Dots versus antidots : computational exploration of structure, magnetism, and half-metallicity in boron−nitride nanostructures

Triangle-shaped nanohole, nanodot, and lattice antidot structures in hexagonal boron-nitride (h-BN) monolayer sheets are characterized with density functional theory calculations utilizing the local spin density approximation. We find that such structures may exhibit very large magnetic moments and associated spin splitting. N-terminated nanodots and antidots show strong spin anisotropy around the Fermi level, that is, half-metallicity. While B-terminated nanodots are shown to lack magnetism due to edge reconstruction, B-terminated nanoholes can retain magnetic character due to the enhanced structural stability of the surrounding two-dimensional matrix. In spite of significant lattice contraction due to the presence of multiple holes, antidot super lattices are predicted to be stable, exhibiting amplified magnetism as well as greatly enhanced half-metallicity. Collectively, the results indicate new opportunities for designing h-BNbased nanoscale devices with potential applications in the areas of spintronics, light emission, and photocatalysis.

Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

Correlations between designability and various structural characteristics of protein lattice models

Using six kinds of lattice types (4×4 ,5×5 , and6×6 square lattices;3×3×3 cubic lattice; and2+3+4+3+2 and4+5+6+5+4 triangular lattices), three different size alphabets (HP ,HNUP , and 20 letters), and two energy functions, the designability of proteinstructures is calculated based on random samplings of structures and common biased sampling (CBS) of proteinsequence space. Then three quantities stability (average energy gap),foldability, and partnum of the structure, which are defined to elucidate the designability, are calculated. The authors find that whatever the type of lattice, alphabet size, and energy function used, there will be an emergence of highly designable (preferred) structure. For all cases considered, the local interactions reduce degeneracy and make the designability higher. The designability is sensitive to the lattice type, alphabet size, energy function, and sampling method of the sequence space. Compared with the random sampling method, both the CBS and the Metropolis Monte Carlo sampling methods make the designability higher. The correlation coefficients between the designability, stability, and foldability are mostly larger than 0.5, which demonstrate that they have strong correlation relationship. But the correlation relationship between the designability and the partnum is not so strong because the partnum is independent of the energy. The results are useful in practical use of the designability principle, such as to predict the proteintertiary structure.

Models of collective cell behaviour with crowding effects : comparing lattice-based and lattice-free approaches

Individual-based models describing the migration and proliferation of a population of cells frequently restrict the cells to a predefined lattice. An implicit assumption of this type of lattice based model is that a proliferative population will always eventually fill the lattice. Here we develop a new lattice-free individual-based model that incorporates cell-to-cell crowding effects. We also derive approximate mean-field descriptions for the lattice-free model in two special cases motivated by commonly used experimental setups. Lattice-free simulation results are compared to these mean-field descriptions and to a corresponding lattice-based model. Data from a proliferation experiment is used to estimate the parameters for the new model, including the cell proliferation rate, showing that the model fits the data well. An important aspect of the lattice-free model is that the confluent cell density is not predefined, as with lattice-based models, but an emergent model property. As a consequence of the more realistic, irregular configuration of cells in the lattice-free model, the population growth rate is much slower at high cell densities and the population cannot reach the same confluent density as an equivalent lattice-based model.

Rate of torque and electromyographic development during anticipated eccentric contraction is lower in previously strained hamstrings

Background: Hamstring strain injuries are prevalent in sport and re-injury rates have been high for many years. Whilst much focus has centred on the impact of previous hamstring strain injury on maximal eccentric strength, high rates of torque development is also of interest, given the important role of the hamstrings during the terminal swing phase of running. The impact of prior strain injury on myoelectrical activity of the hamstrings during tasks requiring high rates of torque development has received little attention. Purpose: To determine if recreational athletes with a history of unilateral hamstring strain injury, who have returned to training and competition, will exhibit lower levels of myoelectrical activity during eccentric contraction, rate of torque development and impulse 30, 50 and 100ms after the onset of myoelectrical activity or torque development in the previously injured limb compared to the uninjured limb. Study design: Case-control study Methods: Twenty-six recreational athletes were recruited. Of these, 13 athletes had a history of unilateral hamstring strain injury (all confined to biceps femoris long head) and 13 had no history of hamstring strain injury. Following familiarisation, all athletes undertook isokinetic dynamometry testing and surface electromyography assessment of the biceps femoris long head and medial hamstrings during eccentric contractions at -60 and -1800.s-1. Results: In the injured limb of the injured group, compared to the contralateral uninjured limb rate of torque development and impulse was lower during -600.s-1 eccentric contractions at 50 (RTD, injured limb = 312.27 ± 191.78Nm.s-1 vs. uninjured limb = 518.54 ± 172.81Nm.s-1, p=0.008; IMP, injured limb = 0.73 ± 0.30 Nm.s vs. uninjured limb = 0.97 ± 0.23 Nm.s, p=0.005) and 100ms (RTD, injured limb = 280.03 ± 131.42Nm.s-1 vs. uninjured limb = 460.54.54 ± 152.94Nm.s-1,p=0.001; IMP, injured limb = 2.15 ± 0.89 Nm.s vs. uninjured limb = 3.07 ± 0.63 Nm.s, p<0.001) after the onset of contraction. Biceps femoris long head muscle activation was lower at 100ms at both contraction speeds (-600.s-1, normalised iEMG activity (x1000), injured limb = 26.25 ± 10.11 vs. uninjured limb 33.57 ± 8.29, p=0.009; -1800.s-1, normalised iEMG activity (x1000), injured limb = 31.16 ± 10.01 vs. uninjured limb 39.64 ± 8.36, p=0.009). Medial hamstring activation did not differ between limbs in the injured group. Comparisons in the uninjured group showed no significant between limbs difference for any variables. Conclusion: Previously injured hamstrings displayed lower rate of torque development and impulse during slow maximal eccentric contraction compared to the contralateral uninjured limb. Lower myoelectrical activity was confined to the biceps femoris long head. Regardless of whether these deficits are the cause of or the result of injury, these findings could have important implications for hamstring strain injury and re-injury. Particularly, given the importance of high levels of muscle activity to bring about specific muscular adaptations, lower levels of myoelectrical activity may limit the adaptive response to rehabilitation interventions and suggest greater attention be given to neural function of the knee flexors following hamstring strain injury.

Impact of previous hamstring strain injury on rate of torque and EMG development during eccentric contraction.

Background: Hamstring strain injuries (HSIs) are prevalent in sport and re-injury rates have been high for many years. Whilst much focus has centred on the impact of previous hamstring strain injury on maximal eccentric strength, high rates of torque development is also of interest, given the important role of the hamstrings during the terminal swing phase of gait. The impact of prior strain injury on neuromuscular function of the hamstrings during tasks requiring high rates of torque development has received little attention. The purpose of this study is to determine if recreational athletes with a history of unilateral hamstring strain injury, who have returned to training and competition, will exhibit lower levels of eccentric muscle activation, rate of torque development and impulse 30, 50 and 100ms after the onset of electromyographical or torque development in the previously injured limb compared to the uninjured limb. Methods: Twenty-six recreational athletes were recruited. Of these, 13 athletes had a history of unilateral hamstring strain injury (all confined to biceps femoris long head) and 13 had no history of hamstring strain injury. Following familiarisation, all athletes undertook isokinetic dynamometry testing and surface electromyography assessment of the biceps femoris long head and medial hamstrings during eccentric contractions at -60 and -1800.s-1. Results: In the injured limb of the injured group, compared to the contralateral uninjured limb rate of torque development and impulse was lower during -600.s-1 eccentric contractions at 50 (RTD, p=0.008; IMP, p=0.005) and 100ms (RTD, p=0.001; IMP p<0.001) after the onset of contraction. There was also a non-significant trend for rate of torque development during -1800.s-1 to be lower 100ms after onset of contraction (p=0.064). Biceps femoris long head muscle activation was lower at 100ms at both contraction speeds (-600.s-1, p=0.009; -1800.s-1, p=0.009). Medial hamstring activation did not differ between limbs in the injured group. Comparisons in the uninjured group showed no significant between limbs difference for any variables. Conclusion: Previously injured hamstrings displayed lower rate of torque development and impulse during eccentric contraction. Lower muscle activation was confined to the biceps femoris long head. Regardless of whether these deficits are the cause of or the result of injury, these findings have important implications for hamstring strain injury and re-injury and suggest greater attention be given to neural function of the knee flexors.

An accurate numerical scheme for the contraction of a bubble in a Hele-Shaw cell

We report on an accurate numerical scheme for the evolution of an inviscid bubble in radial Hele-Shaw flow, where the nonlinear boundary effects of surface tension and kinetic undercooling are included on the bubble-fluid interface. As well as demonstrating the onset of the Saffman-Taylor instability for growing bubbles, the numerical method is used to show the effect of the boundary conditions on the separation (pinch-off) of a contracting bubble into multiple bubbles, and the existence of multiple possible asymptotic bubble shapes in the extinction limit. The numerical scheme also allows for the accurate computation of bubbles which pinch off very close to the theoretical extinction time, raising the possibility of computing solutions for the evolution of bubbles with non-generic extinction behaviour.

Lattice-free models of cell invasion : discrete simulations and travelling waves

Invasion waves of cells play an important role in development, disease and repair. Standard discrete models of such processes typically involve simulating cell motility, cell proliferation and cell-to-cell crowding effects in a lattice-based framework. The continuum-limit description is often given by a reaction–diffusion equation that is related to the Fisher–Kolmogorov equation. One of the limitations of a standard lattice-based approach is that real cells move and proliferate in continuous space and are not restricted to a predefined lattice structure. We present a lattice-free model of cell motility and proliferation, with cell-to-cell crowding effects, and we use the model to replicate invasion wave-type behaviour. The continuum-limit description of the discrete model is a reaction–diffusion equation with a proliferation term that is different from lattice-based models. Comparing lattice based and lattice-free simulations indicates that both models lead to invasion fronts that are similar at the leading edge, where the cell density is low. Conversely, the two models make different predictions in the high density region of the domain, well behind the leading edge. We analyse the continuum-limit description of the lattice based and lattice-free models to show that both give rise to invasion wave type solutions that move with the same speed but have very different shapes. We explore the significance of these differences by calibrating the parameters in the standard Fisher–Kolmogorov equation using data from the lattice-free model. We conclude that estimating parameters using this kind of standard procedure can produce misleading results.

Contraction-induced changes in TNFα and Akt-mediated signalling are associated with increased myofibrillar protein in rat skeletal muscle

Resistance training results in skeletal muscle hypertrophy, but the molecular signalling mechanisms responsible for this altered phenotype are incompletely understood. We used a resistance training (RT) protocol consisting of three sessions [day 1 (d1), day 3 (d3), day 5 (d5)] separated by 48 h recovery (squat exercise, 4 sets × 10 repetitions, 3 min recovery) to determine early signalling responses to RT in rodent skeletal muscle. Six animals per group were killed 3 h after each resistance training session and 24 and 48 h after the last training session (d5). There was a robust increase in TNF? protein expression, and IKKSer180/181 and p38MAPK Thr180/Tyr182 phosphorylation on d1 (P < 0.05), which abated with subsequent RT, returning to control levels by d5 for TNF? and IKK Ser180/181. There was a trend for a decrease in MuRF-1 protein expression, 48 h following d5 of training (P = 0.08). Notably, muscle myofibrillar protein concentration was elevated compared to control 24 and 48 h following RT (P < 0.05). AktSer473 and mTORSer2448 phosphorylation were unchanged throughout RT. Phosphorylation of p70S6k Thr389 increased 3 h post-exercise on d1, d3 and d5 (P < 0.05), whilst phosphorylation of S6Ser235/236 increased on d1 and d3 (P < 0.05). Our results show a rapid attenuation of inflammatory signalling with repeated bouts of resistance exercise, concomitant with summation in translation initiation signalling in skeletal muscle. Indeed, the cumulative effect of these signalling events was associated with myofibrillar protein accretion, which likely contributes to the early adaptations in response to resistance training overload in the skeletal muscle.

Lattice-free descriptions of collective motion with crowding and adhesion

Cell-to-cell adhesion is an important aspect of malignant spreading that is often observed in images from the experimental cell biology literature. Since cell-to-cell adhesion plays an important role in controlling the movement of individual malignant cells, it is likely that cell-to-cell adhesion also influences the spatial spreading of populations of such cells. Therefore, it is important for us to develop biologically realistic simulation tools that can mimic the key features of such collective spreading processes to improve our understanding of how cell-to-cell adhesion influences the spreading of cell populations. Previous models of collective cell spreading with adhesion have used lattice-based random walk frameworks which may lead to unrealistic results, since the agents in the random walk simulations always move across an artificial underlying lattice structure. This is particularly problematic in high-density regions where it is clear that agents in the random walk align along the underlying lattice, whereas no such regular alignment is ever observed experimentally. To address these limitations, we present a lattice-free model of collective cell migration that explicitly incorporates crowding and adhesion. We derive a partial differential equation description of the discrete process and show that averaged simulation results compare very well with numerical solutions of the partial differential equation.

Rapid yet accurate speech indexing using dynamic match lattice spotting

The support for typically out-of-vocabulary query terms such as names, acronyms, and foreign words is an important requirement of many speech indexing applications. However, to date many unrestricted vocabulary indexing systems have struggled to provide a balance between good detection rate and fast query speeds. This paper presents a fast and accurate unrestricted vocabulary speech indexing technique named Dynamic Match Lattice Spotting (DMLS). The proposed method augments the conventional lattice spotting technique with dynamic sequence matching, together with a number of other novel algorithmic enhancements, to obtain a system that is capable of searching hours of speech in seconds while maintaining excellent detection performance

Lattice basis delegation in fixed dimension and shorter-ciphertext hierarchical IBE

We present a technique for delegating a short lattice basis that has the advantage of keeping the lattice dimension unchanged upon delegation. Building on this result, we construct two new hierarchical identity-based encryption (HIBE) schemes, with and without random oracles. The resulting systems are very different from earlier lattice-based HIBEs and in some cases result in shorter ciphertexts and private keys. We prove security from classic lattice hardness assumptions.