Geoenvironmental Site Characterization to Treatment: Lead Contaminated Firing Range Case Study

The methodologies employed and the results obtained during the performance of a comprehensive geoenvironmental site characterization case study are presented. The study demonstrates the need to integrate research tools from various disciplines including geotechnical, analytical and mineralogical specialties in order to develop a thorough understanding of both the nature and extent of the environmental issues associated with the site and the most viable alternatives for its remediation. Particle size distribution coupled with contaminant fractionation studies and mineralogical and micromorphological analyses were performed on the soil samples collected onsite to identify the metals present, their concentrations and the mechanisms of transformation. Lead fragments found in the soil samples were analyzed by means of X-ray diffraction (XRD) and scanning electron microscopy (SEM). Quantitative phase analysis studies showed that the fine soil fractions contained considerable amounts of lead carbonates, which owing to their colloidal nature could not be readily removed using gravitational methods. To mitigate this deficiency, a bench-scale chemical treatment experiment based on dissolution of the Pb was performed. Although the study is still in progress, the benefits derived from using the multi-disciplinary approach for site characterization described herein warrant consideration by others who may face similar challenges in the future

Stabilization and reuse of heavy metal contaminated soils by means of quicklime sulfate salt treatment. Final report, September 1992--February 1995

Capillary and hydraulic flows of water in porous media contaminated by heavy metal species often result in severe aquifer contamination. In the present study a chemical admixture stabilization approach is proposed, where heavy metal stabilization/immobilization is achieved by means of quicklime-based treatment. Both in-situ treatment by injection and on-site stabilization by excavation, mixing, and compaction will be investigated. In addition, the potential to reuse the resulting stabilized material as readily available construction material will also be investigated. The heavy metals under study include: arsenic, chromium, lead, and mercury. The proposed technical approach consists of three separate phases. During phase A, both artificial and naturally occurring contaminated soil mixes were treated, and then tested for stress-strain properties, leachability, micromorphology, mineralogical composition, permeability, setting time, and durability. In such a way, the effectiveness of the proposed remediation technology was verified, the treatment approach was optimized, and the underlying mechanisms responsible for stabilization were established. During phase B, the proposed technology will be tested for two DOE-site subscale systems, involving naturally occurring contaminated soil, using the same testing methodology as the one outlined for phase A. Provided that the proposed technology is proven effective for the subscale systems, a field application will be demonstrated. Again process quality monitoring will be performed by testing undisturbed samples collected from the treated sites, in the same fashion as for the previous phases. Following completion of the proposed study, a set of comprehensive guidelines for field applications will be developed. 42 refs., 196 figs., 26 tabs

Prosody-Based Automatic Segmentation of Speech into Sentences and Topics

A crucial step in processing speech audio data for information extraction, topic detection, or browsing/playback is to segment the input into sentence and topic units. Speech segmentation is challenging, since the cues typically present for segmenting text (headers, paragraphs, punctuation) are absent in spoken language. We investigate the use of prosody (information gleaned from the timing and melody of speech) for these tasks. Using decision tree and hidden Markov modeling techniques, we combine prosodic cues with word-based approaches, and evaluate performance on two speech corpora, Broadcast News and Switchboard. Results show that the prosodic model alone performs on par with, or better than, word-based statistical language models -- for both true and automatically recognized words in news speech. The prosodic model achieves comparable performance with significantly less training data, and requires no hand-labeling of prosodic events. Across tasks and corpora, we obtain a significant improvement over word-only models using a probabilistic combination of prosodic and lexical information. Inspection reveals that the prosodic models capture language-independent boundary indicators described in the literature. Finally, cue usage is task and corpus dependent. For example, pause and pitch features are highly informative for segmenting news speech, whereas pause, duration and word-based cues dominate for natural conversation.Comment: 30 pages, 9 figures. To appear in Speech Communication 32(1-2), Special Issue on Accessing Information in Spoken Audio, September 200

Behavior policy learning: Learning multi-stage tasks via solution sketches and model-based controllers

Multi-stage tasks are a challenge for reinforcement learning methods, and require either specific task knowledge (e.g., task segmentation) or big amount of interaction times to be learned. In this paper, we propose Behavior Policy Learning (BPL) that effectively combines 1) only few solution sketches, that is demonstrations without the actions, but only the states, 2) model-based controllers, and 3) simulations to effectively solve multi-stage tasks without strong knowledge about the underlying task. Our main intuition is that solution sketches alone can provide strong data for learning a high-level trajectory by imitation, and model-based controllers can be used to follow this trajectory (we call it behavior) effectively. Finally, we utilize robotic simulations to further improve the policy and make it robust in a Sim2Real style. We evaluate our method in simulation with a robotic manipulator that has to perform two tasks with variations: 1) grasp a box and place it in a basket, and 2) re-place a book on a different level within a bookcase. We also validate the Sim2Real capabilities of our method by performing real-world experiments and realistic simulated experiments where the objects are tracked through an RGB-D camera for the first task

Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech

We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speech-act-like units such as Statement, Question, Backchannel, Agreement, Disagreement, and Apology. Our model detects and predicts dialogue acts based on lexical, collocational, and prosodic cues, as well as on the discourse coherence of the dialogue act sequence. The dialogue model is based on treating the discourse structure of a conversation as a hidden Markov model and the individual dialogue acts as observations emanating from the model states. Constraints on the likely sequence of dialogue acts are modeled via a dialogue act n-gram. The statistical dialogue grammar is combined with word n-grams, decision trees, and neural networks modeling the idiosyncratic lexical and prosodic manifestations of each dialogue act. We develop a probabilistic integration of speech recognition with dialogue modeling, to improve both speech recognition and dialogue act classification accuracy. Models are trained and evaluated using a large hand-labeled database of 1,155 conversations from the Switchboard corpus of spontaneous human-to-human telephone speech. We achieved good dialogue act labeling accuracy (65% based on errorful, automatically recognized words and prosody, and 71% based on word transcripts, compared to a chance baseline accuracy of 35% and human accuracy of 84%) and a small reduction in word recognition error.Comment: 35 pages, 5 figures. Changes in copy editing (note title spelling changed

Study of lead levels in soils by weathering of metallic Pb bullets used in dove hunting in Córdoba, Argentina

A study of level of Pb in soils of the center-north of the Province of Córdoba, a worldwide recognized tourist region for dove hunting, was performed in this work. The native forest of the region has a great population of doves associated with the grainproductivefields of the surrounding. Contamination of soils due to hunting activities is regulated by national and local norms. The Córdoba Environmental Secretary by resolution no. 1115/2011 approved a new regulation that categorizes this activity as generator of Y31 (Pb) industrial waste. Lead from pellets alloy is deposited on the soil of the shootingfields. Samples were taken at depth of 50 mm from 315 pits referenced by GPS in accordance with local environmental authorities as well as the hunting outfitters companies. Sampling sites are distributed between parallels 31 °S (S31) up to 30 °S (S30) and between meridians W64 up to W63. Soils samples were analyzed by X-rayfluorescence spectroscopy while Pb bullets were analyzed by scanning electron microscopy (SEM) and X-ray diffraction (XRD). The average concentration obtained for Pb in dry soil sieved (200 mesh) was 80 ppm. Powder XRD patterns of crust material removed from the corroded surface of weathered bullets were obtained. Three Pb mineral compounds were identified by XRD analysis and also studied by optical microscopy and SEM.submittedVersionFil: Bonzi, Edgardo Venusto. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina.Fil: Rubio, Marcelo. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina.Fil: Rubio, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Rubio, Marcelo. Ministerio de Ciencia y Tecnología de la Provincia de Córdoba. Centro de Excelencia en Procesos y Productos de Córdoba; Argentina.Física Atómica, Molecular y Química (física de átomos y moléculas incluyendo colisión, interacción con radiación, resonancia magnética, Moessbauer Efecto.

Mineral phase analysis of deep-sea hydrothermal particulates by a Raman spectroscopy expert algorithm : toward autonomous in situ experimentation and exploration

Author Posting. © American Geophysical Union, 2009. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geochemistry Geophysics Geosystems 10 (2009): Q05T05, doi:10.1029/2008GC002314.This paper demonstrates that a Raman spectroscopy, point-counting technique can be used for phase analysis of minerals commonly found in deep-sea hydrothermal plumes, even for minerals with similar chemical compositions. It also presents our robust autonomous identification algorithm and spectral database, both of which were developed specifically for deep-sea hydrothermal studies. The Raman spectroscopy expert algorithm was developed and tested against multicomponent mixtures of minerals relevant to the deep-sea hydrothermal environment. It is intended for autonomous classification where many spectra must be examined with little or no human involvement to increase analytic precision, accuracy, and data volume or to enable in situ measurements and experimentation.Support for J.A.B. was provided through a RIDGE 2000 Postdoctoral Fellowship (NSF OCE-0550331)

Accelerated swell testing of artificial sulfate bearing lime stabilised cohesive soils

This paper reports on the physico-chemical response of two lime stabilised sulfate bearing artificial soils subject to the European Accelerated Volumetric Swell Test (EN13286-49). At various intervals during the test, a specimen was removed and subject to compositional and microstructural analysis. Ettringite was formed by both soils types, but with significant differences in crystal morphology. Ettringite crystals formed from kaolin based soils were very small, colloidal in size and tended to form on the surface of other particles. Conversely, those formed from montmorillonite were relatively large and typically formed away from the surface in the pore solution. It was concluded that the mechanism by which ettringite forms is determined by the hydroxide ion concentration in the pore solution and the fundamental structure of the bulk clay. In the kaolin soil, ettringite forms by a topochemical mechanism and expands by crystal swelling. In the montmorillonite soil, it forms by a through-solution mechanism and crystal growth