Shaping Water Quality Decisions: An Evaluation of a Public Consultation Programme

ABSTRACT

Effective natural resources management is enhanced when scientific understanding is coupled with informed public support. Public consultation panels were used by the Canadian/U.S. International Reference Group on Great Lakes Pollution from Land Use Activities (PLUARG) set up by the International Joint Commission (I.J.C.). This paper assesses the utilization of the input from the public consultation panels by means of a comparative content analysis of the eight Canadian panels' reports and the PLUARG draft report. This approach yields objective data and replicable research. The findings from a parallel study of the 17 U.S./Canadian panels are also discussed.

More than 30 issues were raised in the panel reports; of these, 17 were examined in detail. The most critical step in the analysis is the compilation of a list of questions that reflect the content of each presentation and of the planning report. On the basis of this comparative analysis, fourteen of the land use activities discussed by the panels were dismissed in the PLUARG Draft Report as being local in nature or as being point sources (as opposed to diffuse sources).

Agricultural land uses, urban run-off and waste disposal from septic tanks and industrial sources were recognized by practically all the panels as serious sources of pollution from land use activities to the Great Lakes. PLUARG and the public consultation panels showed a veiy high degree of congruency on these three critical issues.

The main lesson from the case study is that the public should have been consulted earlier, i.e. when the terms of reference were set so that the public's views on which issues needed attention would be more congruent with the planners' views.     

Catalytic oxidation with Al-Ce-Fe-PILC as a post-treatment system for coffee wet processing wastewater

The effluent from the anaerobic biological treatment of coffee wet processing wastewater (CWPW) contains a non-biodegradable compound that must be treated before it is discharged into a water source. In this paper, the wet hydrogen peroxide catalytic oxidation (WHPCO) process using Al-Ce-Fe-PILC catalysts was researched as a post-treatment system for CWPW and tested in a semi-batch reactor at atmospheric pressure and 25 °C. The Al-Ce-Fe-PILC achieved a high conversion rate of total phenolic compounds (70%) and mineralization to CO(2) (50%) after 5 h reaction time. The chemical oxygen demand (COD) of coffee processing wastewater after wet hydrogen peroxide catalytic oxidation was reduced in 66%. The combination of the two treatment methods, biological (developed by Cenicafé) and catalytic oxidation with Al-Ce-Fe-PILC, achieved a 97% reduction of COD in CWPW. Therefore, the WHPCO using Al-Ce-Fe-PILC catalysts is a viable alternative for the post-treatment of coffee processing wastewater.     

The Social Sustainable Aquifer Yield: An Indicator for the Analysis and Assessment of the Integrated Aquifers Management

Integrated Aquifers Management (IAM) demands innovative tools and methods that are able to consider as much perspectives as possible. This research is aimed to design, apply and provide an indicator named Social Sustainable Aquifer Yield (SSAY), expressed in units of time that includes pure hydrological variables as well as social ones. The indicator is defined as the relation between the Residence Time, which is the relation between aquifer Storage (S) and Recharge (R) (S/R), and the relation between the aquifer Pumping (P) and the new variable named Aquifer Social Yield (ASY). The whole indicator is defined by this formula: (S/R)/(P/ASY). The assessment of the residence time is essential in aquifers with at least one of the following features: i) high hydraulic diffusivity, and ii) small volume of reserves. Finally, the variable ASY is defined as the average perception from the stakeholders about the maximum acceptable aquifer exploitation. This indicator has been successfully applied in the aquifers located in southern Jaen province (South Spain) belonging to the Water System SE4-Jaén Water Supply. The results probe the high utility of the indicator, especially in regards to the public participation processes.     

Methodological design and comparative evaluation of a MAS providing AmI

Researches on Ambient Intelligent and Ubiquitous Computing using wireless technologies have increased in the last years. In this work, we review several scenarios to define a multi-agent architecture that support the information needs of these new technologies, for heterogeneous domain. Our contribution consists of designing in a methodological way a Context Aware System (involving location services) using agents that can be used in very different domains. We describe all the steps followed in the design of the agent system. We apply a hybridizing methodology between GAIA and AUML. Additionally we propose a way to compare different agent architectures for Context Aware System using agent interactions. So, in this paper, we describe the assignment of weight values to agents interaction in two different MAS architectures for Context Aware problems solving different scenarios inspired in FIPA standard negotiation protocols.     

Self-Organising Maps: A new way to screen the level of satisfaction of dialysis patients

Evaluation of patient satisfaction has become an important indicator for assessing health care quality. Fresenius Medical Care (FME) as a global provider of dialysis services through its NephroCare network has a strong interest in monitoring patient satisfaction.The aim of the paper is to test and validate a methodology for detecting a residual area of low satisfaction in dialysis patients.The FME Patient Satisfaction Programme questionnaire was distributed to haemodialysis (HD) patients treated in 335 centers of its network. It contained 79 questions covering various satisfaction aspects regarding Dialysis Unit, Dialysis Arrangement, Nurses, Doctors, etc.To analyse the data provided by the questionnaire, the Self-Organising Map (SOM) method was used. SOM is a neural network model for clustering and projecting high-dimensional data into a low-dimensional space, preserving topological relationships of original high-dimensional data spaces.10,632 HD patients completed the questionnaire. Mean age was 63.05 ± 14.93 years with 56.69% males. Response rate was 66%. Overall level of satisfaction was 1.99 (range from ?3 to +3). On average patients were very satisfied with all issues. Nevertheless, a group of patients, around 60 years old, balanced gender ratio, whose level of satisfaction was lower than 1, were highlighted.In the NephroCare clinics patient satisfaction with service is rather high. While traditional analysis usually stops here, the SOM method allows identification of areas of potential improvement for specific patient groups.     

Selecting Significant Effects in Factorial Designs Taking Type II Errors into Account

When analysing the effects of a factorial design, it is customary to take into account the probability of making a Type I error (the probability of considering an effect significant when it is non‐significant), but not to consider the probability of making a Type II error (the probability of considering an effect as non‐significant when it is significant). Making a Type II error, however, may lead to incorrect decisions regarding the values that the factors should take or how subsequent experiments should be conducted. In this paper, we introduce the concept of minimum effect size of interest and present a visualization method for selecting the critical value of the effects, the threshold value above which an effect should be considered significant, which takes into account the probability of Type I and Type II errors. Copyright © 2006 John Wiley & Sons, Ltd.     

Multivariate Modeling of Age and Retest in Longitudinal Studies of Cognitive Abilities.

Longitudinal multivariate mixed models were used to examine the correlates of change between memory and processing speed and the contribution of age and retest to such change correlates. Various age- and occasion-mixed models were fitted to 2 longitudinal data sets of adult individuals (N > 1,200). For both data sets, the results indicated that the correlation between the age slopes of memory and processing speed decreased when retest effects were included in the model. If retest effects existed in the data but were not modeled, the correlation between the age slopes was positively biased. The authors suggest that although the changes in memory and processing speed may be correlated over time, age alone does not capture such a covariation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modelling and Validating a multiple-configuration railway signalling system using SDL

This paper discusses some issues about the usage of SDL and related commercial SDL support tools for the validation of a railway signalling system: in particular, the issue of the multiple configurations presented by this system is addressed, discussing the possible strategies to validate the system regardless to the actual configuration.     

Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit

In this paper, we review an extension of the learning rules in a Principal Component Analysis network which has been derived to be optimal for a specific probability density function. We note that this probability density function is one of a family of pdfs and investigate the learning rules formed in order to be optimal for several members of this family. We show that, whereas we have previously (Lai et al., 2000; Fyfe and MacDonald, 2002) viewed the single member of the family as an extension of PCA, it is more appropriate to view the whole family of learning rules as methods of performing Exploratory Projection Pursuit. We illustrate this on both artificial and real data sets.     

Parameter estimation in Bayesian reconstruction of SPECT images: An aid in nuclear medicine diagnosis

Despite the adequacy of Bayesian methods to reconstruct nuclear medicine SPECT (single‐photon emission computed tomography) images, they are rarely used in everyday medical practice. This is primarily because of their computational cost and the need to appropriately select the prior model hyperparameters. We propose a simple procedure for the estimation of these hyperparameters and the reconstruction of the original image and test the procedure on both synthetic and real SPECT images. The experimental results demonstrate that the proposed hyperparameter estimation method produces satisfactory reconstructions. Although we have used generalized Gaussian Markov random fields (GGMRF) as prior models, the proposed estimation method can be applied to any priors with convex potential and tractable partition function with respect to the scale hyperparameter. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol 14, 21–27, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20003