Fuzzy methods for analysis of microarrays and networks

Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

Developing a fuzzy multi-criteria decision-making model for selecting design-build operational variations

Many academic researchers have conducted studies on the selection of design-build (DB) delivery method; however, there are few studies on the selection of DB operational variations, which poses challenges to many clients. The selection of DB operational variation is a multi-criteria decision making process that requires clients to objectively evaluate the performance of each DB operational variation with reference to the selection criteria. This evaluation process is often characterized by subjectivity and uncertainty. In order to resolve this deficiency, the current investigation aimed to establish a fuzzy multicriteria decision-making (FMCDM) model for selecting the most suitable DB operational variation. A three-round Delphi questionnaire survey was conducted to identify the selection criteria and their relative importance. A fuzzy set theory approach, namely the modified horizontal approach with the bisector error method, was applied to establish the fuzzy membership functions, which enables clients to perform quantitative calculations on the performance of each DB operational variation. The FMCDM was developed using the weighted mean method to aggregate the overall performance of DB operational variations with regard to the selection criteria. The proposed FMCDM model enables clients to perform quantitative calculations in a fuzzy decision-making environment and provides a useful tool to cope with different project attributes.

Vibrational spectroscopy of synthetic archerite (K,NH4)H2PO4 : and in comparison with the natural cave mineral

In order to mimic the formation of archerite in cave minerals, the mineral analogue has been synthesised. The cave mineral is formed by the reaction of the chemicals in bat guano with calcite substrates. X-ray diffraction proves that the synthesised archerite analogue was pure. The vibrational spectra of the synthesised mineral are compared with that of the natural cave mineral. Raman and infrared bands are assigned to H2PO4-, OH and NH stretching and bending vibrations. The Raman band at 917 cm-1 is assigned to the HOP stretching vibration of the H2PO4- units. Bands in the 1200 to 1800 cm-1 region are associated with NH4+ bending modes. Vibrational spectroscopy enables the molecular structure of archerite to be analysed.

Use of a zeolite synthesised from alkali treated kaolin as a K fertiliser : glasshouse experiments on leaching and uptake of K by wheat plants in sandy soil

Zeolite N, a zeolite referred to in earlier publications as MesoLite, is made by caustic reaction of kaolin at temperatures between 80 °C and 95 °C. This material has a very high cation exchange capacity (CEC ≈ 500 meq/100 g). Soil column leaching experiments have shown that K-zeolite N additions greatly reduce leaching of NH4+ fertilisers but the agronomic effectiveness of the retained K+ and NH4+ is unknown. To measure the bioavailability of K in this zeolite, wheat was grown in a glasshouse with K-zeolite N as the K fertiliser in highly-leached and non-leached pots for four weeks and compared with a soluble K fertiliser (KCl). The plants grown in non-leached pots and fertilised with K-zeolite N were slightly larger than those grown with KCl. The elemental compositions in the plants were similar except for Si being significantly more concentrated in the plants supplied with K-zeolite N. Thus K-zeolite N may be an effective K-fertiliser. Plants grown in highly-leached pots were significantly smaller than those grown in non-leached pots. Plants grown in highly-leached pots were severely K deficient as half of the K from both KCl and K-zeolite N was leached from the pots within three days.

Where not to have a Heart Attack in Australia!: The Cardiac ARIA Index

Background/aims: Access to appropriate health care following an acute cardiac event is important for positive outcomes. The aim of the Cardiac ARIA index was to derive an objective, comparable, geographic measure reflecting access to cardiac services across Australia. Methods: Geographic Information Systems (GIS) were used to model a numeric-alpha index based on acute management from onset of symptoms to return to the community. Acute time frames have been calculated to include time for ambulance to arrive, assess and load patient, and travel to facility by road 40–80 kph. Results: The acute phase of the index was modelled into five categories: 1 [24/7 percutaneous cardiac intervention (PCI) ≤1 h]; 2 [24/7 PCI 1–3 h, and PCI less than an additional hour to nearest accident and emergency room (A&E)]: 3 [Nearest A&E ≤3 h (no 24/7 PCI within an extra hour)]: 4 [Nearest A&E 3–12 h (no 24/7 PCI within an extra hour)]: 5 [Nearest A&E 12–24 h (no 24/7 PCI within an extra hour)]. Discharge care was modelled into three categories based on time to a cardiac rehabilitation program, retail pharmacy, pathology services, hospital, GP or remote clinic: (A) all services ≤30 min; (B) >30 min and ≤60 min; (C) >60 min. Examples of the index indicate that the majority of population locations within capital cities were category 1A; Alice Springs and Byron Bay were 3A; and the Northern Territory town of Maningrida had minimal access to cardiac services with an index ranking of 5C. Conclusion: The Cardiac ARIA index provides an invaluable tool to inform appropriate strategies for the use of scarce cardiac resources.

Development of distributed fuzzy systems with a runtime-adaptable mobile components framework

A distributed fuzzy system is a real-time fuzzy system in which the input, output and computation may be located on different networked computing nodes. The ability for a distributed software application, such as a distributed fuzzy system, to adapt to changes in the computing network at runtime can provide real-time performance improvement and fault-tolerance. This paper introduces an Adaptable Mobile Component Framework (AMCF) that provides a distributed dataflow-based platform with a fine-grained level of runtime reconfigurability. The execution location of small fragments (possibly as little as few machine-code instructions) of an AMCF application can be moved between different computing nodes at runtime. A case study is included that demonstrates the applicability of the AMCF to a distributed fuzzy system scenario involving multiple physical agents (such as autonomous robots). Using the AMCF, fuzzy systems can now be developed such that they can be distributed automatically across multiple computing nodes and are adaptable to runtime changes in the networked computing environment. This provides the opportunity to improve the performance of fuzzy systems deployed in scenarios where the computing environment is resource-constrained and volatile, such as multiple autonomous robots, smart environments and sensor networks.

Vibrational spectroscopic study of the copper silicate mineral ajoite (K,Na)Cu7AlSi9O24(OH)6•3H2O

Ajoite (K,Na)Cu7AlSi9O24(OH)6•3H2O is a mineral named after the Ajo district of Arizona. Raman and infrared spectroscopy were used to characterise the molecular structure of ajoite. The structure of the mineral shows disorder which is reflected in the difficulty of obtaining quality Raman spectra. The Raman spectrum is characterised by a broad spectral profile with a band at 1048 cm-1 assigned to the ν1 (A1g) symmetric stretching vibration. Strong bands at 962, 1015 and 1139 cm-1 are assigned to the ν3 SiO4 antisymmetric stretching vibrations. Multiple ν4 SiO4 vibrational modes indicate strong distortion of the SiO4 tetrahedra. Multiple AlO and CuO stretching bands are observed. Raman spectroscopy and confirmed by infrared spectroscopy clearly shows that hydroxyl units are involved in the ajoite structure. Based upon the infrared spectra, water is involved in the ajoite structure, probably as zeolitic water.

See-and-avoid quadcopter using fuzzy control optimized by cross-entropy

In this work we present an optimized fuzzy visual servoing system for obstacle avoidance using an unmanned aerial vehicle. The cross-entropy theory is used to optimise the gains of our controllers. The optimization process was made using the ROS-Gazebo 3D simulation with purposeful extensions developed for our experiments. Visual servoing is achieved through an image processing front-end that uses the Camshift algorithm to detect and track objects in the scene. Experimental flight trials using a small quadrotor were performed to validate the parameters estimated from simulation. The integration of cross- entropy methods is a straightforward way to estimate optimal gains achieving excellent results when tested in real flights.

Quadcopter see and avoid using a fuzzy controller

Unmanned Aerial Vehicles (UAVs) industry is a fast growing sector. Nowadays, the market offers numerous possibilities for off-the-shelf UAVs such as quadrotors or fixed-wings. Until UAVs demonstrate advance capabilities such as autonomous collision avoidance they will be segregated and restricted to flight in controlled environments. This work presents a visual fuzzy servoing system for obstacle avoidance using UAVs. To accomplish this task we used the visual information from the front camera. Images are processed off-board and the result send to the Fuzzy Logic controller which then send commands to modify the orientation of the aircraft. Results from flight test are presented with a commercial off-the-shelf platform.

UAS See-and-Avoid using two different approaches of Fuzzy Control

This work presents two UAS See and Avoid approaches using Fuzzy Control. We compare the performance of each controller when a Cross-Entropy method is applied to optimase the parameters for one of the controllers. Each controller receive information from an image processing front-end that detect and track targets in the environment. Visual information is then used under a visual servoing approach to perform autonomous avoidance. Experimental flight trials using a small quadrotor were performed to validate and compare the behaviour of both controllers

Intuitionistic fuzzy Choquet integral operator-based approach for black-start decision-making

Determining the optimal of black-start strategies is very important for speeding the restoration speed of a power system after a global blackout. Most existing black-start decision-making methods are based on the assumption that all indexes are independent of each other, and little attention has been paid to the group decision-making method which is more reliable. Given this background, the intuitionistic fuzzy set and further intuitionistic fuzzy Choquet integral operator are presented, and a black-start decision-making method based on this integral operator is presented. Compared to existing methods, the proposed algorithm cannot only deal with the relevance among the indexes, but also overcome some shortcomings of the existing methods. Finally, an example is used to demonstrate the proposed method. © 2012 The Institution of Engineering and Technology.

Inhibition of guinea-pig renal [Na + K]-ATPase by normotensive human plasma : effects of a high sodium diet

The effect of plasma taken from normotensive humans, while on a low and high sodium diet, on [Na + K]-ATPase and 3H-ouabain binding was measured in tubules from guinea-pig kidneys. Plasma from the high sodium, compared to the low sodium, diet period: (a) inhibited [Na + K]-ATPase activity; (b) decreased 3H-ouabain affinity for binding sites; (c) increased the number of available 3H-ouabain binding sites; (d) decreased [Na + K]-ATPase turnover (activity/3H-ouabain binding sites). The inhibition of [Na + K]-ATPase suggests an increase in a (possible) natriuretic factor. The decreased affinity of 3H-ouabain binding suggests an endogenous ouabainoid, which may be the natriuretic factor.

Book review: "English for telecoms and information technology" by T. Ricca and M. Duckworth; "English for legal professionals" by A. Frost; "English for the pharmaceutical industry" by M. Buchler, K. Jaehnig, G. Matzig, and T. Weindler; "English for cabin crews" by S. Ellis and L. Lansford; and "English for negotiating" by C. Lafond, S. Vine, and B. Welch.

This review examines five books in the Oxford Business English Express Series, including "English for telecoms and information technology" by T. Ricca and M. Duckworth; "English for legal professionals" by A. Frost; "English for the pharmaceutical industry" by M. Buchler, K. Jaehnig, G. Matzig, and T. Weindler; "English for cabin crews" by S. Ellis and L. Lansford; and "English for negotiating" by C. Lafond, S. Vine, and B. Welch.