Flume testing of underwater seep detection using temperature sensing on or just below the surface of sand or gravel sediments

Temperature anomalies can identify locations of seeps of groundwater into surface waters. However, the method’s sensitivity to details such as thermometer burial depth, sediment material, seep velocity, and surface water current are largely unknown. We report on a series of laboratory flume experiments in which controlled seeps under variable sediment texture, surface currents, burial depth, and temperature differentials were imposed. The focus of the study is temperature effects at the sediment surface to a few centimeters below the sediment surface, as these locations are of particular interest when using fiber-optic distributed temperature sensors (DTS). The data demonstrate: (1) without surface water flow, seep-related thermal anomalies were apparent in all cases, i.e., the method is feasible in such cases; (2) probe burial is helpful for fine sediment although not effective with coarse bed sediment, i.e., the method is strongly sensitive to sediment properties; (3) placing a thin rubber sheet over an unburied thermal probe increases detection of seeps in some circumstances, but not in others, and is generally not as robust as probe burial; and (4) local surface flow velocity, details of probe position and depth, and seepage velocity all influence observed temperature anomalies, limiting the opportunity to quantify seepage velocity, particularly with unburied temperature sensors. Overall, these findings suggest optimal installation would be at a well-defined depth within fine sediment, that installation in gravel and coarser sediment is not suited to the method if there are any significant surface currents, and that more data would be required to obtain accurate estimates of seepage velocity, though a single sensor may be sufficient to identify the location of seepage.Keywords: Temperature, Gravel, Sand, Flow, Sediment, Seepag

Who Does Better with a Big Interface? Improving Voting Performance of Reading for Disabled Voters

This study shows how ballot interfaces variably affect the voting performance of people with different abilities. An interface with all information viewable simultaneously might either help orient or overwhelm a voter, depending on he/her skill-set. Voters with diagnosed reading disabilities performed significantly better on full-faced voting machines than those who demonstrated a high likelihood of similar, but undiagnosed, disabilities. In contrast, the diagnosed group performed worse than others when using standard-sized Direct Recording Electronic (DRE) systems. We suspect that this observed difference in performance is due to the interaction of system features with learned coping techniques, which allow diagnosed reading disabled voters to function effectively in other parts of everyday life. The full-faced system provides a means of orienting but not of guiding the voter, while the standard DRE guides the users through the voting process without giving the voter a means of orienting themselves. A hybrid design that incorporates the advantages of both these systems might be beneficial for both reading disabled and non-reading disabled voters

Active-distributed temperature sensing to continuously quantify vertical flow in boreholes

We show how a distributed borehole flowmeter can be created from armored Fiber Optic cables with the Active-Distributed Temperature Sensing (A-DTS) method. The principle is that in a flowing fluid, the difference in temperature between a heated and unheated cable is a function of the fluid velocity. We outline the physical basis of the methodology and report on the deployment of a prototype A-DTS flowmeter in a fractured rock aquifer. With this design, an increase in flow velocity from 0.01 to 0.3 m s−1 elicited a 2.5°C cooling effect. It is envisaged that with further development this method will have applications where point measurements of borehole vertical flow do not fully capture combined spatiotemporal dynamics

Automatic covariate selection in logistic models for chest pain diagnosis: A new approach

A newly established method for optimizing logistic models via a minorization-majorization procedure is applied to the problem of diagnosing acute coronary syndromes (ACS). The method provides a principled approach to the selection of covariates which would otherwise require the use of a suboptimal method owing to the size of the covariate set. A strategy for building models is proposed and two models optimized for performance and for simplicity are derived via ten-fold cross-validation. These models confirm that a relatively small set of covariates including clinical and electrocardiographic features can be used successfully in this task. The performance of the models is comparable with previously published models using less principled selection methods. The models prove to be portable when tested on data gathered from three other sites. Whilst diagnostic accuracy and calibration diminishes slightly for these new settings, it remains satisfactory overall. The prospect of building predictive models that are as simple as possible for a required level of performance is valuable if data-driven decision aids are to gain wide acceptance in the clinical situation owing to the need to minimize the time taken to gather and enter data at the bedside

Probabilistic classification of acute myocardial infarction from multiple cardiac markers

Logistic regression and Gaussian mixture model (GMM) classifiers have been trained to estimate the probability of acute myocardial infarction (AMI) in patients based upon the concentrations of a panel of cardiac markers. The panel consists of two new markers, fatty acid binding protein (FABP) and glycogen phosphorylase BB (GPBB), in addition to the traditional cardiac troponin I (cTnI), creatine kinase MB (CKMB) and myoglobin. The effect of using principal component analysis (PCA) and Fisher discriminant analysis (FDA) to preprocess the marker concentrations was also investigated. The need for classifiers to give an accurate estimate of the probability of AMI is argued and three categories of performance measure are described, namely discriminatory ability, sharpness, and reliability. Numerical performance measures for each category are given and applied. The optimum classifier, based solely upon the samples take on admission, was the logistic regression classifier using FDA preprocessing. This gave an accuracy of 0.85 (95% confidence interval: 0.78–0.91) and a normalised Brier score of 0.89. When samples at both admission and a further time, 1–6 h later, were included, the performance increased significantly, showing that logistic regression classifiers can indeed use the information from the five cardiac markers to accurately and reliably estimate the probability AMI

Thermal-Plume fibre Optic Tracking (T-POT) test for flow velocity measurement in groundwater boreholes

International audienceWe develop an approach for measuring in-well fluid velocities using point electrical heating combined with spatially and temporally continuous temperature monitoring using Distributed Temperature Sensing (DTS). The method uses a point heater to warm a discrete volume of water. The rate of advection of this plume, once the heating is stopped, equates to the average flow velocity in the well. We conducted Thermal-Plume fibre Optic Tracking (T-POT) tests in a borehole in a fractured rock aquifer with the heater at the same depth and multiple pumping rates. Tracking of the thermal plume peak allowed the spatially varying velocity to be estimated up to 50 m downstream from the heating point, depending on the pumping rate. The T-POT technique can be used to estimate the velocity throughout long intervals provided that thermal dilution due to inflows, dispersion, or cooling by conduction do not render the thermal pulse unresolvable with DTS. A complete flow log may be obtained by deploying the heater at multiple depths, or with multiple point heaters

Comparison of Time Domain Reflectometry Performance Factors for Several Dielectric Geometries: Theory and Experiments

We propose three nontraditional dielectric geometries and present an experimental and theoretical analysis and comparison of time domain reflectometry (TDR) performances for them. The traditional geometry (the probes inserted in material of essentially infinite extent) is compared to three nontraditional geometries where the probes are affixed outside of a core sample, inside of a bore, or flat on the surface of a semi‐infinite solid. Our derivation relates the velocity of electromagnetic wave propagation to the complex permittivities and permeabilities of the media and the geometry for the three nontraditional configurations. Experimental results for air, styrofoam, dry sand, wet sand of varying water content, nylon, dry wood, and ferromagnetic steel are obtained for the three proposed configurations and are in fair agreement with the literature within the experimental uncertainties. Through experiments and theoretical analysis, the TDR performance is found to be the same within the experimental uncertainties for the three nontraditional geometries. The proposed geometries yield slightly lower sensitivities compared to the traditional geometry. Advantages and disadvantages of the geometries compared to the traditional geometry are also discussed

A Cytosine Methyltransferase Homologue Is Essential for Sexual Development in Aspergillus nidulans

Background: The genome defense processes RIP (repeat-induced point mutation) in the filamentous fungus Neurospora crassa, and MIP (methylation induced premeiotically) in the fungus Ascobolus immersus depend on proteins with DNA methyltransferase (DMT) domains. Nevertheless, these proteins, RID and Masc1, respectively, have not been demonstrated to have DMT activity. We discovered a close homologue in Aspergillus nidulans, a fungus thought to have no methylation and no genome defense system comparable to RIP or MIP. Principal Findings: We report the cloning and characterization of the DNA methyltransferase homologue A (dmtA) gene from Aspergillus nidulans. We found that the dmtA locus encodes both a sense (dmtA) and an anti-sense transcript (tmdA). Both transcripts are expressed in vegetative, conidial and sexual tissues. We determined that dmtA, but not tmdA, is required for early sexual development and formation of viable ascospores. We also tested if DNA methylation accumulated in any of the dmtA/tmdA mutants we constructed, and found that in both asexual and sexual tissues, these mutants, just like wild-type strains, appear devoid of DNA methylation. Conclusions/Significance: Our results demonstrate that a DMT homologue closely related to proteins implicated in RIP and MIP has an essential developmental function in a fungus that appears to lack both DNA methylation and RIP or MIP. It remains formally possible that DmtA is a bona fide DMT, responsible for trace, undetected DNA methylation that i

RIPCAL: a tool for alignment-based analysis of repeat-induced point mutations in fungal genomic sequences

Background Repeat-induced point mutation (RIP) is a fungal-specific genome defence mechanism that alters the sequences of repetitive DNA, thereby inactivating coding genes. Repeated DNA sequences align between mating and meiosis and both sequences undergo C:G to T:A transitions. In most fungi these transitions preferentially affect CpA di-nucleotides thus altering the frequency of certain di-nucleotides in the affected sequences. The majority of previously published in silico analyses were limited to the comparison of ratios of pre- and post-RIP di-nucleotides in putatively RIP-affected sequences – so-called RIP indices. The analysis of RIP is significantly more informative when comparing sequence alignments of repeated sequences. There is, however, a dearth of bioinformatics tools available to the fungal research community for alignment-based RIP analysis of repeat families. Results We present RIPCAL http://www.sourceforge.net/projects/ripcal, a software tool for the automated analysis of RIP in fungal genomic DNA repeats, which performs both RIP index and alignment-based analyses. We demonstrate the ability of RIPCAL to detect RIP within known RIP-affected sequences of Neurospora crassa and other fungi. We also predict and delineate the presence of RIP in the genome of Stagonospora nodorum – a Dothideomycete pathogen of wheat. We show that RIP has affected different members of the S. nodorum rDNA tandem repeat to different extents depending on their genomic contexts. Conclusion The RIPCAL alignment-based method has considerable advantages over RIP indices for the analysis of whole genomes. We demonstrate its application to the recently published genome assembly of S. nodorum

Distributed temperature sensing as a down-hole tool in hydrogeology

Distributed Temperature Sensing (DTS) technology enables down-hole temperature monitoring to study hydrogeological processes at unprecedentedly high frequency and spatial resolution. DTS has been widely applied in passive mode in site investigations of groundwater flow, in-well flow, and subsurface thermal property estimation. However, recent years have seen the further development of the use of DTS in an active mode (A-DTS) for which heat sources are deployed. A suite of recent studies using A-DTS down-hole in hydrogeological investigations illustrate the wide range of different approaches and creativity in designing methodologies. The purpose of this review is to outline and discuss the various applications and limitations of DTS in down-hole investigations for hydrogeological conditions and aquifer geological properties. To this end, we first review examples where passive DTS has been used to study hydrogeology via down-hole applications. Secondly, we discuss and categorize current A-DTS borehole methods into three types. These are thermal advection tests, hybrid cable flow logging, and heat pulse tests. We explore the various options with regards to cable installation, heating approach, duration, and spatial extent in order to improve their applicability in a range of settings. These determine the extent to which each method is sensitive to thermal properties, vertical in well flow, or natural gradient flow. Our review confirms that the application of DTS has significant advantages over discrete point temperature measurements, particularly in deep wells, and highlights the potential for further method developments in conjunction with other emerging fiber optic based sensors such as Distributed Acoustic Sensing. This article is protected by copyright. All rights reserved