A hollow-cathode copper halide laser

We have successfully operated a CuCl laser in a metal tube in a hollow-cathode configuration. An average output of 400 mW was obtained with 0.06 percent "wall plug" efficiency. Excitation was by pulse burst with a repetition rate of 1-15 kHz within the burst. Despite the use of an unsealed vacuum system and cold windows the laser was operated for more than 300 h on a single charge of CuCl. The hollow-cathode configuration appears to offer significant improvement in mechanical strength and lasant conservation over Pyrex- or quartz-walled longitudinally pumped copper halide lasers.     

Effect of goal acceptance on the relationship of goal difficulty to performance.

Tested the hypotheses that goal acceptance moderates the relationship of goal difficulty to task performance as follows: (a) The relationship is positive and linear for accepted goals; (b) it is negative and linear if the goal is rejected; and thus, (c) slope reversal from positively to negatively linear relationships is associated with transition from positive to negative values of goal acceptance. The experiment was a within-S design, allowing for high variance in acceptance, with technicians and engineers (21–50 yrs of age) divided at random into a 2-phase experimental condition (n?=?104) with specific goal difficulty gradually increasing from Trial 1 to 7 and a control group (n?=?36) with the general instructions to "do your best." Instructions for Phase 2 differed from Phase 1 in that Ss were instructed to reassess their acceptance of difficult goals. The task consisted of determining, within 2-min trials, how many digits or letters in a row were the same as the circled one to the left of each row. Results support the hypotheses. (16 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Do the high-frequency indexes of HRV provide a faithful assessment of cardiac vagal tone? A critical theoretical evaluation

When spectral analysis of the heart rate (HR) signal is performed, it is quite common to attribute the HF indexes of heart rate variability (HRV) to cardiac vagal control. The paradigm underlying this attribution states that changes in cardiac vagal outflow correspond to a proportional change in respiratory sinus arrhythmia (RSA). However, recent studies have demonstrated that variations in these indexes do not necessarily reflect proportional changes in vagal tone. The current study provides a theoretical evaluation of the relationship between mean HR, RSA, and cardiac vagal tone. This evaluation is based on a theoretical model, which quantifies the differential effects of vagal blockade by a competitive muscarinic antagonist on the HF indexes of HRV. The model relies on several assumptions that reflect the basic physiology of the sinoatrial (SA) node, as well as pharmacological relations that describe agonist/antagonist equilibrium at the SA receptors. The mathematical framework of this model is the integral-pulse-frequency-modulation (IPFM) process, and its derivations lead to a specific expressions for the dependence of HF and mean HR on the level of vagal blockade. These expressions provide a new insight into the relationship between mean HR, RSA, and vagal tone, and explain conflicting experimental results previously published.     

Constructing cities,deconstructing scaling laws

Cities can be characterized and modelled through different urban measures. Consistency within these observables is crucial in order to advance towards a science of cities. Bettencourt et al. have proposed that many of these urban measures can be predicted through universal scaling laws. We develop a framework to consistently define cities, using commuting to work and population density thresholds, and construct thousands of realizations of systems of cities with different boundaries for England and Wales. These serve as a laboratory for the scaling analysis of a large set of urban indicators. The analysis shows that population size alone does not provide us enough information to describe or predict the state of a city as previously proposed, indicating that the expected scaling laws are not corroborated. We found that most urban indicators scale linearly with city size, regardless of the definition of the urban boundaries. However, when nonlinear correlations are present, the exponent fluctuates considerably.     

Dead time corrections on the Feynman-Y curve using the backward extrapolation method

Dead time losses in neutron detection, caused by both the detector and the electronics dead time, is a highly nonlinear effect, known to create high biasing in physical experiments as the power grows over a certain threshold. Analytic modeling of the dead time losses is a highly complicated task due to the different nature of the dead time in the different components of the monitoring system (paralyzing vs. non-paralyzing), and the stochastic nature of the fission chains. The most basic analytic models for a paralyzing dead time correction assume a non-correlated source, resulting in an exponential model for the dead time correction. While this model is often used and very useful for correcting the average count rate in low count rates, it is totally impractical in noise experiments and the so-called Feynman-α experiments. In the present study, a new technique is introduced for dead time corrections, based on backward extrapolation of the losses, created by imposing increasing artificial dead time on the data, back to zero. The method is implemented on neutron noise measurements carried out in the MINERVE reactor, demonstrating high accuracy in restoring the corrected values of the Feynman-Y variance-to-mean-ratio.     

Delineating the Tnt1 Insertion Landscape of the Model Legume Medicago truncatula cv. R108 at the Hi-C Resolution Using a Chromosome-Length Genome Assembly

Legumes are of great interest for sustainable agricultural production as they fix atmospheric nitrogen to improve the soil. Medicago truncatula is a well-established model legume, and extensive studies in fundamental molecular, physiological, and developmental biology have been undertaken to translate into trait improvements in economically important legume crops worldwide. However, M. truncatula reference genome was generated in the accession Jemalong A17, which is highly recalcitrant to transformation. M. truncatula R108 is more attractive for genetic studies due to its high transformation efficiency and Tnt1-insertion population resource for functional genomics. The need to perform accurate synteny analysis and comprehensive genome-scale comparisons necessitates a chromosome-length genome assembly for M. truncatula cv. R108. Here, we performed in situ Hi-C (48×) to anchor, order, orient scaffolds, and correct misjoins of contigs in a previously published genome assembly (R108 v1.0), resulting in an improved genome assembly containing eight chromosome-length scaffolds that span 97.62% of the sequenced bases in the input assembly. The long-range physical information data generated using Hi-C allowed us to obtain a chromosome-length ordering of the genome assembly, better validate previous draft misjoins, and provide further insights accurately predicting synteny between A17 and R108 regions corresponding to the known chromosome 4/8 translocation. Furthermore, mapping the Tnt1 insertion landscape on this reference assembly presents an important resource for M. truncatula functional genomics by supporting efficient mutant gene identification in Tnt1 insertion lines. Our data provide a much-needed foundational resource that supports functional and molecular research into the Leguminosae for sustainable agriculture and feeding the future.     

A multi-layer model for the early detection of COVID-19

Current COVID-19 screening efforts mainly rely on reported symptoms and the potential exposure to infected individuals. Here, we developed a machine-learning model for COVID-19 detection that uses four layers of information: (i) sociodemographic characteristics of the individual, (ii) spatio-temporal patterns of the disease, (iii) medical condition and general health consumption of the individual and (iv) information reported by the individual during the testing episode. We evaluated our model on 140 682 members of Maccabi Health Services who were tested for COVID-19 at least once between February and October 2020. These individuals underwent, in total, 264 516 COVID-19 PCR tests, out of which 16 512 were positive. Our multi-layer model obtained an area under the curve (AUC) of 81.6% when evaluated over all the individuals in the dataset, and an AUC of 72.8% when only individuals who did not report any symptom were included. Furthermore, considering only information collected before the testing episode—i.e. before the individual had the chance to report on any symptom—our model could reach a considerably high AUC of 79.5%. Our ability to predict early on the outcomes of COVID-19 tests is pivotal for breaking transmission chains, and can be used for a more efficient testing policy.     

No-reference assessment of blur and noise impacts on image quality

The quality of images may be severely degraded in various situations such as imaging during motion, sensing through a diffusive medium, and low signal to noise. Often in such cases, the ideal un-degraded image is not available (no reference exists). This paper overviews past methods that dealt with no-reference (NR) image quality assessment, and then proposes a new NR method for the identification of image distortions and quantification of their impacts on image quality. The proposed method considers both noise and blur distortion types that may exist in the image. The same methodology employed in the spatial frequency domain is used to evaluate both distortion impacts on image quality, while noise power is further independently estimated in the spatial domain. Specific distortions addressed here include additive white noise, Gaussian blur and de-focus blur. Estimation results are compared to the true distortion quantities, over a set of 75 different images.     

Improving retinal image resolution with iterative weighted shift-and-add

High-resolution retinal imaging requires dilating the pupil, and therefore exposing more aberrations that blur the image. We developed an image processing technique that takes advantage of the natural movement of the eye to average out some of the high-order aberrations and to oversample the retina. This method was implemented on a long sequence of retinal images of subjects with normal vision. We were able to resolve the structures of the size of single cells in the living human retina. The improvement of resolution is independent of the acquisition method, as long as the image is not warped during scanning. Consequently, even better results can be expected by implementing this technique on higher-resolution images.