Are We In A Simulation?

Graeme A Forbes asks David Chalmers, Michaela mcSweeney and Darren Bradley about this disturbing possibilit

The practical application of an enhanced conveyance calculation in flood prediction

An enhanced one-dimensional mathematical model for simulating flood levels and calculating stage-discharge relationships is presented. Enhanced conveyance subroutines have been developed and incorporated into the commercially available river modelling software ISIS. The newly developed software has been verified using experimental and field data. When a river overtops its banks there is a vigorous interaction between slow moving flood plain flow and faster moving main channel flow. This interaction mechanism has been the focus of intense research over the past forty years. A selective review of this research is detailed with particular attention to the case of meandering channels. The Ackers Method and the James and Wark Method are two discharge capacity methods that have emanated from this recent research and are considered to be the most practically suitable methods and are indeed recommended by the Environment Agency of England and Wales. The methods account for interaction effects when flow is overbank in a straight and meandering channel respectively. It is these methods that have been incorporated into the commercially available and industry leading one-dimensional river model ISIS to enable an enhanced conveyance calculation. The newly developed software has been tested against the Flood Channel Facility Series A and B experiments to a satisfactory level of accuracy. The testing included predicted of stage discharge relationships and water level prediction. In addition it has been applied to the River Dane in Cheshire which is highly meandering and suited to the James and Wark methodology. This was intended to give practical advice concerning the use of the James and Wark Method and the degree of accuracy in estimating the 'channel parameters' which are required by this method. The results of this work showed that a significant rise in water level prediction is obtained when using the enhanced code. Also, it was clear that a high degree of accuracy was not required in estimating the 'channel parameters' with the possible exception of the sinuosity term

Why a 10,000-year clock is being built under a mountain – and why 10,000 years is too long

Discussio

In vitro studies on the inhibitory effect of lymphoid cells. II. Antitumor activity of lymphoid cells from spontaneous mammary tumor-bearing mice on the autochthonous primary culture tumor cells

As a step in the elucidation of human cancer immunity we studied antitumor activity of lymphoid cells by conducting a series of cultures using the primary culture of cells from spontaneous mammary cancers from C3H and RIll mice mixed with autochthonous lymphoid cells, and obtained the following results. 1) With 24 mammary tumors obtained from 24 mammary cancer. bearing mice, we prepared 22 suspensions containing sufficient numbers of free tumor cells, and attempted primary culture with them. As a result we were able to attain satisfactory primary culture cells in 18 trials. 2) With each group of the 18 primary culture tumor cells we conducted mixed cultures with autochthonous lymphoid cells (mainly spleen cells) in proportion of 1 : 40, for 48 hours, and counted viable tumor cells after the culture. As a result it was found that in 11 trials the lymphoid cells showed antitumor activity. In the remaining 7 groups of lymphoid cells there could be observed no antitumor activity, but some of them showed tendency to slightly accelerate the growth of tumor cells. 3) On looking at the correlation between the antitumor activity of lymphoid cells and the ratio of tumor weight/body weight, it was revealed that the antitumor activity is greatest when the tumor is around 10% the body weight, and as the tumor grows larger, such antitumor activity disappears. From these results, it may be concluded that even in spontaneous mammary cancer of mouse, autochthonous lymphoid cells exhibit anti. tumor activity on indigenous tumor, and this seems to indicate that cell. mediated immunity has been established.</p

Influence of cell surface and nanomechanical properties on the flocculation ability of industrial <i>Saccharomyces cerevisiae</i> strains

In the past few years, atomic force microscopy (AFM) has provided novel information on the ultrastructural and nanomechanical properties of yeast cell walls that play a major role in determining the flocculation characteristics of the yeasts. In this study, we used AFM to visualize at the nanoscale the cell surface topography and to determine cell wall nanomechanical properties (e.g. elasticity) of different strains of S. cerevisiae employed for brewing, winemaking and fuel alcohol production. Cell surface topography was found to correlate with the flocculation behaviour of these strains during their late stationary phase, with the cell surface of flocculent cells being rougher than that of weakly flocculent cells. The elastic modulus of the yeast cell walls showed that weakly flocculent strains had a more rigid cell wall than highly flocculent strains. This difference in elasticity seemed to have an effect on the adhesive properties of the yeast cell walls, with weakly flocculent yeasts displaying higher adhesion energy than the highly flocculent strains. These findings seem to indicate that yeast cell surface nanomechanical properties play an important role in governing flocculation

Flocculation in industrial strains of <i>Saccharomyces cerevisiae</i>:role of cell wall polysaccharides and lectin-like receptors

Yeast flocculation is the reversible aggregation of yeast cells promoted by the interaction between lectin-like protein receptors with mannose side chains on adjacent cell walls. Flocculation is governed by several physiological factors, including the type of nutrient sugar available to yeast. We grew four industrial strains of Saccharomyces cerevisiae, representing applications in the brewing, winemaking and bioethanol sectors, to late stationary phase and quantified the cellular content of mannans, glucans and lectin-like proteins on yeast cell surfaces. Results indicated that brewing and champagne strains showed moderate to high flocculation ability when grown with glucose, fructose, maltose or galactose, whereas winemaking and fuel alcohol strains only showed moderate flocculation when grown on maltose and galactose. All yeast strains studied were weakly flocculent when grown on mannose. With regard to lectin-like receptors, their number played a more important role in governing yeast flocculation than the mannan and glucan contents in yeast cell walls. We conclude that all the industrial strains of S. cerevisiae belonged to New-Flo type on the basis of their flocculation behaviour observed when cultured on different sugars. Quantification of yeast cell wall polysaccharides and receptor sites indicates that mannan and glucan levels remain almost constant, irrespective of the strain under investigation. The main difference in flocculation characteristics in industrial yeast strains appears to be due to variations in concentrations of lectin-like cell surface receptors. Our findings may benefit brewers, winemakers and other yeast-based technologies in design of media to prevent premature flocculation during fermentation

Monitoring health in smart homes using simple sensors.

We consider use of an ambient sensor network, installed in Smart Homes, to identify low level events taking place which can then be analysed to generate a resident's profile of activities of daily living (ADLs). These ADL profiles are compared to both the resident's typical profile and to known 'risky' profiles to support evidence-based interventions. Human activity recognition to identify ADLs from sensor data is a key challenge, a windowbased representation is compared on four existing datasets. We find that windowing works well, giving consistent performance. We also introduce FITsense, which is building a Smart Home environment to specifically identify increased risk of falls to allow interventions before falls occurs

Representing temporal dependencies in human activity recognition.

Smart Homes offer the opportunity to perform continuous, long-term behavioural and vitals monitoring of residents, which may be employed to aid diagnosis and management of chronic conditions without placing additional strain on health services. A profile of the resident’s behaviour can be produced from sensor data, and then compared over time. Activity Recognition is a primary challenge for profile generation, however many of the approaches adopted fail to take full advantage of the inherent temporal dependencies that exist in the activities taking place. Long Short Term Memory (LSTM) is a form of recurrent neural network that uses previously learned examples to inform classification decisions. In this paper we present a variety of approaches to human activity recognition using LSTMs and consider the temporal dependencies that exist in binary ambient sensor data in order to produce case-based representations. These LSTM approaches are compared to the performance of a selection of baseline classification algorithms on several real world datasets. In general, it was found that accuracy in LSTMs improved as additional temporal information was presented to the classifier