Communicating eye gaze across a distance without rooting participants to the spot

Eye gaze is an important conversational resource that until now could only be supported across a distance if people were rooted to the spot. We introduce EyeCVE, the worldpsilas first tele-presence system that allows people in different physical locations to not only see what each other are doing but follow each otherpsilas eyes, even when walking about. Projected into each space are avatar representations of remote participants, that reproduce not only body, head and hand movements, but also those of the eyes. Spatial and temporal alignment of remote spaces allows the focus of gaze as well as activity and gesture to be used as a resource for non-verbal communication. The temporal challenge met was to reproduce eye movements quick enough and often enough to interpret their focus during a multi-way interaction, along with communicating other verbal and non-verbal language. The spatial challenge met was to maintain communicational eye gaze while allowing free movement of participants within a virtually shared common frame of reference. This paper reports on the technical and especially temporal characteristics of the system.

Different splitting techniques with application to air pollution models

Splitting techniques are commonly used when large-scale models, which appear in different fields of science and engineering, are treated numerically. Four types of splitting procedures are defined and discussed. The problem of the choice of a splitting procedure is investigated. Several numerical tests, by which the influence of the splitting errors on the accuracy of the results is studied, are given. It is shown that the splitting errors decrease linearly when (1) the splitting procedure is of first order and (2) the splitting errors are dominant. Three examples for splitting procedures used in all large-scale air pollution models are presented. Numerical results obtained by a particular air pollution model, Unified Danish Eulerian Model (UNI-DEM), are given and analysed.

Night-time tropospheric chemistry of the unsaturated alcohols (Z)-pent-2-en-1-ol and pent-1-en-3-ol: Kinetic studies of reactions of NO3 and N2O5 with stress-induced plant emissions

The night-time tropospheric chemistry of two stress-induced volatile organic compounds (VOCs), (Z)-pent-2-en-1-ol and pent-1-en-3-ol, has been studied at room temperature. Rate coefficients for reactions of the nitrate radical (NO3) with these pentenols were measured using the discharge-flow technique. Because of the relatively low volatility of these compounds, we employed off-axis continuous-wave cavity-enhanced absorption spectroscopy for detection of NO3 in order to be able to work in pseudo first-order conditions with the pentenols in large excess over NO3. The rate coefficients were determined to be (1.53 +/- 0.23) x 10(-13) and (1.39 +/- 0.19) x 10(-14) cm(3) molecule(-1) s(-1) for reactions of NO3 with (Z)-pent-2-en-1-ol and pent-1-en-3-ol. An attempt to study the kinetics of these reactions with a relative-rate technique, using N2O5 as source of NO3 resulted in significantly higher apparent rate coefficients. Performing relative-rate experiments in known excesses of NO2 allowed us to determine the rate coefficients for the N2O5 reactions to be (5.0 +/- 2.8) x 10(-19) cm(3) molecule(-1) s(-1) for (Z)-pent-2-en-1-ol, and (9.1 +/- 5.8) x 10(-19) cm(3) molecule(-1) s(-1) for pent-1-en-3-ol. We show that these relatively slow reactions can indeed interfere with rate determinations in conventional relative-rate experiments.

On-line handwritten segmentation in linear drawings

This paper addresses the problem of tracking line segments corresponding to on-line handwritten obtained through a digitizer tablet. The approach is based on Kalman filtering to model linear portions of on-line handwritten, particularly, handwritten numerals, and to detect abrupt changes in handwritten direction underlying a model change. This approach uses a Kalman filter framework constrained by a normalized line equation, where quadratic terms are linearized through a first-order Taylor expansion. The modeling is then carried out under the assumption that the state is deterministic and time-invariant, while the detection relies on double thresholding mechanism which tests for a violation of this assumption. The first threshold is based on an approach of layout kinetics. The second one takes into account the jump in angle between the past observed direction of layout and its current direction. The method proposed enables real-time processing. To illustrate the methodology proposed, some results obtained from handwritten numerals are presented.

Periodic time series modeling of environmental proxy records with guaranteed positive growth rate estimation

Identifying a periodic time-series model from environmental records, without imposing the positivity of the growth rate, does not necessarily respect the time order of the data observations. Consequently, subsequent observations, sampled in the environmental archive, can be inversed on the time axis, resulting in a non-physical signal model. In this paper an optimization technique with linear constraints on the signal model parameters is proposed that prevents time inversions. The activation conditions for this constrained optimization are based upon the physical constraint of the growth rate, namely, that it cannot take values smaller than zero. The actual constraints are defined for polynomials and first-order splines as basis functions for the nonlinear contribution in the distance-time relationship. The method is compared with an existing method that eliminates the time inversions, and its noise sensitivity is tested by means of Monte Carlo simulations. Finally, the usefulness of the method is demonstrated on the measurements of the vessel density, in a mangrove tree, Rhizophora mucronata, and the measurement of Mg/Ca ratios, in a bivalve, Mytilus trossulus.

Can we explain the dynamics of the UK FTSE 100 stock and stock index futures markets?

If stock and stock index futures markets are functioning properly price movements in these markets should best be described by a first order vector error correction model with the error correction term being the price differential between the two markets (the basis). Recent evidence suggests that there are more dynamics present than should be in effectively functioning markets. Using self-exciting threshold autoregressive (SETAR) models, this study analyses whether such dynamics can be related to different regimes within which the basis can fluctuate in a predictable manner without triggering arbitrage. These findings reveal that the basis shows strong evidence of autoregressive behaviour when its value is between the two thresholds but that the extra dynamics disappear once the basis moves above the upper threshold and their persistence is reduced, although not eradicated, once the basis moves below the lower threshold. This suggests that once nonlinearity associated with transactions costs is accounted for, stock and stock index futures markets function more effectively than is suggested by linear models of the pricing relationship.

The correlation structure of spatial autoregressions

This paper investigates how the correlations implied by a first-order simultaneous autoregressive (SAR(1)) process are affected by the weights matrix and the autocorrelation parameter. A graph theoretic representation of the covariances in terms of walks connecting the spatial units helps to clarify a number of correlation properties of the processes. In particular, we study some implications of row-standardizing the weights matrix, the dependence of the correlations on graph distance, and the behavior of the correlations at the extremes of the parameter space. Throughout the analysis differences between directed and undirected networks are emphasized. The graph theoretic representation also clarifies why it is difficult to relate properties ofW to correlation properties of SAR(1) models defined on irregular lattices.

Optimisation of the aqueous extraction conditions of phenols from meadowsweet (Filipendula ulmaria L.) for incorporation into beverages

Meadowsweet was extracted in water at a range of temperatures (60–100 °C), and the total phenols, tannins, quercetin, salicylic acid content and colour were analysed. The extraction of total phenols followed pseudo first-order kinetics, the rate constant (k) increased from 0.09 ± 0.02 min−1 to 0.44 ± 0.09 min−1, as the temperature increased from 60 to 100 °C. An increase in temperature from 60 to 100 °C increased the concentration of total phenols extracted from 39 ± 2 to 63 ± 3 mg g−1 gallic acid equivalents, although it did not significantly affect the proportion of tannin and non-tannin fractions. The extraction of quercetin and salicyclic acid from meadowsweet also followed pseudo first-order kinetics, the rate constant of both compounds increasing with an increase in temperature up until 90 °C. Therefore, the aqueous extraction of meadowsweet at temperatures at or above 90 °C for 15 min yields extracts high in phenols, which may be added to beverages.

Optimisation of the extraction and processing conditions of chamomile (Matricaria chamomilla L.) for incorporation into a beverage

The total phenols, apigenin 7-glucoside, turbidity and colour of extracts from dried chamomile flowers were studied with a view to develop chamomile extracts with potential anti-inflammatory properties for incorporation into beverages. The extraction of all constituents followed pseudo first-order kinetics. In general, the rate constant (k) increased as the temperature increased from 57 to 100 °C. The turbidity only increased significantly between 90 and 100 °C. Therefore, aqueous chamomile extracts had maximum total phenol concentration and minimum turbidity when extracted at 90 °C for 20 min. The effect of drying conditions on chamomile extracted using these conditions was determined. A significant reduction in phenol concentration, from 19.7 ± 0.5 mg/g GAE in fresh chamomile to 13 ± 1 mg/g GAE, was found only in the plant material oven-dried at 80 °C (p ⩽ 0.05). The biggest colour change was between fresh chamomile and that oven-dried at 80 °C, followed by samples air-dried. There was no significant difference in colour of material freeze-dried and oven-dried at 40 °C.

The last glacial cycle: transient simulations with an AOGCM

A number of transient climate runs simulating the last 120kyr have been carried out using FAMOUS, a fast atmosphere-ocean general circulation model (AOGCM). This is the first time such experiments have been done with a full AOGCM, providing a three-dimensional simulation of both atmosphere and ocean over this period. Our simulation thus includes internally generated temporal variability over periods from days to millennia, and physical, detailed representations of important processes such as clouds and precipitation. Although the model is fast, computational restrictions mean that the rate of change of the forcings has been increased by a factor of 10, making each experiment 12kyr long. Atmospheric greenhouse gases (GHGs), northern hemisphere ice sheets and variations in solar radiation arising from changes in the Earth's orbit are treated as forcing factors, and are applied either separately or combined in different experiments. The long-term temperature changes on Antarctica match well with reconstructions derived from ice-core data, as does variability on timescales longer than 10 kyr. Last Glacial Maximum (LGM) cooling on Greenland is reasonably well simulated, although our simulations, which lack ice-sheet meltwater forcing, do not reproduce the abrupt, millennial scale climate shifts seen in northern hemisphere climate proxies or their slower southern hemisphere counterparts. The spatial pattern of sea surface cooling at the LGM matches proxy reconstructions reasonably well. There is significant anti-correlated variability in the strengths of the Atlantic Meridional Overturning Circulation (AMOC) and the Antarctic Circumpolar Current (ACC) on timescales greater than 10kyr in our experiments. We find that GHG forcing weakens the AMOC and strengthens the ACC, whilst the presence of northern hemisphere ice-sheets strengthens the AMOC and weakens the ACC. The structure of the AMOC at the LGM is found to be sensitive to the details of the ice-sheet reconstruction used. The precessional component of the orbital forcing induces ~20kyr oscillations in the AMOC and ACC, whose amplitude is mediated by changes in the eccentricity of the Earth's orbit. These forcing influences combine, to first order, in a linear fashion to produce the mean climate and ocean variability seen in the run with all forcings.

Thermal and high hydrostatic pressure inactivation of myrosinase from green cabbage: a kinetic study

Myrosinase, a family of enzymes which coexist with glucosinolates in all Brassica vegetables, catalyses the hydrolysis of glucosinolates to yield compounds that can have beneficial effects on human health. In this study, the thermal and pressure inactivation of myrosinase from green cabbage was kinetically investigated. Thermal inactivation started at 35 C and inactivation kinetics was studied in the temperature range 35–55 C. Thermal inactivation of green cabbage myrosinase followed the well known consecutive step model. Pressure inactivation started at 300 MPa, even at 10 C, and the consecutive step model effectively described pressure inactivation in the range 300–450 MPa at 10 C. The combined effects of applying various pressures and temperatures on myrosinase inactivation kinetics were studied in the ranges 35–50 C and, 100–400 MPa. The inactivation followed first-order kinetics at all of the applied combinations. This study demonstrates that myrosinase from green cabbage is highly susceptible to both thermal and high pressure processing. Furthermore, it is also noted that myrosinase stability during processing appears to vary widely between different Brassica species.

Robust eigenstructure assignment in quadratic matrix polynomials: nonsingular case

Feedback design for a second-order control system leads to an eigenstructure assignment problem for a quadratic matrix polynomial. It is desirable that the feedback controller not only assigns specified eigenvalues to the second-order closed loop system but also that the system is robust, or insensitive to perturbations. We derive here new sensitivity measures, or condition numbers, for the eigenvalues of the quadratic matrix polynomial and define a measure of the robustness of the corresponding system. We then show that the robustness of the quadratic inverse eigenvalue problem can be achieved by solving a generalized linear eigenvalue assignment problem subject to structured perturbations. Numerically reliable methods for solving the structured generalized linear problem are developed that take advantage of the special properties of the system in order to minimize the computational work required. In this part of the work we treat the case where the leading coefficient matrix in the quadratic polynomial is nonsingular, which ensures that the polynomial is regular. In a second part, we will examine the case where the open loop matrix polynomial is not necessarily regular.

On the numerical integration of a class of singular perturbation problems

A three-point difference scheme recently proposed in Ref. 1 for the numerical solution of a class of linear, singularly perturbed, two-point boundary-value problems is investigated. The scheme is derived from a first-order approximation to the original problem with a small deviating argument. It is shown here that, in the limit, as the deviating argument tends to zero, the difference scheme converges to a one-sided approximation to the original singularly perturbed equation in conservation form. The limiting scheme is shown to be stable on any uniform grid. Therefore, no advantage arises from using the deviating argument, and the most accurate and efficient results are obtained with the deviation at its zero limit.

Large is fast, small is tight: determinants of speed and affinity in subunit capture by a periplasmic chaperone

The chaperone/usher pathway assembles surface virulence organelles of Gram-negative bacteria, consisting of fibers of linearly polymerized protein subunits. Fiber subunits are connected through 'donor strand complementation': each subunit completes the immunoglobulin (Ig)-like fold of the neighboring subunit by donating the seventh β-strand in trans. Whereas the folding of Ig domains is a fast first-order process, folding of Ig modules into the fiber conformation is a slow second-order process. Periplasmic chaperones separate this process in two parts by forming transient complexes with subunits. Interactions between chaperones and subunits are also based on the principle of donor strand complementation. In this study, we have performed mutagenesis of the binding motifs of the Caf1M chaperone and Caf1 capsular subunit from Yersinia pestis and analyzed the effect of the mutations on the structure, stability, and kinetics of Caf1M-Caf1 and Caf1-Caf1 interactions. The results suggest that a large hydrophobic effect combined with extensive main-chain hydrogen bonding enables Caf1M to rapidly bind an early folding intermediate of Caf1 and direct its partial folding. The switch from the Caf1M-Caf1 contact to the less hydrophobic, but considerably tighter and less dynamic Caf1-Caf1 contact occurs via the zip-out-zip-in donor strand exchange pathway with pocket 5 acting as the initiation site. Based on these findings, Caf1M was engineered to bind Caf1 faster, tighter, or both faster and tighter. To our knowledge, this is the first successful attempt to rationally design an assembly chaperone with improved chaperone function.

Statistical decadal predictions for sea surface temperatures: a benchmark for dynamical GCM predictions

Accurate decadal climate predictions could be used to inform adaptation actions to a changing climate. The skill of such predictions from initialised dynamical global climate models (GCMs) may be assessed by comparing with predictions from statistical models which are based solely on historical observations. This paper presents two benchmark statistical models for predicting both the radiatively forced trend and internal variability of annual mean sea surface temperatures (SSTs) on a decadal timescale based on the gridded observation data set HadISST. For both statistical models, the trend related to radiative forcing is modelled using a linear regression of SST time series at each grid box on the time series of equivalent global mean atmospheric CO2 concentration. The residual internal variability is then modelled by (1) a first-order autoregressive model (AR1) and (2) a constructed analogue model (CA). From the verification of 46 retrospective forecasts with start years from 1960 to 2005, the correlation coefficient for anomaly forecasts using trend with AR1 is greater than 0.7 over parts of extra-tropical North Atlantic, the Indian Ocean and western Pacific. This is primarily related to the prediction of the forced trend. More importantly, both CA and AR1 give skillful predictions of the internal variability of SSTs in the subpolar gyre region over the far North Atlantic for lead time of 2 to 5 years, with correlation coefficients greater than 0.5. For the subpolar gyre and parts of the South Atlantic, CA is superior to AR1 for lead time of 6 to 9 years. These statistical forecasts are also compared with ensemble mean retrospective forecasts by DePreSys, an initialised GCM. DePreSys is found to outperform the statistical models over large parts of North Atlantic for lead times of 2 to 5 years and 6 to 9 years, however trend with AR1 is generally superior to DePreSys in the North Atlantic Current region, while trend with CA is superior to DePreSys in parts of South Atlantic for lead time of 6 to 9 years. These findings encourage further development of benchmark statistical decadal prediction models, and methods to combine different predictions.