Ultrafast optical ranging using microresonator soliton frequency combs

Light detection and ranging (LIDAR) is critical to many fields in science and industry. Over the last decade, optical frequency combs were shown to offer unique advantages in optical ranging, in particular when it comes to fast distance acquisition with high accuracy. However, current comb-based concepts are not suited for emerging high-volume applications such as drone navigation or autonomous driving. These applications critically rely on LIDAR systems that are not only accurate and fast, but also compact, robust, and amenable to cost-efficient mass-production. Here we show that integrated dissipative Kerr-soliton (DKS) comb sources provide a route to chip-scale LIDAR systems that combine sub-wavelength accuracy and unprecedented acquisition speed with the opportunity to exploit advanced photonic integration concepts for wafer-scale mass production. In our experiments, we use a pair of free-running DKS combs, each providing more than 100 carriers for massively parallel synthetic-wavelength interferometry. We demonstrate dual-comb distance measurements with record-low Allan deviations down to 12 nm at averaging times of 14 $\mu$s as well as ultrafast ranging at unprecedented measurement rates of up to 100 MHz. We prove the viability of our technique by sampling the naturally scattering surface of air-gun projectiles flying at 150 m/s (Mach 0.47). Combining integrated dual-comb LIDAR engines with chip-scale nanophotonic phased arrays, the approach could allow widespread use of compact ultrafast ranging systems in emerging mass applications.Comment: 9 pages, 3 figures, Supplementary information is attached in 'Ancillary files

Microresonator solitons for massively parallel coherent optical communications

Optical solitons are waveforms that preserve their shape while propagating, relying on a balance of dispersion and nonlinearity. Soliton-based data transmission schemes were investigated in the 1980s, promising to overcome the limitations imposed by dispersion of optical fibers. These approaches, however, were eventually abandoned in favor of wavelength-division multiplexing (WDM) schemes that are easier to implement and offer improved scalability to higher data rates. Here, we show that solitons may experience a comeback in optical communications, this time not as a competitor, but as a key element of massively parallel WDM. Instead of encoding data on the soliton itself, we exploit continuously circulating dissipative Kerr solitons (DKS) in a microresonator. DKS are generated in an integrated silicon nitride microresonator by four-photon interactions mediated by Kerr nonlinearity, leading to low-noise, spectrally smooth and broadband optical frequency combs. In our experiments, we use two interleaved soliton Kerr combs to transmit a data stream of more than 50Tbit/s on a total of 179 individual optical carriers that span the entire telecommunication C and L bands. Equally important, we demonstrate coherent detection of a WDM data stream by using a pair of microresonator Kerr soliton combs - one as a multi-wavelength light source at the transmitter, and another one as a corresponding local oscillator (LO) at the receiver. This approach exploits the scalability advantages of microresonator soliton comb sources for massively parallel optical communications both at the transmitter and receiver side. Taken together, the results prove the significant potential of these sources to replace arrays of continuous-wave lasers in high-speed communications.Comment: 10 pages, 3 figure

Association of grain iron and zinc content with other nutrients in pearl millet germplasm, breeding lines, and hybrids

Micronutrient deficiency is most prevalent in developing regions of the world, including Africa and Southeast Asia where pearl millet (Pennisetum glaucum L.) is a major crop. Increasing essential minerals in pearl millet through biofortification could reduce malnutrition caused by deficiency. This study evaluated the extent of variability of micronutrients (Fe, Zn, Mn, and Na) and macronutrients (P, K, Ca, and Mg) and their relationship with Fe and Zn content in 14 trials involving pearl millet hybrids, inbreds, and germplasm. Significant genetic variability of macronutrients and micronutrients was found within and across the trials (Ca: 4.2–40.0 mg 100 g−1 , Fe: 24–145 mg kg−1 , Zn: 22–96 mg kg−1 , and Na: 3.0–63 mg kg−1 ). Parental lines showed significantly larger variation for nutrients than hybrids, indicating their potential for use in hybrid parent improvement through recurrent selection. Fe and Zn contents were positively correlated and highly significant (r = 0.58–0.81; p 0.60) for multiple grain minerals provide good selection accuracy prospects for genetic enhancement. A highly positive significant correlation between Fe and Zn and the nonsignificant correlation of grain macronutrients and micronutrients with Fe and Zn suggest that there is scope to achieve higher levels of Fe/Zn simultaneously in current pearl millet biofortification efforts without affecting other grain nutrients. Results suggest major prospects for improving multiple nutrients in pearl millet

Biofortification in underutilized staple crops for nutrition in Asia and Africa

Malnutrition is one of the biggest public health challenges of the century with about 2 billion people affected by it globally. Biofortification is the process of breeding micronutrients traits into staple food crops, which is bioavailable to make a positive measurable impact to the population that eats such staples on a daily basis. It is a cost-effective, sustainable strategy and complementary in nature to the existing market interventions. Iron pearl millet, iron beans, vitamin A cassava and orange sweet potato can contribute to increase household nutrition in the Asia and Africa. Over the years evidences gathered by partners in crop breeding, nutrition studies and delivery experiences will help to build the foundation for scaling out further to reach millions who need the most

Evaluating Depressive Symptoms in Schizophrenia: A Psychometric Comparison of the Calgary Depression Scale for Schizophrenia and the Hamilton Depression Rating Scale

Background: The aim of this study was to compare two measures of depression in patients with schizophrenia and schizophrenia spectrum disorder, including patients with delusional and schizoaffective disorder, to conclude implications for their application. Sampling and Methods: A total of 278 patients were assessed using the Calgary Depression Scale for Schizophrenia (CDSS) and the Hamilton Depression Rating Scale (HAMD-17). The Positive and Negative Syndrome Scale (PANSS) was also applied. At admission and discharge, a principal component analysis was performed with each depression scale. The two depression rating scales were furthermore compared using correlation and regression analyses. Results: Three factors were revealed for the CDSS and HAMD-17 factor component analysis. A very similar item loading was found for the CDSS at admission and discharge, whereas results of the loadings of the HAMD-17 items were less stable. The first two factors of the CDSS revealed correlations with positive, negative and general psychopathology. In contrast, multiple significant correlations were found for the HAMD-17 factors and the PANSS sub-scores. Multiple regression analyses demonstrated that the HAMD-17 accounted more for the positive and negative symptom domains than the CDSS. Conclusions:The present results suggest that compared to the HAMD-17, the CDSS is a more specific instrument to measure depressive symptoms in schizophrenia and schizophrenia spectrum disorder, especially in acutely ill patients. Copyright (c) 2012 S. Karger AG, Base

Folate catabolites in spot urine as non-invasive biomarkers of folate status during habitual intake and folic acid supplementation.

Folate status, as reflected by red blood cell (RCF) and plasma folates (PF), is related to health and disease risk. Folate degradation products para-aminobenzoylglutamate (pABG) and para-acetamidobenzoylglutamate (apABG) in 24 hour urine have recently been shown to correlate with blood folate. Since blood sampling and collection of 24 hour urine are cumbersome, we investigated whether the determination of urinary folate catabolites in fasted spot urine is a suitable non-invasive biomarker for folate status in subjects before and during folic acid supplementation. Immediate effects of oral folic acid bolus intake on urinary folate catabolites were assessed in a short-term pre-study. In the main study we included 53 healthy men. Of these, 29 were selected for a 12 week folic acid supplementation (400 µg). Blood, 24 hour and spot urine were collected at baseline and after 6 and 12 weeks and PF, RCF, urinary apABG and pABG were determined. Intake of a 400 µg folic acid bolus resulted in immediate increase of urinary catabolites. In the main study pABG and apABG concentrations in spot urine correlated well with their excretion in 24 hour urine. In healthy men consuming habitual diet, pABG showed closer correlation with PF (rs = 0.676) and RCF (rs = 0.649) than apABG (rs = 0.264, ns and 0.543). Supplementation led to significantly increased folate in plasma and red cells as well as elevated urinary folate catabolites, while only pABG correlated significantly with PF (rs = 0.574) after 12 weeks. Quantification of folate catabolites in fasted spot urine seems suitable as a non-invasive alternative to blood or 24 hour urine analysis for evaluation of folate status in populations consuming habitual diet. In non-steady-state conditions (folic acid supplementation) correlations between folate marker (RCF, PF, urinary catabolites) decrease due to differing kinetics

Testing gravitational-wave searches with numerical relativity waveforms: Results from the first Numerical INJection Analysis (NINJA) project

The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave data analysis communities. The purpose of NINJA is to study the sensitivity of existing gravitational-wave search algorithms using numerically generated waveforms and to foster closer collaboration between the numerical relativity and data analysis communities. We describe the results of the first NINJA analysis which focused on gravitational waveforms from binary black hole coalescence. Ten numerical relativity groups contributed numerical data which were used to generate a set of gravitational-wave signals. These signals were injected into a simulated data set, designed to mimic the response of the Initial LIGO and Virgo gravitational-wave detectors. Nine groups analysed this data using search and parameter-estimation pipelines. Matched filter algorithms, un-modelled-burst searches and Bayesian parameter-estimation and model-selection algorithms were applied to the data. We report the efficiency of these search methods in detecting the numerical waveforms and measuring their parameters. We describe preliminary comparisons between the different search methods and suggest improvements for future NINJA analyses.Comment: 56 pages, 25 figures; various clarifications; accepted to CQ

Probing Real Sensory Worlds of Receivers with Unsupervised Clustering

The task of an organism to extract information about the external environment from sensory signals is based entirely on the analysis of ongoing afferent spike activity provided by the sense organs. We investigate the processing of auditory stimuli by an acoustic interneuron of insects. In contrast to most previous work we do this by using stimuli and neurophysiological recordings directly in the nocturnal tropical rainforest, where the insect communicates. Different from typical recordings in sound proof laboratories, strong environmental noise from multiple sound sources interferes with the perception of acoustic signals in these realistic scenarios. We apply a recently developed unsupervised machine learning algorithm based on probabilistic inference to find frequently occurring firing patterns in the response of the acoustic interneuron. We can thus ask how much information the central nervous system of the receiver can extract from bursts without ever being told which type and which variants of bursts are characteristic for particular stimuli. Our results show that the reliability of burst coding in the time domain is so high that identical stimuli lead to extremely similar spike pattern responses, even for different preparations on different dates, and even if one of the preparations is recorded outdoors and the other one in the sound proof lab. Simultaneous recordings in two preparations exposed to the same acoustic environment reveal that characteristics of burst patterns are largely preserved among individuals of the same species. Our study shows that burst coding can provide a reliable mechanism for acoustic insects to classify and discriminate signals under very noisy real-world conditions. This gives new insights into the neural mechanisms potentially used by bushcrickets to discriminate conspecific songs from sounds of predators in similar carrier frequency bands