Life Cycle Assessment (LCA) Applied to the Design of an Innovative Drying Process for Sewage Sludge

Most adverse environmental impacts result from design decisions made long before manufacturing or usage. In order to prevent this situation, several authors have proposed the application of life cycle assessment (LCA) at the very first phases of the design of a process, a product or a service. The study in this paper presents an innovative thermal drying process for sewage sludge called fry-drying, in which dewatered sludge is directly contacted in the dryer with hot recycled cooking oils (RCO) as the heat medium. Considering the practical difficulties for the disposal of these two wastes, fry-drying presents a potentially convenient method for their combined elimination by incineration of the final fry-dried sludge. An analytical comparison between a conventional drying process and the new proposed fry-drying process is reported, with reference to some environmental impact categories. The results of this study, applied at the earliest stages of the design of the process, assist evaluation of the feasibility of such system compared to a current disposal process for the drying and incineration of sewage sludge.

Enhancing Life in the Hyper-surveillance Mini-world of a Space Station: The Role of Situation Awareness, Communication, and Reality TV in the Life of Astronauts

This is the third article of a series entitled Astronauts as Audiences. In this article, we investigate the roles that situation awareness (SA), communications, and reality TV (including media communications) might have on the lives of astronauts in remote space communities. We examined primary data about astronauts’ living and working environments, applicable theories of SA, communications, and reality TV (including media communications). We then surmised that the collective application of these roles might be a means of enhancing the lives of astronauts in remote space communities.

A Correlation Analysis on LSA and HAL Semantic Space Models

In this paper, we compare a well-known semantic spacemodel, Latent Semantic Analysis (LSA) with another model, Hyperspace Analogue to Language (HAL) which is widely used in different area, especially in automatic query refinement. We conduct this comparative analysis to prove our hypothesis that with respect to ability of extracting the lexical information from a corpus of text, LSA is quite similar to HAL. We regard HAL and LSA as black boxes. Through a Pearsonrsquos correlation analysis to the outputs of these two black boxes, we conclude that LSA highly co-relates with HAL and thus there is a justification that LSA and HAL can potentially play a similar role in the area of facilitating automatic query refinement. This paper evaluates LSA in a new application area and contributes an effective way to compare different semantic space models.