Accuracy and uncertainty of single-shot, nonresonant laser-induced thermal acoustics

We study the accuracy and uncertainty of single-shot nonresonant laser-induced thermal acoustics measurements of the speed of sound and the thermal diffusivity in unseeded atmospheric air from electrostrictive gratings as a function of the laser power settings. For low pump energies, the measured speed of sound is too low, which is due to the influence of noise on the numerical data analysis scheme. For pump energies comparable to and higher than the breakdown energy of the gas, the measured speed of sound is too high. This is an effect of leaving the acoustic limit, and instead creating finite-amplitude density perturbations. The measured thermal diffusivity is too large for high noise levels but it decreases below the predicted value for high pump energies. The pump energy where the error is minimal coincides for the speed of sound and for the thermal diffusivity measurements. The errors at this minimum are 0.03% and 1%, respectively. The uncertainties for the speed of sound and the thermal diffusivity decrease monotonically with signal intensity to 0.25% and 5%, respectively

Ultrafast Optical Excitation of a Persistent Surface-State Population in the Topological Insulator Bi2Se3

Using femtosecond time- and angle- resolved photoemission spectroscopy, we investigated the nonequilibrium dynamics of the topological insulator Bi2Se3. We studied p-type Bi2Se3, in which the metallic Dirac surface state and bulk conduction bands are unoccupied. Optical excitation leads to a meta-stable population at the bulk conduction band edge, which feeds a nonequilibrium population of the surface state persisting for >10ps. This unusually long-lived population of a metallic Dirac surface state with spin texture may present a channel in which to drive transient spin-polarized currents

Disrupted Human–Pathogen Co-Evolution: A Model for Disease

A major goal in infectious disease research is to identify the human and pathogenic genetic variants that explain differences in microbial pathogenesis. However, neither pathogenic strain nor human genetic variation in isolation has proven adequate to explain the heterogeneity of disease pathology. We suggest that disrupted co-evolution between a pathogen and its human host can explain variation in disease outcomes, and that genome-by-genome interactions should therefore be incorporated into genetic models of disease caused by infectious agents. Genetic epidemiological studies that fail to take both the pathogen and host into account can lead to false and misleading conclusions about disease etiology. We discuss our model in the context of three pathogens, Helicobacter pylori, Mycobacterium tuberculosis and human papillomavirus, and generalize the conditions under which it may be applicable

Disrupted Human–Pathogen Co-Evolution: A Model for Disease

A major goal in infectious disease research is to identify the human and pathogenic genetic variants that explain differences in microbial pathogenesis. However, neither pathogenic strain nor human genetic variation in isolation has proven adequate to explain the heterogeneity of disease pathology. We suggest that disrupted co-evolution between a pathogen and its human host can explain variation in disease outcomes, and that genome-by-genome interactions should therefore be incorporated into genetic models of disease caused by infectious agents. Genetic epidemiological studies that fail to take both the pathogen and host into account can lead to false and misleading conclusions about disease etiology. We discuss our model in the context of three pathogens, Helicobacter pylori, Mycobacterium tuberculosis and human papillomavirus, and generalize the conditions under which it may be applicable

Human and Helicobacter Pylori Coevolution Shapes the Risk of Gastric Disease

Helicobacter pylori is the principal cause of gastric cancer, the second leading cause of cancer mortality worldwide. However, H. pylori prevalence generally does not predict cancer incidence. To determine whether coevolution between host and pathogen influences disease risk, we examined the association between the severity of gastric lesions and patterns of genomic variation in matched human and H. pylori samples. Patients were recruited from two geographically distinct Colombian populations with significantly different incidences of gastric cancer, but virtually identical prevalence of H. pylori infection. All H. pylori isolates contained the genetic signatures of multiple ancestries, with an ancestral African cluster predominating in a low-risk, coastal population and a European cluster in a high-risk, mountain population. The human ancestry of the biopsied individuals also varied with geography, with mostly African ancestry in the coastal region (58%), and mostly Amerindian ancestry in the mountain region (67%). The interaction between the host and pathogen ancestries completely accounted for the difference in the severity of gastric lesions in the two regions of Colombia. In particular, African H. pylori ancestry was relatively benign in humans of African ancestry but was deleterious in individuals with substantial Amerindian ancestry. Thus, coevolution likely modulated disease risk, and the disruption of coevolved human and H. pylori genomes can explain the high incidence of gastric disease in the mountain population

The scaling or ontogeny of human gait kinetics and walk-run transition: The implications of work vs. peak power minimization

A simple model is developed to find vertical force profiles and stance durations that minimize either limb mechanical work or peak power demands during bipedal locomotion. The model predicts that work minimization is achieved with a symmetrical vertical force profile, consistent with previous models and observations of adult humans, and data for 487 participants (predominantly 11–18 years old) required to walk at a range of speeds at a Science Fair. Work minimization also predicts the discrete walk-run transition, familiar for adult humans. In contrast, modeled peak limb mechanical power demands are minimized with an early skew in vertical ground reaction force that increases with speed, and stance durations that decrease steadily with speed across the work minimizing walk-run transition speed. The peak power minimization model therefore predicts a continuous walk-run gait transition that is quantitatively consistent with measurements of younger children (1.1–4.7 years) required to locomote at a range of speeds but free to select their own gaits