Retransmission of Hydrometric Data in Canada

There are no author-identified significant results in this report

Plasticizer degradation by marine bacterial isolates : a proteogenomic and metabolomic characterization

Many commercial plasticizers are toxic endocrine-disrupting chemicals that are added to plastics during manufacturing and may leach out once they reach the environment. Traditional phthalic acid ester plasticizers (PAEs), such as dibutyl phthalate (DBP) and bis(2-ethyl hexyl) phthalate (DEHP), are now increasingly being replaced with more environmentally friendly alternatives, such as acetyl tributyl citrate (ATBC). While the metabolic pathways for PAE degradation have been established in the terrestrial environment, to our knowledge, the mechanisms for ATBC biodegradation have not been identified previously and plasticizer degradation in the marine environment remains underexplored. From marine plastic debris, we enriched and isolated microbes able to grow using a range of plasticizers and, for the first time, identified the pathways used by two phylogenetically distinct bacteria to degrade three different plasticizers (i.e., DBP, DEHP, and ATBC) via a comprehensive proteogenomic and metabolomic approach. This integrated multi-OMIC study also revealed the different mechanisms used for ester side-chain removal from the different plasticizers (esterases and enzymes involved in the β-oxidation pathway) as well as the molecular response to deal with toxic intermediates, that is, phthalate, and the lower biodegrading potential detected for ATBC than for PAE plasticizers. This study highlights the metabolic potential that exists in the biofilms that colonize plastics-the Plastisphere-to effectively biodegrade plastic additives and flags the inherent importance of microbes in reducing plastic toxicity in the environment

Facilitating positive spillover effects: new insights from a mixed-methods approach exploring factors enabling people to live more sustainable lifestyles

Positive spillover occurs when changes in one behavior influence changes in subsequent behaviors. Evidence for such spillover and an understanding of when and how it may occur are still limited. This paper presents findings of a 1-year longitudinal behavior change project led by a commercial retailer in the United Kingdom and Ireland to examine behavior change and potential spillover of pro-environmental behavior, and how this may be associated with changes in environmental identity and perceptions of ease and affordability as well as perceptions of how participation in the project has helped support behavior change. We draw on both quantitative and qualitative data. Study 1 examines quantitative data from the experimental and a matched control group. Study 2 reports qualitative findings from a follow up interview study with participants of the experimental group. As expected, we found significant changes in reported pro-environmental behavior and identity in the experimental group as well as some indications of behavioral spillover. These changes were not significantly associated with changes in environmental identity. The interviews suggested that group dynamics played an important role in facilitating a sense of efficacy and promoting sustained behavior change and spillover. Moreover, the support by a trusted entity was deemed to be of crucial importance

A Survey of Sequential Pattern Based E-Commerce Recommendation Systems

E-commerce recommendation systems usually deal with massive customer sequential databases, such as historical purchase or click stream sequences. Recommendation systems’ accuracy can be improved if complex sequential patterns of user purchase behavior are learned by integrating sequential patterns of customer clicks and/or purchases into the user–item rating matrix input of collaborative filtering. This review focuses on algorithms of existing E-commerce recommendation systems that are sequential pattern-based. It provides a comprehensive and comparative performance analysis of these systems, exposing their methodologies, achievements, limitations, and potential for solving more important problems in this domain. The review shows that integrating sequential pattern mining of historical purchase and/or click sequences into a user–item matrix for collaborative filtering can (i) improve recommendation accuracy, (ii) reduce user–item rating data sparsity, (iii) increase the novelty rate of recommendations, and (iv) improve the scalability of recommendation systems

The 2004 Claremont Debate: Lipsey vs. Scriven

While there is little disagreement about the need for, and value of, program evaluation, there remain major disagreements in the field about best practices (Donaldson & Lipsey, in press). For example, Donaldson and Scriven (2003) invited a diverse group of evaluators to Claremont in 2001 to share their visions for “how we should practice evaluation” in the new millennium. Theorists and practitioners discussed a wide range of views and evaluation approaches, many at odds with one another, on how best to improve evaluation practice (e.g., the experimental paradigm, evaluation as a transdiscipline, results-oriented management, empowerment evaluation, fourth generation evaluation, inclusive evaluation, theory-driven evaluation and the like). In response to some of the heated exchanges, Mark (2003) noted “it seems ironic when evaluators who espouse inclusion, empowerment, and participation would like to exclude, disempower, and see no participation by evaluators who hold different views.” Hefurther concluded that whatever peace has been achieved in the so-call quantitative-qualitative paradigm wars remains an uneasy peace