National Center for High-Performance Computing

We report the observation of gravitational waves from two compact binary coalescences in LIGO's and Virgo's third observing run with properties consistent with neutron star-black hole (NSBH) binaries. The two events are named GW200105_162426 and GW200115_042309, abbreviated as GW200105 and GW200115; the first was observed by LIGO Livingston and Virgo and the second by all three LIGO-Virgo detectors. The source of GW200105 has component masses, whereas the source of GW200115 has component masses and (all measurements quoted at the 90% credible level). The probability that the secondary's mass is below the maximal mass of a neutron star is 89%-96% and 87%-98%, respectively, for GW200105 and GW200115, with the ranges arising from different astrophysical assumptions. The source luminosity distances are and, respectively. The magnitude of the primary spin of GW200105 is less than 0.23 at the 90% credible level, and its orientation is unconstrained. For GW200115, the primary spin has a negative spin projection onto the orbital angular momentum at 88% probability. We are unable to constrain the spin or tidal deformation of the secondary component for either event. We infer an NSBH merger rate density of when assuming that GW200105 and GW200115 are representative of the NSBH population or under the assumption of a broader distribution of component masses. © 2021. The Author(s). Published by the American Astronomical Society.

Electronic structure calculations of $\ensuremath{\beta}\ensuremath{-}{\mathrm{BaB}}_{2}{\mathrm{O}}_{4}$ from first principles are performed based on a plane-wave pseudopotential method, and the linear optical properties are then obtained. The static second-harmonic generation (SHG) coefficients are calculated at the independent-particle level with a formalism originally given by Aversa and Sipe [Phys. Rev. B 52, 14 636 (1995)] and later rearranged by Rashkeev et al. [Phys. Rev. B 57, 3905 (1998)] to explicitly show Kleinman's symmetry. The formalism is improved to be more efficient in reducing the $k$ points necessary for convergence. A real-space atom-cutting method is suggested to analyze the respective contributions of various transitions among ions and ion groups to optical response. The contribution of the cation Ba to SHG effects is found to be not important but non-negligible, while its contribution to birefringence is negligible.

The recent detections of gravitational waves (GWs) reported by LIGO/Virgo collaborations have made significant impact on physics and astronomy. A global network of GW detectors will play a key role to solve the unknown nature of the sources in coordinated observations with astronomical telescopes and detectors. Here we introduce KAGRA (former name LCGT; Large-scale Cryogenic Gravitational wave Telescope), a new GW detector with two 3-km baseline arms arranged in the shape of an "L", located inside the Mt. Ikenoyama, Kamioka, Gifu, Japan. KAGRA's design is similar to those of the second generations such as Advanced LIGO/Virgo, but it will be operating at the cryogenic temperature with sapphire mirrors. This low temperature feature is advantageous for improving the sensitivity around 100 Hz and is considered as an important feature for the third generation GW detector concept (e.g. Einstein Telescope of Europe or Cosmic Explorer of USA). Hence, KAGRA is often called as a 2.5 generation GW detector based on laser interferometry. The installation and commissioning of KAGRA is underway and its cryogenic systems have been successfully tested in May, 2018. KAGRA's first observation run is scheduled in late 2019, aiming to join the third observation run (O3) of the advanced LIGO/Virgo network. In this work, we describe a brief history of KAGRA and highlights of main feature. We also discuss the prospects of GW observation with KAGRA in the era of O3. When operating along with the existing GW detectors, KAGRA will be helpful to locate a GW source more accurately and to determine the source parameters with higher precision, providing information for follow-up observations of a GW trigger candidate.

We report results of a search for an isotropic gravitational-wave background (GWB) using data from Advanced LIGO's and Advanced Virgo's third observing run (O3) combined with upper limits from the earlier O1 and O2 runs. Unlike in previous observing runs in the advanced detector era, we include Virgo in the search for the GWB. The results of the search are consistent with uncorrelated noise, and therefore we place upper limits on the strength of the GWB. We find that the dimensionless energy density GW 5.8 10 -9 at the 95% credible level for a flat (frequency-independent) GWB, using a prior which is uniform in the log of the strength of the GWB, with 99% of the sensitivity coming from the band 20-76.6 Hz; GW f 3.4 10 -9 at 25 Hz for a power-law GWB with a spectral index of 2=3 (consistent with expectations for compact binary coalescences), in the band 20-90.6 Hz; and GW f 3.9 10 -10 at 25 Hz for a spectral index of 3, in the band 20-291.6 Hz. These upper limits improve over our previous results by a factor of 6.0 for a flat GWB, 8.8 for a spectral index of 2=3, and 13.1 for a spectral index of 3. We also search for a GWB arising from scalar and vector modes, which are predicted by alternative theories of gravity; we do not find evidence of these, and place upper limits on the strength of GWBs with these polarizations. We demonstrate that there is no evidence of correlated noise of magnetic origin by performing a Bayesian analysis that allows for the presence of both a GWB and an effective magnetic background arising from geophysical Schumann resonances. We compare our upper limits to a fiducial model for the GWB from the merger of compact binaries, updating the model to use the most recent datadriven population inference from the systems detected during O3a. Finally, we combine our results with observations of individual mergers and show that, at design sensitivity, this joint approach may yield stronger constraints on the merger rate of binary black holes at z 2 than can be achieved with individually resolved mergers alone.

Abstract The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in 2019 April and lasting six months, O3b starting in 2019 November and lasting five months, and O3GK starting in 2020 April and lasting two weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org . The main data set, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages.

Physics and technology issues of importance to the high-gain gyrotron traveling wave amplifier (gyro-TWT) are investigated in theory and experiment. The gyro-TWT is known to be highly susceptible to spurious oscillations, especially in high gain operations. In the current study, oscillations of various origins are classified and characterized with detailed theoretical modeling. They are shown to be intricately connected to the interplay between the absolute/convective instabilities, circuit losses, and reflective feedback. Knowledge of these processes leads to the concept of an ultra high gain scheme which employs distributed wall losses for the suppression of spurious oscillations. A proof-of-principle Ka-band gyro-TWT experiment stable at zero drive has produced 93 kW saturated peak power at 26.5% efficiency and 70 dB gain, with a 3 dB saturated output power bandwidth of 3 GHz. The saturated gain is more than 30 dB beyond that previously achieved.

We search for gravitational-wave signals produced by cosmic strings in the Advanced LIGO and Virgo full O3 dataset. Search results are presented for gravitational waves produced by cosmic string loop features such as cusps, kinks, and, for the first time, kink-kink collisions. A template-based search for short-duration transient signals does not yield a detection. We also use the stochastic gravitational-wave background energy density upper limits derived from the O3 data to constrain the cosmic string tension Gμ as a function of the number of kinks, or the number of cusps, for two cosmic string loop distribution models. Additionally, we develop and test a third model that interpolates between these two models. Our results improve upon the previous LIGO-Virgo constraints on Gμ by 1 to 2 orders of magnitude depending on the model that is tested. In particular, for the one-loop distribution model, we set the most competitive constraints to date: Gμ≲4×10^{-15}. In the case of cosmic strings formed at the end of inflation in the context of grand unified theories, these results challenge simple inflationary models.

The application of a supervised endurance exercise training programme in a home setting offering convenience and prolonged effects is a challenge. In total, 48 patients were initially assessed by the incremental shuttle walk test (ISWT), spirometry and the Short Form-12 (SF-12) quality-of-life questionnaire, and then every 4 weeks for 3 months thereafter and again after 1 yr. During the first 3 months, 24 patients in the cell phone group were asked to perform daily endurance walking at 80% of their maximal capacity by following the tempo of music from a program installed on a cell phone. The level of endurance walking at home was readjusted monthly according to the result of ISWT. In the control group, 24 patients received the same protocol and were verbally asked to take daily walking exercise at home. Patients in the cell phone group significantly improved their ISWT distance and duration of endurance walking after 8 weeks. The improvements in ISWT distance, inspiratory capacity and SF-12 scoring at 12 weeks persisted until the end of the study, with less acute exacerbations and hospitalisations. In the present pilot study, the cell phone-based system provides an efficient, home endurance exercise training programme with good compliance and clinical outcomes in patients with moderate-to-severe chronic obstructive pulmonary disease.

Experiments of bridge pier scour are carried out under steady and unsteady clear-water scour conditions with uniform and nonuniform sediments. Around the pier nose, the sediment size variation of surface bed materials is investigated, and a regressed formula is obtained for estimating the mixing layer thickness in terms of median sediment size and geometric standard deviation of grain size distribution. A method based on the mixing layer concept is developed for calculating the equilibrium scour depth in nonuniform sediment. Based on the experimental data of scour rate, a model simulating the scour-depth evolution under steady flow in nonuniform sediment is presented. By analyzing experimental data, a scheme is proposed for computing the scour-depth evolution under unsteady flow.

With the increasing climatic extremes, the frequency and severity of urban flood events have intensified worldwide. In this study, image-based automated monitoring of flood formation and analyses of water level fluctuation were proposed as value-added intelligent sensing applications to turn a passive monitoring camera into a visual sensor. Combined with the proposed visual sensing method, traditional hydrological monitoring cameras have the ability to sense and analyze the local situation of flood events. This can solve the current problem that image-based flood monitoring heavily relies on continuous manned monitoring. Conventional sensing networks can only offer one-dimensional physical parameters measured by gauge sensors, whereas visual sensors can acquire dynamic image information of monitored sites and provide disaster prevention agencies with actual field information for decision-making to relieve flood hazards. The visual sensing method established in this study provides spatiotemporal information that can be used for automated remote analysis for monitoring urban floods. This paper focuses on the determination of flood formation based on image-processing techniques. The experimental results suggest that the visual sensing approach may be a reliable way for determining the water fluctuation and measuring its elevation and flood intrusion with respect to real-world coordinates. The performance of the proposed method has been confirmed; it has the capability to monitor and analyze the flood status, and therefore, it can serve as an active flood warning system.

Mode competition in the gyrotron traveling wave amplifier is shown to be intricately connected to the interplay between the absolute/convective instabilities, circuit losses, and reflective feedback. Physical origins of spurious oscillations are analyzed and characterized. Fundamental understanding of these processes leads to a device concept which provides zero-drive stability at ultrahigh gain. The scheme was verified in a proof-of-principle experiment in the $\mathrm{Ka}$ band, producing 93 kW saturated peak power at $26.5%$ efficiency, 70 dB gain, and a 3 dB bandwidth of 3 GHz.

Abstract KAGRA is a newly built gravitational wave observatory, a laser interferometer with a 3 km arm length, located at Kamioka, Gifu, Japan. In this series of articles we present an overview of the baseline KAGRA, for which we finished installing the designed configuration in 2019. This article describes the method of calibration (CAL) used for reconstructing gravitational wave signals from the detector outputs, as well as the characterization of the detector (DET). We also review the physical environmental monitoring (PEM) system and the geophysics interferometer (GIF). Both are used for characterizing and evaluating the data quality of the gravitational wave channel. They play important roles in utilizing the detector output for gravitational wave searches. These characterization investigations will be even more important in the near future, once gravitational wave detection has been achieved, and in using KAGRA in the gravitational wave astronomy era.

The eHealth trend has spread globally. Internet of Things (IoT) devices for medical service and pervasive Personal Health Information (PHI) systems play important roles in the eHealth environment. A cloud-based PHI system appears promising but raises privacy and information security concerns. We propose a cloud-based fine-grained health information access control framework for lightweight IoT devices with data dynamics auditing and attribute revocation functions. Only symmetric cryptography is required for IoT devices, such as wireless body sensors. A variant of ciphertext-policy attribute-based encryption, dual encryption, and Merkle hash trees are used to support fine-grained access control, efficient dynamic data auditing, batch auditing, and attribute revocation. Moreover, the proposed scheme also defines and handles the cloud reciprocity problem wherein cloud service providers can help each other avoid fines resulting from data loss. Security analysis and performance comparisons show that the proposed scheme is an excellent candidate for a cloud-based PHI system.

Purpose Supplementation with inorganic nitrate has been suggested to be an ergogenic aid for athletes as nitric oxide donor. The purpose of this study was to determine whether ingestion of inorganic sodium nitrate benefits well-trained athletes performing a 40-min exercise test in laboratory conditions. In addition, we investigated the effect of this supplement on plasma levels of endothelin-1 (ET-1) and in nitrated proteins. Methods Thirteen trained athletes participated in this randomized, double-blind, crossover study. They performed a 40-min cycle ergometer distance-trial test after two 3-d periods of dietary supplementation with sodium nitrate (10 mg·kg−1 of body mass) or placebo. Results Concentration of plasma nitrate (256 ± 35 μM) and nitrite (334 ± 86 nM) increased significantly (P < 0.05) after nitrate supplementation compared with placebo (nitrate: 44 ± 11 μM; nitrite: 187 ± 43 nM). In terms of exercise performance, there were no differences in either the mean distance (nitrate: 26.4 ± 1.1 km; placebo: 26.3 ± 1.2 km; P = 0.61) or mean power output (nitrate: 258 ± 28 W; placebo: 257 ± 28 W; P = 0.89) between treatments. Plasma ET-1 increased significantly (P < 0.05) just after exercise in nitrate (4.0 ± 0.8 pg·mL−1) and placebo (2.4 ± 0.4 pg·mL−1) conditions. This increase was significantly greater (P < 0.05) in the nitrate group. Levels of nitrated proteins did not differ between treatments (nitrate: preexercise, 91% ± 23%; postexercise, 81% ± 23%; placebo: preexercise, 95% ± 20%; postexercise, 99% ± 19%). Conclusion Sodium nitrate supplementation did not improve a 40-min distance-trial performance in endurance athletes. In addition, concentration of plasma ET-1 increased significantly after exercise after supplementation with sodium nitrate.

BACKGROUND: Both adolescent substance use and adolescent depression are major public health problems, and have the tendency to co-occur. Thousands of articles on adolescent substance use or depression have been published. It is labor intensive and time consuming to extract huge amounts of information from the cumulated collections. Topic modeling offers a computational tool to find relevant topics by capturing meaningful structure among collections of documents. METHODS: In this study, a total of 17,723 abstracts from PubMed published from 2000 to 2014 on adolescent substance use and depression were downloaded as objects, and Latent Dirichlet allocation (LDA) was applied to perform text mining on the dataset. Word clouds were used to visually display the content of topics and demonstrate the distribution of vocabularies over each topic. RESULTS: The LDA topics recaptured the search keywords in PubMed, and further discovered relevant issues, such as intervention program, association links between adolescent substance use and adolescent depression, such as sexual experience and violence, and risk factors of adolescent substance use, such as family factors and peer networks. Using trend analysis to explore the dynamics of proportion of topics, we found that brain research was assessed as a hot issue by the coefficient of the trend test. CONCLUSIONS: Topic modeling has the ability to segregate a large collection of articles into distinct themes, and it could be used as a tool to understand the literature, not only by recapturing known facts but also by discovering other relevant topics.

Purpose: To develop and compare deep learning (DL) algorithms to detect keratoconus on the basis of corneal topography and validate with visualization methods. Methods: We retrospectively collected corneal topographies of the study group with clinically manifested keratoconus and the control group with regular astigmatism. All images were divided into training and test datasets. We adopted three convolutional neural network (CNN) models for learning. The test dataset was applied to analyze the performance of the three models. In addition, for better discrimination and understanding, we displayed the pixel-wise discriminative features and class-discriminative heat map of diopter images for visualization. Results: Overall, 170 keratoconus, 28 subclinical keratoconus and 156 normal topographic pictures were collected. The convergence of accuracy and loss for the training and test datasets after training revealed no overfitting in all three CNN models. The sensitivity and specificity of all CNN models were over 0.90, and the area under the receiver operating characteristic curve reached 0.995 in the ResNet152 model. The pixel-wise discriminative features and the heat map of the prediction layer in the VGG16 model both revealed it focused on the largest gradient difference of topographic maps, which was corresponding to the diagnostic clues of ophthalmologists. The subclinical keratoconus was positively predicted with our model and also correlated with topographic indexes. Conclusions: The DL models had fair accuracy for keratoconus screening based on corneal topographic images. The visualization mentioned in the current study revealed that the model focused on the appropriate region for diagnosis and rendered clinical explainability of deep learning more acceptable. Translational Relevance: These high accuracy CNN models can aid ophthalmologists in keratoconus screening with color-coded corneal topography maps.

We present a set of simulated X-band scattering data for civilian vehicles. For ten facet models of civilian vehicles, a high-frequency electromagnetic simulation produced fully polarized, far-field, monostatic scattering for 360 degrees azimuth and elevation angles from 30 to 60 degrees. The 369 GB of phase history data is stored in a MATLAB file format. This paper describes the CVDomes data set along with example imagery using 2D backprojection, single pass 3D, and multi-pass 3D.

The transition from the stationary state to a sequence of nonstationary states in the gyromonotron oscillator is experimentally characterized for the first time. We have also demonstrated the stationary operation of a gyrotron backward-wave oscillator at a beam current far in excess of the generally predicted nonstationary threshold. This difference in nonlinear behavior has been investigated and shown to be fundamental with a comparative analysis of the feedback mechanisms, energy deposition profiles, and field shaping processes involved in these two types of oscillations.

A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate process-based ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest.

A grassroots, global network to examine lake function using sensor data? Why not? That was the perspective of Drs.