Biologists have long been concerned about what constrains variation in cell size; yet, progress on this question has been slow and stymied by experimental limitations1. We describe a new method, ergodic rate analysis (ERA), that uses single cell measurements of fixed steady-state populations to accurately infer the rates of molecular events, including rates of cell growth. ERA exploits the fact that the number of cells in a particular state is related to the average transit time through that state2. With this method, one can calculate full time trajectories of any feature that can be labeled fixed cells, for example levels of phospho-proteins or total cellular mass. Using ERA we find evidence for a size-discriminatory process at the G1/S transition that acts to decrease cell-to-cell size variation.

Reducing the risk of oil spill disasters is essential for protecting the environment and reducing economic losses. Oil spill surveillance constitutes an important component of oil spill disaster management. Advances in remote sensing technologies can help to identify parties potentially responsible for pollution and to identify minor spills before they cause widespread damage. Due to the large number of sensors currently available for oil spill surveillance, there is a need for a comprehensive overview and comparison of existing sensors. Specifically, this paper examines the characteristics and applications of different sensors. A better understanding of the strengths and weaknesses of oil spill surveillance sensors will improve the operational use of these sensors for oil spill response and contingency planning. Laser fluorosensors were found to be the best available sensor for oil spill detection since they not only detect and classify oil on all surfaces but also operate in either the day or night. For example, the Scanning Laser Environmental Airborne Fluorosensor (SLEAF) sensor was identified to be a valuable tool for oil spill surveillance. However, no single sensor was able to provide all information required for oil spill contingency planning. Hence, combinations of sensors are currently used for oil spill surveillance. Specifically, satellite sensors are used for preliminary oil spill assessment while airborne sensors are used for detailed oil spill analysis. While satellite remote sensing is not suitable for tactical oil spill planning it can provide a synoptic coverage of the affected area.

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Risk of hospital admissions in Taipei may be increased by air pollution and sandstorms. Additional research is needed to clarify the lag structure and magnitude of such effects.

Even if earthquake precursory signals can be identified, how can they be useful? This paper investigates relationships among the attributes of 229 proposed earthquake related gasgeochemical and hydrogeological precursory signals, and applies these results to improve future earthquake prediction strategies. Sub-groups of these reported signals and relationships between sub-groups are established using parameters, including earthquake magnitude, signal duration, precursory time, and epicentral distance to the monitoring site (original studies are used wherever possible to improve data quality). A strong correlation (r ¼ 0.86) between signal duration and precursory time was identified. This suggests a relationship between the investigated precursory signals and tectonic processes related to the referenced earthquakes. Moreover, these signals are categorized into four groups, reflecting differences in monitoring station densities, measurement methods and physical processes related to signal occurrence: (a) radon exhalation from the earth's crust, (b) exhalation of other gases (helium, argon and others), (c) temporal variation in water level or discharge of springs and (d) temporal variation in temperature and dissolved ions in the water of the monitoring sites. In addition, boundary functions are used to separate signal group subsets. Finally, it is shown how these boundary functions can be used in the context of an earthquake prediction strategy by identifying potential minimum magnitudes and maximum epicentral distances from the monitoring site.