Plastic compression of a collagen gel forms a much improved scaffold for ocular surface tissue engineering over conventional collagen gels

We compare the use of plastically compressed collagen gels to conventional collagen gels as scaffolds onto which corneal limbal epithelial cells (LECs) are seeded to construct an artificial corneal epithelium. LECs were isolated from bovine corneas (limbus) and seeded onto either conventional uncompressed or novel compressed collagen gels and grown in culture. Scanning electron microscopy (SEM) results showed that fibers within the uncompressed gel were loose and irregularly ordered, whereas the fibers within the compressed gel were densely packed and more evenly arranged. Quantitative analysis of LECs expansion across the surface of the two gels showed similar growth rates (p > 0.05). Under SEM, the LECs, expanded on uncompressed gels, showed a rough and heterogeneous morphology, whereas on the compressed gel, the cells displayed a smooth and homogeneous morphology. Transmission electron microscopy (TEM) results showed the compressed scaffold to contain collagen fibers of regular diameter and similar orientation resembling collagen fibers within the normal cornea. TEM and light microscopy also showed that cell–cell and cell–matrix attachment, stratification, and cell density were superior in LECs expanded upon compressed collagen gels. This study demonstrated that the compressed collagen gel was an excellent biomaterial scaffold highly suited to the construction of an artificial corneal epithelium and a significant improvement upon conventional collagen gels.

Evidence that ice forms primarily in supercooled liquid clouds at temperatures > -27C

Using 4 years of radar and lidar observations of layer clouds from the Chilbolton Observatory in the UK, we show that almost all (95%) ice particles formed at temperatures >-20°C appear to originate from supercooled liquid clouds. At colder temperatures, there is a monotonic decline in the fraction of liquid-topped ice clouds: 50% at -27°C, falling to zero at -37°C (where homogeneous freezing of water droplets occurs). This strongly suggests that deposition nucleation plays a relatively minor role in the initiation of ice in mid-level clouds. It also means that the initial growth of the ice particles occurs predominantly within a liquid cloud, a situation which promotes rapid production of precipitation via the Bergeron-Findeison mechanism.

A study on effect of built forms on urban wind environment by using CFD simulations

This paper presents a numerical study of urban air-flow for a group of five buildings that is located at the University of Reading in the United Kingdom. The airflow around these buildings has been simulated by using ANSYS CFD software package. In this study, the association between certain architectural forms: a street canyon, a semi-closure, and a courtyard-like space in a low-rise building complex, and the wind environment were investigated. The analysis of CFD results has provided detailed information on the wind patterns of these urban built forms. The numerical results have been compared with the experimental measurements within the building complex. The observed characteristics of urban wind pattern with respect to the built structures are presented as a guideline. This information is needed for the design and/or performance assessments of systems such as passive and low energy design approach, a natural or hybrid ventilation, and passive cooling. Also, the knowledge of urban wind patterns allows us to develop better design options for the application of renewable energy technologies within urban environment.

Field studies on the effect of built forms on urban wind environments

Airflow through urban environments is one of the most important factors affecting human health, outdoor and indoor thermal comfort, air quality and the energy performance of buildings. This paper presents a study on the effects of wind induced airflows through urban built form using statistical analysis. The data employed in the analysis are from the year-long simultaneous field measurements conducted at the University of Reading campus in the United Kingdom. In this study, the association between typical architectural forms and the wind environment are investigated; such forms include: a street canyon, a semi-closure, a courtyard form and a relatively open space in a low-rise building complex. Measured data captures wind speed and wind direction at six representative locations and statistical analysis identifies key factors describing the effects of built form on the resulting airflows. Factor analysis of the measured data identified meteorological and architectural layout factors as key factors. The derivation of these factors and their variation with the studied built forms are presented in detail.

A flow system for the on-line quantitative measurement of the retention of dosage forms on biological surfaces using spectroscopy and image analysis

Measuring the retention, or residence time, of dosage forms to biological tissue is commonly a qualitative measurement, where no real values to describe the retention can be recorded. The result of this is an assessment that is dependent upon a user's interpretation of visual observation. This research paper outlines the development of a methodology to quantitatively measure, both by image analysis and by spectrophotometric techniques, the retention of material to biological tissues, using the retention of polymer solutions to ocular tissue as an example. Both methods have been shown to be repeatable, with the spectrophotometric measurement generating data reliably and quickly for further analysis.

Modular non-computational-connectionist-hybrid neural network approach to robotic systems

Spiking neural networks are usually limited in their applications due to their complex mathematical models and the lack of intuitive learning algorithms. In this paper, a simpler, novel neural network derived from a leaky integrate and fire neuron model, the ‘cavalcade’ neuron, is presented. A simulation for the neural network has been developed and two basic learning algorithms implemented within the environment. These algorithms successfully learn some basic temporal and instantaneous problems. Inspiration for neural network structures from these experiments are then taken and applied to process sensor information so as to successfully control a mobile robot.