DH 1st floor SR

Self-renewal and pluripotency of mouse embryonic stem (ES) cells are controlled by a complex transcriptional regulatory network (TRN) which is rich in positive feedback loops. A number of key components of this TRN, including Nanog, show strong temporal expression fluctuations at the single cell level, although the precise molecular basis for this variability remains unknown. In this talk I will discuss recent work which uses a genetic complementation strategy to investigate genome-wide mRNA expression changes during transient periods of Nanog down-regulation. Nanog removal triggers widespread changes in gene expression in ES cells. However, we found that significant early changes in gene expression were reversible upon re-induction of Nanog, indicating that ES cells initially adopt a flexible “primed” state. Nevertheless, these changes rapidly become consolidated irreversible fate decisions in the continued absence of Nanog. Using high-throughput single cell transcriptional profiling we observed that the early molecular changes are both stochastic and reversible at the single cell level. Since positive feedback commonly gives rise to phenotypic variability, we also sought to determine the role of feedback in regulating ES cell heterogeneity and commitment. Analysis of the structure of the ES cell TRN revealed that Nanog acts as a feedback “linchpin”: in its presence positive feedback loops are active and the extended TRN is self-sustaining; while in its absence feedback loops are weakened, the extended TRN is no longer self-sustaining and pluripotency is gradually lost until a critical “point-of-no-return” is reached. Consequently, fluctuations in Nanog expression levels transiently activate different sub-networks in the ES cell TRN, driving transitions between a (Nanog expressing) feedback-rich, robust, self-perpetuating pluripotent state and a (Nanog-diminished), feedback-depleted, differentiation-sensitive state. Taken together, our results indicate that Nanog- dependent feedback loops play a central role in controlling both early fate decisions at the single cell level and cell-cell variability in ES cell populations.

Motivated by industrial and biological applications, the Waves

Group at Manchester has in recent years been interested in

developing methods for obtaining the effective properties of

complex composite materials. As time allows we shall discuss a

number of issues, such as differences between composites

with periodic and aperiodic distributions of inclusions, and

modelling of nonlinear composites.

When a rubber membrane tube is inflated, a localized bulge will initiate when the internal pressure reaches a certain value known as the initiation pressure. As inflation continues, the bulge will grow in diameter until it reaches a maximum size, after which the bulge will spread in both directions. This simple phenomenon has previously been studied both experimentally, numerically, and analytically, but surprisingly it is only recently that the character of the initiation pressure has been fully understood. In this talk, I shall first show how the entire inflation process can be described analytically, and then apply the ideas to the mathematical modelling of aneurysm initiation in human arteries.

It is generally believed that in order to generate waves, a small object (like an insect) moving at the air-water surface must exceed the minimum wave speed (about 23 centimeters per second). We show that this result is only valid for a rectilinear uniform motion, an assumption often overlooked in the literature. In the case of a steady circular motion (a situation of particular importance for the study of whirligig beetles), we demonstrate that no such velocity threshold exists and that even at small velocities a finite wave drag is experienced by the object. This wave drag originates from the emission of a spiral-like wave pattern. The results presented should be important for a better understanding of the propulsion of water-walking insects. For example, it would be very interesting to know if whirligig beetles can take advantage of such spirals for echolocation purposes.

The essential information contained in most large data sets is

small when compared to the size of the data set. That is, the

data can be well approximated using relatively few terms in a

suitable transformation. Compressed sensing and matrix completion

show that this simplicity in the data can be exploited to reduce the

number of measurements. For instance, if a vector of length $N$

can be represented exactly using $k$ terms of a known basis

then $2k\log(N/k)$ measurements is typically sufficient to recover

the vector exactly. This can result in dramatic time savings when

k

We develop a physical understanding of how stress waves propagate in uniform, heterogeneous, ordered and disordered media composed of discrete granular particles. We exploit this understanding to create experimentally novel materials and devices at different scales, (for example, for application in energy absorption, acoustic imaging and energy harvesting). We control the constitutive behavior of the new materials selecting the particles’ geometry, their arrangement and materials properties. One-dimensional chains of particles exhibit a highly nonlinear dynamic response, allowing a completely new type of wave propagation that has opened the door to exciting fundamental physical observations (i.e., compact solitary waves, energy trapping phenomena, and acoustic rectification). This talk will focus on energy localization and redirection in one-, two- and three-dimensional systems. (For an extended abstract please contact Ruth @email).

The University of Oxford’s modelling4all software is a wonderful tool to simulate early medieval populations and their cemeteries in order to evaluate the influence of palaeodemographic variables, such as mortality, fertility, catastrophic events and disease on settlement dispersal. In my DPhil project I will study archaeological sites in Anglo-Saxon England and the German south-west in a comparative approach. The two regions have interesting similarities in their early medieval settlement pattern and include some of the first sites where both cemeteries and settlements were completely excavated.

An important discovery in bioarchaeology is that an excavated cemetery is not a straightforward representation of the living population. Preservation issues and the limitations of age and sex estimation methods using skeletal material must be considered. But also the statistical procedures to calculate the palaeodemographic characteristics of archaeological populations are procrustean. Agent-based models can help archaeologists to virtually bridge the chasm between the excavated dead populations and their living counterparts in which we are really interested in.

This approach leads very far away from the archaeologist’s methods and ways of thinking and the major challenge therefore is to balance innovative ideas with practicability and tangibility.

Some of the problems for the workshop are:

1.) Finding the best fitting virtual living populations for the excavated cemeteries

2.) Sensitivity analyses of palaeodemographic variables

3.) General methodologies to evaluate the outcome of agent based models

4.) Present data in a way that is both statistically correct and up to date & clear for archaeologists like me

5.) Explore how to include analytical procedures in the model to present the archaeological community with a user-friendly and not necessarily overwhelming toolkit

When ice is raised to a temperature above its usual melting temperature
of 273 K, small cylindrical discs of water form within the bulk of the
ice. Subsequent internal melting of the ice causes these liquid discs to
grow radially outwards. However, many experimentalists have observed
that the circular interface of these discs is unstable and eventually
the liquid discs turn into beautiful shapes that resemble flowers or
snowflakes. As a result of their shape, these liquid figures are often
called liquid snowflakes. In this talk I'll discuss a simple
mathematical model of liquid snowflake formation and I'll show how a
combination of analytical and numerical methods can yield much insight
into the dynamics which govern their growth.

In partially molten regions of Earth, rock and magma coexist as a two-phase aggregate in which the solid grains of rock form a viscously deformable matrix. Liquid magma resides within the permeable network of pores between grains. Deviatoric stress causes the distribution of contact area between solid grains to become anisotropic; this causes anisotropy of the matrix viscosity. The anisotropic viscosity tensor couples shear and volumetric components of stress/strain rate. This coupling, acting over a gradient in shear stress, causes segregation of liquid and solid. Liquid typically migrates toward higher shear stress, but under specific conditions, the opposite can occur. Furthermore, in a two-phase aggregate with a porosity-weakening viscosity, matrix shear causes porosity perturbations to grow into a banded structure. We show that viscous anisotropy reduces the angle between these emergent high-porosity features and the shear plane. This is consistent with lab experiments.

The task is to estimate approach time (time-to-go (TTG)) of non-ballistic threats (e.g. missiles) using passive infrared imagery captured from a sensor on the target platform (e.g. a helicopter). The threat information available in a frame of data is angular position and signal amplitude.

A Kalman filter approach is presented that is applied to example amplitude data to estimate TTG. Angular information alone is not sufficient to allow analysis of missile guidance dynamics to provide a TTG estimate. Detection of the launch is required as is additional information in the form of a terrain database to determine initial range. Parameters that relate to missile dynamics might include proportional navigation constant and motor thrust. Differences between actual angular position observations and modelled values can beused to form an estimator for the parameter set and thence to the TTG.

The question posed here is, "how can signal amplitude information be employed to establish observability in a state-estimation-based model of the angular data to improve TTG estimate performance without any other source of range information?"