Covering Dimension of C*-Algebras and 2-Coloured Classification

Peer reviewed

Near-bed hydrodynamics and turbulence below a large-scale plunging breaking wave over a mobile barred bed profile

Funded by The research presented in this paper is part of the SINBAD project. Grant Number: STW (12058) and EPSRC (EP/J00507X/1, EP/J005541/1)

Experimentally estimated dead space for GaAs and InP based planar Gunn diodes

The authors would like to thank the staff of the James Watt Nanofabrication Centre at the University of Glasgow for help in fabricating the devices which is reported in this paper. ‘Part of this work was supported by ESPRC through EP/H011862/ 1, and EP/H012966/1.

'Digital by Default' and the 'hard to reach' : exploring solutions to digital exclusion in remote rural areas

The research reported here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub [award reference: EP/G066051/1].

Control and prediction for blackouts caused by frequency collapse in smart grids

C.-W.W. is supported by a studentship funded by the College of Physical Sciences, University of Aberdeen. M.S.B. acknowledges EPSRC grant NO. EP/I032606/1.

Effects of a 12-week aerobic exercise intervention on eating behaviour, food cravings and 7-day energy intake and energy expenditure in inactive men

This study examined effects of 12 weeks of moderate-intensity aerobic exercise on eating behaviour, food cravings and weekly energy intake and expenditure in inactive men. Eleven healthy men (mean ± SD: age, 26 ± 5 years; body mass index, 24.6 ± 3.8 kg/m2; maximum oxygen uptake, 43.1 ± 7.4 mL/kg/min) completed the 12-week supervised exercise programme. Body composition, health markers (e.g. blood pressure), eating behaviour, food cravings and weekly energy intake and expenditure were assessed before and after the exercise intervention. There were no intervention effects on weekly free-living energy intake (p=0.326, d=-0.12) and expenditure (p=0.799, d=0.04), or uncontrolled eating and emotional eating scores (p>0.05). However, there was a trend with a medium effect size (p=0.058, d=0.68) for cognitive restraint to be greater after the exercise intervention. Total food cravings (p=0.009, d=-1.19) and specific cravings of high-fat foods (p=0.023, d=-0.90), fast-food fats (p=0.009, d=-0.71) and carbohydrates/starches (p=0.009, d=-0.56) decreased from baseline to 12 weeks. Moreover, there was a trend with a large effect size for cravings of sweets (p=0.052, d=-0.86) to be lower after the exercise intervention. In summary, 12 weeks of moderate-intensity aerobic exercise reduced food cravings and increased cognitive restraint, however, these were not accompanied by changes in other eating behaviours and weekly energy intake and expenditure. The results indicate the importance of exercising for health improvements even when reductions in body mass are modest.

Challenges in imaging and predictive modeling of rhizosphere processes

Background Plant-soil interaction is central to human food production and ecosystem function. Thus, it is essential to not only understand, but also to develop predictive mathematical models which can be used to assess how climate and soil management practices will affect these interactions. Scope In this paper we review the current developments in structural and chemical imaging of rhizosphere processes within the context of multiscale mathematical image based modeling. We outline areas that need more research and areas which would benefit from more detailed understanding. Conclusions We conclude that the combination of structural and chemical imaging with modeling is an incredibly powerful tool which is fundamental for understanding how plant roots interact with soil. We emphasize the need for more researchers to be attracted to this area that is so fertile for future discoveries. Finally, model building must go hand in hand with experiments. In particular, there is a real need to integrate rhizosphere structural and chemical imaging with modeling for better understanding of the rhizosphere processes leading to models which explicitly account for pore scale processes.

Towards a smart semi-active prosthetic leg: preliminary assessment and testing

This paper presents a development of a semi-active prosthetic knee, which can work in both active and passive modes based on the energy required during the gait cycle of various activities of daily livings (ADLs). The prosthetic limb is equipped with various sensors to measure the kinematic and kinetic parameters of both prosthetic limbs. This prosthetic knee is designed to be back-drivable in passive mode to provide a potential use in energy regeneration when there negative energy across the knee joint. Preliminary test has been performed on transfemoral amputee in passive mode to provide some insight to the amputee/prosthesis interaction and performance with the designed prosthetic knee.

Absorption of planar waves in a draining bathtub

We present an analysis of the absorption of acoustic waves by a black hole analogue in (2 + 1) dimensions generated by a fluid flow in a draining bathtub. We show that the low-frequency absorption length is equal to the acoustic hole circumference and that the high-frequency absorption length is 4 times the ergoregion radius. For intermediate values of the wave frequency, we compute the absorption length numerically and show that our results are in excellent agreement with the low-and high-frequency limits. We analyze the occurrence of superradiance, manifested as negative partial absorption lengths for corotating modes at low frequencies.

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

Use of the q-Gaussian mutation in evolutionary algorithms

This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q-Gaussian mutation distribution is controlled by a real parameter q. In the proposed method, the real parameter q of the q-Gaussian mutation is encoded in the chromosome of individuals and hence is allowed to evolve during the evolutionary process. In order to test the new mutation operator, evolution strategy and evolutionary programming algorithms with self-adapted q-Gaussian mutation generated from anisotropic and isotropic distributions are presented. The theoretical analysis of the q-Gaussian mutation is also provided. In the experimental study, the q-Gaussian mutation is compared to Gaussian and Cauchy mutations in the optimization of a set of test functions. Experimental results show the efficiency of the proposed method of self-adapting the mutation distribution in evolutionary algorithms.

Crowdsourcing without a crowd : Reliable online species identification using Bayesian models to minimize crowd size

Acknowledgment This research is supported by an award made by the RCUK Digital Economy program to the University of Aberdeen’s dot.rural Digital Economy Hub (ref. EP/G066051/1).

Human Search for a Target on a Textured Background is Consistent with a Stochastic Model

This research was supported by the James S. McDonnell Foundation (ARH). Early version was supported by EPSRC grants EP/F02553X/1 and EP/D059364/1.

Interrogating Capabilities of IoT Devices

This research is supported by the UK Research Councils’ Digital Economy IT as a Utility Network+ (EP/K003569/1) and the dot.rural Digital Economy Hub (EP/G066051/1).

Interrogating Capabilities of IoT Devices

This research is supported by the UK Research Councils’ Digital Economy IT as a Utility Network+ (EP/K003569/1) and the dot.rural Digital Economy Hub (EP/G066051/1).