Nutritional Requirements and Diet Choices of the Pygmy Rabbit (Brachylagus idahoensis): A Sagebrush Specialist

Sagebrush (Artemisia tridentata) comprises up to 99% of the winter and 50% of the summer diets of pygmy rabbits (Brachylagus idahoensis). Few animals specialize on such plants as sagebrush, which contain high levels of plant chemicals that can be toxic. We investigated the nutritional requirements of pygmy rabbits and their ability and propensity to consume sagebrush alone and as part of a mixed diet. We compared diet choices of pygmy rabbits with that of a generalist forager, the eastern cottontail (Sylvilagus floridanus). Pygmy rabbits had a moderately low nitrogen requirement (306.5 mg N/kg^0.75/d), but a relatively high energy requirement, needing 750.8 kJ digestible energy/kg^0.75/d to maintain their body mass while residing in small cages. They digested fiber in pelleted diets similarly to other small hindgut fermenters, but both cottontails and pygmy rabbits digested the fiber in sagebrush better than expected based on its indigestible acid detergent lignin content. Pygmy rabbits consumed more sagebrush than cottontails, regardless of the amount and nutritional quality of supplemental pellets provided. When consuming sagebrush alone, they ate barely enough to meet their energy requirements, whereas cottontails ate only enough sagebrush to meet 67% of theirs. Both rabbit species ate more sagebrush as the quality and quantity of supplemental pellets declined, and more greenhouse-grown sagebrush than sagebrush grown outside. Urine was more acidic when consuming sagebrush than when consuming pellets, indicating detoxification by the liver. Pygmy rabbits do not require sagebrush to survive, but seem to tolerate terpenes and other plant chemicals in sagebrush better than cottontails do.     

Lessons from a Minimal Genome: What Are the Essential Organizing Principles of a Cell Built from Scratch?

One of the primary challenges facing synthetic biology is reconstituting a living system from its component parts. A particularly difficult landmark is reconstituting a self-organizing system that can undergo autonomous chromosome compaction, segregation, and cell division. Here, we discuss how the syn3.0 minimal genome can inform us of the core self-organizing principles of a living cell and how these self-organizing processes can be built from the bottom up. The review underscores the importance of fundamental biology in rebuilding life from its molecular constituents.     

In Situ Liquid-Cell TEM Observation of Multiphase Classical and Nonclassical Nucleation of Calcium Oxalate

Calcium oxalate (CaOx) is the major phase in kidney stones and the primary calcium storage medium in plants. CaOx can form crystals with different lattice types, water contents, and crystal structures. However, the conditions and mechanisms leading to nucleation of particular CaOx crystals are unclear. Here, liquid-cell transmission electron microscopy and atomistic molecular dynamics simulations are used to study in situ CaOx nucleation at different conditions. The observations reveal that rhombohedral CaOx monohydrate (COM) can nucleate via a classical pathway, while square COM can nucleate via a non-classical multiphase pathway. Citrate, a kidney stone inhibitor, increases the solubility of calcium by forming calcium-citrate complexes and blocks oxalate ions from approaching calcium. The presence of multiple hydrated ionic species draws additional water molecules into nucleating CaOx dihydrate crystals. These findings reveal that by controlling the nucleation pathways one can determine the macroscale crystal structure, hydration state, and morphology of CaOx.     

Development of a virtual linearizer for correcting transducer static nonlinearity

This paper reports the development of an artificial neural network based virtual linearizer for correcting nonlinearity associated with transducers connected to the data-acquisition system of a computer-based measurement system. In analog processing techniques, nonlinearity is considered to be a very serious problem that at one time was solved frequently by the piecewise linear segment approach modeled by linear electronic circuits. Since the cost of microcomputers has been reduced drastically, they are currently used in most applications of measurement, including data-acquisition subsystems. Therefore, the hardware-based analog techniques of linearization are often replaced by the software-based numerical ones. In this context, it has been found that a multilayer feed-forward back-propagation network trained with the Levenberg-Marquardt learning rule provides an optimal solution to implement an efficient soft compensator to correct transducer static-nonlinearity.     

Model for assessing organic light‐emitting diode display lifetime across applications

A model for assessing organic light‐emitting diode (OLED) display lifetime is developed and discussed for estimating OLED display lifetime in various applications. The lifetime model extends existing stretched exponential models of luminance decay for OLED devices to permit this decay to be estimated as a function of time and current density. This extended model is illustrated within an application to assess the power consumption and luminance decay of diodes within an OLED display. Various metrics of display lifetime are discussed with the aim of developing methods to assess the perceived lifetime of an OLED display to global and local luminance decay mechanisms. Finally, these metrics are applied to illustrate the performance of the model for assessing the impact of an image processing algorithm on OLED display lifetime.     

Effects of calcium carbonate and its purity on crystallization and melting behavior,mechanical properties,and processability of syndiotactic polypropylene

Calcium carbonate‐filled syndiotactic poly(propylene) (CaCO₃‐filled s‐PP) was prepared in a self‐wiping, co‐rotating twin‐screw extruder. The effects of CaCO₃ of varying particle size (1.9, 2.8 and 10.5 μm), content (0–40 wt %), and type of surface modification (uncoated, stearic acid‐coated, and paraffin‐coated) on the crystallization and melting behavior, mechanical properties, and processability of CaCO₃‐filled s‐PP were investigated. Non‐isothermal crystallization studies indicate that CaCO₃ acts as a good nucleating agent for s‐PP. The nucleating efficiency of CaCO₃ for s‐PP was found to depend strongly on its purity, type of surface treatment, and average particle size. Tensile strength was found to decrease, while Young's modulus increased, with increasing CaCO₃ content. Both types of surface treatment on CaCO₃ particles reduced tensile strength and Young's modulus, but improved impact resistance. Scanning electron microscopy (SEM) observations of the fracture surfaces for selected CaCO₃‐filled s‐PP samples revealed an improvement in CaCO₃ dispersion as a result of surface treatment. Finally, steady‐state shear viscosity of CaCO₃‐filled s‐PP was found to increase with increasing CaCO₃ content and decreasing particle size. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 92: 201–212, 2004     

A pattern recognition technique for structural identification using observed vibration signals: Nonlinear case studies

A novel pattern recognition technique, support vector regression (SVR), has been introduced for linear structural parameter identification in a companion article. It is recognized that structural systems in general are designed to behave nonlinearly when subjected to extreme loading. Therefore SVR-based methods for nonlinear structural identification (SI) have been studied and they are summarized in this paper. The first method uses the SVR technique to identify nonlinear structural parameters, whereby the power parameter controlling the shape of the Bouc–Wen model is known. The second and third methods conduct nonlinear SI in the power parameter unknown condition, with the difference that the third method adopts a model selection strategy to enhance the nonlinear parameter estimation practicability. Five-story nonlinear structural systems whose restoring forces are expressed by the Bouc–Wen model are investigated to demonstrate the effectiveness of the SVR-based SI methods. Verification results show that the third method using the model selection strategy is the most efficient one for nonlinear structural parameter identification.