Scaling and non-scaling of muscle activity, kinematics, and dynamics in sit-ups with different degrees of difficulty

The purpose of this study was to investigate how the CNS adjusts motor patterns for variants of a complex axial movement-the situp. Adjustments were induced by changing the support surface contact and mass distribution of the body. Healthy adults performed straight-legged sit-ups, 3 s in duration, with support added to or removed from the lumbar trunk, or with mass added to the head or to the legs. Each of these interventions either increased or decreased the difficulty of the task. The study addressed the extent to which changes in sit-up difficulty are compensated by scaling of muscle activity, kinematics, and dynamics versus the extent to which they are compensated by changing discretely the motor pattern. The analysis of muscle activity, kinematics, and dynamics focused on the first 30-40% of the sit-up-the trunk flexion phase-since this is the most critical part of the movement. Our results demonstrate that, in some respects, sit-up kinematics and dynamics scaled with difficulty, but in other respects, they did not. Muscle activity also scaled, in many respects, but in more difficult sit-ups, abdominal flexor activity decreased instead of increased. Non-scaling changes in these parameters suggest that complex movements, such as the sit-up, may require discrete changes in motor pattern in order to deal with large loads, which challenge the available leverage. (C) 2005 Elsevier Ltd. All rights reserved.

The emergence of order in random walk resource discovery protocols

While others have attempted to determine, by way of mathematical formulae, optimal resource duplication strategies for random walk protocols, this paper is concerned with studying the emergent effects of dynamic resource propagation and replication. In particular, we show, via modelling and experimentation, that under any given decay (purge) rate the number of nodes that have knowledge of particular resource converges to a fixed point or a limit cycle. We also show that even for high rates of decay - that is, when few nodes have knowledge of a particular resource - the number of hops required to find that resource is small.

Using Q-methodology to study the metaphors of consumption for mobile phone users

Even before business has really come to grips with the intricacies of incorporating emarketing and e-commerce into their organisational strategies, they are now being encouraged to make significant investments in developing capabilities for mobile phone marketing. Fuelled once again by huge profit predictions reminiscent of the mid-1990s when speaking of e-commerce (Anckar and D’Incau 2002) marketers are tapping into this mobility. So, instead of having to drive consumers to web sites through the ‘sit and search’ context, marketers are now exploring ways to develop strategies to deliver relevant and timely information in a ‘roam and receive’ context directly to their potential customers anywhere, anytime, any place (Mort and Drennan 2002).

Not if but when: Out-group reactions to the timing of disclosure of an individual's same-sex attractions

One factor that research suggests impedes positive contact between outgroup members is the experience of anxiety that can occur when anticipating negative consequences of such interactions. Research examining attitudes and behaviour towards same-sex attracted individuals indicates that this intergroup anxiety is particularly evident when the anticipated interaction involves members of the same gender. The current studies investigate the effect of timing of disclosure of a person’s same-sex attractions in an effort to identify a means of reducing this anxiety. Study 1 uses a hypothetical scenario to gain insight into participants’ stated preferences for early or delayed knowledge of a person’s sexual orientation. Results reveal an association between experiencing close contact with gay individuals of the same gender in real life (but not opposite gender), and a preference for early disclosure. Results from an experimental study concur with these findings. After a face-to-face interaction task with a confederate of the same gender, participants sit further from the confederate for the late disclosure condition when compared with the early disclosure and no disclosure control. Future studies investigating the interaction between timing of disclosure of same-sex attractions and the intimacy of disclosure (casual vs. intimate), are discussed.

Using non-parametric search algorithms to forecast daily excess stock returns

Are the learning procedures of genetic algorithms (GAs) able to generate optimal architectures for artificial neural networks (ANNs) in high frequency data? In this experimental study,GAs are used to identify the best architecture for ANNs. Additional learning is undertaken by the ANNs to forecast daily excess stock returns. No ANN architectures were able to outperform a random walk,despite the finding of non-linearity in the excess returns. This failure is attributed to the absence of suitable ANN structures and further implies that researchers need to be cautious when making inferences from ANN results that use high frequency data.

Molecular phase space transport in water:non-stationary random walk model

Molecular transport in phase space is crucial for chemical reactions because it defines how pre-reactive molecular configurations are found during the time evolution of the system. Using Molecular Dynamics (MD) simulated atomistic trajectories we test the assumption of the normal diffusion in the phase space for bulk water at ambient conditions by checking the equivalence of the transport to the random walk model. Contrary to common expectations we have found that some statistical features of the transport in the phase space differ from those of the normal diffusion models. This implies a non-random character of the path search process by the reacting complexes in water solutions. Our further numerical experiments show that a significant long period of non-stationarity in the transition probabilities of the segments of molecular trajectories can account for the observed non-uniform filling of the phase space. Surprisingly, the characteristic periods in the model non-stationarity constitute hundreds of nanoseconds, that is much longer time scales compared to typical lifetime of known liquid water molecular structures (several picoseconds).

Evolution, recurrency and kernels in learning to model inflation

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. We use non-linear, artificial intelligence techniques, namely, recurrent neural networks, evolution strategies and kernel methods in our forecasting experiment. In the experiment, these three methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. There is evidence in the literature that evolutionary methods can be used to evolve kernels hence our future work should combine the evolutionary and kernel methods to get the benefits of both.

On Multi-Dimensional Random Walk Models Approximating Symmetric Space-Fractional Diffusion Processes

Mathematics Subject Classification: 26A33, 47B06, 47G30, 60G50, 60G52, 60G60.

A quantum Jensen-Shannon graph kernel using the continuous-time quantum walk

In this paper, we use the quantum Jensen-Shannon divergence as a means to establish the similarity between a pair of graphs and to develop a novel graph kernel. In quantum theory, the quantum Jensen-Shannon divergence is defined as a distance measure between quantum states. In order to compute the quantum Jensen-Shannon divergence between a pair of graphs, we first need to associate a density operator with each of them. Hence, we decide to simulate the evolution of a continuous-time quantum walk on each graph and we propose a way to associate a suitable quantum state with it. With the density operator of this quantum state to hand, the graph kernel is defined as a function of the quantum Jensen-Shannon divergence between the graph density operators. We evaluate the performance of our kernel on several standard graph datasets from bioinformatics. We use the Principle Component Analysis (PCA) on the kernel matrix to embed the graphs into a feature space for classification. The experimental results demonstrate the effectiveness of the proposed approach. © 2013 Springer-Verlag.

A continuous-time quantum walk kernel for unattributed graphs

Kernel methods provide a way to apply a wide range of learning techniques to complex and structured data by shifting the representational problem from one of finding an embedding of the data to that of defining a positive semidefinite kernel. In this paper, we propose a novel kernel on unattributed graphs where the structure is characterized through the evolution of a continuous-time quantum walk. More precisely, given a pair of graphs, we create a derived structure whose degree of symmetry is maximum when the original graphs are isomorphic. With this new graph to hand, we compute the density operators of the quantum systems representing the evolutions of two suitably defined quantum walks. Finally, we define the kernel between the two original graphs as the quantum Jensen-Shannon divergence between these two density operators. The experimental evaluation shows the effectiveness of the proposed approach. © 2013 Springer-Verlag.

Spiral Walk Exposed

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015

Probabilistic Approach to the Neumann Problem for a Symmetric Operator

2000 Mathematics Subject Classification: Primary 60J45, 60J50, 35Cxx; Secondary 31Cxx.

The Euro Area's Tightrope Walk: Debt and Competitiveness in Italy and Spain

- Competitiveness adjustment in struggling southern euro-area members requires persistently lower inflation than in major trading partners, but low inflation worsens public debt sustainability. When average euro-area inflation undershoots the two percent target, the conflict between intra-euro relative price adjustment and debt sustainability is more severe. - In our baseline scenario, the projected public debt ratio reduction in Italy and Spain is too slow and does not meet the European fiscal rule. Debt projections are very sensitive to underlying assumptions and even small negative deviations from GDP growth, inflation and budget surplus assumptions can easily result in a runaway debt trajectory. - The case for a greater than five percent of GDP primary budget surplus is very weak. Beyond vitally important structural reforms, the top priority is to ensure that euro-area inflation does not undershoot the two percent target, which requires national policy actions and more accommodative monetary policy. The latter would weaken the euro exchange rate, thereby facilitating further intra-euro adjustment. More effective policies are needed to foster growth. But if all else fails, the European Central Bank’s Outright Monetary Transactions could reduce borrowing costs.

TV news team covering Walk-a-thon for ERA

Inscriptions: Verso: [stamped] Credit must be given to Leinwand from Monkmeyer Press Photo Service]

The relationship between changes in cardiovascular function and changes in VO2peak following SIT

Background: It is well known that sprint interval training (SIT), induces significant increases in peak oxygen uptake (VO2peak) at the group level. However, there have been only a few studies that have addressed the variability of VO2peak response following SIT, and precise mechanism(s) that may explain individual magnitude of response are unknown. Purpose: Therefore, the purpose of this thesis was to: 1) examine the inter-individual variability of the VO2peak response following SIT, 2) to inspect the relationship between changes in both central and peripheral measures and changes in VO2peak, and 3) to assess if peripheral or central adaptations play a role in whether an individual is a high or low responder with respect to VO2peak. Subjects: Twenty-two young, recreationally active males (age: 20.4 1.7 years; weight: 78.4 10.2 kg; VO2peak: 3.7 0.62 L/min) Methods: VO2peak (L/min), peak cardiac output (Qpeak [L/min]), and peak deoxygenated hemoglobin (HHbpeak [mM]) were measured before and after 16 sessions of SIT (Tabata Protocol) over four weeks. Peak a-vO2diff was calculated using a derivation of the Fick equation. Results: Due to a systematic error, HHbpeak could not be used to differentiate between individual responses. There was a large range of VO2peak response from pre to post testing (-4.75 to 32.18% change) and there was a significant difference between the Low Response Group (LRG) (n=8) and the High Response Group (HRG) (n=8) [f(1, 14)= 64.27, p<0.001]. Furthermore, there was no correlation between delta () VO2peak and Qpeak (r=-0.18, p=0.46) for all participants, nor was there an interaction effect between the Low and High Response Groups [f(1,11)=0.572, p=0.47]. Lastly, there was a significant correlation between VO2peak and peak a-vO2diff [r=0.692, p<0.001], and a significant interaction effect with peak a-vO2diff [f(1, 14)= 13.27, p<0.004] when comparing the HRG to the LRG. Conclusions: There was inter-individual variability of VO2peak response following 4 weeks of SIT, but central adaptations did not influence this variation. This suggests that peripheral adaptations may be responsible for VO2peak adaptation.