MaB-flocs for a more sustainable wastewater treatment

Conventional wastewater treatment with activated sludge has a large carbon footprint, high aeration rates are combined with CO2 emission from bacteria. By using micro-algal bacterial flocs (MaB-flocs), CO2 could be captured within the biomass and oxygen could be produced in situ. In order to maximize this photosynthetic aeration and CO2 mitigation, we investigated whether inorganic carbon could alter the algae/bacteria ratio while keeping a good removal performance and settleability of the MaB-flocs. Therefore, three illuminated sequencing batch reactors with MaB-flocs were fed with synthetic wastewater enriched with 84.2, 42.1 and 0 mg L-1 C-KHCO3 supplemented with 0, 42.1, 84.2 mg L-1 C-sucrose, respectively, representing the inorganic carbon source compared to an organic carbon source. Bicarbonate significantly increased the chlorophyll a concentration of the MaB-flocs, but only poor settling flocs could be obtained causing a high turbidity of the effluent. Moreover, significant lower nitrogen removal efficiencies were measured feeding bicarbonate compared to sucrose and the pH increased (9.5). Sucrose benefited a good reactor performance and showed a good settleability of MaB-flocs. Despite the lower chlorophyll a concentration of the biomass and the lower in situ oxygen concentration, average soluble COD removal efficiencies of 95 % were achieved with sucrose. Furthermore sucrose was successful in containing the optimal pH at 7. This study shows the importance of the carbon source for a good reactor performance. As a consequence, the inorganic/organic carbon ratio of the wastewater should be taken into account when algal bacterial reactors are used for wastewater treatment

De Natuurschoonwet: Borger van Nederlands natuurschoon?

De Natuurschoonwet (NSW) biedt voor landgoederen in Nederland diverse fiscale voordelen. De NSW stelt geen eisen aan de kwaliteit van het natuurschoon, wel aan de omvang van het landgoed (namelijk minstens 5 ha groot). Wat is de invloed van deze wet op landgoederen. Dat is nagegaan in een studentenonderzoek (Schuurman) door drie landgoederen onder de loep te nemen en tevens bij 23 landgoederen de toekomstmogelijkheden na te gaan, en wel in Overijssel en Gelderlan

Random-set methods identify distinct aspects of the enrichment signal in gene-set analysis

A prespecified set of genes may be enriched, to varying degrees, for genes that have altered expression levels relative to two or more states of a cell. Knowing the enrichment of gene sets defined by functional categories, such as gene ontology (GO) annotations, is valuable for analyzing the biological signals in microarray expression data. A common approach to measuring enrichment is by cross-classifying genes according to membership in a functional category and membership on a selected list of significantly altered genes. A small Fisher's exact test $p$-value, for example, in this $2\times2$ table is indicative of enrichment. Other category analysis methods retain the quantitative gene-level scores and measure significance by referring a category-level statistic to a permutation distribution associated with the original differential expression problem. We describe a class of random-set scoring methods that measure distinct components of the enrichment signal. The class includes Fisher's test based on selected genes and also tests that average gene-level evidence across the category. Averaging and selection methods are compared empirically using Affymetrix data on expression in nasopharyngeal cancer tissue, and theoretically using a location model of differential expression. We find that each method has a domain of superiority in the state space of enrichment problems, and that both methods have benefits in practice. Our analysis also addresses two problems related to multiple-category inference, namely, that equally enriched categories are not detected with equal probability if they are of different sizes, and also that there is dependence among category statistics owing to shared genes. Random-set enrichment calculations do not require Monte Carlo for implementation. They are made available in the R package allez.Comment: Published at http://dx.doi.org/10.1214/07-AOAS104 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Synthetic microbial ecosystems : an exciting tool to understand and apply microbial communities

Many microbial ecologists have described the composition of microbial communities in a plenitude of environments, which has greatly improved our basic understanding of microorganisms and ecosystems. However, the factors and processes that influence the behaviour and functionality of an ecosystem largely remain black boxes when using conventional approaches. Therefore, synthetic microbial ecology has gained a lot of interest in the last few years. Because of their reduced complexity and increased controllability, synthetic communities are often preferred over complex communities to examine ecological theories. They limit the factors that influence the microbial community to a minimum, allowing their management and identifying specific community responses. However, besides their use for basic research, synthetic ecosystems also found their way towards different applications, like industrial fermentation and bioremediation. Here, we review why and how synthetic microbial communities are applied for research purposes and for which applications they have been and could be successfully used

The Effects of Fiber Orientation and Volume Fraction of Fiber on Mechanical Properties of Additively Manufactured Composite Material

Additive manufacturing (AM) also known as 3D printing has tremendous advancements in recent days with a vast number of applications in industrial, automotive, architecture, consumer projects, fashion, toys, food, art, etc. Composite materials are widely used in structures with weight as a critical factor especially in aerospace industry. Recently, additive manufacturing technology, a rapidly growing innovative technology, has gained lot of importance in making composite materials. The properties of composite materials depend upon the properties of constituent’s matrix and fiber. There is lot of research on effect of fiber orientation on mechanical properties of composite materials made using conventional manufacturing methods. It will be interesting and relevant to study the relationship between the fiber orientation and fiber volume with mechanical properties of additively manufactured composite materials. This thesis work presents experimental investigation of mechanical behavior like tensile strength and fatigue life with variation in fiber orientation and fiber volume fraction of 3D printed composite materials. The aim is to study the best combination of volume fraction of fiber and fiber orientation that has better fatigue strength for additive manufactured composite materials. Using this study, we can decide the type of orientation and volume percent for desired properties. This study also finds the range of fatigue limits of 3d printed composite materials

Association Between Smoking and Tuberculosis Infection: A Population Survey in a High Tuberculosis Incidence Area

Associations between smoking and tuberculosis disease including death from tuberculosis have been reported, but there are few reports on the influence of smoking on the risk of developing Mycobacterium tuberculosis infection. The aim of this study was to determine the association between smoking and M tuberculosis infection. In a cross sectional population survey, data on smoking and tuberculin skin test (TST) results of 2401 adults aged >15 years were compared. A total of 1832 (76%) subjects had a positive TST (>10 mm induration). Of 1309 current smokers or ex-smokers, 1070 (82%) had a positive TST. This was significantly higher than for never smokers (unadjusted OR 1.99, 95% confidence interval (CI) 1.62 to 2.45). A positive relationship with pack-years was observed, with those smoking more than 15 pack-years having the highest risk (adjusted OR 1.90,95% CI 1.28 to 2.81). Smoking may increase the risk of M tuberculosis infection.\u