JPEG compression brings artifacts into the compressed image, which not only degrades visual quality but also affects the performance of other image processing tasks. Many learning-based compression artifacts removal methods have been developed to address this issue in recent years, with remarkable success. However, existing learning-based methods generally only exploit spatial information and lack exploration of frequency domain information. Exploring frequency domain information is critical because JPEG compression is actually performed in the frequency domain using the Discrete Cosine Transform (DCT). To effectively leverage information from both the spatial and frequency domains, we propose a novel Dual-Domain Learning Network for JPEG artifacts removal (D2LNet). Our approach first transforms the spatial domain image to the frequency domain by the fast Fourier transform (FFT). We then introduce two core modules, Amplitude Correction Module (ACM) and Phase Correction Module (PCM), which facilitate interactive learning of spatial and frequency domain information. Extensive experimental results performed on color and grayscale images have clearly demonstrated that our method achieves better results than the previous state-of-the-art methods. Code will be available at https://github.com/YeunkSuzy/Dual_Domain_Learning .

The goal of the Amazon Last Mile Routing Research Challenge is to integrate the real-life experience of Amazon drivers into the solution of optimal route planning and optimization. This paper presents our method that tackles this challenge by hierarchically combining machine learning and conventional Traveling Salesperson Problem (TSP) solvers. Our method reaps the benefits from both worlds. On the one hand, our method encodes driver know-how by learning a sequential probability model from historical routes at the zone level, where each zone contains a few parcel stops. It then uses a single step policy iteration method, known as the Rollout algorithm, to generate plausible zone sequences sampled from the learned probability model. On the other hand, our method utilizes proven methods developed in the rich TSP literature to sequence stops within each zone efficiently. The outcome of such a combination appeared to be promising. Our method obtained an evaluation score of 0.0374, which is comparable to what the top three teams have achieved on the official Challenge leaderboard. Moreover, our learning-based method is applicable to driving routes that may exhibit distinct sequential patterns beyond the scope of this Challenge. The source code of our method is publicly available at https://github.com/aws-samples/amazon-sagemaker-amazon-routing-challenge-sol

As the largest radio telescope in the world, the Square Kilometre Array (SKA) will lead the next generation of radio astronomy. The feats of engineering required to construct the telescope array will be matched only by the techniques developed to exploit the rich scientific value of the data. To drive forward the development of efficient and accurate analysis methods, we are designing a series of data challenges that will provide the scientific community with high-quality datasets for testing and evaluating new techniques. In this paper we present a description and results from the first such Science Data Challenge (SDC1). Based on SKA MID continuum simulated observations and covering three frequencies (560 MHz, 1400MHz and 9200 MHz) at three depths (8 h, 100 h and 1000 h), SDC1 asked participants to apply source detection, characterization and classification methods to simulated data. The challenge opened in November 2018, with nine teams submitting results by the deadline of April 2019. In this work we analyse the results for 8 of those teams, showcasing the variety of approaches that can be successfully used to find, characterise and classify sources in a deep, crowded field. The results also demonstrate the importance of building domain knowledge and expertise on this kind of analysis to obtain the best performance. As high-resolution observations begin revealing the true complexity of the sky, one of the outstanding challenges emerging from this analysis is the ability to deal with highly resolved and complex sources as effectively as the unresolved source population.

AbstractThe GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) is a radio continuum survey at 76–227 MHz of the entire southern sky (Declination$<\!{+}30^{\circ}$) with an angular resolution of${\approx}2$arcmin. In this paper, we combine GLEAM data with optical spectroscopy from the 6dF Galaxy Survey to construct a sample of 1 590 local (median$z \approx 0.064$) radio sources with$S_{200\,\mathrm{MHz}} > 55$mJy across an area of${\approx}16\,700\,\mathrm{deg}^{2}$. From the optical spectra, we identify the dominant physical process responsible for the radio emission from each galaxy: 73% are fuelled by an active galactic nucleus (AGN) and 27% by star formation. We present the local radio luminosity function for AGN and star-forming (SF) galaxies at 200 MHz and characterise the typical radio spectra of these two populations between 76 MHz and${\sim}1$GHz. For the AGN, the median spectral index between 200 MHz and${\sim}1$GHz,$\alpha_{\mathrm{high}}$, is$-0.600 \pm 0.010$(where$S \propto \nu^{\alpha}$) and the median spectral index within the GLEAM band,$\alpha_{\mathrm{low}}$, is$-0.704 \pm 0.011$. For the SF galaxies, the median value of$\alpha_{\mathrm{high}}$is$-0.650 \pm 0.010$and the median value of$\alpha_{\mathrm{low}}$is$-0.596 \pm 0.015$. Among the AGN population, flat-spectrum sources are more common at lower radio luminosity, suggesting the existence of a significant population of weak radio AGN that remain core-dominated even at low frequencies. However, around 4% of local radio AGN have ultra-steep radio spectra at low frequencies ($\alpha_{\mathrm{low}} < -1.2$). These ultra-steep-spectrum sources span a wide range in radio luminosity, and further work is needed to clarify their nature.

The execution framework would significantly decrease the operation costs and improve the execution performance, but developing applications of the execution framework is not an easy job. In this chapter, we present a series of examples to demonstrate how to design and develop execution framework technology-based applications.

The basal nucleus of Meynert (BNM) shows structural abnormalities in Parkinson's disease with mild cognitive impairment (PD-MCI). However, it is yet unknown whether functional connectivity (FC) in the BNM (BNM-FC) is altered in patients with PD-MCI. Therefore, in this study, we compared the BNM-FC of patients with PD-MCI and PD patients with normal cognition (PD-NC), to evaluate the relationship between the observed differences of BNM-FC and neuropsychological test scores. Three patient groups, namely PD-MCI, PD-NC, and healthy controls (HCs) (n = 22 each) including were recruited for functional magnetic resonance imaging (fMRI) scanning and neuropsychological assessment. Analysis of covariance was used to assess the inter-group differences. The relationships between BNM-FC and results of cognitive tests were evaluated by partial correlation analysis. Multivariate pattern analysis was used to test whether PD-MCI can be distinguished from PD-NC based on the BNM-FC. Classifier performance was assessed through permutation testing. Compared to PD-NC and HCs, PD-MCI showed reduced BNM-FC in the right superior parietal lobe (SPL) and the right postcentral gyrus. Furthermore, a positive correlation was observed between BNM-FC and the clock copying test (CLOX)/auditory verbal learning test (AVLT) immediate recall scores. We found that 86.36% subjects were correctly classified based on the BNM-FC using the leave-one-out cross-validation (LOOCV) method, with a sensitivity of 90.91% and specificity of 81.82%. Our study provides new insights into the neural basis of cognitive dysfunction in PD patients. We also found that BNM-FC can be an effective feature to distinguish PD-MCI from PD-NC.

The compact configuration of Phase II of the Murchison Widefield Array (MWA) consists of both a redundant subarray and pseudo-random baselines, offering unique opportunities to perform sky-model and redundant interferometric calibration. The highly redundant hexagonal cores give improved power spectrum sensitivity. In this paper, we present the analysis of nearly 40 hr of data targeting one of the MWA's epoch of reionization (EoR) fields observed in 2016. We use both improved analysis techniques presented in Barry et al. and several additional techniques developed for this work, including data quality control methods and interferometric calibration approaches. We show the EoR power spectrum limits at redshift 6.5, 6.8, and 7.1 based on our deep analysis on this 40 hr data set. These limits span a range in k-space of 0.18 h Mpc(-1) < k < 1.6 h Mpc(-1), with a lowest measurement of Delta(2) <= 2.39 x 10(3) mK(2) at k = 0.59 h Mpc(-1) and z = 6.5.

We present a modular framework, the Workload Characterisation Framework (WCF), that is developed to reproducibly obtain, store and compare key characteristics of radio astronomy processing software. As a demonstration, we discuss the experiences using the framework to characterise a LOFAR calibration and imaging pipeline.

Abstract The Murchison Widefield Array (MWA) is an electronically steered low-frequency (<300 MHz) radio interferometer, with a ‘slew’ time less than 8 s. Low-frequency (∼100 MHz) radio telescopes are ideally suited for rapid response follow-up of transients due to their large field of view, the inverted spectrum of coherent emission, and the fact that the dispersion delay between a 1 GHz and 100 MHz pulse is on the order of 1–10 min for dispersion measures of 100–2000 pc/cm3. The MWA has previously been used to provide fast follow-up for transient events including gamma-ray bursts (GRBs), fast radio bursts (FRBs), and gravitational waves, using systems that respond to gamma-ray coordinates network packet-based notifications. We describe a system for automatically triggering MWA observations of such events, based on Virtual Observatory Event standard triggers, which is more flexible, capable, and accurate than previous systems. The system can respond to external multi-messenger triggers, which makes it well-suited to searching for prompt coherent radio emission from GRBs, the study of FRBs and gravitational waves, single pulse studies of pulsars, and rapid follow-up of high-energy superflares from flare stars. The new triggering system has the capability to trigger observations in both the regular correlator mode (limited to ≥0.5 s integrations) and using the Voltage Capture System (VCS, 0.1 ms integration) of the MWA and represents a new mode of operation for the MWA. The upgraded standard correlator triggering capability has been in use since MWA observing semester 2018B (July–Dec 2018), and the VCS and buffered mode triggers will become available for observing in a future semester.

We apply two methods to estimate the 21-cm bispectrum from data taken within the Epoch of Reionisation (EoR) project of the Murchison Widefield Array (MWA). Using data acquired with the Phase II compact array allows a direct bispectrum estimate to be undertaken on the multiple redundantly spaced triangles of antenna tiles, as well as an estimate based on data gridded to the uv-plane. The direct and gridded bispectrum estimators are applied to 21 h of high-band (167-197 MHz; z = 6.2-7.5) data from the 2016 and 2017 observing seasons. Analytic predictions for the bispectrum bias and variance for point-source foregrounds are derived. We compare the output of these approaches, the foreground contribution to the signal, and future prospects for measuring the bispectra with redundant and non-redundant arrays. We find that some triangle configurations yield bispectrum estimates that are consistent with the expected noise level after 10 h, while equilateral configurations are strongly foreground-dominated. Careful choice of triangle configurations may be made to reduce foreground bias that hinders power spectrum estimators, and the 21-cm bispectrum may be accessible in less time than the 21-cm power spectrum for some wave modes, with detections in hundreds of hours.

Abstract. Cataract is one of the most prevalent causes of blindness around the world. Understanding the mechanisms of cataract development and progression is important for clinical diagnosis and treatment. Cold cataract has proven to be a robust model for cataract formation that can be easily controlled in the laboratory. There is evidence that the biomechanical properties of the lens can be significantly changed by cataract. Therefore, early detection of cataract, as well as evaluation of therapies, could be guided by characterization of lenticular biomechanical properties. In this work, we utilized optical coherence elastography (OCE) to monitor the changes in biomechanical properties of ex vivo porcine lenses during formation of cold cataract. Elastic waves were induced in the porcine lenses by a focused micro air-pulse while the lenses were cooled, and the elastic wave velocity was translated to Young’s modulus of the lens. The results show an increase in the stiffness of the lens due to formation of the cold cataract (from 11.3  ±  3.4 to 21.8  ±  7.8  kPa). These results show a relation between lens opacity and stiffness and demonstrate that OCE can assess lenticular biomechanical properties and may be useful for detecting and potentially characterizing cataracts.

We present a study of 16 H i-detected galaxies found in 178 h of observations from Epoch 1 of the COSMOS H i Large Extragalactic Survey (CHILES). We focus on two redshift ranges between 0.108 ≤ |$z$| ≤ 0.127 and 0.162 ≤ |$z$| ≤ 0.183 which are among the worst affected by radio frequency interference (RFI). While this represents only 10 per cent of the total frequency coverage and 18 per cent of the total expected time on source compared to what will be the full CHILES survey, we demonstrate that our data reduction pipeline recovers high-quality data even in regions severely impacted by RFI. We report on our in-depth testing of an automated spectral line source finder to produce H i total intensity maps which we present side-by-side with significance maps to evaluate the reliability of the morphology recovered by the source finder. We recommend that this become a common place manner of presenting data from upcoming H i surveys of resolved objects. We use the COSMOS 20k group catalogue and extract the filamentary structure using the topological DisPerSE algorithm to evaluate the H i morphology in the context of both local and large-scale environments and we discuss the shortcomings of both methods. Many of the detections show disturbed H i morphologies suggesting they have undergone a recent interaction which is not evident from deep optical imaging alone. Overall, the sample showcases the broad range of ways in which galaxies interact with their environment. This is a first look at the population of galaxies and their local and large-scale environments observed in H i by CHILES at redshifts beyond the |$z$| = 0.1 Universe.

Embryonic development involves the interplay of driving forces that shape the tissue and the mechanical resistance that the tissue offers in response. While increasing evidence has suggested the crucial role of physical mechanisms underlying embryo development, tissue biomechanics is not well understood due to the lack of techniques that can quantify the stiffness of tissue in-situ with 3D high-resolution and in a non-contact manner. In this work, we used two all-optical technique, optical coherence tomography (OCT) and Brillouin microscopy, to map the longitudinal modulus of the neural tube tissue of mouse embryo in-situ. We found the tissue stiffens significantly after the closure of the neural tube at cranial regions by comparing embryos at E 8.5 and E 9.5. In addition, we observed that the region of fusion following neural tube closure is softer than the adjacent neural folds, and the neural folds show a modulus gradient along dorsal-ventral direction. Furthermore, we found the overlaying ectoderm is much softer and more pliable than the closed neural tube, and thus can be distinguished based on its mechanical properties. In conclusion, we demonstrated the capability of OCT and Brillouin microscopy to quantify tissue modulus of mouse embryos in-situ, and observed a distinct change of tissue modulus during the closure of cranial neural tube, suggesting this method could be helpful in investigating the role of tissue biomechanics in the regulation of embryo development.

One of the major challenges for pulsar timing array (PTA) experiments is the mitigation of the effects of the turbulent interstellar medium (ISM) from timing data. These can potentially lead to measurable delays and/or distortions in the pulse profiles and scale strongly with the inverse of the radio frequency. Low-frequency observations are therefore highly appealing for characterizing them. However, in order to achieve the necessary time resolution to resolve profile features of short-period millisecond pulsars, phase-coherent dedispersion is essential, especially at frequencies below 300 MHz. We present the lowest-frequency (80–220 MHz), coherently dedispersed detections of one of the most promising pulsars for current and future PTAs, PSR J2241–5236, using our new beamformer software for the MWA’s voltage capture system, which reconstructs the time series at a much higher time resolution of ∼1 μs by resynthesizing the recorded voltage data at 10 kHz/100 μs native resolutions. Our data reveal a dual-precursor type feature in the pulse profile that is either faint or absent in high-frequency observations from Parkes. The resultant high-fidelity detections have enabled dispersion measure determinations with very high precision, of the order of (2–6) × 10−6 , owing to the microsecond level timing achievable for this pulsar at the MWA’s low frequencies. This underscores the usefulness of low-frequency observations for probing the ISM toward PTA pulsars and informing optimal observing strategies for PTA experiments.

Normal intraocular pressure (TOP) is crucial for proper maintaining of eye-globe geometry, ocular tissue health, and visual acuity. An elevated IOP is associated with diseases such as glaucoma and uveitis. While the effects of an elevated IOP on the delicate tissues of the optic nerve head and retina are well-studied, the changes in lenticular biomechanical properties as a function of IOP are not as clear. Moreover, changes in lenticular biomechanical properties have been implicated in conditions and diseases such as presbyopia and cataract. However, measuring the biomechanical properties of the lens as it sits inside the eye-globe is a challenge, but it is necessary to correctly understand the interplay between lenticular biomechanical properties and IOP. In this work, we utilized optical coherence elastography (OCE) to measure the biomechanical properties of the porcine lens in situ.

Maintaining a normal intraocular pressure (TOP) is important for visual health. Elevated IOPs have been implicated in many diseases, such as glaucoma and uveitis. The effects of an elevated IOP on the delicate tissues of the optic nerve head and retina are well-studied, but there is a lack of information about the effects of high IOPs on the stiffness of the crystalline lens. Changes in lenticular biomechanical properties have been implicated in diseases such as presbyopia and cataract, therefore, measuring lenticular biomechanical properties is crucial to understanding the etiology and progression of the leading causes of vision impairment. Additionally, there has been even less research focused on the effects of storage media on lenticular stiffness. Previous studies have been focused on the "gold standard" of mechanical testing on excised lenses. However, mechanical testing is invasive and destructive, and removal of the lens from the eye-globe does not allow for properly replicating the lens environment in the eye-globe. Thus, there is a need for noninvasive measurement techniques capable of performing in situ and in vivo elastographic measurements of the lens. Here, we artificially controlled the IOP of whole porcine eye-globes (N=3). Acoustic radiation force induced low amplitude displacements (<10 mu m) at the apex of the lenses, which then propagated as an elastic wave. The elastic wave propagation was detected by a phase-sensitive optical coherence elastography (PhS-OCE) system. The results show that the stiffness of the lenses increased when IOP increased from 10 mmHg IOP to 40 mmHg. Additional OCE measurements were made on excised lenses stored in various media (PBS, DMEM, and M-199) at different pHs (4-7) and at different temperatures (4 degrees C, 22 degrees C, and 37 degrees C). The results show that the stiffness of the lenses increased slightly when incubated at 4 degrees C or 22 degrees C, but decreased when the lenses were incubated at 37 degrees C, while lenses incubated in M-199 showed more stability in their stiffness than lenses incubated in PBS and DMEM. Moreover, the lenses stored in M-199 at a pH of 7 showed a decrease in stiffness over 24 hours, while the more acidic M-199 media caused an increase in lenticular stiffness.

AbstractThe Murchison Widefield Array (MWA) is an open access telescope dedicated to studying the low-frequency (80–300 MHz) southern sky. Since beginning operations in mid-2013, the MWA has opened a new observational window in the southern hemisphere enabling many science areas. The driving science objectives of the original design were to observe 21 cm radiation from the Epoch of Reionisation (EoR), explore the radio time domain, perform Galactic and extragalactic surveys, and monitor solar, heliospheric, and ionospheric phenomena. All together$60+$programs recorded 20 000 h producing 146 papers to date. In 2016, the telescope underwent a major upgrade resulting in alternating compact and extended configurations. Other upgrades, including digital back-ends and a rapid-response triggering system, have been developed since the original array was commissioned. In this paper, we review the major results from the prior operation of the MWA and then discuss the new science paths enabled by the improved capabilities. We group these science opportunities by the four original science themes but also include ideas for directions outside these categories.

The upcoming next-generation large area radio continuum surveys can expect tens of millions of radio sources, rendering the traditional method for radio morphology classification through visual inspection unfeasible. We present Claran - Classifying Radio sources Automatically with Neural networks - a proof-of-concept radio source morphology classifier based upon the Faster Region-based Convolutional Neutral Networks method. Specifically, we train and test Claran on the FIRST and WISE (Wide-field Infrared Survey Explorer) images from the Radio Galaxy Zoo Data Release 1 catalogue. Claran provides end users with automated identification of radio source morphology classifications from a simple input of a radio image and a counterpart infrared image of the same region. Claran is the first open-source, end-to-end radio source morphology classifier that is capable of locating and associating discrete and extended components of radio sources in a fast (< 200 ms per image) and accurate (>= 90 per cent) fashion. Future work will improve Claran's relatively lower success rates in dealing with multisource fields and will enable Claran to identify sources on much larger fields without loss in classification accuracy.

Interferometric arrays seeking to measure the 21 cm signal from the epoch of reionization (EOR) must contend with overwhelmingly bright emission from foreground sources. Accurate recovery of the 21 cm signal will require precise calibration of the array, and several new avenues for calibration have been pursued in recent years, including methods using redundancy in the antenna configuration. The newly upgraded Phase II of Murchison Widefield Array (MWA) is the first interferometer that has large numbers of redundant baselines while retaining good instantaneous UV coverage. This array therefore provides a unique opportunity to compare redundant calibration with sky-model-based algorithms. In this paper, we present the first results from comparing both calibration approaches with MWA Phase II observations. For redundant calibration, we use the package OMNICAL and produce sky-based calibration solutions with the analysis package Fast Holographic Deconvolution (FHD). There are three principal results: (1) We report the success of OMNICAL on observations of ORBComm satellites, showing substantial agreement between redundant visibility measurements after calibration. (2) We directly compare OMNICAL calibration solutions with those from FHD and demonstrate that these two different calibration schemes give extremely similar results. (3) We explore improved calibration by combining OMNICAL and FHD. We evaluate these combined methods using power spectrum techniques developed for EOR analysis and find evidence for marginal improvements mitigating artifacts in the power spectrum. These results are likely limited by the signal-to-noise ratio in the 6 hr of data used, but they suggest future directions for combining these two calibration schemes.