Environmental contaminants: Environmental estrogens - Hazard characterization.

Environmental estrogens are compounds which can mimic or interfere in the action of the female hormone estrogen and are found in food either as natural components of plant material (phytoestrogens) or as man-made chemicals (xenoestrogens) which enter food from environmental pollution or from storage procedures. This review discusses the source of these compounds, their molecular basis of action and their potential to impact on human health.

Neo-Gramscianism

Gramscian concepts have been utilized by scholars to analyze and illuminate various aspects of GLOBAL ENVIRONMENTAL GOVERNANCE. A foremost application of neo-Gramscianism to the scholarship on global environmental governance has been in challenging the basic premise of orthodox regime theory that international environmental rule-making is the exclusive preserve of state actors. Gramscian theory is very sensitive to the role and importance of political contestations, accommodations and compromises, which many have noted as the ‘stuff’ of environmental governance. Crucially, while a Gramscian analysis is sensitive to the counter-hegemonic potential of the subordinate class and the ever contested and changing contours of power in a social regime, it does not subscribe to the unlimited possibility of outcome. Given the utility of neo-Gramscian ideas, as demonstrated by the scholarship discussed, it is surprising that the approach has not been deployed more widely in the scholarship on global environmental governance.

Wikis: collaborative virtual learning environments

Ward Cunningham used the word wiki (the Hawaiian word meaning quick) to name the collaborative tool he developed for use on the internet in 1994. Wikis are fully editable websites. Users can visit, read, re-organize and update the structure and content (text and pictures) of a wiki as they see fit. This functionality is called open editing (Leuf & Cunningham, 2001). All a user needs to edit and read a wiki, is a web browser. Consequently, the wiki has great potential for use as a collaborative virtual learning environment. Wikis abound on the internet. A well known wiki is Wikipedia an online collaborative encyclopaedia, where anybody can read, edit, re-organize and update the encyclopaedia content (Wikipedia, 2004).

Wikipedia model for collective intelligence : a review of information quality

Online information seekers increasingly utilise the online encyclopaedia Wikipedia as a key reference source. Wikipedia's special feature is that it is based on the collective intelligence (CI) of lay citizens. Its consensus-building participatory knowledge-building processes replace traditional encyclopaedia processes founded on the knowledge of experts and gatekeeping practices. However there have been reports of concerns with the level of information quality provided by Wikipedia articles. This paper explores information quality for Wikipedia theoretically. First, it conceptualises the Wikipedia model of knowledge production and second, it analyses information quality for the model. Finally, the paper recommends some improvements for the model and discusses other implications for knowledge management theory and practice.

Eight very vary(s): towards a program of mistakes-on-purpose

In 2007, I spent eight weeks in Residency at the Architectural body Research Foundation (Houston Street, NY, NY) with Arakawa and Madeline. In addition to discussion current projects, meeting researcher practitioners and students who would come by the office or talking to people on the phone who had just written or done something of interest, reviewing texts and discussing pressing ideas, Madeline had started work on an Encyclopaedia of Mistakes prompted by the mistakes on Purpose procedure. Every afternoon we would spend three hours or more at the end of the day working on the spectrum and placement of mistakes on the spectrum, lists of mistakes and refinement of what the role of mistakes might be across the organism-person-surround and the potential for perceptual knowing. As the work is an unfinished 31 page manuscript, I will not cite it directly but rather speak about it and the thinking process that went into the many many versions and amendments that produced in February and March of 2007.

The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.