Effect of dissociation pulse circuit inductance on the CuCl laser

The performance of the double-pulsed CuCI laser is improved by a decrease in the inductance of the dissociation pulse circuit. Higher efficiency is obtained due to a larger ground state copper atom population and lower optimum dissociation energy

Classifying faces by sex is more accurate with 3D shape information than with texture

Purpose: We compared quality of information available in 3D surface models versus texture maps for classifying human faces by sex. Methods: 3D surface models and texture maps from laser scans of 130 human heads (65 male, 65 female) were analyzed with separate principal components analyses (PCAs). Individual principal components (PCs) from the 3D head data characterized complex structural differences between male and female heads. Likewise, individual PCs in the texture analysis contrasted characteristically male vs. female texture patterns (e.g., presence/absence of facial hair shadowing). More formally, representing faces with only their projection coefficients onto the PCs, and varying the subspace from 1 to 50 dimensions, we trained a series of perceptrons to predict the sex of the faces using either the 3D or texture data. A "leave-one-out" technique was applied to measure the gen-eralizability of the perceptron's sex predictions. Results: While very good sex generalization performance was obtained for both representations, even with very low dimensional subspaces (e.g., 76.1 correct with only one 3D projection coefficient), the 3D data supported more accurate sex classification across nearly the entire range of subspaces tested. For texture, 93.8 correct sex generalization was achieved with a minimun subspace of 20 projection coefficients. For 3D data, 96.9 correct generalization was achieved with 17 projection coefficients. Conclusions: These data highlight the importance of considering the kinds of information available in different face representations with respect to the task demands

Amygdala fMRI Signal as a Predictor of Reaction Time

Reaction times (RTs) are a valuable measure for assessing cognitive processes. However, RTs are susceptible to confounds and therefore variable. Exposure to threat, for example, speeds up or slows down responses. Distinct task types to some extent account for differential effects of threat on RTs. But also do inter-individual differences like trait anxiety. In this functional magnetic resonance imaging (fMRI) study, we investigated whether activation within the amygdala, a brain region closely linked to the processing of threat, may also function as a predictor of RTs, similar to trait anxiety scores. After threat conditioning by means of aversive electric shocks, 45 participants performed a choice RT task during alternating 30 s blocks in the presence of the threat conditioned stimulus [CS+] or of the safe control stimulus [CS-]. Trait anxiety was assessed with the State-Trait Anxiety Inventory and participants were median split into a high- and a low-anxiety subgroup. We tested three hypotheses: (1) RTs will be faster during the exposure to threat compared to the safe condition in individuals with high trait anxiety. (2) The amygdala fMRI signal will be higher in the threat condition compared to the safe condition. (3) Amygdala fMRI signal prior to a RT trial will be correlated with the corresponding RT. We found that, the high-anxious subgroup showed faster responses in the threat condition compared to the safe condition, while the low-anxious subgroup showed no significant difference in RTs in the threat condition compared to the safe condition. Though the fMRI analysis did not reveal an effect of condition on amygdala activity, we found a trial-by-trial correlation between blood-oxygen-level-dependent signal within the right amygdala prior to the CRT task and the subsequent RT. Taken together, the results of this study showed that exposure to threat modulates task performance. This modulation is influenced by personality trait. Additionally and most importantly, activation in the amygdala predicts behavior in a simple task that is performed during the exposure to threat. This finding is in line with “attentional capture by threat”—a model that includes the amygdala as a key brain region for the process that causes the response slowing

A low-energy rate-adaptive bit-interleaved passive optical network

Energy consumption of customer premises equipment (CPE) has become a serious issue in the new generations of time-division multiplexing passive optical networks, which operate at 10 Gb/s or higher. It is becoming a major factor in global network energy consumption, and it poses problems during emergencies when CPE is battery-operated. In this paper, a low-energy passive optical network (PON) that uses a novel bit-interleaving downstream protocol is proposed. The details about the network architecture, protocol, and the key enabling implementation aspects, including dynamic traffic interleaving, rate-adaptive descrambling of decimated traffic, and the design and implementation of a downsampling clock and data recovery circuit, are described. The proposed concept is shown to reduce the energy consumption for protocol processing by a factor of 30. A detailed analysis of the energy consumption in the CPE shows that the interleaving protocol reduces the total energy consumption of the CPE significantly in comparison to the standard 10 Gb/s PON CPE. Experimental results obtained from measurements on the implemented CPE prototype confirm that the CPE consumes significantly less energy than the standard 10 Gb/s PON CPE

Negative time delay for wave reflection from a one-dimensional semi-harmonic well

It is reported that the phase time of particles which are reflected by a one-dimensional semi-harmonic well includes a time delay term which is negative for definite intervals of the incoming energy. In this interval, the absolute value of the negative time delay becomes larger as the incident energy becomes smaller. The model is a rectangular well with zero potential energy at its right and a harmonic-like interaction at its left.Comment: 6 pages, 5 eps figures. Talk presented at the XXX Workshop on Geometric Methods in Physics, Bialowieza, Poland, 201

Towards targeted dietary support for shift workers with type 2 diabetes (Shift-Diabetes study): A mixed-methods case study protocol

BACKGROUND: Blood glucose is higher in people working night-shifts compared to day-workers. Changes to eating behaviour, activity, and sleep patterns in addition to circadian disruption are likely to impact glucose management in night-shift workers with Type 2 diabetes. AIM: To investigate current dietary intake and glucose variability during night work, including barriers and facilitators to dietary behavior in this context. METHODS: A mixed-methods case study will be conducted. Shift workers with Type 2 diabetes working in a hospital setting will be recruited to this two-part study. Part 1: 70 participants will complete a 10-day observational study collecting data on continuous glucose, diet (self-report diary), sleep and physical activity during a period covering night work, rest days and non-night workdays. Mean glucose concentration and variability, and the mean healthy diet index score, will be compared between days of night work, non-night work and rest, after adjusting for other individual factors (sleep/physical activity/demographics). Part 2: A sample (n~13) will complete semi-structured interviews based on behavioural science frameworks to explore barriers/enablers to dietary behaviour when working night shifts. This will inform a quantitative survey to explore the generalisability of interview findings. DISCUSSION: Findings from Part 1 and 2 will be triangulated to identify potential intervention strategies to address key barriers and enablers to healthier eating, and in turn improved glucose control, in shift workers with Type 2 diabetes. This will be facilitated through stakeholder consultation and application of behavioural science frameworks

Identification of highly brominated analogues of Q1 in marine mammals

Author Posting. © The Authors, 2005. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Environmental Pollution 144 (2006): 336-344, doi:10.1016/j.envpol.2005.10.052.Three novel halogenated organic compounds (HOCs) have been identified in the blubber of marine mammals from coastal New England with the molecular formulae C9H3N2Br6Cl, C9H3N2Br7, and C9H4N2Br5Cl. They were identified using high and low resolution electron ionization (EI) and electron capture negative ionization (ECNI) gas chromatography mass spectrometry (GCMS) and appear to be highly brominated analogues of Q1, a heptachlorinated HOC that has been suspected to be naturally-produced. These new compounds were found in Atlantic white sided dolphin (Lagenorhynchus acutus), bottlenose dolphin (Tursiops truncatus), common dolphin (Delphinus delphis), Risso’s dolphin (Grampus griseus), harbor porpoise (Phocoena phocoena), beluga whale (Delphinapterus leucas), fin whale (Balaenoptera physalus), grey seal (Halichoerus grypus), harp seal (Phoca groenlandica) and a potential food source (Loligo pealei) with concentrations as high as 2.7 μg/g (lipid weight). The regiospecificity of C9H3N2Br6Cl is suggestive of a biogenic origin. Debromination of C9H3N2Br6Cl may be significant in the formation of C9H4N2Br5Cl.This work was supported by the National Science Foundation (OCE-0221181), the Woods Hole Oceanographic Institution (WHOI) Ocean Life Institute, the Postdoctoral Scholar Program at WHOI (with funding from The Camille and Henry Dreyfus Foundation, Inc. and The J. Seward Johnson Fund) (ELT) and The Island Foundation, Inc (BEP)