Gain control in molecular information processing: Lessons from neuroscience

Statistical properties of environments experienced by biological signaling systems in the real world change, which necessitate adaptive responses to achieve high fidelity information transmission. One form of such adaptive response is gain control. Here we argue that a certain simple mechanism of gain control, understood well in the context of systems neuroscience, also works for molecular signaling. The mechanism allows to transmit more than one bit (on or off) of information about the signal independently of the signal variance. It does not require additional molecular circuitry beyond that already present in many molecular systems, and, in particular, it does not depend on existence of feedback loops. The mechanism provides a potential explanation for abundance of ultrasensitive response curves in biological regulatory networks.Comment: 10 pages, 5 figure

A Method for Upscaling In Situ Soil Moisture Measurements to Satellite Footprint Scale Using Random Forests

Geophysical products generated from remotely sensed data require validation to evaluate their accuracy. Typically in situ measurements are used for validation, as is the case for satellite-derived soil moisture products. However, a large disparity in scales often exists between in situ measurements (covering meters to 10 s of meters) and satellite footprints (often hundreds of meters to several kilometers), making direct comparison difficult. Before using in situ measurements for validation, they must be “upscaled” to provide the mean soil moisture within the satellite footprint. There are a number of existing upscaling methods previously applied to soil moisture measurements, but many place strict requirements on the number and spatial distribution of soil moisture sensors difficult to achieve with permanent/semipermanent ground networks necessary for long-term validation efforts. A new method for upscaling is presented here, using Random Forests to fit a model between in situ measurements and a number of landscape parameters and variables impacting the spatial and temporal distributions of soil moisture. The method is specifically intended for validation of the NASA soil moisture active passive (SMAP) products at 36-, 9-, and 3-km scales. The method was applied to in situ data from the SoilSCAPE network in California, validated with data from the SMAPVEX12 campaign in Manitoba, Canada with additional verification from the TxSON network in Texas. For the SMAPVEX12 site, the proposed method was compared to extensive field measurements and was able to predict mean soil moisture over a large area more accurately than other upscaling approaches

Myosin-I nomenclature.

We suggest that the vertebrate myosin-I field adopt a common nomenclature system based on the names adopted by the Human Genome Organization (HUGO). At present, the myosin-I nomenclature is very confusing; not only are several systems in use, but several different genes have been given the same name. Despite their faults, we believe that the names adopted by the HUGO nomenclature group for genome annotation are the best compromise, and we recommend universal adoption

QCD Strings as Constrained Grassmannian Sigma Model:

We present calculations for the effective action of string world sheet in R3 and R4 utilizing its correspondence with the constrained Grassmannian sigma model. Minimal surfaces describe the dynamics of open strings while harmonic surfaces describe that of closed strings. The one-loop effective action for these are calculated with instanton and anti-instanton background, reprsenting N-string interactions at the tree level. The effective action is found to be the partition function of a classical modified Coulomb gas in the confining phase, with a dynamically generated mass gap.Comment: 22 pages, Preprint: SFU HEP-116-9

The Impact of Anthropogenic Land Use and Land Cover Change on Regional Climate Extremes

Recent research highlights the role of land surface processes in heat waves, droughts, and other extreme events. Here we use an earth system model (ESM) from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the regional impacts of historical anthropogenic land useland cover change (LULCC) on combined extremes of temperature and humidity. A bivariate assessment allows us to consider aridity and moist enthalpy extremes, quantities central to human experience of near-surface climate conditions. We show that according to this model, conversion of forests to cropland has contributed to much of the upper central US and central Europe experiencing extreme hot, dry summers every 2-3 years instead of every 10 years. In the tropics, historical patterns of wood harvesting, shifting cultivation and regrowth of secondary vegetation have enhanced near surface moist enthalpy, leading to extensive increases in the occurrence of humid conditions throughout the tropics year round. These critical land use processes and practices are not included in many current generation land models, yet these results identify them as critical factors in the energy and water cycles of the midlatitudes and tropics