Crack healing utilising bacterial spores in concrete

This self repair system is based upon harmless ground borne bacteria as the self healing agent. The bacteria is activated after the concrete is cracked and the bacterial spores are exposed to moisture and air. The bacterial reproduction process creates a calcite by-product which fills the cracks in the concrete. By sealing the cracks in concrete, an effective barrier to air or liquid borne deleterious materials is formed and as a consequence of his, enhanced durability is achieved in the structure, resulting in lower life cycle costs. The concrete/mortar prisms were cracked and tested for water flow. They were then left for 56 days to heal and were subject to a test for water tightness. Healing was observed and a reduced water flow (74% and 32% healed) measured with the healed samples when compared to the specimens that were cracked and subjected to a water flow test without any healing agent. The number of samples were limited and a larger scale test is recommended for further work, however this is proof of concept of the process of healing and testing

'100% Renewable Electricity in Australia'

This study was prepared by Prof. Andrew Blakers, a leading researcher of the energy cluster. The research, initially focused on Australia, is being extended to Indonesian market under the AIC funded project

Multi life cycle assessment: a potential assessment method for product lifespan and environmental performance

Product lifespan is one of key factors for product life cycle environmental performance. Lifespan extending is always considered positive for better life cycle environmental performance. From the view of one product, extended product lifespan can mitigate the environmental performance for avoided new production. But compared with the newer products those with same product function, there may be a tradeoff between lifespan extending and products replacement, because generally the newer products always have the higher energy efficiency and better function. It requires a systematic evaluation method under these circumstances. Multi Life Cycle Assessment (MLCA) may be a potential solution. The system boundary of MLCA is larger, including two or more life cycles of products. The end-of-life options of products, such as components reuse and materials recovery, can be integrated within the system boundary. In this study, MLCA was applied to two types of products, air-conditioner and notebook computer, in China to verify its practicability. The results of MLCA indicated that lifespan extending is better than frequent replacement for the notebook computer in the environmental performance view, for the energy efficiency improvement of notebook improves not so fast. While the MLCA results indicated that products replacement is better for air-conditioners, because the energy efficiency improved fast and evidently. In conclusion, MLCA can be useful for assessment of product lifespan extending point based on the life cycle environmental performance. Further, environmentally friendly technology innovation as an important factor beyond the product itself should be taken into consideration for optimal product lifespan assessment

Alternative placements of turtles in the current phylogeny of living tetrapods.

<p>Alternative placements of turtles in the current phylogeny of living tetrapods.</p

The phylogenetic hypotheses derived from the 7-species data.

<p>Amino-acid and nucleotide sequences were analyzed by maximum parsimony (MP) and maximum likelihood (ML) methods, respectively. Numbers near the nodes are bootstrap values.</p

The phylogenetic hypotheses derived from using genes as characters.

<p>Individual gene tree was first estimated and used as character-state tree. Each gene was then treated as a character and a parsimony analysis was used to construct the species trees. Amino-acid and nucleotide sequences were analyzed separately. Numbers near the nodes are bootstrap values. Note the different placements of turtles and the low bootstrap values for the associated nodes.</p

The procedural flowchart of using genes as characters in phylogenomic analysis.

<p>The procedural flowchart of using genes as characters in phylogenomic analysis.</p

A simple tally of genes that support alternative hypotheses.

<p>Hu = <u>Hu</u>man (<i>Homo sapiens</i>), Fr = Western Clawed <u>Fr</u>og (<i>Xenopus tropicalis</i>), ZF = <u>Z</u>ebra <u>F</u>inch (<i>Taeniopygia guttata</i>), Ch = <u>Ch</u>icken (<i>Gallus gallus</i>), An = Green <u>An</u>ole (<i>Anolis carolinensis</i>), PT = Chinese <u>P</u>ond <u>T</u>urtle (<i>Mauremys reevesii</i>), ST = <u>S</u>oft-shelled <u>T</u>urtle (<i>Pelodiscus sinensis</i>), Py = Royal <u>Py</u>thon (<i>Python regius</i>), Tu = <u>Tu</u>atara (<i>Sphenodon punctatus</i>), Op = <u>Op</u>ossum (<i>Monodelphis domestica</i>), Cr = Nile <u>Cr</u>ocodile (<i>Crocodylus niloticus</i>).</p><p>For example, the clade ((ZF,Ch),PT) appears on 2117 gene trees without regarding other relationships. The 7-species dataset includes 4,584 putatively orthologous proteins and coding genes; the 11-species dataset includes 1,638 putatively orthologous proteins and coding genes.</p

Chi-square test of the relationship between genes under positive selection and alternative hypotheses.

<p>ZF = <u>Z</u>ebra <u>F</u>inch (<i>Taeniopygia guttata</i>), Ch = <u>Ch</u>icken (<i>Gallus gallus</i>), PT = Chinese <u>P</u>ond <u>T</u>urtle (<i>Mauremys reevesii</i>), An = Green <u>An</u>ole (<i>Anolis carolinensis</i>).</p><p>Numbers in parentheses are expected numbers of genes under random distribution. Significantly more positively selected genes support the archosaur hypothesis.</p

Chi-square tests of the relationship between genes functions and phylogenetic hypotheses.

<p>Only significant results are presented. A: the archosaur hypothesis; L: the lepidosaur hypothesis; O: other hypotheses. +: number of genes which have a particular GO category or KEGG pathway; −: number of genes which do not have the GO category or KEGG pathway. Numbers in parentheses are expected numbers of genes under random distribution. For example, of the 2117 genes that support the Archosaur hypothesis, 2036 genes have the GO category of “biological process”; among them, 61 have the GO category of “organophosphate metabolic process” and 1975 genes do not have the term.</p