Microbial diversity in the municipal composting process and development of detection methods

Composting refers to aerobic degradation of organic material and is one of the main waste treatment methods used in Finland for treating separated organic waste. The composting process allows converting organic waste to a humus-like end product which can be used to increase the organic matter in agricultural soils, in gardening, or in landscaping. Microbes play a key role as degraders during the composting-process, and the microbiology of composting has been studied for decades, but there are still open questions regarding the microbiota in industrial composting processes. It is known that with the traditional, culturing-based methods only a small fraction, below 1%, of the species in a sample is normally detected. In recent years an immense diversity of bacteria, fungi and archaea has been found to occupy many different environments. Therefore the methods of characterising microbes constantly need to be developed further. In this thesis the presence of fungi and bacteria in full-scale and pilot-scale composting processes was characterised with cloning and sequencing. Several clone libraries were constructed and altogether nearly 6000 clones were sequenced. The microbial communities detected in this study were found to differ from the compost microbes observed in previous research with cultivation based methods or with molecular methods from processes of smaller scale, although there were similarities as well. The bacterial diversity was high. Based on the non-parametric coverage estimations, the number of bacterial operational taxonomic units (OTU) in certain stages of composting was over 500. Sequences similar to Lactobacillus and Acetobacteria were frequently detected in the early stages of drum composting. In tunnel stages of composting the bacterial community comprised of Bacillus, Thermoactinomyces, Actinobacteria and Lactobacillus. The fungal diversity was found to be high and phylotypes similar to yeasts were abundantly found in the full-scale drum and tunnel processes. In addition to phylotypes similar to Candida, Pichia and Geotrichum moulds from genus Thermomyces and Penicillium were observed in tunnel stages of composting. Zygomycetes were detected in the pilot-scale composting processes and in the compost piles. In some of the samples there were a few abundant phylotypes present in the clone libraries that masked the rare ones. The rare phylotypes were of interest and a method for collecting them from clone libraries for sequencing was developed. With negative selection of the abundant phylotyps the rare ones were picked from the clone libraries. Thus 41% of the clones in the studied clone libraries were sequenced. Since microbes play a central role in composting and in many other biotechnological processes, rapid methods for characterization of microbial diversity would be of value, both scientifically and commercially. Current methods, however, lack sensitivity and specificity and are therefore under development. Microarrays have been used in microbial ecology for a decade to study the presence or absence of certain microbes of interest in a multiplex manner. The sequence database collected in this thesis was used as basis for probe design and microarray development. The enzyme assisted detection method, ligation-detection-reaction (LDR) based microarray, was adapted for species-level detection of microbes characteristic of each stage of the composting process. With the use of a specially designed control probe it was established that a species specific probe can detect target DNA representing as little as 0.04% of total DNA in a sample. The developed microarray can be used to monitor composting processes or the hygienisation of the compost end product. A large compost microbe sequence dataset was collected and analysed in this thesis. The results provide valuable information on microbial community composition during industrial scale composting processes. The microarray method was developed based on the sequence database collected in this study. The method can be utilised in following the fate of interesting microbes during composting process in an extremely sensitive and specific manner. The platform for the microarray is universal and the method can easily be adapted for studying microbes from environments other than compost.

Characterization of genomic diversity in extraintestinal pathogenic Escherichia coli (ExPEC) and development of a diagnostic DNA microarray for the differentiation of ExPEC isolates causing urinary tract infections

Extraintestinal pathogenic Escherichia coli (ExPEC) represent a diverse group of strains of E. coli, which infect extraintestinal sites, such as the urinary tract, the bloodstream, the meninges, the peritoneal cavity, and the lungs. Urinary tract infections (UTIs) caused by uropathogenic E. coli (UPEC), the major subgroup of ExPEC, are among the most prevalent microbial diseases world wide and a substantial burden for public health care systems. UTIs are responsible for serious morbidity and mortality in the elderly, in young children, and in immune-compromised and hospitalized patients. ExPEC strains are different, both from genetic and clinical perspectives, from commensal E. coli strains belonging to the normal intestinal flora and from intestinal pathogenic E. coli strains causing diarrhea. ExPEC strains are characterized by a broad range of alternate virulence factors, such as adhesins, toxins, and iron accumulation systems. Unlike diarrheagenic E. coli, whose distinctive virulence determinants evoke characteristic diarrheagenic symptoms and signs, ExPEC strains are exceedingly heterogeneous and are known to possess no specific virulence factors or a set of factors, which are obligatory for the infection of a certain extraintestinal site (e. g. the urinary tract). The ExPEC genomes are highly diverse mosaic structures in permanent flux. These strains have obtained a significant amount of DNA (predictably up to 25% of the genomes) through acquisition of foreign DNA from diverse related or non-related donor species by lateral transfer of mobile genetic elements, including pathogenicity islands (PAIs), plasmids, phages, transposons, and insertion elements. The ability of ExPEC strains to cause disease is mainly derived from this horizontally acquired gene pool; the extragenous DNA facilitates rapid adaptation of the pathogen to changing conditions and hence the extent of the spectrum of sites that can be infected. However, neither the amount of unique DNA in different ExPEC strains (or UPEC strains) nor the mechanisms lying behind the observed genomic mobility are known. Due to this extreme heterogeneity of the UPEC and ExPEC populations in general, the routine surveillance of ExPEC is exceedingly difficult. In this project, we presented a novel virulence gene algorithm (VGA) for the estimation of the extraintestinal virulence potential (VP, pathogenicity risk) of clinically relevant ExPECs and fecal E. coli isolates. The VGA was based on a DNA microarray specific for the ExPEC phenotype (ExPEC pathoarray). This array contained 77 DNA probes homologous with known (e.g. adhesion factors, iron accumulation systems, and toxins) and putative (e.g. genes predictably involved in adhesion, iron uptake, or in metabolic functions) ExPEC virulence determinants. In total, 25 of DNA probes homologous with known virulence factors and 36 of DNA probes representing putative extraintestinal virulence determinants were found at significantly higher frequency in virulent ExPEC isolates than in commensal E. coli strains. We showed that the ExPEC pathoarray and the VGA could be readily used for the differentiation of highly virulent ExPECs both from less virulent ExPEC clones and from commensal E. coli strains as well. Implementing the VGA in a group of unknown ExPECs (n=53) and fecal E. coli isolates (n=37), 83% of strains were correctly identified as extraintestinal virulent or commensal E. coli. Conversely, 15% of clinical ExPECs and 19% of fecal E. coli strains failed to raster into their respective pathogenic and non-pathogenic groups. Clinical data and virulence gene profiles of these strains warranted the estimated VPs; UPEC strains with atypically low risk-ratios were largely isolated from patients with certain medical history, including diabetes mellitus or catheterization, or from elderly patients. In addition, fecal E. coli strains with VPs characteristic for ExPEC were shown to represent the diagnostically important fraction of resident strains of the gut flora with a high potential of causing extraintestinal infections. Interestingly, a large fraction of DNA probes associated with the ExPEC phenotype corresponded to novel DNA sequences without any known function in UTIs and thus represented new genetic markers for the extraintestinal virulence. These DNA probes included unknown DNA sequences originating from the genomic subtractions of four clinical ExPEC isolates as well as from five novel cosmid sequences identified in the UPEC strains HE300 and JS299. The characterized cosmid sequences (pJS332, pJS448, pJS666, pJS700, and pJS706) revealed complex modular DNA structures with known and unknown DNA fragments arranged in a puzzle-like manner and integrated into the common E. coli genomic backbone. Furthermore, cosmid pJS332 of the UPEC strain HE300, which carried a chromosomal virulence gene cluster (iroBCDEN) encoding the salmochelin siderophore system, was shown to be part of a transmissible plasmid of Salmonella enterica. Taken together, the results of this project pointed towards the assumptions that first, (i) homologous recombination, even within coding genes, contributes to the observed mosaicism of ExPEC genomes and secondly, (ii) besides en block transfer of large DNA regions (e.g. chromosomal PAIs) also rearrangements of small DNA modules provide a means of genomic plasticity. The data presented in this project supplemented previous whole genome sequencing projects of E. coli and indicated that each E. coli genome displays a unique assemblage of individual mosaic structures, which enable these strains to successfully colonize and infect different anatomical sites.

NUPARM and NUCGEN: software for analysis and generation of sequence dependent nucleic acid structures

Software packages NUPARM and NUCGEN, are described, which can be used to understand sequence directed structural variations in nucleic acids, by analysis and generation of non-uniform structures. A set of local inter basepair parameters (viz. tilt, roll, twist, shift, slide and rise) have been defined, which use geometry and coordinates of two successive basepairs only and can be used to generate polymeric structures with varying geometries for each of the 16 possible dinucleotide steps. Intra basepair parameters, propeller, buckle, opening and the C6...C8 distance can also be varied, if required, while the sugar phosphate backbone atoms are fixed in some standard conformation ill each of the nucleotides. NUPARM can be used to analyse both DNA and RNA structures, with single as well as double stranded helices. The NUCGEN software generates double helical models with the backbone fixed in B-form DNA, but with appropriate modifications in the input data, it can also generate A-form DNA ar rd RNA duplex structures.

Analysis and Improvements to the Green Falcon Solar Powered UAV

There has recently been a rapidly increasing interest in solar powered UAVs. With the emergence of high power density batteries, long range and low-power micro radio devices, airframes, and powerful micro-processors and motors, small/micro UAVs have become applicable in civilian applications such as remote sensing, mapping, traffic monitoring, search and rescue. The Green Falcon UAV is an innovative project from Queensland University of Technology and has been developed and tested during these past years. It comprises a wide range of subsystems to be analyses and studied such as Solar Panel Cells, Gas sensor, Aerodynamics of the wing and others. Previous test however, resulted in damage to the solar cells and some of the subsystems including motor and ESC. This report describes the repair and verification process followed to improve the efficiency of the Green Falcon UAV. The report shows some of the results obtained in previous static and flight tests as well as some of recommendations.

History and development of public health

This chapter and the others that follow have the study of population health as their focus, as opposed to a focus on individual care and treatment. Clearly, however, we are concerned with the way in which population health is influenced by biomedical theories and practices, and the way population health is funded, and is influenced by the importance placed on therapeutic medicine. The discussions that follow include a brief overview of the ancient history of public health, and the modern history of Western public health dating from 1850. This date signifies the beginnings of a more organised, collective effort to protect the public’s health. These discussions will help you further expand your definition of public health. You will have an entertaining journey through public health achievements, and less successful outcomes, by examining the historical developments that have led us to a modern understanding of public health. The ancient Greeks and Romans, for example, had public health measures to ensure the safety and health of their populations, for a range of social and economic reasons. Convicts arrived in Australia with many health problems, and were put to work to satisfy the needs of a fledgling colony. It is important to understand the historical journey of public health and the way it is critically analysed, as it provides a looking-glass onto the present and the future.

Why we should design smart cities for getting lost

If smart cities run on big data and algorithms that channel only 'relevant' information and opinions to us, how do we maintain the diversity of ideas and possibilities that drives truly smart cities?

Classification of Indian meteorological stations using cluster and fuzzy cluster analysis, and Kohonen artificial neural networks

The present study deals with the application of cluster analysis, Fuzzy Cluster Analysis (FCA) and Kohonen Artificial Neural Networks (KANN) methods for classification of 159 meteorological stations in India into meteorologically homogeneous groups. Eight parameters, namely latitude, longitude, elevation, average temperature, humidity, wind speed, sunshine hours and solar radiation, are considered as the classification criteria for grouping. The optimal number of groups is determined as 14 based on the Davies-Bouldin index approach. It is observed that the FCA approach performed better than the other two methodologies for the present study.

Place making for knowledge generation and innovation: Planning and branding Brisbane’s knowledge community precincts

Knowledge generation and innovation have been a priority for global city administrators particularly during the last couple of decades. This is mainly due to the growing consensus in identifying knowledge-based urban development as a panacea to the burgeoning economic problems. Place making has become a critical element for success in knowledge-based urban development as planning and branding places is claimed to be an effective marketing tool for attracting investment and talent. This paper aims to investigate the role of planning and branding in place making by assessing the effectiveness of planning and branding strategies in the development of knowledge and innovation milieus. The methodology of the study comprises reviewing the literature thoroughly, developing an analysis framework, and utilizing this framework in analyzing Brisbane’s knowledge community precincts—namely Boggo Road Knowledge Precinct, Kelvin Grove Urban Knowledge Village, and Sippy Downs Knowledge Town. The analysis findings generate invaluable insights in Brisbane’s journey in place making for knowledge and innovation milieus and communities. The results suggest as much as good planning, branding strategies and practice, the requirements of external and internal conditions also need to be met for successful place making in knowledge community precincts.

SIR Analysis and Interference Cancellation in Uplink OFDMA with Large Carrier Frequency/Timing Offsets

In uplink OFDMA, carrier frequency offsets (CFO) and/or timing offsets (TO) of other users with respect to a desired user can cause multiuser interference (MUI). In practical uplink OFDMA systems (e.g., IEEE 802.16e standard), effect of this MUI is made acceptably small by requiring that frequency/timing alignment be achieved at the receiver with high precision (e.g., CFO must be within 1 % of the subcarrier spacing and TO must be within 1/8th of the cyclic prefix duration in IEEE 802.16e), which is realized using complex closed-loop frequency/timing correction between the transmitter and the receiver. An alternate open-loop approach to handle the MUI induced by large CFOs and TOs is to employ interference cancellation techniques at the receiver. In this paper, we first analytically characterize the degradation in the average output signal-to-interference ratio (SIR) due to the combined effect of large CFOs and TOs in uplink OFDMA. We then propose a parallel interference canceller (PIC) for the mitigation of interference due to CFOs and TOs in this system. We show that the proposed PIC effectively mitigates the performance loss due to CFO/TO induced interference in uplink OFDMA.

Automatic Road Extraction using High Resolution Satellite Image Based on Texture Progressive Analysis and Normalized Cut Method

In this paper the approach for automatic road extraction for an urban region using structural, spectral and geometric characteristics of roads has been presented. Roads have been extracted based on two levels: Pre-processing and road extraction methods. Initially, the image is pre-processed to improve the tolerance by reducing the clutter (that mostly represents the buildings, parking lots, vegetation regions and other open spaces). The road segments are then extracted using Texture Progressive Analysis (TPA) and Normalized cut algorithm. The TPA technique uses binary segmentation based on three levels of texture statistical evaluation to extract road segments where as, Normalizedcut method for road extraction is a graph based method that generates optimal partition of road segments. The performance evaluation (quality measures) for road extraction using TPA and normalized cut method is compared. Thus the experimental result show that normalized cut method is efficient in extracting road segments in urban region from high resolution satellite image.

Splitting Algorithms for Fast Relay Selection: Generalizations, Analysis, and a Unified View

Relay selection for cooperative communications promises significant performance improvements, and is, therefore, attracting considerable attention. While several criteria have been proposed for selecting one or more relays, distributed mechanisms that perform the selection have received relatively less attention. In this paper, we develop a novel, yet simple, asymptotic analysis of a splitting-based multiple access selection algorithm to find the single best relay. The analysis leads to simpler and alternate expressions for the average number of slots required to find the best user. By introducing a new contention load' parameter, the analysis shows that the parameter settings used in the existing literature can be improved upon. New and simple bounds are also derived. Furthermore, we propose a new algorithm that addresses the general problem of selecting the best Q >= 1 relays, and analyze and optimize it. Even for a large number of relays, the scalable algorithm selects the best two relays within 4.406 slots and the best three within 6.491 slots, on average. We also propose a new and simple scheme for the practically relevant case of discrete metrics. Altogether, our results develop a unifying perspective about the general problem of distributed selection in cooperative systems and several other multi-node systems.