High resolution angle resolved photoemission studies on quasi-particle dynamics in graphite

We obtained the spectral function of the graphite H point using high resolution angle resolved photoelectron spectroscopy (ARPES). The extracted width of the spectral function (inverse of the photo-hole lifetime) near the H point is approximately proportional to the energy as expected from the linearly increasing density of states (DOS) near the Fermi energy. This is well accounted by our electron-phonon coupling theory considering the peculiar electronic DOS near the Fermi level. And we also investigated the temperature dependence of the peak widths both experimentally and theoretically. The upper bound for the electron-phonon coupling parameter is ~0.23, nearly the same value as previously reported at the K point. Our analysis of temperature dependent ARPES data at K shows that the energy of phonon mode of graphite has much higher energy scale than 125K which is dominant in electron-phonon coupling.Comment: 9 pages, 8 figures, accepted for publication in Phys. Rev.

mHealth hyperspectral learning for instantaneous spatiospectral imaging of hemodynamics

Hyperspectral imaging acquires data in both the spatial and frequency domains to offer abundant physical or biological information. However, conventional hyperspectral imaging has intrinsic limitations of bulky instruments, slow data acquisition rate, and spatiospectral tradeoff. Here we introduce hyperspectral learning for snapshot hyperspectral imaging in which sampled hyperspectral data in a small subarea are incorporated into a learning algorithm to recover the hypercube. Hyperspectral learning exploits the idea that a photograph is more than merely a picture and contains detailed spectral information. A small sampling of hyperspectral data enables spectrally informed learning to recover a hypercube from an RGB image. Hyperspectral learning is capable of recovering full spectroscopic resolution in the hypercube, comparable to high spectral resolutions of scientific spectrometers. Hyperspectral learning also enables ultrafast dynamic imaging, leveraging ultraslow video recording in an off-the-shelf smartphone, given that a video comprises a time series of multiple RGB images. To demonstrate its versatility, an experimental model of vascular development is used to extract hemodynamic parameters via statistical and deep-learning approaches. Subsequently, the hemodynamics of peripheral microcirculation is assessed at an ultrafast temporal resolution up to a millisecond, using a conventional smartphone camera. This spectrally informed learning method is analogous to compressed sensing; however, it further allows for reliable hypercube recovery and key feature extractions with a transparent learning algorithm. This learning-powered snapshot hyperspectral imaging method yields high spectral and temporal resolutions and eliminates the spatiospectral tradeoff, offering simple hardware requirements and potential applications of various machine-learning techniques.Comment: This paper will appear in PNAS Nexu

Verifying Quantitative Reliability of Programs That Execute on Unreliable Hardware

Emerging high-performance architectures are anticipated to contain unreliable components that may exhibit soft errors, which silently corrupt the results of computations. Full detection and recovery from soft errors is challenging, expensive, and, for some applications, unnecessary. For example, approximate computing applications (such as multimedia processing, machine learning, and big data analytics) can often naturally tolerate soft errors. In this paper we present Rely, a programming language that enables developers to reason about the quantitative reliability of an application -- namely, the probability that it produces the correct result when executed on unreliable hardware. Rely allows developers to specify the reliability requirements for each value that a function produces. We present a static quantitative reliability analysis that verifies quantitative requirements on the reliability of an application, enabling a developer to perform sound and verified reliability engineering. The analysis takes a Rely program with a reliability specification and a hardware specification, that characterizes the reliability of the underlying hardware components, and verifies that the program satisfies its reliability specification when executed on the underlying unreliable hardware platform. We demonstrate the application of quantitative reliability analysis on six computations implemented in Rely.This research was supported in part by the National Science Foundation (Grants CCF-0905244, CCF-1036241, CCF-1138967, CCF-1138967, and IIS-0835652), the United States Department of Energy (Grant DE-SC0008923), and DARPA (Grants FA8650-11-C-7192, FA8750-12-2-0110)

Delayed onset of changes in soma action potential genesis in nociceptive A-beta DRG neurons in vivo in a rat model of osteoarthritis

<p>Abstract</p> <p>Background</p> <p>Clinical data on osteoarthritis (OA) suggest widespread changes in sensory function that vary during the progression of OA. In previous studies on a surgically-induced animal model of OA we have observed that changes in structure and gene expression follow a variable trajectory over the initial days and weeks. To investigate mechanisms underlying changes in sensory function in this model, the present electrophysiological study compared properties of primary sensory nociceptive neurons at one and two months after model induction with properties in naïve control animals. Pilot data indicated no difference in C- or Aδ-fiber associated neurons and therefore the focus is on Aβ-fiber nociceptive neurons.</p> <p>Results</p> <p>At one month after unilateral derangement of the knee by cutting the anterior cruciate ligament and removing the medial meniscus, the only changes observed in Aβ-fiber dorsal root ganglion (DRG) neurons were in nociceptor-like unresponsive neurons bearing a hump on the repolarization phase; these changes consisted of longer half width, reflecting slowed dynamics of AP genesis, a depolarized Vm and an increased AP amplitude. At two months, changes observed were in Aβ-fiber high threshold mechanoreceptors, which exhibited shorter AP duration at base and half width, shorter rise time and fall time, and faster maximum rising rate/maximum falling rate, reflecting accelerated dynamics of AP genesis.</p> <p>Conclusion</p> <p>These data indicate that Aβ nociceptive neurons undergo significant changes that vary in time and occur later than changes in structure and in nociceptive scores in this surgically induced OA model. Thus, if changes in Aβ-fiber nociceptive neurons in this model reflect a role in OA pain, they may relate to mechanisms underlying pain associated with advanced OA.</p

Observation of inhibited electron-ion coupling in strongly heated graphite

Creating non-equilibrium states of matter with highly unequal electron and lattice temperatures (Tele≠Tion) allows unsurpassed insight into the dynamic coupling between electrons and ions through time-resolved energy relaxation measurements. Recent studies on low-temperature laser-heated graphite suggest a complex energy exchange when compared to other materials. To avoid problems related to surface preparation, crystal quality and poor understanding of the energy deposition and transport mechanisms, we apply a different energy deposition mechanism, via laser-accelerated protons, to isochorically and non-radiatively heat macroscopic graphite samples up to temperatures close to the melting threshold. Using time-resolved x ray diffraction, we show clear evidence of a very small electron-ion energy transfer, yielding approximately three times longer relaxation times than previously reported. This is indicative of the existence of an energy transfer bottleneck in non-equilibrium warm dense matter

Cognitive Function Is Disrupted by Both Hypo- and Hyperglycemia in School-AgedChildren With Type 1 Diabetes: A Field Study

Objective: We developed a field procedure using personal digital assistant (PDA) technology to test the hypothesis that naturally occurring episodes of hypo- and hyperglycemia are associated with deterioration in cognitive function in children with type 1 diabetes. Research Design and Methods: A total of 61 children aged 6–11 years with type 1 diabetes received a PDA programmed with two brief cognitive tests (mental math and choice reaction time), which they completed just before home glucose readings. The computer recorded time to complete each test and number of correct responses. Children completed several trials per day over 4–6 weeks for a total of 70 trials. Performance variables were compared across glucose ranges. Individual impairment scores (IISs) were also computed for each child by calculating the SD between performance during euglycemia and that during glucose extremes. Results: Time to complete both mental math and reaction time was significantly longer during hypoglycemia. During hyperglycemia, time to complete math was significantly longer and reaction time was marginally significant (P = 0.053). There were no differences on task accuracy. Decline in mental math performance was equivalent at glucose levels 22.2 mmol/l. IISs varied greatly across children, with no age or sex differences. Conclusions: A decrease in mental efficiency occurs with naturally occurring hypo- and hyperglycemic glucose fluctuations in children with type 1 diabetes, and this effect can be detected with a field procedure using PDA technology. With blood glucose levels >22.2 mmol/l, cognitive deterioration equals that associated with significant hypoglycemia

Piezo voltage controlled planar hall effect devices

The electrical control of the magnetization switching in ferromagnets is highly desired for future spintronic applications. Here we report on hybrid piezoelectric (PZT)/ferromagnetic (Co2FeAl) devices in which the planar Hall voltage in the ferromagnetic layer is tuned solely by piezo voltages. The change of planar Hall voltage is associated with magnetization switching through 90° in the plane under piezo voltages. Room temperature magnetic NOT and NOR gates are demonstrated based on the piezo voltage controlled Co2FeAl planar Hall effect devices without the external magnetic field. Our demonstration may lead to the realization of both information storage and processing using ferromagnetic materials

Rare Exonic Minisatellite Alleles in MUC2 Influence Susceptibility to Gastric Carcinoma

BACKGROUND: Mucins are the major components of mucus and their genes share a common, centrally-located region of sequence that encodes tandem repeats. Mucins are well known genes with respect to their specific expression levels; however, their genomic levels are unclear because of complex genomic properties. In this study, we identified eight novel minisatellites from the entire MUC2 region and investigated how allelic variation in these minisatellites may affect susceptibility to gastrointestinal cancer. METHODOLOGY/PRINCIPLE FINDINGS: We analyzed genomic DNA from the blood of normal healthy individuals and multi-generational family groups. Six of the eight minisatellites exhibited polymorphism and were transmitted meiotically in seven families, following Mendelian inheritance. Furthermore, a case-control study was performed that compared genomic DNA from 457 cancer-free controls with DNA from individuals with gastric (455), colon (192) and rectal (271) cancers. A statistically significant association was identified between rare exonic MUC2-MS6 alleles and the occurrence of gastric cancer: odds ratio (OR), 2.56; 95% confidence interval (CI), 1.31-5.04; and p = 0.0047. We focused on an association between rare alleles and gastric cancer. Rare alleles were divided into short (40, 43 and 44) and long (47, 50 and 54), according to their TR (tandem repeats) lengths. Interestingly, short rare alleles were associated with gastric cancer (OR = 5.6, 95% CI: 1.93-16.42; p = 0.00036). Moreover, hypervariable MUC2 minisatellites were analyzed in matched blood and cancer tissue from 28 patients with gastric cancer and in 4 cases of MUC2-MS2, minisatellites were found to have undergone rearrangement. CONCLUSIONS/SIGNIFICANCE: Our observations suggest that the short rare MUC2-MS6 alleles could function as identifiers for risk of gastric cancer. Additionally, we suggest that minisatellite instability might be associated with MUC2 function in cancer cells