrates, axonal regeneration is robust following spinal cord injury, and this results in virtually complete behavioral recovery. Therefore, identification of the mechanisms for axonal regeneration in lower vertebrates might provide information about the requirements for regenerating neurons in higher vertebrates. Examination of neurite outgrowth in culture is often used to identify the cellular and molecular mechanisms for axonal regeneration. In our laboratory, we have shown that application of glutamate, an excitatory neurotransmitter, to growth cones of RS neurons in culture causes neurite retraction, presumably by causing depolarization and calcium influx. Intracellular calcium levels are thought to be one of the important regulatory factors for neurite outgrowth. Glutamate might mediate calcium influx via at least two types of channels: chemically-gated channels (e.g. NMDA channels); or voltage-gated calcium channels. The purpose of the present study was to determine if calcium influx via voltage-gated channels is necessary for neurite retraction. The anatomical tracer DiI was applied to the spinal cord to pre-label RS neurons. Following transport, RS neurons were isolated and placed in cell culture. Glutamate was pressure ejected onto the growth cones of RS neurons in the presence of w-conotoxin MVIIC, which is a specific blocker for N and P voltage-gated calcium channels. Under these conditions, conotoxin reduced but did not block glutamate-induced neurite retraction. In conclusion, glutamate-induced neurite retraction of lamprey RS neurons probably is mediated by calcium influx via both chemically-gated and voltage-gated channels. Determination of the factors that regulate neurite outgrowth in culture may provide insights into the mechanisms for axonal regeneration and behavioral recovery following spinal cord injury in whole animals.Life Sciences Undergraduate Research Opportunity Progra

Decision Curve Analysis for Personalized Treatment Choice between Multiple Options.

BACKGROUND Decision curve analysis can be used to determine whether a personalized model for treatment benefit would lead to better clinical decisions. Decision curve analysis methods have been described to estimate treatment benefit using data from a single randomized controlled trial. OBJECTIVES Our main objective is to extend the decision curve analysis methodology to the scenario in which several treatment options exist and evidence about their effects comes from a set of trials, synthesized using network meta-analysis (NMA). METHODS We describe the steps needed to estimate the net benefit of a prediction model using evidence from studies synthesized in an NMA. We show how to compare personalized versus one-size-fit-all treatment decision-making strategies, such as "treat none" or "treat all patients with a specific treatment" strategies. First, threshold values for each included treatment need to be defined (i.e., the minimum risk difference compared with control that renders a treatment worth taking). The net benefit per strategy can then be plotted for a plausible range of threshold values to reveal the most clinically useful strategy. We applied our methodology to an NMA prediction model for relapsing-remitting multiple sclerosis, which can be used to choose between natalizumab, dimethyl fumarate, glatiramer acetate, and placebo. RESULTS We illustrated the extended decision curve analysis methodology using several threshold value combinations for each available treatment. For the examined threshold values, the "treat patients according to the prediction model" strategy performs either better than or close to the one-size-fit-all treatment strategies. However, even small differences may be important in clinical decision making. As the advantage of the personalized model was not consistent across all thresholds, improving the existing model (by including, for example, predictors that will increase discrimination) is needed before advocating its clinical usefulness. CONCLUSIONS This novel extension of decision curve analysis can be applied to NMA-based prediction models to evaluate their use to aid treatment decision making. HIGHLIGHTS Decision curve analysis is extended into a (network) meta-analysis framework.Personalized models predicting treatment benefit are evaluated when several treatment options are available and evidence about their effects comes from a set of trials.Detailed steps to compare personalized versus one-size-fit-all treatment decision-making strategies are outlined.This extension of decision curve analysis can be applied to (network) meta-analysis-based prediction models to evaluate their use to aid treatment decision making

Decision support system for proactive maintenance of earthworks assets

Introduction A key component of management of water resources lies in asset monitoring of the structures that contain water, e.g., dams and embankments. Earthworks failures can lead to disastrous consequences, including flooding, and can be very expensive to remediate. This paper presents a solution to assess the physical integrity of vulnerable earth structures (dams, embankments and cuttings) - thereby facilitating the shift from more costly responsive remediation of earthwork failures to early intervention. While current methods (including sophisticated automated procedures, sensors and SCADA systems) do provide some information regarding the health of the assets, they have a number of limitations: (1) the cost of deploying and maintaining these solutions; (2) the level of intrusiveness; (3) the need for experienced engineers validating measurements by visual inspection; (4) remoteness of many sites; and (5) low temporal resolution with limited scope for predictive approaches to asset failure. Methodology Early intervention and prevention requires identification of the incremental development of internal conditions that ultimately trigger failure. The low cost of the devices allows deployments of higher density, increasing spatial resolution and monitoring in real-time. This, unlike conventional approaches, allows better representation the soil heterogeneity both spatially and temporarily. To this end, we will present observations from our trials of automated resistivity, movement and pressure measurements. The developed sensor nodes operate at low voltages, integrates a range of analogue and digital sensors, using a single interface for measuring resistivity, pressure, motion pore pressure, and temperature, can be developed in compact form (currently 32.5cm high with diameter 14.5cm for prototyping), are non-intrusive to their compact nature and continually log data with no human intervention. We will also discuss the design aspects of the casing so that our electronic sensor nodes are robust to harsh conditions, including extreme temperatures, moisture, high voltages, and wildlife, when buried. Data is stored on a data collection hub, and due to remoteness of these sites, remote communications has been enabled through near white-space frequencies to highlight potential risks to the appropriate stakeholders in real-time. Results and conclusions This paper presents a unique, customized and cost-effective platform for automated monitoring of earthworks through prototyping a novel hardware/firmware solution in consultation with various stakeholders: (i) integration of analogue and digital sensors for measuring pressure and motion, (ii) resistivity board that is controlled by main board, (iii) variable and on-demand sampling rates that can be dynamically controlled, (iv) a prototype mechanical waterproof design for housing main board, resistivity board and relevant sensors. We show initial results for ground movement, pressure and resistivity. Resistivity results are as expected based on the literature for clay-type soil. We also observe noticeable ground movement variation with artificially induced disturbance. We conclude that it is possible, through trials at Scottish Canals assets at Falkirk Wheel, to accurately monitor multiple earthworks parameters simultaneously, continuously, in real-time and without human intervention, as well as communicate data remotely in real-time to enable prediction of the onset of earthworks failures

Evolved galaxies in high-density environments across 2.0≤z<4.22.0\leq z<4.2 using the ZFOURGE survey

To explore the role environment plays in influencing galaxy evolution at high redshifts, we study $2.0\leq z<4.2$ environments using the FourStar Galaxy Evolution (ZFOURGE) survey. Using galaxies from the COSMOS legacy field with ${\rm log(M_{*}/M_{\odot})}\geq9.5$, we use a seventh nearest neighbour density estimator to quantify galaxy environment, dividing this into bins of low, intermediate and high density. We discover new high density environment candidates across $2.0\leq z<2.4$ and $3.1\leq z<4.2$. We analyse the quiescent fraction, stellar mass and specific star formation rate (sSFR) of our galaxies to understand how these vary with redshift and environment. Our results reveal that, across $2.0\leq z<2.4$, the high density environments are the most significant regions, which consist of elevated quiescent fractions, ${\rm log(M_{*}/M_{\odot})}\geq10.2$ massive galaxies and suppressed star formation activity. At $3.1\leq z<4.2$, we find that high density regions consist of elevated stellar masses but require more complete samples of quiescent and sSFR data to study the effects of environment in more detail at these higher redshifts. Overall, our results suggest that well-evolved, passive galaxies are already in place in high density environments at $z\sim2.4$, and that the Butcher-Oemler effect and SFR-density relation may not reverse towards higher redshifts as previously thought.Comment: 11 pages, 5 figures, final version published in PAS