Search

Whole slide images (WSIs) pose unique challenges when training deep learning models. They are very large which makes it necessary to break each image down into smaller patches for analysis, image features have to be extracted at multiple scales in order to capture both detail and context, and extreme class imbalances may exist. Significant progress has been made in the analysis of these images, thanks largely due to the availability of public annotated datasets. We postulate, however, that even if a method scores well on a challenge task, this success may not translate to good performance in a more clinically relevant workflow. Many datasets consist of image patches which may suffer from data curation bias; other datasets are only labelled at the whole slide level and the lack of annotations across an image may mask erroneous local predictions so long as the final decision is correct. In this paper, we outline the differences between patch or slide-level classification versus methods that need to localize or segment cancer accurately across the whole slide, and we experimentally verify that best practices differ in both cases. We apply a binary cancer detection network on post neoadjuvant therapy breast cancer WSIs to find the tumor bed outlining the extent of cancer, a task which requires sensitivity and precision across the whole slide. We extensively study multiple design choices and their effects on the outcome, including architectures and augmentations. Furthermore, we propose a negative data sampling strategy, which drastically reduces the false positive rate (7% on slide level) and improves each metric pertinent to our problem, with a 15% reduction in the error of tumor extent.

Suppose we are interested in the effect of a treatment in a clinical trial. The efficiency of inference may be limited due to small sample size. However, external control data are often available from historical studies. Motivated by an application to Helicobacter pylori infection, we show how to borrow strength from such data to improve efficiency of inference in the clinical trial. Under an exchangeability assumption about the potential outcome mean, we show that the semiparametric efficiency bound for estimating the average treatment effect can be reduced by incorporating both the clinical trial data and external controls. We then derive a doubly robust and locally efficient estimator. The improvement in efficiency is prominent especially when the external control dataset has a large sample size and small variability. Our method allows for a relaxed overlap assumption, and we illustrate with the case where the clinical trial only contains a treated group. We also develop doubly robust and locally efficient approaches that extrapolate the causal effect in the clinical trial to the external population and the overall population. Our results also offer a meaningful implication for trial design and data collection. We evaluate the finite-sample performance of the proposed estimators via simulation. In the Helicobacter pylori infection application, our approach shows that the combination treatment has potential efficacy advantages over the triple therapy., Comment: Accepted for publication in Biometrics; 1 figure, 3 tables

Reliable and low latency multicast communication is important for future vehicular communication. Sparse random linear network coding approach used to ensure the reliability of multicast communication has been widely investigated. A fundamental problem of such communication is to characterize the decoding success probability, which is given by the probability of a sparse random matrix over a finite field being full rank. However, the exact expression for the probability of a sparse random matrix being full rank is still unknown, and existing approximations are recursive or not consistently tight. In this paper, we provide a tight and closed-form approximation to the probability of a sparse random matrix being full rank, by presenting the explicit structure of the reduced row echelon form of a full rank matrix and using the product theorem. Simulation results show that our proposed approximation is of high accuracy regardless of the generation size, the number of coded packets, the field size and the sparsity, and tighter than the state-of-the-art approximations for a large range of parameters.

We present the observational results from a detailed timing analysis of the black hole candidate EXO 1846-031 during its outburst in 2019 with the observations of Insight-HXMT, NICER and MAXI. This outburst can be classfied roughly into four different states. Type-C quasi-periodic oscillations (QPOs) observed by NICER (about 0.1-6Hz) and Insight-HXMT (about 0.7-8Hz) are also reported in this work. Meanwhile, we study various physical quantities related to QPO frequency.The QPO rms-frequency relationship in three energy band 1-10 keV indicates that there is a turning pointing in frequency around 2 Hz,which is similar to that of GRS 1915+105. A possible hypothesis for the relationship above may be related to the inclination of the source, which may require a high inclination to explain it. The relationships between QPO frequency and QPO rms,hardness,total fractional rms and count rate have also been found in other transient sources, which can indicate that the origin of type-C QPOs is non-thermal.

Low-frequency quasi-periodic oscillations (LFQPOs) are commonly found in black hole X-ray binaries, and their origin is still under debate. The properties of LFQPOs at high energies (above 30 keV) are closely related to the nature of the accretion flow in the innermost regions, and thus play a crucial role in critically testing various theoretical models. The Hard X-ray Modulation Telescope (Insight-HXMT) is capable of detecting emissions above 30 keV, and is therefore an ideal instrument to do so. Here we report the discovery of LFQPOs above 200 keV in the new black hole MAXI J1820+070 in the X-ray hard state, which allows us to understand the behaviours of LFQPOs at hundreds of kiloelectronvolts. The phase lag of the LFQPO is constant around zero below 30 keV, and becomes a soft lag (that is, the high-energy photons arrive first) above 30 keV. The soft lag gradually increases with energy and reaches ~0.9s in the 150-200 keV band. The detection at energies above 200 keV, the large soft lag and the energy-related behaviors of the LFQPO pose a great challenge for most currently existing models, but suggest that the LFQPO probably originates from the precession of a small-scale jet., Comment: 36 pages, 12 figures, 3 tables; published in Nature Astronomy

LE is the low energy telescope of Insight-HXMT. It uses swept charge devices (SCDs) to detect soft X-ray photons. The time response of LE is caused by the structure of SCDs. With theoretical analysis and Monte Carlo simulations we discuss the influence of LE time response (LTR) on the timing analysis from three aspects: the power spectral density, the pulse profile and the time lag. After the LTR, the value of power spectral density monotonously decreases with the increasing frequency. The power spectral density of a sinusoidal signal reduces by a half at frequency 536 Hz. The corresponding frequency for QPO signals is 458 Hz. The Root mean square (RMS) of QPOs holds the similar behaviour. After the LTR, the centroid frequency and full width at half maxima (FWHM) of QPOs signals do not change. The LTR reduces the RMS of pulse profiles and shifts the pulse phase. In the time domain, the LTR only reduces the peak value of the crosscorrelation function while it does not change the peak position. Thus it will not affect the result of the time lag. When considering the time lag obtained from two instruments and one among them is LE, a 1.18 ms lag is expected caused by the LTR. The time lag calculated in the frequency domain is the same as that in the time domain., Comment: 11 pages, 9 figures

Accurate background estimation is essential for spectral and temporal analysis in astrophysics. In this work, we construct the in-orbit background model for the High-Energy Telescope (HE) of the Hard X-ray Modulation Telescope (dubbed as Insight-HXMT). Based on the two-year blank sky observations of Insight-HXMT/HE, we first investigate the basic properties of the background and find that both the background spectral shape and intensity have long-term evolution at different geographical sites. The entire earth globe is then divided into small grids, each with a typical area of 5x5 square degrees in geographical coordinate system. For each grid, an empirical function is used to describe the long-term evolution of each channel of the background spectrum; the intensity of the background can be variable and a modification factor is introduced to account for this variability by measuring the contemporary flux of the blind detector. For a given pointing observation, the background model is accomplished by integrating over the grids that are passed by the track of the satellite in each orbit. Such a background model is tested with both the blank sky observations and campaigns for observations of a series of celestial sources. The results show an average systematic error of 1.5% for the background energy spectrum (26-100 keV) under a typical exposure of 8 ks, and <3% for background light curve estimation (30-150 keV). Therefore, the background model introduced in this paper is included in the Insight-HXMT software as a standard part specialized for both spectral and temporal analyses., Comment: 27 pages, 16 figures, accepted by Journal of High Energy Astrophysics

With more than 150 blank sky observations at high Galactic latitude, we make a systematic study to the background of the Low Energy Telescope (LE) of the Hard X-ray Modulation Telescope (dubbed as Insight-HXMT). Both the on-ground simulation and the in-orbit observation indicate that the background spectrum mainly has two components. One is the particle background that dominates above 7 keV and its spectral shape is consistent in every geographical locations. Another is the diffuse X-ray background that dominates below 7 keV and has a stable spectrum less dependent of the sky region. The particle background spectral shape can be obtained from the blind detector data of all the blank sky observations, and the particle background intensity can be measured by the blind detector at 10-12.5 keV. The diffuse X-ray background in the high Galactic latitude can also be obtained from the blank sky spectra after subtracting the particle background. Based on these characteristics, we develop the background model for both the spectrum and the light curve. The systematic error for the background spectrum is investigated with different exposures (T_exp). For the spectrum with T_exp=1 ks, the average systematic errors in 1-7 keV and 1-10 keV are 4.2% and 3.7%, respectively. We also perform the systematic error analyses of the background light curves with different energy bands and time bins. The results show that the systematic errors for the light curves with different time bins are <8% in 1-10 keV., Comment: 24 pages, 17 figures, accepted by Journal of High Energy Astrophysics

As we enter the era of domain-specific architectures, systems researchers must understand the requirements of emerging application domains. Augmented and virtual reality (AR/VR) or extended reality (XR) is one such important domain. This paper presents ILLIXR, the first open source end-to-end XR system (1) with state-of-the-art components, (2) integrated with a modular and extensible multithreaded runtime, (3) providing an OpenXR compliant interface to XR applications (e.g., game engines), and (4) with the ability to report (and trade off) several quality of experience (QoE) metrics. We analyze performance, power, and QoE metrics for the complete ILLIXR system and for its individual components. Our analysis reveals several properties with implications for architecture and systems research. These include demanding performance, power, and QoE requirements, a large diversity of critical tasks, inter-dependent execution pipelines with challenges in scheduling and resource management, and a large tradeoff space between performance/power and human perception related QoE metrics. ILLIXR and our analysis have the potential to propel new directions in architecture and systems research in general, and impact XR in particular. ILLIXR is open-source and available at https://illixr.github.io

The Medium Energy X-ray Telescope (ME) is one of the main payloads of the Hard X-ray Modulation Telescope (dubbed as Insight-HXMT). The background of Insight-HXMT/ME is mainly caused by the environmental charged particles and the background intensity is modulated remarkably by the geomagnetic field, as well as the geographical location. At the same geographical location, the background spectral shape is stable but the intensity varies with the level of the environmental charged particles. In this paper, we develop a model to estimate the ME background based on the ME database that is established with the two-year blank sky observations of the high Galactic latitude. In this model, the entire geographical area covered by Insight-HXMT is divided into grids of $5^{\circ}\times5^{\circ}$ in geographical coordinate system. For each grid, the background spectral shape can be obtained from the background database and the intensity can be corrected by the contemporary count rate of the blind FOV detectors. Thus the background spectrum can be obtained by accumulating the background of all the grids passed by Insight-HXMT during the effective observational time. The model test with the blank sky observations shows that the systematic error of the background estimation in $8.9-44.0$ keV is $\sim1.3\%$ for a pointing observation with an average exposure $\sim5.5$ ks. We also find that the systematic error is anti-correlated with the exposure, which indicates the systematic error is partly contributed by the statistical error of count rate measured by the blind FOV detectors., Comment: to be published in Journal of High Energy Astrophysics

In this work we study the weak decays of $\Xi_{cc}\to\Xi_c$ and $\Xi_{cc}\to\Xi'_c$ in the light-front quark model. Generally, a naive, but reasonable conjecture suggests that the $cc$ subsystem in $\Xi_{cc}$ ( $us$ pair in $\Xi^{(')}_c$) stands as a diquark with definite spin and color assignments. During the concerned processes, the diquark of the initial state is not a spectator, and must be broken. A Racah transformation would decompose the original $(cc)q$ into a combination of $c(cq)$ components. Thus we may deal with the decaying $c$ quark alone while keeping the $(cq)$ subsystem as a spectator. With the re-arrangement of the inner structure we calculate the form factors numerically and then obtain the rates of semi-leptonic decays and non-leptonic decays, which will be measured in the future., Comment: 18 pages, 4 firures. arXiv admin note: text overlap with arXiv:1904.05705

The Hard X-ray Modulation Telescope (HXMT) named Insight is China's first X-ray astronomical satellite. The Low Energy X-ray Telescope (LE) is one of its main payloads onboard. The detectors of LE adopt swept charge device CCD236 with L-shaped transfer electrodes. Charges in detection area are read out continuously along specific paths, which leads to a time response distribution of photons readout time. We designed a long exposure readout mode to measure the time response distribution. In this mode, CCD236 firstly performs exposure without readout, then all charges generated in preceding exposure phase are read out completely. Through analysis of the photons readout time in this mode, we obtained the probability distribution of photons readout time.