Screening Level Risk Assessment of Heavy Metal Contamination in Cleveland Area Commons

Commons are public lands that are often used for recreational activities and are generally assumed to be free of soil contamination. However, in old industrial cities, urban commons may have accumulated heavy metal burdens from airborne contamination. This paper examines the heavy metal burdens and risk analysis results for 50 commons in the greater Cleveland, Ohio area. The U.S. Environmental Protection Agency Method 3050B and 1N HCl soil extraction results are presented for Cd, Cr, Cu, Ni, Pb, and Zn mass burdens, and are interpreted relative to Ohio residential soil guidance and “typical” values from the remediation guidance of 30 states. Results demonstrate that most of these soils have heavy metal burdens that are well above naturally occurring levels, and several (at least 8 of the 50 sites tested) have heavy metal burdens that exceed Ohio’s residential soil contamination guidance. Lead and cadmium were found to be the most significant contributors to site hazard index values.     

Reputation Formalization for an Information–Sharing Multi–Agent System

We propose that through the formalization of concepts related to trust, a more accurate model of trust can be implemented. This paper presents a new model of trust that is based on the formalization of reputation. A multidisciplinary approach is taken to understanding the nature of trust and its relation to reputation. Through this approach, a practical definition of reputation is adopted from sociological contexts and a model of reputation is designed and presented.
Reputation is defined as role fulfillment. To formalize reputation, it is necessary to formalize the expectations placed upon an agent within a particular multi–agent system (MAS). In this case, the agents are part of an information–sharing society. Five roles are defined along with the ways in which these roles are objectively fulfilled. Through the measurement of role fulfillment, a vector representing reputation can be developed. This vector embodies the magnitude of the reputation and describes the patterns of behavior associated with the direction of the vector.
Experiments are conducted to verify the sensibility of the proposed models for role fulfillment and overall reputation. The simulation results show that the roles, defined for building reputation in an information–sharing MAS environment, react to different agent and user actions in a manner consistent with the formal definitions.     

The ACODEA framework: Developing segmentation and classification schemes for fully automatic analysis of online discussions

Research related to online discussions frequently faces the problem of analyzing huge corpora. Natural Language Processing (NLP) technologies may allow automating this analysis. However, the state-of-the-art in machine learning and text mining approaches yields models that do not transfer well between corpora related to different topics. Also, segmenting is a necessary step, but frequently, trained models are very sensitive to the particulars of the segmentation that was used when the model was trained. Therefore, in prior published research on text classification in a CSCL context, the data was segmented by hand. We discuss work towards overcoming these challenges. We present a framework for developing coding schemes optimized for automatic segmentation and context-independent coding that builds on this segmentation. The key idea is to extract the semantic and syntactic features of each single word by using the techniques of part-of-speech tagging and named-entity recognition before the raw data can be segmented and classified. Our results show that the coding on the micro-argumentation dimension can be fully automated. Finally, we discuss how fully automated analysis can enable context-sensitive support for collaborative learning.     

Spectral definition of the macro-algae Ulva curvata in the back-barrier bays of the Eastern Shore of Virginia,USA

We have developed methods to determine the visible (VIS) to near-infrared (NIR) spectral properties of thalli and epiphytes of bloom-forming and green macrophyte Ulva curvata in back-barrier lagoons in Virginia, USA. A 2% increase in NIR thalli reflectance from winter to summer (ca. 9.5%) matched the drop in summer NIR transmittance (ca. 90%). In contrast, summer and winter VIS reflectance (reaching 6%) were nearly identical while winter transmittance (ca. 85%) was 10–20% higher. NIR absorption remained at 5% but VIS absorption increased by 10–20% from winter to summer. Replicate consistency substantiated the high transmittance difference indicating thallus composition changed from summer to winter. Epiphytes increased thallus reflectance (<ca. 4%) and decreased transmittance (<ca. 10%) and exhibited broadband VIS and NIR absorptions in summer and selective peaks in winter. A simulation coupling water extinction with thallus reflectance and transmittance found seven submerged thalli maximized the surface reflectance enhancement (ca. 2.5%).     

Flat-plate techniques for measuring reflectance of macro-algae (Ulva curvata)

We tested the consistency and accuracy of flat-plate spectral measurements (400–1000 nm) of the marine macrophyte Ulva curvata. With sequential addition of Ulva thallus layers, the reflectance progressively increased from 6% to 9% with six thalli in the visible (VIS) and from 5% to 19% with ten thalli in the near infrared (NIR). This progressive increase was simulated by a mathematical calculation based on an Ulva thallus diffuse reflectance weighted by a transmittance power series. Experimental and simulated reflectance differences that were particularly high in the NIR most likely resulted from residual water and layering structure unevenness in the experimental progression. High spectral overlap existed between fouled and non-fouled Ulva mats and the coexistent lagoon mud in the VIS, whereas in the NIR, spectral contrast was retained but substantially dampened by fouling.