A study of surface diffusion with the scanning tunneling microscope from fluctuations of the tunneling current

We introduce a new technique with high time resolution to measure surface diffusion by monitoring the time dependence of the STM tunneling current fluctuations. Diffusion parameters may be extracted from the decay of the tunneling current fluctuation autocorrelation function, c(t) = \langle[delta] i(0)[delta] i(t)\rangle , or from its Fourier transform, the power spectrum, W(f). Results were obtained for W(f) of oxygen adsorbed on stepped Si(111). Spectra for clean Si(111) show no temperature dependence while that for oxygen-covered Si(111) have signals which are two orders of magnitude greater and exhibit a strong temperature dependence: the spectra broadens with increasing temperature. The data fit the expected theoretical form well and by considering the low frequency regime, W(f) ~ -ln(f)/D, f → 0, the diffusion barrier for O/Si(111) was extracted, giving Ed = 0.92 ± 0.15 eV;The technique is tested if it can distinguish adsorbate diffusion from other surface processes which may interfere with the measurement. We have investigated how certain factors influence the shape of the correlation function or the power spectrum through a combination of experiments and Monte Carlo simulations. These factors include simultaneous diffusion on the substrate and on the tip, and the effect of inhomogeneous surface potentials caused by the electric field or impurities. Simultaneous diffusion on the substrate and on the tip produces a two-segment correlation function which is easily distinguished from that of a single diffusion process. Surface diffusion in inhomogeneous surface potentials (which can cause atoms to diffuse toward or away from the tip) result in correlation functions and power spectra that deviate from the theoretical forms as well. The technique is very highly local, can be used in a wide range of temperatures, and is able to measure a rather wide range of diffusion coefficients: ~10-15-10-8 cm2/sec

Cognitive performance effects of nicotine and industry affiliation: a systematic review.

Background and aimsStudies assessing the cognitive performance effects of nicotine show inconsistent results and tobacco industry funding has been correlated with study outcomes. We conducted a systematic review of the primary literature assessing the cognitive performance effects of nicotine and assessed potential associations between tobacco and pharmaceutical industry affiliation and reported study conclusions.MethodsWe searched PubMed, EMBASE, PsycINFO, BIOSIS, and Web of Science for peer-reviewed journal articles published between 2009 and 2016 that: (1) were randomized controlled trials; (2) investigated the effects of nicotine on cognitive performance in a laboratory setting; (3) administered nicotine to healthy adults (18-60 years); and (4) included participants were nonsmokers or minimally deprived smokers (⩽2 hours of abstaining from smoking). Study disclosures and tobacco industry documents were reviewed to determine industry funding.ResultsSearches yielded 3,771 abstracts; 32 studies were included in the review. The majority of studies investigated the effects of nicotine on attention (n = 22). Nicotine had a non-uniform effect on attention: studies reported positive (41%; n = 9), mixed (41%; n = 9), and no effect (18%; n = 4). The majority of study authors had received prior tobacco industry funding (59%; n = 19), however over half of tobacco-industry funded authors did not report this (53%; n = 10).ConclusionsNicotine does not appear to be associated with consistent cognitive performance effects. Although no association was found between reported outcomes and tobacco or pharmaceutical industry funding, findings likely underestimate the influence of industry funding due to strict inclusion criteria and incomplete data on pharmaceutical industry funding.Clinical trial registrationNot applicable

Impact of Social Contact on Predator-Induced Fear Responses in Young Male Chicks

Post-Traumatic Stress Disorder (PTSD) is thought to involve unusually strong associative memories between the intense fear felt during a traumatic experience and other environmental cues present at the time of the trauma. Our study uses an animal model to investigate social contact, one of the factors that can impact fear responses, to learn more about possible risk factors or interventions that may be relevant to humans who may experience PTSD. Freezing, or the cessation of movement, is a common fear response observed in laboratory animals in the presence of a perceived threat. We tested whether or not the degree of fear expressed by a social companion impacted the level of fear demonstrated by young male chicks. We initially predicted that the presence of a companion would reduce the fear demonstrated by a chick in response to an audiovisual predator stimulus, known as social buffering of fear. Previous results in our lab actually demonstrated the opposite effect. Chicks that experienced predator stimuli in the presence of another chick remained immobile longer than those who experienced the predator alone. It seemed as though chicks were mirroring the fear expressed by their companion. The current study was aimed at investigating whether social transmission of fear is, in fact, occurring between chicks. In order to more carefully control the fear response of companion chicks, we created two different videos to serve as the “companion” stimuli in this experiment. In one, a control chick walked around naturally, and in another, the chick demonstrated fear that was timed to the onset of the predator stimulus. After three daily habituation sessions to the testing apparatus and video screen, 48 Cornish Cross chicks were exposed to one of four conditions: no predator stimulus and a non-fearful video companion, no predator stimulus and a fearful companion, predator stimulus and a non-fearful companion, or predator stimulus and a fearful companion. One chick from each home cage was randomly assigned to each condition. Half of the chicks were exposed to the predator stimuli and half were not. In each group, half were paired with a fearful companion video and half were paired with a non-fearful companion video. Activity of each chick was recorded and quantified by behavioral analysis software (Smart 3.0, Panlab). Statistical analysis revealed a significant main effect of the predator stimulus, F(1, 89) = 28.11,

Cardiovascular measures display robust phenotypic stability across long-duration intervals involving repeated sleep deprivation and recovery

IntroductionWe determined whether cardiovascular (CV) measures show trait-like responses after repeated total sleep deprivation (TSD), baseline (BL) and recovery (REC) exposures in two long-duration studies (total N = 11 adults).MethodsA 5-day experiment was conducted twice at months 2 and 4 in a 4-month study (N = 6 healthy adults; 3 females; mean age ± SD, 34.3 ± 5.7 years; mean BMI ± SD, 22.5 ± 3.2 kg/m2), and three times at months 2, 4, and 8 in an 8-month study (N = 5 healthy adults; 2 females; mean age ± SD, 33.6 ± 5.17 years; mean BMI ± SD, 27.1 ± 4.9 kg/m2). Participants were not shift workers or exposed to TSD in their professions. During each experiment, various seated and standing CV measures were collected via echocardiography [stroke volume (SV), heart rate (HR), cardiac index (CI), left ventricular ejection time (LVET), and systemic vascular resistance index (SVRI)] or blood pressure monitor [systolic blood pressure (SBP)] after (1) two BL 8h time in bed (TIB) nights; (2) an acute TSD night; and (3) two REC 8–10 h TIB nights. Intraclass correlation coefficients (ICCs) assessed CV measure stability during BL, TSD, and REC and for the BL and REC average (BL + REC) across months 2, 4, and 8; Spearman’s rho assessed the relative rank of individuals’ CV responses across measures.ResultsSeated BL (0.693–0.944), TSD (0.643–0.962) and REC (0.735–0.960) CV ICCs showed substantial to almost perfect stability and seated BL + REC CV ICCs (0.552–0.965) showed moderate to almost perfect stability across months 2, 4, and 8. Individuals also exhibited significant, consistent responses within seated CV measures during BL, TSD, and REC. Standing CV measures showed similar ICCs for BL, TSD, and REC and similar response consistency.DiscussionThis is the first demonstration of remarkably robust phenotypic stability of a number of CV measures in healthy adults during repeated TSD, BL and REC exposures across 2, 4, and 8 months, with significant consistency of responses within CV measures. The cardiovascular measures examined in our studies, including SV, HR, CI, LVET, SVRI, and SBP, are useful biomarkers that effectively track physiology consistently across long durations and repeated sleep deprivation and recovery

Next generation farms at Fermilab

The current generation of UNIX farms at Fermilab are rapidly approaching the end of their useful life. The workstations were purchased during the years 1991-1992 and represented the most cost-effective computing available at that time. Acquisition of new workstations is being made to upgrade the UNIX farms for the purpose of providing large amounts of computing for reconstruction of data being collected at the 1996-1997 fixed-target run, as well as to provide simulation computing for CMS, the Auger project, accelerator calculations and other projects that require massive amounts of CPU. 4 refs., 1 fig., 2 tabs

Measurement of the mass difference m(D-s(+))-m(D+) at CDF II

We present a measurement of the mass difference m(D-s(+))-m(D+), where both the D-s(+) and D+ are reconstructed in the phipi(+) decay channel. This measurement uses 11.6 pb(-1) of data collected by CDF II using the new displaced-track trigger. The mass difference is found to be m(D-s(+))-m(D+)=99.41+/-0.38(stat)+/-0.21(syst) MeV/c(2)

A study of surface diffusion with the scanning tunneling microscope from fluctuations of the tunneling current

We introduce a new technique with high time resolution to measure surface diffusion by monitoring the time dependence of the STM tunneling current fluctuations. Diffusion parameters may be extracted from the decay of the tunneling current fluctuation autocorrelation function, c(t) = \langle[delta] i(0)[delta] i(t)\rangle , or from its Fourier transform, the power spectrum, W(f). Results were obtained for W(f) of oxygen adsorbed on stepped Si(111). Spectra for clean Si(111) show no temperature dependence while that for oxygen-covered Si(111) have signals which are two orders of magnitude greater and exhibit a strong temperature dependence: the spectra broadens with increasing temperature. The data fit the expected theoretical form well and by considering the low frequency regime, W(f) ~ -ln(f)/D, f → 0, the diffusion barrier for O/Si(111) was extracted, giving Ed = 0.92 ± 0.15 eV;The technique is tested if it can distinguish adsorbate diffusion from other surface processes which may interfere with the measurement. We have investigated how certain factors influence the shape of the correlation function or the power spectrum through a combination of experiments and Monte Carlo simulations. These factors include simultaneous diffusion on the substrate and on the tip, and the effect of inhomogeneous surface potentials caused by the electric field or impurities. Simultaneous diffusion on the substrate and on the tip produces a two-segment correlation function which is easily distinguished from that of a single diffusion process. Surface diffusion in inhomogeneous surface potentials (which can cause atoms to diffuse toward or away from the tip) result in correlation functions and power spectra that deviate from the theoretical forms as well. The technique is very highly local, can be used in a wide range of temperatures, and is able to measure a rather wide range of diffusion coefficients: ~10-15-10-8 cm2/sec.</p

FNAL central email systems

The FNAL Email System is the primary point of entry for email destined for an employee or user at Fermilab. This centrally supported system is designed for reliability and availability. It uses multiple layers of protection to help ensure that: (1) SPAM messages are tagged properly; (2) All mail is inspected for viruses; and (3) Valid mail gets delivered. This system employs numerous redundant subsystems to accomplish these tasks

Cognitive performance effects of nicotine and industry affiliation: a systematic review.

Background and aimsStudies assessing the cognitive performance effects of nicotine show inconsistent results and tobacco industry funding has been correlated with study outcomes. We conducted a systematic review of the primary literature assessing the cognitive performance effects of nicotine and assessed potential associations between tobacco and pharmaceutical industry affiliation and reported study conclusions.MethodsWe searched PubMed, EMBASE, PsycINFO, BIOSIS, and Web of Science for peer-reviewed journal articles published between 2009 and 2016 that: (1) were randomized controlled trials; (2) investigated the effects of nicotine on cognitive performance in a laboratory setting; (3) administered nicotine to healthy adults (18-60 years); and (4) included participants were nonsmokers or minimally deprived smokers (⩽2 hours of abstaining from smoking). Study disclosures and tobacco industry documents were reviewed to determine industry funding.ResultsSearches yielded 3,771 abstracts; 32 studies were included in the review. The majority of studies investigated the effects of nicotine on attention (n = 22). Nicotine had a non-uniform effect on attention: studies reported positive (41%; n = 9), mixed (41%; n = 9), and no effect (18%; n = 4). The majority of study authors had received prior tobacco industry funding (59%; n = 19), however over half of tobacco-industry funded authors did not report this (53%; n = 10).ConclusionsNicotine does not appear to be associated with consistent cognitive performance effects. Although no association was found between reported outcomes and tobacco or pharmaceutical industry funding, findings likely underestimate the influence of industry funding due to strict inclusion criteria and incomplete data on pharmaceutical industry funding.Clinical trial registrationNot applicable