Focused time-lapse inversion of radio and audio magnetotelluric data

Geoelectrical techniques are widely used to monitor groundwater processes, while surprisingly few studies have considered audio (AMT) and radio (RMT) magnetotellurics for such purposes. In this numerical investigation, we analyze to what extent inversion results based on AMT and RMT monitoring data can be improved by (1) time-lapse difference inversion; (2) incorporation of statistical information about the expected model update (i.e., the model regularization is based on a geostatistical model); (3) using alternative model norms to quantify temporal changes (i.e., approximations of l(1) and Cauchy norms using iteratively reweighted least-squares), (4) constraining model updates to predefined ranges (i.e., using Lagrange Multipliers to only allow either increases or decreases of electrical resistivity with respect to background conditions). To do so, we consider a simple illustrative model and a more realistic test case related to seawater intrusion. The results are encouraging and show significant improvements when using time-lapse difference inversion with non l(2) model norms. Artifacts that may arise when imposing compactness of regions with temporal changes can be suppressed through inequality constraints to yield models without oscillations outside the true region of temporal changes. Based on these results, we recommend approximate l(1)-norm solutions as they can resolve both sharp and smooth interfaces within the same model. (C) 2012 Elsevier B.V. All rights reserved.

Imaging and quantifying salt-tracer transport in a riparian groundwater system by means of 3D ERT monitoring

Determining groundwater flow paths of infiltrated river water is necessary for studying biochemical processes in the riparian zone, but their characterization is complicated by strong temporal and spatial heterogeneity. We investigated to what extent repeat 3D surface electrical resistance tomography (ERT) can be used to monitor transport of a salt-tracer plume under close to natural gradient conditions. The aim is to estimate groundwater flow velocities and pathways at a site located within a riparian groundwater system adjacent to the perialpine Thur River in northeastern Switzerland. Our ERT time-lapse images provide constraints on the plume's shape, flow direction, and velocity. These images allow the movement of the plume to be followed for 35 m. Although the hydraulic gradient is only 1.43 parts per thousand, the ERT time-lapse images demonstrate that the plume's center of mass and its front propagate with velocities of 2x10(-4) m/s and 5x10(-4) m/s, respectively. These velocities are compatible with groundwater resistivity monitoring data in two observation wells 5 m from the injection well. Five additional sensors in the 5-30 m distance range did not detect the plume. Comparison of the ERT time-lapse images with a groundwater transport model and time-lapse inversions of synthetic ERT data indicate that the movement of the plume can be described for the first 6 h after injection by a uniform transport model. Subsurface heterogeneity causes a change of the plume's direction and velocity at later times. Our results demonstrate the effectiveness of using time-lapse 3D surface ERT to monitor flow pathways in a challenging perialpine environment over larger scales than is practically possible with crosshole 3D ERT.

Effect of groundwater composition on arsenic detection by bacterial biosensors.

A luminescent bacterial biosensor was used to quantify bioavailable arsenic in artificial groundwater. Its light production above the background emission was proportional to the arsenite concentration in the toxicologically relevant range of 0 to 0.5 mu M. Effects of the inorganic solutes phosphate, Fe(II) and silicate on the biosensor signal were studied. Phosphate at a concentration of 0.25 g L-1 phosphate slightly stimulated the light emission, but much less than toxicologically relevant concentrations of the much stronger inducer arsenite. No effect of phosphate was oberved in the presence of arsenite. Freshly prepared sodium silicate solution at a concentration of 10 g L-1 Si reduced the arsenite-induced light production by roughly 37%, which can be explained by transient polymerization leading to sequestration of some arsenic. After three days of incubation, silicate did not have this effect anymore, probably because depolymerization occurred. In the presence of 0.4 g L-1 Fe(II), the arsenite-induced light emission was reduced by up to 90%, probably due to iron oxidation followed by arsenite adsorption on the less soluble Fe(III) possibly along with some oxidation to the stronger adsorbing As(V). Addition of 100 mu M EDTA was capable of releasing all arsenic from the precipitate and to transform it into the biologically measurable, dissolved state. The biosensor also proved valuable for monitoring the effectiveness of an arsenic removal procedure based on water filtration through a mixture of sand and iron granules.

Field testing of arsenic in groundwater samples of Bangladesh using a test kit based on lyophilized bioreporter bacteria.

A test kit based on living, lyophilized bacterial bioreporters emitting bioluminescence as a response to arsenite and arsenate was applied during a field campaign in six villages across Bangladesh. Bioreporter field measurements of arsenic in groundwater from tube wells were in satisfying agreement with the results of spectroscopic analyses of the same samples conducted in the lab. The practicability of the bioreporter test in terms of logistics and material requirements, suitability for high sample throughput, and waste disposal was much better than that of two commercial chemical test kits that were included as references. The campaigns furthermore demonstrated large local heterogeneity of arsenic in groundwater, underscoring the use of well switching as an effective remedy to avoid high arsenic exposure.

Bacterial bioassay for rapid and accurate analysis of arsenic in highly variable groundwater samples.

In this study, we report the first ever large-scale environmental validation of a microbial reporter-based test to measure arsenic concentrations in natural water resources. A bioluminescence-producing arsenic-inducible bacterium based on Escherichia coli was used as the reporter organism. Specific protocols were developed with the goal to avoid the negative influence of iron in groundwater on arsenic availability to the bioreporter cells. A total of 194 groundwater samples were collected in the Red River and Mekong River Delta regions of Vietnam and were analyzed both by atomic absorption spectroscopy (AAS) and by the arsenic bioreporter protocol. The bacterial cells performed well at and above arsenic concentrations in groundwater of 7 microg/L, with an almost linearly proportional increase of the bioluminescence signal between 10 and 100 microg As/L (r2 = 0.997). Comparisons between AAS and arsenic bioreporter determinations gave an overall average of 8.0% false negative and 2.4% false positive identifications for the bioreporter prediction at the WHO recommended acceptable arsenic concentration of 10 microg/L, which is far betterthan the performance of chemical field test kits. Because of the ease of the measurement protocol and the low application cost, the microbiological arsenic test has a great potential in large screening campaigns in Asia and in other areas suffering from arsenic pollution in groundwater resources.

Estimating traveltimes and groundwater flow patterns using 3D time-lapse crosshole ERT imaging of electrical resistivity fluctuations induced by infiltrating river water

The infiltration of river water into aquifers is of high relevance to drinking-water production and is a key driver of biogeochemical processes in the hyporheic and riparian zone, but the distribution and quantification of the infiltrating water are difficult to determine using conventional hydrological methods (e.g., borehole logging and tracer tests). By time-lapse inverting crosshole ERT (electrical resistivity tomography) monitoring data, we imaged groundwater flow patterns driven by river water infiltrating a perialpine gravel aquifer in northeastern Switzerland. This was possible because the electrical resistivity of the infiltrating water changed during rainfall-runoff events. Our time-lapse resistivity models indicated rather complex flow patterns as a result of spatially heterogeneous bank filtration and aquifer heterogeneity. The upper part of the aquifer was most affected by the river infiltrate, and the highest groundwater velocities and possible preferential flow occurred at shallow to intermediate depths. Time series of the reconstructed resistivity models matched groundwater electrical resistivity data recorded on borehole loggers in the upper and middle parts of the aquifer, whereas the resistivity models displayed smaller variations and delayed responses with respect to the logging data. in the lower part. This study demonstrated that crosshole ERT monitoring of natural electrical resistivity variations of river infiltrate could be used to image and quantify 3D bank filtration and aquifer dynamics at a high spatial resolution.

Bioluminescent sensor proteins for point-of-care therapeutic drug monitoring.

For many drugs, finding the balance between efficacy and toxicity requires monitoring their concentrations in the patient's blood. Quantifying drug levels at the bedside or at home would have advantages in terms of therapeutic outcome and convenience, but current techniques require the setting of a diagnostic laboratory. We have developed semisynthetic bioluminescent sensors that permit precise measurements of drug concentrations in patient samples by spotting minimal volumes on paper and recording the signal using a simple point-and-shoot camera. Our sensors have a modular design consisting of a protein-based and a synthetic part and can be engineered to selectively recognize a wide range of drugs, including immunosuppressants, antiepileptics, anticancer agents and antiarrhythmics. This low-cost point-of-care method could make therapies safer, increase the convenience of doctors and patients and make therapeutic drug monitoring available in regions with poor infrastructure.

Ambulatory blood pressure monitoring in adolescent untreated hypertensive patients.

Ambulatory blood pressure profiles were obtained with the portable semi-automatic blood pressure recorder Remler M2000 in groups of 20 adolescents, 20 young and 20 middle-aged adults and 20 elderly untreated patients, all considered by their physician to be hypertensive. It was found that adolescents who are hypertensive when seeing their physician are more often normotensive outside the physician's office than adult and elderly patients under similar conditions. The increased heart rate variability which was detected in adolescents was not associated with an enhanced blood pressure variability.

Electronic compliance monitoring in resistant hypertension: the basis for rational therapeutic decisions.

OBJECTIVE: Incomplete compliance is one of several possible causes of uncontrolled hypertension. Yet, non-compliance remains largely unrecognized and is falsely interpreted as treatment resistance, because it is difficult to confirm or exclude objectively. The goal of this study was to evaluate the potential benefits of electronic monitoring of drug compliance in the management of patients with resistant hypertension. METHODS: Forty-one hypertensive patients resistant to a three-drug regimen (average blood pressure 156/ 106 +/- 23/11 mmHg, mean +/- SD) were studied prospectively. They were informed that for the next 2 months, their presently prescribed drugs would be provided in electronic monitors, without any change in treatment, so as to provide the treating physician with a measure of their compliance. Thereafter, patients were offered the possibility of prolonging the monitoring of compliance for another 2 month period, during which treatment was adapted if necessary. RESULTS: Monitoring of compliance alone was associated with a significant improvement of blood pressure at 2 months (145/97 +/- 20/15 mmHg, P < 0.01). During monitoring, blood pressure was normalized (systolic < 140 mmHg or diastolic < 90 mmHg) in one-third of the patients and insufficient compliance was unmasked in another 20%. When analysed according to tertiles of compliance, patients with the lowest compliance exhibited significantly higher achieved diastolic blood pressures (P = 0.04). In 30 patients, compliance was monitored up to 4 months and drug therapy was adapted whenever necessary. In these patients, a further significant decrease in blood pressure was obtained (from 150/100 +/- 18/15 to 143/94 +/- 22/11 mmHg, P = 0.04/0.02). CONCLUSIONS: These results suggest that objective monitoring of compliance using electronic devices may be a useful step in the management of patients with refractory hypertension, as it enables physicians to take rational decisions based on reliable and objective data of drug compliance and hence to improve blood pressure control.

Using active learning for monitoring networks design: The example of wind power plants sites evaluation

Locating new wind farms is of crucial importance for energy policies of the next decade. To select the new location, an accurate picture of the wind fields is necessary. However, characterizing wind fields is a difficult task, since the phenomenon is highly nonlinear and related to complex topographical features. In this paper, we propose both a nonparametric model to estimate wind speed at different time instants and a procedure to discover underrepresented topographic conditions, where new measuring stations could be added. Compared to space filling techniques, this last approach privileges optimization of the output space, thus locating new potential measuring sites through the uncertainty of the model itself.

Benchmarking therapeutic drug monitoring software: A review of available computer tools

Therapeutic drug monitoring (TDM) aims to optimize treatments by individualizing dosage regimens based on the measurement of blood concentrations. Dosage individualization to maintain concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculations currently represent the gold standard TDM approach but require computation assistance. In recent decades computer programs have been developed to assist clinicians in this assignment. The aim of this survey was to assess and compare computer tools designed to support TDM clinical activities. The literature and the Internet were searched to identify software. All programs were tested on personal computers. Each program was scored against a standardized grid covering pharmacokinetic relevance, user friendliness, computing aspects, interfacing and storage. A weighting factor was applied to each criterion of the grid to account for its relative importance. To assess the robustness of the software, six representative clinical vignettes were processed through each of them. Altogether, 12 software tools were identified, tested and ranked, representing a comprehensive review of the available software. Numbers of drugs handled by the software vary widely (from two to 180), and eight programs offer users the possibility of adding new drug models based on population pharmacokinetic analyses. Bayesian computation to predict dosage adaptation from blood concentration (a posteriori adjustment) is performed by ten tools, while nine are also able to propose a priori dosage regimens, based only on individual patient covariates such as age, sex and bodyweight. Among those applying Bayesian calculation, MM-USC*PACK© uses the non-parametric approach. The top two programs emerging from this benchmark were MwPharm© and TCIWorks. Most other programs evaluated had good potential while being less sophisticated or less user friendly. Programs vary in complexity and might not fit all healthcare settings. Each software tool must therefore be regarded with respect to the individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Computer-assisted TDM is gaining growing interest and should further improve, especially in terms of information system interfacing, user friendliness, data storage capability and report generation.

Diagnostic yield of short-term video-EEG monitoring for epilepsy and PNESs: a European assessment.

INTRODUCTION: Although long-term video-EEG monitoring (LVEM) is routinely used to investigate paroxysmal events, short-term video-EEG monitoring (SVEM) lasting <24 h is increasingly recognized as a cost-effective tool. Since, however, relatively few studies addressed the yield of SVEM among different diagnostic groups, we undertook the present study to investigate this aspect. METHODS: We retrospectively analyzed 226 consecutive SVEM recordings over 6 years. All patients were referred because routine EEGs were inconclusive. Patients were classified into 3 suspected diagnostic groups: (1) group with epileptic seizures, (2) group with psychogenic nonepileptic seizures (PNESs), and (3) group with other or undetermined diagnoses. We assessed recording lengths, interictal epileptiform discharges, epileptic seizures, PNESs, and the definitive diagnoses obtained after SVEM. RESULTS: The mean age was 34 (±18.7) years, and the median recording length was 18.6 h. Among the 226 patients, 127 referred for suspected epilepsy - 73 had a diagnosis of epilepsy, none had a diagnosis of PNESs, and 54 had other or undetermined diagnoses post-SVEM. Of the 24 patients with pre-SVEM suspected PNESs, 1 had epilepsy, 12 had PNESs, and 11 had other or undetermined diagnoses. Of the 75 patients with other diagnoses pre-SVEM, 17 had epilepsy, 11 had PNESs, and 47 had other or undetermined diagnoses. After SVEM, 15 patients had definite diagnoses other than epilepsy or PNESs, while in 96 patients, diagnosis remained unclear. Overall, a definitive diagnosis could be reached in 129/226 (57%) patients. CONCLUSIONS: This study demonstrates that in nearly 3/5 patients without a definitive diagnosis after routine EEG, SVEM allowed us to reach a diagnosis. This procedure should be encouraged in this setting, given its time-effectiveness compared with LVEM.

How reliable is the monitoring of permanent vegetation plots? A test with multiple observers

Questions: A multiple plot design was developed for permanent vegetation plots. How reliable are the different methods used in this design and which changes can we measure? Location: Alpine meadows (2430 m a.s.l.) in the Swiss Alps. Methods: Four inventories were obtained from 40 m(2) plots: four subplots (0.4 m(2)) with a list of species, two 10m transects with the point method (50 points on each), one subplot (4 m2) with a list of species and visual cover estimates as a percentage and the complete plot (40 m(2)) with a list of species and visual estimates in classes. This design was tested by five to seven experienced botanists in three plots. Results: Whatever the sampling size, only 45-63% of the species were seen by all the observers. However, the majority of the overlooked species had cover < 0.1%. Pairs of observers overlooked 10-20% less species than single observers. The point method was the best method for cover estimate, but it took much longer than visual cover estimates, and 100 points allowed for the monitoring of only a very limited number of species. The visual estimate as a percentage was more precise than classes. Working in pairs did not improve the estimates, but one botanist repeating the survey is more reliable than a succession of different observers. Conclusion: Lists of species are insufficient for monitoring. It is necessary to add cover estimates to allow for subsequent interpretations in spite of the overlooked species. The choice of the method depends on the available resources: the point method is time consuming but gives precise data for a limited number of species, while visual estimates are quick but allow for recording only large changes in cover. Constant pairs of observers improve the reliability of the records.