Detection and Characterization of Preferential Flow Paths in the Downstream Area of a Hazardous Landfill

We have used surface-based electrical resistivity tomography to detect and characterize preferential hydraulic pathways in the immediate downstream area of an abandoned, hazardous landfill. The landfill occupies the void left by a former gravel pit and its base is close to the groundwater table and lacking an engineered barrier. As such, this site is remarkably typical of many small- to medium-sized waste deposits throughout the densely populated and heavily industrialized foreland on both sides of the Alpine arc. Outflows of pollutants lastingly contaminated local drinking water supplies and necessitated a partial remediation in the form of a synthetic cover barrier, which is meant to prevent meteoric water from percolating through the waste before reaching the groundwater table. Any future additional isolation of the landfill in the form of lateral barriers thus requires adequate knowledge of potential preferential hydraulic pathways for outflowing contaminants. Our results, inferred from a suite of tomographically inverted surfaced-based electrical resistivity profiles oriented roughly perpendicular to the local hydraulic gradient, indicate that potential contaminant outflows would predominantly occur along an unexploited lateral extension of the original gravel deposit. This finds its expression as a distinct and laterally continuous high-resistivity anomaly in the resistivity tomograms. This interpretation is ground-truthed through a litholog from a nearby well. Since the probed glacio-fluvial deposits are largely devoid of mineralogical clay, the geometry of hydraulic and electrical pathways across the pore space of a given lithological unit can be assumed to be identical, which allows for an order-of-magnitude estimation of the overall permeability structure. These estimates indicate that the permeability of the imaged extension of the gravel body is at least two to three orders-of-magnitude higher than that of its finer-grained embedding matrix. This corroborates the preeminent role of the high-resistivity anomaly as a potential preferential flow path.

Neutron structure of type-III antifreeze protein allows the reconstruction of AFP-ice interface.

Antifreeze proteins (AFPs) inhibit ice growth at sub-zero temperatures. The prototypical type-III AFPs have been extensively studied, notably by X-ray crystallography, solid-state and solution NMR, and mutagenesis, leading to the identification of a compound ice-binding surface (IBS) composed of two adjacent ice-binding sections, each which binds to particular lattice planes of ice crystals, poisoning their growth. This surface, including many hydrophobic and some hydrophilic residues, has been extensively used to model the interaction of AFP with ice. Experimentally observed water molecules facing the IBS have been used in an attempt to validate these models. However, these trials have been hindered by the limited capability of X-ray crystallography to reliably identify all water molecules of the hydration layer. Due to the strong diffraction signal from both the oxygen and deuterium atoms, neutron diffraction provides a more effective way to determine the water molecule positions (as D(2) O). Here we report the successful structure determination at 293 K of fully perdeuterated type-III AFP by joint X-ray and neutron diffraction providing a very detailed description of the protein and its solvent structure. X-ray data were collected to a resolution of 1.05 Å, and neutron Laue data to a resolution of 1.85 Å with a "radically small" crystal volume of 0.13 mm(3). The identification of a tetrahedral water cluster in nuclear scattering density maps has allowed the reconstruction of the IBS-bound ice crystal primary prismatic face. Analysis of the interactions between the IBS and the bound ice crystal primary prismatic face indicates the role of the hydrophobic residues, which are found to bind inside the holes of the ice surface, thus explaining the specificity of AFPs for ice versus water.

Seizure detection with automated EEG analysis: a validation study focusing on periodic patterns.

OBJECTIVE: To evaluate an automated seizure detection (ASD) algorithm in EEGs with periodic and other challenging patterns. METHODS: Selected EEGs recorded in patients over 1year old were classified into four groups: A. Periodic lateralized epileptiform discharges (PLEDs) with intermixed electrical seizures. B. PLEDs without seizures. C. Electrical seizures and no PLEDs. D. No PLEDs or seizures. Recordings were analyzed by the Persyst P12 software, and compared to the raw EEG, interpreted by two experienced neurophysiologists; Positive percent agreement (PPA) and false-positive rates/hour (FPR) were calculated. RESULTS: We assessed 98 recordings (Group A=21 patients; B=29, C=17, D=31). Total duration was 82.7h (median: 1h); containing 268 seizures. The software detected 204 (=76.1%) seizures; all ictal events were captured in 29/38 (76.3%) patients; in only in 3 (7.7%) no seizures were detected. Median PPA was 100% (range 0-100; interquartile range 50-100), and the median FPR 0/h (range 0-75.8; interquartile range 0-4.5); however, lower performances were seen in the groups containing periodic discharges. CONCLUSION: This analysis provides data regarding the yield of the ASD in a particularly difficult subset of EEG recordings, showing that periodic discharges may bias the results. SIGNIFICANCE: Ongoing refinements in this technique might enhance its utility and lead to a more extensive application.