Showing papers by "National Tsing Hua University published in 2020"
TL;DR: In 2019, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9 and the Virgo detector was also taking data that did not contribute to detection due to a low SINR but were used for subsequent parameter estimation as discussed by the authors.
Abstract: On 2019 April 25, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9. The Virgo detector was also taking data that did not contribute to detection due to a low signal-to-noise ratio, but were used for subsequent parameter estimation. The 90% credible intervals for the component masses range from to if we restrict the dimensionless component spin magnitudes to be smaller than 0.05). These mass parameters are consistent with the individual binary components being neutron stars. However, both the source-frame chirp mass and the total mass of this system are significantly larger than those of any other known binary neutron star (BNS) system. The possibility that one or both binary components of the system are black holes cannot be ruled out from gravitational-wave data. We discuss possible origins of the system based on its inconsistency with the known Galactic BNS population. Under the assumption that the signal was produced by a BNS coalescence, the local rate of neutron star mergers is updated to 250-2810.
1,189 citations
TL;DR: In this paper, the authors reported the observation of a compact binary coalescence involving a 222 −243 M ⊙ black hole and a compact object with a mass of 250 −267 M ⋆ (all measurements quoted at the 90% credible level) The gravitational-wave signal, GW190814, was observed during LIGO's and Virgo's third observing run on 2019 August 14 at 21:10:39 UTC and has a signal-to-noise ratio of 25 in the three-detector network.
Abstract: We report the observation of a compact binary coalescence involving a 222–243 M ⊙ black hole and a compact object with a mass of 250–267 M ⊙ (all measurements quoted at the 90% credible level) The gravitational-wave signal, GW190814, was observed during LIGO's and Virgo's third observing run on 2019 August 14 at 21:10:39 UTC and has a signal-to-noise ratio of 25 in the three-detector network The source was localized to 185 deg2 at a distance of ${241}_{-45}^{+41}$ Mpc; no electromagnetic counterpart has been confirmed to date The source has the most unequal mass ratio yet measured with gravitational waves, ${0112}_{-0009}^{+0008}$, and its secondary component is either the lightest black hole or the heaviest neutron star ever discovered in a double compact-object system The dimensionless spin of the primary black hole is tightly constrained to ≤007 Tests of general relativity reveal no measurable deviations from the theory, and its prediction of higher-multipole emission is confirmed at high confidence We estimate a merger rate density of 1–23 Gpc−3 yr−1 for the new class of binary coalescence sources that GW190814 represents Astrophysical models predict that binaries with mass ratios similar to this event can form through several channels, but are unlikely to have formed in globular clusters However, the combination of mass ratio, component masses, and the inferred merger rate for this event challenges all current models of the formation and mass distribution of compact-object binaries
913 citations
TL;DR: It is inferred that the primary black hole mass lies within the gap produced by (pulsational) pair-instability supernova processes, with only a 0.32% probability of being below 65 M⊙, which can be considered an intermediate mass black hole (IMBH).
Abstract: On May 21, 2019 at 03:02:29 UTC Advanced LIGO and Advanced Virgo observed a short duration gravitational-wave signal, GW190521, with a three-detector network signal-to-noise ratio of 14.7, and an estimated false-alarm rate of 1 in 4900 yr using a search sensitive to generic transients. If GW190521 is from a quasicircular binary inspiral, then the detected signal is consistent with the merger of two black holes with masses of 85_{-14}^{+21} M_{⊙} and 66_{-18}^{+17} M_{⊙} (90% credible intervals). We infer that the primary black hole mass lies within the gap produced by (pulsational) pair-instability supernova processes, with only a 0.32% probability of being below 65 M_{⊙}. We calculate the mass of the remnant to be 142_{-16}^{+28} M_{⊙}, which can be considered an intermediate mass black hole (IMBH). The luminosity distance of the source is 5.3_{-2.6}^{+2.4} Gpc, corresponding to a redshift of 0.82_{-0.34}^{+0.28}. The inferred rate of mergers similar to GW190521 is 0.13_{-0.11}^{+0.30} Gpc^{-3} yr^{-1}.
876 citations
TL;DR: A comparative study of deep techniques in image denoising by classifying the deep convolutional neural networks for additive white noisy images, the deep CNNs for real noisy images; the deepCNNs for blind Denoising and the deep network for hybrid noisy images.
518 citations
TL;DR: In this article, the authors reported the observation of gravitational waves from a binary-black-hole coalescence during the first two weeks of LIGO and Virgo's third observing run.
Abstract: We report the observation of gravitational waves from a binary-black-hole coalescence during the first two weeks of LIGO’s and Virgo’s third observing run. The signal was recorded on April 12, 2019 at 05∶30∶44 UTC with a network signal-to-noise ratio of 19. The binary is different from observations during the first two observing runs most notably due to its asymmetric masses: a ∼30 M⊙ black hole merged with a ∼8 M⊙ black hole companion. The more massive black hole rotated with a dimensionless spin magnitude between 0.22 and 0.60 (90% probability). Asymmetric systems are predicted to emit gravitational waves with stronger contributions from higher multipoles, and indeed we find strong evidence for gravitational radiation beyond the leading quadrupolar order in the observed signal. A suite of tests performed on GW190412 indicates consistency with Einstein’s general theory of relativity. While the mass ratio of this system differs from all previous detections, we show that it is consistent with the population model of stellar binary black holes inferred from the first two observing runs.
507 citations
TL;DR: The GW190521 signal is consistent with a binary black hole (BBH) merger source at redshift 0.13-0.30 Gpc-3 yr-1.8 as discussed by the authors.
Abstract: The gravitational-wave signal GW190521 is consistent with a binary black hole (BBH) merger source at redshift 0.8 with unusually high component masses, 85-14+21 M o˙ and 66-18+17 M o˙, compared to previously reported events, and shows mild evidence for spin-induced orbital precession. The primary falls in the mass gap predicted by (pulsational) pair-instability supernova theory, in the approximate range 65-120 M o˙. The probability that at least one of the black holes in GW190521 is in that range is 99.0%. The final mass of the merger (142-16+28 M o˙) classifies it as an intermediate-mass black hole. Under the assumption of a quasi-circular BBH coalescence, we detail the physical properties of GW190521's source binary and its post-merger remnant, including component masses and spin vectors. Three different waveform models, as well as direct comparison to numerical solutions of general relativity, yield consistent estimates of these properties. Tests of strong-field general relativity targeting the merger-ringdown stages of the coalescence indicate consistency of the observed signal with theoretical predictions. We estimate the merger rate of similar systems to be 0.13-0.11+0.30 Gpc-3 yr-1. We discuss the astrophysical implications of GW190521 for stellar collapse and for the possible formation of black holes in the pair-instability mass gap through various channels: via (multiple) stellar coalescences, or via hierarchical mergers of lower-mass black holes in star clusters or in active galactic nuclei. We find it to be unlikely that GW190521 is a strongly lensed signal of a lower-mass black hole binary merger. We also discuss more exotic possible sources for GW190521, including a highly eccentric black hole binary, or a primordial black hole binary.
347 citations
01 Jul 2020
TL;DR: The development of neuro-inspired computing chips and their key benchmarking metrics are reviewed, providing a co-design tool chain and proposing a roadmap for future large-scale chips are provided and a future electronic design automation tool chain is proposed.
Abstract: The rapid development of artificial intelligence (AI) demands the rapid development of domain-specific hardware specifically designed for AI applications. Neuro-inspired computing chips integrate a range of features inspired by neurobiological systems and could provide an energy-efficient approach to AI computing workloads. Here, we review the development of neuro-inspired computing chips, including artificial neural network chips and spiking neural network chips. We propose four key metrics for benchmarking neuro-inspired computing chips — computing density, energy efficiency, computing accuracy, and on-chip learning capability — and discuss co-design principles, from the device to the algorithm level, for neuro-inspired computing chips based on non-volatile memory. We also provide a future electronic design automation tool chain and propose a roadmap for the development of large-scale neuro-inspired computing chips. This Review Article examines the development of neuro-inspired computing chips and their key benchmarking metrics, providing a co-design tool chain and proposing a roadmap for future large-scale chips.
303 citations
TL;DR: In this article, a search for the electroweak production of charginos and sleptons decaying into final states with two electrons or muons is presented, based on 139.fb$^{-1}$ of proton-proton collisions recorded by the ATLAS detector at the Large Hadron Collider at
Abstract: A search for the electroweak production of charginos and sleptons decaying into final states with two electrons or muons is presented. The analysis is based on 139 fb$^{-1}$ of proton–proton collisions recorded by the ATLAS detector at the Large Hadron Collider at $\sqrt{s}=13$ $\text {TeV}$. Three R-parity-conserving scenarios where the lightest neutralino is the lightest supersymmetric particle are considered: the production of chargino pairs with decays via either W bosons or sleptons, and the direct production of slepton pairs. The analysis is optimised for the first of these scenarios, but the results are also interpreted in the others. No significant deviations from the Standard Model expectations are observed and limits at 95% confidence level are set on the masses of relevant supersymmetric particles in each of the scenarios. For a massless lightest neutralino, masses up to 420 $\text {Ge}\text {V}$ are excluded for the production of the lightest-chargino pairs assuming W-boson-mediated decays and up to 1 $\text {TeV}$ for slepton-mediated decays, whereas for slepton-pair production masses up to 700 $\text {Ge}\text {V}$ are excluded assuming three generations of mass-degenerate sleptons.
272 citations
TL;DR: A nanohybrid-based wireless monitoring system with capabilities for selectivity and sensing for volatile organic compounds that are enhanced by heterojunction interfaces that could guide future exploration of next-generation field-deployable sensors.
Abstract: Two-dimensional transition metal carbides/nitrides, known as MXenes, have been recently receiving attention for gas sensing. However, studies on hybridization of MXenes and 2D transition metal dichalcogenides as gas-sensing materials are relatively rare at this time. Herein, Ti3C2Tx and WSe2 are selected as model materials for hybridization and implemented toward detection of various volatile organic compounds. The Ti3C2Tx/WSe2 hybrid sensor exhibits low noise level, ultrafast response/recovery times, and good flexibility for various volatile organic compounds. The sensitivity of the hybrid sensor to ethanol is improved by over 12-fold in comparison with pristine Ti3C2Tx. Moreover, the hybridization process provides an effective strategy against MXene oxidation by restricting the interaction of water molecules from the edges of Ti3C2Tx. An enhancement mechanism for Ti3C2Tx/WSe2 heterostructured materials is proposed for highly sensitive and selective detection of oxygen-containing volatile organic compounds. The scientific findings of this work could guide future exploration of next-generation field-deployable sensors.
268 citations
TL;DR: It is shown that optimal distribution of surgical-standard face masks in the population, or universal coverage of homemade face coverings, could reduce total infections and deaths.
Abstract: The ongoing novel coronavirus disease (COVID-19) pandemic has already infected millions worldwide and, with no vaccine available, interventions to mitigate transmission are urgently needed. While there is broad agreement that travel restrictions and social distancing are beneficial in limiting spread, recommendations around face mask use are inconsistent. Here, we use mathematical modeling to examine the epidemiological impact of face masks, considering resource limitations and a range of supply and demand dynamics. Even with a limited protective effect, face masks can reduce total infections and deaths, and can delay the peak time of the epidemic. However, random distribution of masks is generally suboptimal; prioritized coverage of the elderly improves outcomes, while retaining resources for detected cases provides further mitigation under a range of scenarios. Face mask use, particularly for a pathogen with relatively common asymptomatic carriage, is an effective intervention strategy, while optimized distribution is important when resources are limited.
225 citations
TL;DR: In this paper, the authors identify the origin of this shift as arising from the exponentiation of spin operators for the recently defined minimally coupled three-particle amplitudes of spinning particles coupled to gravity, in the large-spin limit.
Abstract: Long ago, Newman and Janis showed that a complex deformation z → z + ia of the Schwarzschild solution produces the Kerr solution. The underlying explanation for this relationship has remained obscure. The complex deformation has an electromagnetic counterpart: by shifting the Coloumb potential, we obtain the EM field of a certain rotating charge distribution which we term $$ \sqrt{\mathrm{Kerr}} $$
. In this note, we identify the origin of this shift as arising from the exponentiation of spin operators for the recently defined “minimally coupled” three-particle amplitudes of spinning particles coupled to gravity, in the large- spin limit. We demonstrate this by studying the impulse imparted to a test particle in the background of the heavy spinning particle. We first consider the electromagnetic case, where the impulse due to $$ \sqrt{\mathrm{Kerr}} $$
is reproduced by a charged spinning particle; the shift of the Coloumb potential is matched to the exponentiated spin-factor appearing in the amplitude. The known impulse due to the Kerr black hole is then trivially derived from the gravitationally coupled spinning particle via the double copy.
TL;DR: A surface functionalization strategy for Ti3C2Tx with fluoroalkylsilane (FOTS) molecules through surface treatment is demonstrated, providing not only a superhydrophobic surface, mechanical/environmental stability, but also enhanced sensing performance.
Abstract: Two-dimensional (2D) transition-metal carbides (Ti3C2Tx MXene) have received a great deal of attention for potential use in gas sensing showing the highest sensitivity among 2D materials and good gas selectivity. However, one of the long-standing challenges of the MXenes is their poor stability against hydration and oxidation in a humid environment, limiting their long-term storage and applications. Integration of an effective protection layer with MXenes shows promise for overcoming this major drawback. Herein, we demonstrate a surface functionalization strategy for Ti3C2Tx with fluoroalkylsilane (FOTS) molecules through surface treatment, providing not only a superhydrophobic surface, mechanical/environmental stability but also enhanced sensing performance. The experimental results show that high sensitivity, good repeatability, long-term stability, and selectivity and faster response/recovery property were achieved by the FOTS-functionalized when Ti3C2Tx was integrated into chemoresistive sensors sensitive to oxygen-containing volatile organic compounds (ethanol, acetone). FOTS functionalization provided protection to sensing response when the dynamic response of the Ti3C2Tx-F sensor to 30 ppm of ethanol was measured over in the 5 to 80% relative humidity range. Density functional theory simulations suggested that the strong adsorption energy of ethanol on Ti3C2Tx-F and the local structure deformation induced by ethanol adsorption, contributing to the gas-sensing enhancement. This study offers a facile and practical solution for developing highly reliable MXene based gas-sensing devices with response that is stable in air and in the presence of water.
TL;DR: In this paper, the trigger algorithms and selection were optimized to control the rates while retaining a high efficiency for physics analyses at the ATLAS experiment to cope with a fourfold increase of peak LHC luminosity from 2015 to 2018 (Run 2), and a similar increase in the number of interactions per beam-crossing to about 60.
Abstract: Electron and photon triggers covering transverse energies from 5 GeV to several TeV are essential for the ATLAS experiment to record signals for a wide variety of physics: from Standard Model processes to searches for new phenomena in both proton–proton and heavy-ion collisions. To cope with a fourfold increase of peak LHC luminosity from 2015 to 2018 (Run 2), to 2.1×1034cm-2s-1, and a similar increase in the number of interactions per beam-crossing to about 60, trigger algorithms and selections were optimised to control the rates while retaining a high efficiency for physics analyses. For proton–proton collisions, the single-electron trigger efficiency relative to a single-electron offline selection is at least 75% for an offline electron of 31 GeV, and rises to 96% at 60 GeV; the trigger efficiency of a 25 GeV leg of the primary diphoton trigger relative to a tight offline photon selection is more than 96% for an offline photon of 30 GeV. For heavy-ion collisions, the primary electron and photon trigger efficiencies relative to the corresponding standard offline selections are at least 84% and 95%, respectively, at 5 GeV above the corresponding trigger threshold.
TL;DR: A search for heavy neutral Higgs bosons is performed using the LHC Run 2 data, corresponding to an integrated luminosity of 139 fb^{-1} of proton-proton collisions at sqrt[s]=13TeV recorded with the ATLAS detector.
Abstract: A search for heavy neutral Higgs bosons is performed using the LHC Run 2 data, corresponding to an integrated luminosity of 139 fb^{-1} of proton-proton collisions at sqrt[s]=13 TeV recorded with the ATLAS detector. The search for heavy resonances is performed over the mass range 0.2-2.5 TeV for the τ^{+}τ^{-} decay with at least one τ-lepton decaying into final states with hadrons. The data are in good agreement with the background prediction of the standard model. In the M_{h}^{125} scenario of the minimal supersymmetric standard model, values of tanβ>8 and tanβ>21 are excluded at the 95% confidence level for neutral Higgs boson masses of 1.0 and 1.5 TeV, respectively, where tanβ is the ratio of the vacuum expectation values of the two Higgs doublets.
TL;DR: In this article, exciton delocalization, which serves to decouple the exciton band from highly vibrational ladders in the ground state, can bring substantial enhancements in the photoluminescence quantum yield of emitters, bypassing the energy gap law.
Abstract: The development of high-performance near-infrared organic light-emitting diodes is hindered by strong non-radiative processes as governed by the energy gap law Here, we show that exciton delocalization, which serves to decouple the exciton band from highly vibrational ladders in the S0 ground state, can bring substantial enhancements in the photoluminescence quantum yield of emitters, bypassing the energy gap law Experimental proof is provided by the design and synthesis of a series of new Pt(ii) complexes with a delocalization length of 5–9 molecules that emit at 866–960 nm with a photoluminescence quantum yield of 5–12% in solid films The corresponding near-infrared organic light-emitting diodes emit light with a 930 nm peak wavelength and a high external quantum efficiency up to 214% and a radiance of 416 W sr−1 m−2 Both theoretical and experimental results confirm the exciton–vibration decoupling strategy, which should be broadly applicable to other well-aligned molecular solids Pt(ii) complexes allow the fabrication of efficient near-infrared organic light-emitting diodes that operate beyond the 900 nm region
TL;DR: In this paper, the authors present a charter for tourism, travel, and hospitality after COVID-19 as a contribution to the industry, which is essential to investigate how the industry will recover after the virus outbreak.
Abstract: The SARS-CoV-2 virus that causes the COVID-19 disease is highly infectious and contagious. The long-term consequences for individuals are as yet unknown, while the long-term effects on the international community will be dramatic. COVID-19 has changed the world forever in every imaginable respect and has impacted heavily on the international travel, tourism demand, and hospitality industry, which is one of the world’s largest employers and is highly sensitive to significant shocks like the COVID-19 pandemic. It is essential to investigate how the industry will recover after COVID-19 and how the industry can be made sustainable in a dramatically changed world. This paper presents a charter for tourism, travel, and hospitality after COVID-19 as a contribution to the industry.
TL;DR: The first confirmed case of novel coronavirus pneumonia (NCP) imported from China in Taiwan is reported, revealing a natural course of NCP with self-recovery, which may be a good example in comparison with medical treatments.
TL;DR: The LIGO Scientific Collaboration and the Virgo Collaboration have cataloged eleven confidently detected gravitational-wave events during the first two observing runs of the advanced detector era as discussed by the authors.
Abstract: The LIGO Scientific Collaboration and the Virgo Collaboration have cataloged eleven confidently detected gravitational-wave events during the first two observing runs of the advanced detector era. All eleven events were consistent with being from well-modeled mergers between compact stellar-mass objects: black holes or neutron stars. The data around the time of each of these events have been made publicly available through the gravitational-wave open science center. The entirety of the gravitational-wave strain data from the first and second observing runs have also now been made publicly available. There is considerable interest among the broad scientific community in understanding the data and methods used in the analyses. In this paper, we provide an overview of the detector noise properties and the data analysis techniques used to detect gravitational-wave signals and infer the source properties. We describe some of the checks that are performed to validate the analyses and results from the observations of gravitational-wave events. We also address concerns that have been raised about various properties of LIGO–Virgo detector noise and the correctness of our analyses as applied to the resulting data.
TL;DR: In this paper, the authors proposed a time-dependent susceptible-infected-recovered (SIR) model that tracks two time series: (i) the transmission rate at time t and (ii) the recovering rate at t. This model is more adaptive than traditional static SIR models and more robust than direct estimation methods.
Abstract: In this paper, we conduct mathematical and numerical analyses to address the following crucial questions for COVID-19: (Q1) Is it possible to contain COVID-19? (Q2) When will be the peak and the end of the epidemic? (Q3) How do the asymptomatic infections affect the spread of disease? (Q4) What is the ratio of the population that needs to be infected to achieve herd immunity? (Q5) How effective are the social distancing approaches? (Q6) What is the ratio of the population infected in the long run? For (Q1) and (Q2), we propose a time-dependent susceptible-infected-recovered (SIR) model that tracks 2 time series: (i) the transmission rate at time t and (ii) the recovering rate at time t. Such an approach is more adaptive than traditional static SIR models and more robust than direct estimation methods. Using the data provided by China, we show that the one-day prediction errors for the numbers of confirmed cases are almost in 3%, and the total number of confirmed cases is precisely predicted. Also, the turning point, defined as the day that the transmission rate is less than the recovering rate can be accurately predicted. After that day, the basic reproduction number $R_0$ is less than 1. For (Q3), we extend our SIR model by considering 2 types of infected persons: detectable and undetectable infected persons. Whether there is an outbreak in such a model is characterized by the spectral radius of a 2 by 2 matrix that is closely related to $R_0$. For (Q4), we show that herd immunity can be achieved after at least 1-1/$R_0$ fraction of individuals being infected. For (Q5) and (Q6), we analyze the independent cascade (IC) model for disease propagation in a configuration random graph. By relating the propagation probabilities in the IC model to the transmission rates and recovering rates in the SIR model, we show 2 approaches of social distancing that can lead to a reduction of $R_0$.
01 Feb 2020
TL;DR: This work implements a fully-integrated 784-100-10 MLP model on an integrated CIM chip with158.8kb analog ReRAMs and proposes a low-power interface design with resolution-adjustable LPAR-ADC to realize flexible tradeoff between system accuracy and power consumption.
Abstract: Non-volatile memory (NVM) based computing-in-memory (CIM) shows significant advantages in handling deep learning tasks for artificial intelligence (AI) applications. To overcome the decreasing cost effectiveness of transistor scaling and the intrinsic inefficiency of data-shuttling in the von-Neumann architecture, CIM is proposed to realize high-speed and low-power system with parallel multiplication accumulation (MAC) computing [1] [2]. However, current demonstrations are mainly based on single macro and present limited computing parallelism. Realizing a fully-integrated CIM chip with a complete neural network model is still missing. The major challenges lie in: (1) The IR drop and transient errors when carrying out MAC operations in non-volatile memory arrays decrease the computing accuracy and further limit the parallelism; (2) The inefficiency of the interface blocks between different arrays due to the power overhead of the A/D and D/A converters (shown in Fig. 33.2.1). To address these challenges, this work proposes: (1) A sign-weighted 2T2R (SW-2T2R) array to reduce IR drop by decreasing the accumulative SL current (ISL), and eventually boost the computing parallelism; (2) a low-power interface design with resolution-adjustable LPAR-ADC to realize flexible tradeoff between system accuracy and power consumption. In this manner, this work implements a fully-integrated 784-100-10 MLP model on an integrated CIM chip with158.8kb analog ReRAMs. This chip realizes high recognition accuracy (94.4%) on MNIST database, high inference speed (77 µs/lmage), and 78.4 TOPS/W peak energy efficiency. The CMOS circuits are fabricated in a 130nm process.
TL;DR: Hierarchically ordered mesoporous materials have gained significant scientific attention due to their high surface areas, uniform porosity over various lengths scales, high volume storage capability, shape selectivity, enhanced mass transport and diffusion.
Abstract: Hierarchically ordered mesoporous materials have gained significant scientific attention due to their high surface areas, uniform porosity over various lengths scales, high-volume storage capability, shape selectivity, enhanced mass transport and diffusion. These materials have been widely applied in the fields of photocatalysis, separation, adsorption, photovoltaic solar cells, energy storage and conversion, chemical sensing, and drug delivery. In general, hierarchically porous materials can be generated in two ways: through sol-gel template approaches and a combination of surfactant-assisted procedures. In this review, we discuss recent progress in the preparation, properties, and potential applications of four hierarchically ordered porous materials: hierarchical mesoporous silica, mesoporous phenolic/carbon, nitrogen-doped mesoporous carbon, and mesoporous/microporous covalent organic frameworks.
TL;DR: In this article, it was shown that at null infinity, the complex transformation is equivalent to a complexified Bondi-Metzner-Sachs supertranslation, which rotates the supertranslation and the dual (magnetic) supertranslation charges.
Abstract: We argue that the complex transformation relating the Schwarzschild to the Taub-NUT metric, introduced by Talbot, is in fact an electric-magnetic duality transformation. We show that at null infinity, the complex transformation is equivalent to a complexified Bondi-Metzner-Sachs supertranslation, which rotates the supertranslation and the dual (magnetic) supertranslation charges. This can also be seen from the cubic coupling between the classical source and its background, which for Taub-NUT is given by a complex phase rotation acting on gravitational minimal couplings. The same phase rotation generates dyons from electrons at the level of minimally coupled amplitudes, manifesting the double copy relation between the two solutions.
14 Jun 2020
TL;DR: Zhang et al. as discussed by the authors used an object detector to obtain cropped object images and then used an instance colorization network to extract object-level features and applied a fusion module to full object level and image level features to predict the final colors.
Abstract: Image colorization is inherently an ill-posed problem with multi-modal uncertainty. Previous methods leverage the deep neural network to map input grayscale images to plausible color outputs directly. Although these learning-based methods have shown impressive performance, they usually fail on the input images that contain multiple objects. The leading cause is that existing models perform learning and colorization on the entire image. In the absence of a clear figure-ground separation, these models cannot effectively locate and learn meaningful object-level semantics. In this paper, we propose a method for achieving instance-aware colorization. Our network architecture leverages an off-the-shelf object detector to obtain cropped object images and uses an instance colorization network to extract object-level features. We use a similar network to extract the full-image features and apply a fusion module to full object-level and image-level features to predict the final colors. Both colorization networks and fusion modules are learned from a large-scale dataset. Experimental results show that our work outperforms existing methods on different quality metrics and achieves state-of-the-art performance on image colorization.
TL;DR: N nanotechnology-enabled dual delivery of siRNA and plasmid DNA that selectively targets and reprograms the immunosuppressive tumor microenvironment to improve cancer immunotherapy is presented.
Abstract: While immunotherapy holds great promise for combating cancer, the limited efficacy due to an immunosuppressive tumor microenvironment and systemic toxicity hinder the broader application of cancer immunotherapy. Here, we report a combinatorial immunotherapy approach that uses a highly efficient and tumor-selective gene carrier to improve anticancer efficacy and circumvent the systemic toxicity. In this study, we engineered tumor-targeted lipid-dendrimer-calcium-phosphate (TT-LDCP) nanoparticles (NPs) with thymine-functionalized dendrimers that exhibit not only enhanced gene delivery capacity but also immune adjuvant properties by activating the stimulator of interferon genes (STING)–cGAS pathway. TT-LDCP NPs delivered siRNA against immune checkpoint ligand PD-L1 and immunostimulatory IL-2–encoding plasmid DNA to hepatocellular carcinoma (HCC), increased tumoral infiltration and activation of CD8+ T cells, augmented the efficacy of cancer vaccine immunotherapy, and suppressed HCC progression. Our work presents nanotechnology-enabled dual delivery of siRNA and plasmid DNA that selectively targets and reprograms the immunosuppressive tumor microenvironment to improve cancer immunotherapy.
TL;DR: Crown ethers are employed to modulate perovskite films, affording passivation of undercoordinated surface defects, which reduces the concentration of surface electronic defects and suppresses nonradiative recombination, accompanied by enhanced stability under ambient and operational conditions.
Abstract: The use of molecular modulators to reduce the defect density at the surface and grain boundaries of perovskite materials has been demonstrated to be an effective approach to enhance the photovoltaic performance and device stability of perovskite solar cells. Herein, we employ crown ethers to modulate perovskite films, affording passivation of undercoordinated surface defects. This interaction has been elucidated by solid-state nuclear magnetic resonance and density functional theory calculations. The crown ether hosts induce the formation of host-guest complexes on the surface of the perovskite films, which reduces the concentration of surface electronic defects and suppresses nonradiative recombination by 40%, while minimizing moisture permeation. As a result, we achieved substantially improved photovoltaic performance with power conversion efficiencies exceeding 23%, accompanied by enhanced stability under ambient and operational conditions. This work opens a new avenue to improve the performance and stability of perovskite-based optoelectronic devices through supramolecular chemistry.
14 Jun 2020
TL;DR: A bi-projection fusion scheme along with learnable masks to balance the feature map from the two projections is proposed to predict the depth map of a monocular 360 image by mimicking both peripheral and foveal vision of the human eye.
Abstract: Depth estimation from a monocular 360 image is an emerging problem that gains popularity due to the availability of consumer-level 360 cameras and the complete surrounding sensing capability. While the standard of 360 imaging is under rapid development, we propose to predict the depth map of a monocular 360 image by mimicking both peripheral and foveal vision of the human eye. To this end, we adopt a two-branch neural network leveraging two common projections: equirectangular and cubemap projections. In particular, equirectangular projection incorporates a complete field-of-view but introduces distortion, whereas cubemap projection avoids distortion but introduces discontinuity at the boundary of the cube. Thus we propose a bi-projection fusion scheme along with learnable masks to balance the feature map from the two projections. Moreover, for the cubemap projection, we propose a spherical padding procedure which mitigates discontinuity at the boundary of each face. We apply our method to four panorama datasets and show favorable results against the existing state-of-the-art methods.
TL;DR: A summary of the recent advancements in the fundamental understanding of high entropy alloys (HEAs) as well as igniting new ideas and activities in this rapidly evolving field of use-inspired basic research is provided in this article.
Posted Content•
TL;DR: A learning-based inpainting model is presented that iteratively synthesizes new local color-and-depth content into the occluded region in a spatial context-aware manner and can be efficiently rendered with motion parallax using standard graphics engines.
Abstract: We propose a method for converting a single RGB-D input image into a 3D photo - a multi-layer representation for novel view synthesis that contains hallucinated color and depth structures in regions occluded in the original view. We use a Layered Depth Image with explicit pixel connectivity as underlying representation, and present a learning-based inpainting model that synthesizes new local color-and-depth content into the occluded region in a spatial context-aware manner. The resulting 3D photos can be efficiently rendered with motion parallax using standard graphics engines. We validate the effectiveness of our method on a wide range of challenging everyday scenes and show fewer artifacts compared with the state of the arts.