PowerNap: an efficient power management scheme for mobile devices

We present PowerNap, an OS power management scheme, which can significantly improve the battery life of mobile devices. The key feature of PowerNap is the skipping of the periodic system timer ticks associated with the operating system. On an idle device, this modification increases the time between successive timer interrupts and enables us to put the processor/system into a more efficient low power state. This saves the energy consumed by workless timer interrupts and the excess energy consumed by the processor in less efficient low power states. PowerNap is tightly integrated with the kernel and is designed for optimal control of the latency and energy associated with transitioning in and out of the low power states. We describe an implementation of PowerNap and its impact on system software. Experiments with IBM's WatchPad verify the ability of PowerNap to extend battery life. An analytical model that quantifies the ability of the scheme to reduce power is also presented. The model is in good agreement with experimental results. We apply the model to small form-factor devices which use processors that have a PowerDown state. In such devices, PowerNap may extend battery life by more than 42 percent for small processor workloads and for background power levels below 10 mW.     

Impact on the photothermal emission from single wall nanotubes by some alkali halide salts

We demonstrate that alkali-halide salts, particularly potassium bromide, can reduce the photothermal emission (PTE) from single walled carbon nanotubes (SWNT). PTE is a prominent spectral feature in Raman spectroscopy when a near infrared laser is used to analyze a dark colored sample. We subsequently show that trapping salts inside SWNT and coating SWNT with the salt has a more pronounced impact on not only reducing PTE, but also enhancing the intensity of the Raman spectral features. The effect, which we have called nanotube enhanced Raman spectroscopy (NERS), has differences and similarities to the widely studied surface enhanced Raman spectroscopy (SERS).     

Egg handling and storage

The relative importance of fat and lean tissue mass in determining bone mineral mass among postmenopausal women was examined in this 1-year longitudinal study. Fifty postmenopausal Caucasian women entered the study; 45 of them completed a 1-year follow-up. Dual-energy X-ray absorptiometry was employed for measuring total and regional bone mineral density (BMD) and bone mineral content (BMC), fat tissue mass (FTM), lean tissue mass (LTM), and body weight. Results from linear regression analysis using the cross-sectional data (n = 50) of the study indicated that LTM explained a larger percentage of variation in bone mineral mass than did FTM. FTM and LTM were found to be moderately correlated (r = 0.55); when FTM was entered in the same predicting regression models, LTM was a significant predictor (p < 0.05) of the total and regional BMC, but not BMD. The percent FTM (and inversely %LTM) was correlated with BMD and BMC, but significant correlation was primarily found only for total body BMD (or BMC). Weight was the best predictor of total body BMD and BMC. Longitudinally (n = 45), annual changes in both FTM and weight were significantly associated with annual changes in regional BMD after adjustment for initial bone mineral values (p < 0.05). We conclude that bone mineral mass is more closely related to LTM than to FTM, while annual changes in regional BMD are more closely correlated with changes in FTM in healthy postmenopausal women. Meanwhile, increased body weight is significantly associated with increased bone mineral mass.     

Evaluating hyperspectral imaging of wetland vegetation as a tool for detecting estuarine nutrient enrichment

Nutrient enrichment and eutrophication are major concerns in many estuarine and wetland ecosystems, and the need is urgent for fast, efficient, and synoptic ways to detect and monitor nutrients in wetlands and other coastal systems across multiple spatial and temporal scales. We integrated three approaches in a multi-disciplinary evaluation of the potential for using hyperspectral imaging as a tool to assess nutrient enrichment and vegetation responses in tidal wetlands. For hyperspectral imaging to be an effective tool, spectral signatures must vary in ways correlated with water nutrient content either directly, or indirectly via such proxies as vegetation responses to elevated nitrogen. Working in Elkhorn Slough, central California, where intensive farming practices generate considerable runoff of fertilizers and pesticides, we looked first for long- and short-term trends among temporally ephemeral point data for nutrients and other water quality characters collected monthly at 18 water sampling stations since 1988. Second, we assessed responses of the dominant wetland plant, Salicornia virginica (common pickleweed) to two fertilizer regimes in 0.25 m² experimental plots, and measured changes in tissue composition (C, H, N), biomass, and spectral responses at leaf and at canopy scales. Third, we used HyMap hyperspectral imagery (126 bands; 15–19 nm spectral resolution; 2.5 m spatial resolution) for a synoptic assessment of the entire wetland ecosystem of Elkhorn Slough. We mapped monospecific Salicornia patches (～ 56–500 m²) on the ground adjacent to the 18 regular water sampling sites, and then located these patches in the hyperspectral imagery to correlate long-term responses of larger patches to water nutrient regimes. These were used as standards for correlating plant canopy spectral responses with nitrogen variation described by the water sampling program. There were consistent positive relationships between nitrogen levels and plant responses in both the field experiment and the landscape analyses. Two spectral indices, the Photochemical Reflectance Index (PRI) and Derivative Chlorophyll Index (DCI), were correlated significantly with water nutrients. We conclude that hyperspectral imagery can be used to detect nutrient enrichment across three spatial and at least two temporal scales, and suggest that more quantitative information could be extracted with further research and a greater understanding of physiological and physical mechanisms linking water chemistry, plant properties and spectral imaging characteristics.     

Sea-air flux of CO2 in the Caribbean Sea estimated using in situ and remote sensing data

Empirical relationships between sea surface carbon dioxide fugacity (fCO₂^sw) and sea surface temperature (SST) were applied to datasets of remotely sensed SST to create fCO₂^sw fields in the Caribbean Sea. SST datasets from different sensors were used, as well as the SST fields created by optimum interpolation of bias corrected AVHRR data. Empirical relationships were derived using shipboard fCO₂^sw data, in situ SST data, and SST data from the remote sensing platforms. The results show that the application of a relationship based on shipboard SST data, on fields of remotely sensed SST yields biased fCO₂^sw values. This bias is reduced if the fCO₂^sw-SST relationships are derived using the same SST data that are used to create the SST fields. The fCO₂^sw fields found to best reproduce observed fCO₂^sw are used in combination with wind speed data from QuikSCAT to create weekly maps of the sea-air CO₂ flux in the Caribbean Sea in 2002. The region to the SW of Cuba was a source of CO₂ to the atmosphere throughout 2002, and the region to the NE was a sink during winter and spring and a source during summer and fall. The net uptake of CO₂ in the region was doubled when potential skin layer effects on fCO₂^sw were taken into account.     

Solution structure of the superactive monomeric des-[Phe(B25)] human insulin mutant: elucidation of the structural basis for the monomerization of des-[Phe(B25)] insulin and the dimerization of native insulin

The three-dimensional solution structure of des-[Phe(B25)] human insulin has been determined by nuclear magnetic resonance spectroscopy and restrained molecular dynamics calculations. Thirty-five structures were calculated by distance geometry from 581 nuclear Overhauser enhancement-derived distance constraints, ten phi torsional angle restraints, the restraints from 16 helical hydrogen bonds, and three disulfide bridges. The distance geometry structures were optimized using simulated annealing and restrained energy minimization. The average root-mean-square (r.m.s.) deviation for the best 20 refined structures is 1.07 angstroms for the backbone and 1.92 angstroms for all atoms if the less well-defined N and C-terminal residues are excluded. The helical regions are more well defined, with r.m.s. deviations of 0.64 angstroms for the backbone and 1.51 angstroms for all atoms. It is found that the des-[Phe(B25)] insulin is a monomer under the applied conditions (4.6 to 4.7 mM, pH 3.0, 310 K), that the overall secondary and tertiary structures of the monomers in the 2Zn crystal hexamer of native insulin are preserved, and that the conformation-averaged NMR solution structure is close to the structure of molecule 1 in the hexamer. The structure reveals that the lost ability of des-[Phe(B25)] insulin to self-associate is caused by a conformational change of the C-terminal region of the B-chain, which results in an intra-molecular hydrophobic interaction between Pro(B28) and the hydrophobic region Leu(B11)-Leu(B15) of the B-chain alpha-helix. This interaction interferes with the inter-molecular hydrophobic interactions responsible for the dimerization of native insulin, depriving the mutant of the ability to dimerize. Further, the structure displays a series of features that may explain the high potency of the mutant on the basis of the current model for the insulin-receptor interaction. These features are: a change in conformation of the C-terminal region of the B-chain, the absence of strong hydrogen bonds between this region and the rest of the molecule, and a relatively easy accessibility to the Val(A3) residue.     

Functional topography of cat primary auditory cortex: response latencies

Minimum onset latency (Lmin) of single- and multiple-unit responses were mapped in the primary auditory cortex (AI) of barbiturate-anesthetized cats. Contralateral Lmin for multiple units was non-homogeneously distributed along the dorso-ventral/isofrequency axis of the AI. Responses with shorter latencies were more often located in the central, more sharply tuned region while longer latencies were more frequently encountered in the dorsal and ventral portions of the AI. For single units, a large scatter of Lmin values was found throughout the extent of the AI including cortical depth. The relationship between Lmin and previously reported spectral, intensity and temporal parameters was analyzed and revealed statistically significant correlations between minimum onset latency and the following response properties in some but not all studied animals: sharpness of tuning of a frequency response area 10 dB above threshold, broadband transient response, strongest response level, monotonicity of rate/level functions, dynamic range, and preferred frequency modulation sweep direction. This analysis suggests that Lmin is determined by several independent factors and that the prediction of Lmin based on relationships with other spectral and temporal response properties is inherently weak. The spatial distribution and the functional relationship between these response parameters may provide an important aspect of the time-based cortical representation of specific features in the animal's natural environment.