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.     

Optical spin Hall effects in plasmonic chains

Observation of optical spin Hall effects (OSHEs) manifested by a spin-dependent momentum redirection is presented. The effect occurring solely as a result of the curvature of the coupled localized plasmonic chain is regarded as the locally isotropic OSHE, while the locally anisotropic OSHE arises from the interaction between the optical spin and the local anisotropy of the plasmonic mode rotating along the chain. A wavefront phase dislocation was observed in a circular curvature, in which the dislocation strength was enhanced by the locally anisotropic effect.     

Carbon cycling in a zero-discharge mariculture system

Interest in mariculture systems will rise in the near future due to the decreased ability of the ocean to supply the increasing demand for seafood. We present a trace study using stable carbon and nitrogen isotopes and chemical profiles of a zero-discharge mariculture system stocked with the gilthead seabream (Sparus aurata). Water quality maintenance in the system is based on two biofiltration steps. Firstly, an aerobic treatment step comprising a trickling filter in which ammonia is oxidized to nitrate. Secondly, an anaerobic step comprised of a digestion basin and a fluidized bed reactor where excess organic matter and nitrate are removed. Dissolved inorganic carbon and alkalinity values were higher in the anaerobic loop than in the aerobic loop, in agreement with the main biological processes taking place in the two treatment steps. The δ¹³C of the dissolved inorganic carbon (δ¹³C_DIC) was depleted in ¹³C in the anaerobic loop as compared to the aerobic loop by 2.5-3‰. This is in agreement with the higher dissolved inorganic carbon concentrations in the anaerobic loop and the low water retention time and the chemolithotrophic activity of the aerobic loop. The δ¹³C and δ¹⁵N of organic matter in the mariculture system indicated that fish fed solely on feed pellets. Compared to feed pellets and particulate organic matter, the sludge in the digestion basin was enriched in ¹⁵N while δ¹³C was not significantly different. This latter finding points to an intensive microbial degradation of the organic matter taking place in the anaerobic treatment step of the system.     

Acute fungal endocarditis due to Trichosporon beigelli]

We report a 59-year-old woman with acute fungal endocarditis of a prosthetic valve caused by the endogenic organism, Trichosporon beigelli. This slowly developing disease mainly effects drug addicts who use intravenous narcotics. In nonaddicts it is rare, with mortality as high as 50%. There are only sporadic reports of T. beigelli as a complication long after open heart surgery. The ongoing infection is undetected for even years after the primary infection, due to its prolonged latent phase. We present the difficulties of diagnosis, and of treating the disease with a combination of surgery and of long-term chemotherapy.