Framework for the long-term operation of a mobile robot via the Internet

This paper describes an autonomous docking system and web interface that allows long-term unaided use of a sophisticated robot by untrained web users. These systems have been applied to the biologically inspired RatSLAM system as a foundation for testing both its long-term stability and its practicality. While docking and web interface systems already exist, this system allows for a significantly larger margin of error in docking accuracy due to the mechanical design, thereby increasing robustness against navigational errors. Also a standard vision sensor is used for both long-range and short-range docking, compared to the many systems that require both omni-directional cameras and high resolution Laser range finders for navigation. The web interface has been designed to accommodate the significant delays experienced on the Internet, and to facilitate the non- Cartesian operation of the RatSLAM system.

Predicting residue-wise contact orders in proteins by support vector regression

Background The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

Fractal and complex network analyses of protein molecular dynamics

Based on protein molecular dynamics, we investigate the fractal properties of energy, pressure and volume time series using the multifractal detrended fluctuation analysis (MF-DFA) and the topological and fractal properties of their converted horizontal visibility graphs (HVGs). The energy parameters of protein dynamics we considered are bonded potential, angle potential, dihedral potential, improper potential, kinetic energy, Van der Waals potential, electrostatic potential, total energy and potential energy. The shape of the h(q)h(q) curves from MF-DFA indicates that these time series are multifractal. The numerical values of the exponent h(2)h(2) of MF-DFA show that the series of total energy and potential energy are non-stationary and anti-persistent; the other time series are stationary and persistent apart from series of pressure (with H≈0.5H≈0.5 indicating the absence of long-range correlation). The degree distributions of their converted HVGs show that these networks are exponential. The results of fractal analysis show that fractality exists in these converted HVGs. For each energy, pressure or volume parameter, it is found that the values of h(2)h(2) of MF-DFA on the time series, exponent λλ of the exponential degree distribution and fractal dimension dBdB of their converted HVGs do not change much for different proteins (indicating some universality). We also found that after taking average over all proteins, there is a linear relationship between 〈h(2)〉〈h(2)〉 (from MF-DFA on time series) and 〈dB〉〈dB〉 of the converted HVGs for different energy, pressure and volume.

1H and 13C NMR study of pyridylamides and thionamides

1H and 13C NMR spectra are reported for several pyridylamides and thionamides. Complete analyses of the 13C spectra have yielded the chemical shifts and the direct and long range (13C, 1H) coupling constants. 13C chemical shifts show linear relationship with charge densities computed by the CNDO method. The variations in the chemical shifts are discussed.

Role of Capping Ligands on the Nanoparticles in the Modulation of Properties of a Hybrid Matrix of Nanoparticles in a 2D Film and in a Supramolecular Organogel

We incorporate various gold nanoparticles (AuNPs) capped with different ligands in two-dimensional films and three-dimensional aggregates derived from N-stearoyl-L-alanine and N-lauroyl-L-alanine, respectively. The assemblies of N-stearoyl-L-alanine afforded stable films at the air-water interface. More compact assemblies were formed upon incorporation of AuNPs in the air-water interface of N-stearoyl-L-alanine. We then examined the effects of incorporation of various AuNPs functionalized with different capping ligands in three-dimensional assemblies of N-lauroyl-L-alanine, a compound that formed a gel in hydrocarbons. The profound influence of nanoparticle incorporation into physical gels was evident from evaluation of various microscopic and bulk properties. The interaction of AuNPs with the gelator assembly was found to depend critically on the capping ligands protecting the Au surface of the gold nanoparticles. Transmission electron microscopy (TEM) showed a long-range directional assembly of certain AuNPs along the gel fibers. Scanning electron microscopy (SEM) images of the freeze-dried gels and nanocomposites indicate that the morphological transformation in the composite microstructures depends significantly on the capping agent of the nanoparticles. Differential scanning calorimetry (DSC) showed that gel formation from sol occurred at a lower temperature upon incorporation of AuNPs having capping ligands that were able to align and noncovalently interact with the gel fibers. Rheological studies indicate that the gel-nanoparticle composites exhibit significantly greater viscoelasticity compared to the native gel alone when the capping ligands are able to interact through interdigitation into the gelator assembly. Thus, it was possible to define a clear relationship between the materials and the molecular-level properties by means of manipulation of the information inscribed on the NP surface.

Worksite Fitness Policy in an Intellectual Capital Framework

In a framework of Intellectual Capital (IC), the effects and interactions of a Worksite Fitness Program (WFP) policy was studied with a multidisciplinary approach. In a preliminary study, indicators for physical activity (PAI), physical fitness (PFI), activity in WFP on a regular (WFPI) and on a events basis (WFPE) were created in line with positive findings regarding the associations between physical activity and fitness patterns and sick leave, perceived health, and self-assessed work ability. The intensity of physical activity was found to be the most important variable to predict positive associations with the above mentioned wellness parameters. In four case study follow-up settings, the effects and interactions of physical activity and fitness patterns and the company’s WFP-policy on different elements of IC were studied. Qualitative methods were applied in constructing indicators and a descriptive IC measure for each case company. In cross-sectional and follow-up settings, several findings with respect to IC were found regarding physical activity in general and activity in WFP in particular. Findings were relatively strong in health and wellness related indicators in Human Capital, where, as also in Structural Capital indicators such as the company climate and employee-superior relationship, revealed positive associations. Physical activity patterns were found to act in minor role in Relational Capital. Overall, WFP was seen to be an integrated part of Structural Capital. From the viewpoint of Worksite Fitness Program as a phenomenon, this study positioned WFP as an active element of Intellectual Capital. The literature in the field of WFP emphasizes the role of WFP as an instrument to activate employees in physical activity, and thus promote their health and wellbeing. With the wider perspective the active and long range WFP policy can support a company’s Structural and Relational Capital in line with the fundamental role it has on Human Capital.

Dislocation mechanisms for plastic flow of nickel in the temperature range 4.2 – 1200 K

The temperature ranges of thermal and athermal deformation behaviour of nickel are identified by employing the temperature-dependence of flow-stress and strain-rate cycling data. The results are used to present a unified view of dislocation mechanisms of glide encompassing the two thermally activated and the intermediate athermal regimes of plastic flow.In the low-temperature thermally activated region (<250 K) the strain rate is found to be controlled by the repulsive intersection of glide and forest dislocations, in accordance with current ideas. The athermal stress in this region can be attributed mainly to the presence of strong attractive junctions which are overcome by means of Orowan bowing, a small contribution also coming from the elastic interactions between dislocations. The values of activation area and activation energy obtained in the high-temperature region (> 750 K) negate the operation of a diffusion-controlled mechanism. Instead, the data support a thermal activation model involving unzipping of the attractive junctions. The internal (long-range) stress contribution here results solely from the elastic interactions between dislocations. This view concerning the high-temperature plastic flow is further supported by the observation that the Cottrell–Stokes law is obeyed over large strains in the range 750–1200 K.

First passage distributions for long memory processes

We study the distribution of first passage time for Levy type anomalous diffusion. A fractional Fokker-Planck equation framework is introduced.For the zero drift case, using fractional calculus an explicit analytic solution for the first passage time density function in terms of Fox or H-functions is given. The asymptotic behaviour of the density function is discussed. For the nonzero drift case, we obtain an expression for the Laplace transform of the first passage time density function, from which the mean first passage time and variance are derived.

Insights into the Fold Organization of TIM Barrel from Interaction Energy Based Structure Networks

There are many well-known examples of proteins with low sequence similarity, adopting the same structural fold. This aspect of sequence-structure relationship has been extensively studied both experimentally and theoretically, however with limited success. Most of the studies consider remote homology or ``sequence conservation'' as the basis for their understanding. Recently ``interaction energy'' based network formalism (Protein Energy Networks (PENs)) was developed to understand the determinants of protein structures. In this paper we have used these PENs to investigate the common non-covalent interactions and their collective features which stabilize the TIM barrel fold. We have also developed a method of aligning PENs in order to understand the spatial conservation of interactions in the fold. We have identified key common interactions responsible for the conservation of the TIM fold, despite high sequence dissimilarity. For instance, the central beta barrel of the TIM fold is stabilized by long-range high energy electrostatic interactions and low-energy contiguous vdW interactions in certain families. The other interfaces like the helix-sheet or the helix-helix seem to be devoid of any high energy conserved interactions. Conserved interactions in the loop regions around the catalytic site of the TIM fold have also been identified, pointing out their significance in both structural and functional evolution. Based on these investigations, we have developed a novel network based phylogenetic analysis for remote homologues, which can perform better than sequence based phylogeny. Such an analysis is more meaningful from both structural and functional evolutionary perspective. We believe that the information obtained through the ``interaction conservation'' viewpoint and the subsequently developed method of structure network alignment, can shed new light in the fields of fold organization and de novo computational protein design.

A novel acoustic-vibratory multimodal duet

The communication strategy of most crickets and bushcrickets typically consists of males broadcasting loud acoustic calling songs, while females perform phonotaxis, moving towards the source of the call. Males of the pseudophylline bushcricket species Onomarchus uninotatus produce an unusually low-pitched call, and we found that the immediate and most robust response of females to the male acoustic call was a bodily vibration, or tremulation, following each syllable of the call. We hypothesized that these bodily oscillations might send out a vibrational signal along the substrate on which the female stands, which males could use to localize her position. We quantified these vibrational signals using a laser vibrometer and found a clear phase relationship of alternation between the chirps of the male acoustic call and the female vibrational response. This system therefore constitutes a novel multimodal duet with a reliable temporal structure. We also found that males could localize the source of vibration but only if both the acoustic and vibratory components of the duet were played back. This unique multimodal duetting system may have evolved in response to higher levels of bat predation on searching bushcricket females than calling males, shifting part of the risk associated with partner localization onto the male. This is the first known example of bushcricket female tremulation in response to a long-range male acoustic signal and the first known example of a multimodal duet among animals.

Influence of composition on the structure, electric and magnetic properties of Pd-Mn-P and Pd-Co-P amorphous alloys

The influence of composition on the structure and on the electric and magnetic properties of amorphous Pd-Mn-P and Pd-Co-P prepared by rapid quenching techniques were investigated in terms of (1) the 3d band filling of the first transition metal group, (2) the phosphorus concentration effect which acts as an electron donor and (3) the transition metal concentration.

The structure is essentially characterized by a set of polyhedra subunits essentially inverse to the packing of hard spheres in real space. Examination of computer generated distribution functions using Monte Carlo random statistical distribution of these polyhedra entities demonstrated tile reproducibility of the experimentally calculated atomic distribution function. As a result, several possible "structural parameters" are proposed such as: the number of nearest neighbors, the metal-to-metal distance, the degree of short-range order and the affinity between metal-metal and metal-metalloid. It is shown that the degree of disorder increases from Ni to Mn. Similar behavior is observed with increase in the phosphorus concentration.

The magnetic properties of Pd-Co-P alloys show that they are ferromagnetic with a Curie temperature between 272 and 399°K as the cobalt concentration increases from 15 to 50 at.%. Below 20 at.% Co the short-range exchange interactions which produce the ferromagnetism are unable to establish a long-range magnetic order and a peak in the magnetization shows up at the lowest temperature range . The electric resistivity measurements were performed from liquid helium temperatures up to the vicinity of the melting point (900°K). The thermomagnetic analysis was carried out under an applied field of 6.0 kOe. The electrical resistivity of Pd-Co-P shows the coexistence of a Kondo-like minimum with ferromagnetism. The minimum becomes less important as the transition metal concentration increases and the coefficients of ℓn T and T^2 become smaller and strongly temperature dependent. The negative magnetoresistivity is a strong indication of the existence of localized moment.

The temperature coefficient of resistivity which is positive for Pd- Fe-P, Pd-Ni-P, and Pd-Co-P becomes negative for Pd-Mn-P. It is possible to account for the negative temperature dependence by the localized spin fluctuation model and the high density of states at the Fermi energy which becomes maximum between Mn and Cr. The magnetization curves for Pd-Mn-P are typical of those resulting from the interplay of different exchange forces. The established relationship between susceptibility and resistivity confirms the localized spin fluctuation model. The magnetoresistivity of Pd-Mn-P could be interpreted in tenns of a short-range magnetic ordering that could arise from the Rudennan-Kittel type interactions.

Diving behavior of immature Steller sea lions (Eumetopias jubatus)

Understanding the ontogenetic relationship between juvenile Steller sea lions (Eumetopias jubatus) and their foraging habitat is key to understanding their relationship to available prey and ultimately their survival. We summarize dive and movement data from 13 young-of-the-year (YOY) and 12 yearling Steller sea lions equipped with satellite dive recorders in the Gulf of Alaska and Aleutian Islands (n=18), and Washington (n=7) from 1994 to 2000. A total of 1413 d of transmission (x =56.5 d, range: 14.5–104.1 d) were received. We recorded 222,073 dives, which had a mean depth of 18.4 m (range of means: 5.8−67.9 m; SD=16.4). Alaska YOY dived for shorter periods and at shallower depths (mean depth=7.7 m, mean duration=0.8 min, mean maximum depth=25.7 m, and maximum depth=252 m) than Alaska yearlings (x =16.6 m, 0=1.1 min, x = 63.4 m, 288 m), whereas Washington yearlings dived the longest and deepest (mean depth=39.4 m, mean duration=1.8 min, mean maximum depth=144.5 m, and maximum depth=328 m). Mean distance for 564 measured trips was 16.6 km; for sea lions ≤10 months of age, trip distance (7.0 km) was significantly less than for those >10 months of age (24.6 km). Mean trip duration for 10 of the 25 sea lions was 12.1 h; for sea lions ≤10 months of age, trip duration was 7.5 h and 18.1 h for those >10 months of age. We identified three movements types: long-range trips (>15 km and >20 h), short-range trips (<15 km and <20 h) during which the animals left and returned to the same site, and transits to other haul-out sites. Long-range trips started around 9 months of age and occurred most frequently around the assumed time of weaning, whereas short-range trips happened almost daily (0.9 trips/day, n=426 trips). Transits began as early as 7 months of age, occurred more often after 9 months of age, and ranged between 6.5 and 454 km. The change in dive characteristics coincided with the assumed onset of weaning. These yearling sea lion movement patterns and dive characteristics suggest that immature Steller sea lions are as capable of making the same types of movements as adults.

Geographical constraints to range-based attacks on links in complex networks

In this paper, we studied range-based attacks on links in geographically constrained scale-free networks and found that there is a continuous switching of roles of short-and long-range attacks on links when tuning the geographical constraint strength. Our results demonstrate that the geography has a significant impact on the network efficiency and security; thus one can adjust the geographical structure to optimize the robustness and the efficiency of the networks. We introduce a measurement of the impact of links on the efficiency of the network, and an effective attacking strategy is suggested