I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting

3D object classification has attracted appealing attentions in academic researches and industrial applications. However, most existing methods need to access the training data of past 3D object classes when facing the common real-world scenario: new classes of 3D objects arrive in a sequence. Moreover, the performance of advanced approaches degrades dramatically for past learned classes (i.e., catastrophic forgetting), due to the irregular and redundant geometric structures of 3D point cloud data. To address these challenges, we propose a new Incremental 3D Object Learning (i.e., I3DOL) model, which is the first exploration to learn new classes of 3D object continually. Specifically, an adaptive-geometric centroid module is designed to construct discriminative local geometric structures, which can better characterize the irregular point cloud representation for 3D object. Afterwards, to prevent the catastrophic forgetting brought by redundant geometric information, a geometric-aware attention mechanism is developed to quantify the contributions of local geometric structures, and explore unique 3D geometric characteristics with high contributions for classes incremental learning. Meanwhile, a score fairness compensation strategy is proposed to further alleviate the catastrophic forgetting caused by unbalanced data between past and new classes of 3D object, by compensating biased prediction for new classes in the validation phase. Experiments on 3D representative datasets validate the superiority of our I3DOL framework.Comment: Accepted by Association for the Advancement of Artificial Intelligence 2021 (AAAI 2021

On the dust temperatures of high redshift galaxies

Dust temperature is an important property of the interstellar medium (ISM) of galaxies. It is required when converting (sub)millimeter broadband flux to total infrared luminosity (L_IR), and hence star formation rate, in high-z galaxies. However, different definitions of dust temperatures have been used in the literature, leading to different physical interpretations of how ISM conditions change with, e.g., redshift and star formation rate. In this paper, we analyse the dust temperatures of massive (M* > 10^10 Msun) z=2-6 galaxies with the help of high-resolution cosmological simulations from the Feedback in Realistic Environments (FIRE) project. At z~2, our simulations successfully predict dust temperatures in good agreement with observations. We find that dust temperatures based on the peak emission wavelength increase with redshift, in line with the higher star formation activity at higher redshift, and are strongly correlated with the specific star formation rate. In contrast, the mass-weighted dust temperature does not strongly evolve with redshift over z=2-6 at fixed IR luminosity but is tightly correlated with L_IR at fixed z. The mass-weighted temperature is important for accurately estimating the total dust mass. We also analyse an 'equivalent' dust temperature for converting (sub)millimeter flux density to total IR luminosity, and provide a fitting formula as a function of redshift and dust-to-metal ratio. We find that galaxies of higher equivalent (or higher peak) dust temperature ('warmer dust') do not necessarily have higher mass-weighted temperatures. A 'two-phase' picture for interstellar dust can explain the different scaling relations of the various dust temperatures.Comment: 26 pages, 15 figures, accepted for publication in MNRA

On the dust temperatures of high-redshift galaxies

Dust temperature is an important property of the interstellar medium (ISM) of galaxies. It is required when converting (sub)millimetre broad-band flux to total infrared luminosity (LIR), and hence star formation rate, in high-redshift galaxies. However, different definitions of dust temperatures have been used in the literature, leading to different physical interpretations of how ISM conditions change with, e.g. redshift and star formation rate. In this paper, we analyse the dust temperatures of massive (⁠Mstar>1010M⊙⁠) z = 2–6 galaxies with the help of high-resolution cosmological simulations from the Feedback in Realistic Environments (fire) project. At z ∼ 2, our simulations successfully predict dust temperatures in good agreement with observations. We find that dust temperatures based on the peak emission wavelength increase with redshift, in line with the higher star formation activity at higher redshift, and are strongly correlated with the specific star formation rate. In contrast, the mass-weighted dust temperature, which is required to accurately estimate the total dust mass, does not strongly evolve with redshift over z = 2–6 at fixed IR luminosity but is tightly correlated with LIR at fixed z⁠. We also analyse an ‘equivalent’ dust temperature for converting (sub)millimetre flux density to total IR luminosity, and provide a fitting formula as a function of redshift and dust-to-metal ratio. We find that galaxies of higher equivalent (or higher peak) dust temperature (‘warmer dust’) do not necessarily have higher mass-weighted temperatures. A ‘two-phase’ picture for interstellar dust can explain the different scaling relations of the various dust temperatures

Integrating Virtual Realities and Psychotherapy: SWOT Analysis on VR and MR Based Treatments of Anxiety and Stress-related Disorders

The use of virtual reality (VR) and mixed reality (MR) technology in clinical psychology is growing. Efficacious VR-based treatments for a variety of disorders have been developed. However, the field of technology-assisted psychotherapy is constantly changing with the advancement in technology. Factors such as interdisciplinary collaboration, consumer familiarity and adoption of VR products, and progress in clinical science all need to be taken into consideration when integrating virtual technologies into psychotherapies. We aim to present an overview of current expert opinions on the use of virtual technologies in the treatment of anxiety and stress-related disorders. An anonymous survey was distributed to a select group of researchers and clinicians, using an analytic framework known as Strengths, Weaknesses, Opportunities, and Threats (SWOT). Overall, the respondents had an optimistic outlook regarding the current use as well as future development and implementation of technology-assisted interventions. VR and MR psychotherapies offer distinct advantages that can overcome shortcomings associated with traditional therapy. The respondents acknowledged and discussed current limitations of VR and MR psychotherapies. They recommended consolidation of existing knowledge and encouraged standardisation in both theory and practice. Continued research is needed to leverage the strengths of VR and MR to develop better treatments

Dust attenuation, dust emission, and dust temperature in galaxies at z ≥ 5: a view from the FIRE-2 simulations

We present a suite of 34 high-resolution cosmological zoom-in simulations consisting of thousands of haloes up to M_(halo) ∼ 10^(12) M_⊙ (⁠M_∗ ∼ 10^(10.5) M_⊙⁠) at z ≥ 5 from the Feedback in Realistic Environments project. We post-process our simulations with a three-dimensional Monte Carlo dust radiative transfer code to study dust attenuation, dust emission, and dust temperature within these simulated z ≥ 5 galaxies. Our sample forms a tight correlation between infrared excess (IRX ≡ F_(IR)/F_(UV)) and ultraviolet (UV)-continuum slope (βUV), despite the patchy, clumpy dust geometry shown in our simulations. We find that the IRX–βUV relation is mainly determined by the shape of the attenuation law and is independent of its normalization (set by the dust-to-gas ratio). The bolometric IR luminosity (L_(IR)) correlates with the intrinsic UV luminosity and the star formation rate (SFR) averaged over the past 10 Myr. We predict that at a given L_(IR), the peak wavelength of the dust spectral energy distributions for z ≥ 5 galaxies is smaller by a factor of 2 (due to higher dust temperatures on average) than at z = 0. The higher dust temperatures are driven by higher specific SFRs and SFR surface densities with increasing redshift. We derive the galaxy UV luminosity functions (UVLFs) at z = 5–10 from our simulations and confirm that a heavy attenuation is required to reproduce the observed bright-end UVLFs. We also predict the IR luminosity functions (IRLFs) and UV luminosity densities at z = 5–10. We discuss the implications of our results on current and future observations probing dust attenuation and emission in z ≥ 5 galaxies

On the dust temperatures of high redshift galaxies

Dust temperature is an important property of the interstellar medium (ISM) of galaxies. It is required when converting (sub)millimetre broad-band flux to total infrared luminosity (L_(IR)), and hence star formation rate, in high-redshift galaxies. However, different definitions of dust temperatures have been used in the literature, leading to different physical interpretations of how ISM conditions change with, e.g. redshift and star formation rate. In this paper, we analyse the dust temperatures of massive (⁠M_(star) > 10¹⁰M⊙⁠) z = 2–6 galaxies with the help of high-resolution cosmological simulations from the Feedback in Realistic Environments (FIRE) project. At z ∼ 2, our simulations successfully predict dust temperatures in good agreement with observations. We find that dust temperatures based on the peak emission wavelength increase with redshift, in line with the higher star formation activity at higher redshift, and are strongly correlated with the specific star formation rate. In contrast, the mass-weighted dust temperature, which is required to accurately estimate the total dust mass, does not strongly evolve with redshift over z = 2–6 at fixed IR luminosity but is tightly correlated with LIR at fixed z⁠. We also analyse an ‘equivalent’ dust temperature for converting (sub)millimetre flux density to total IR luminosity, and provide a fitting formula as a function of redshift and dust-to-metal ratio. We find that galaxies of higher equivalent (or higher peak) dust temperature (‘warmer dust’) do not necessarily have higher mass-weighted temperatures. A ‘two-phase’ picture for interstellar dust can explain the different scaling relations of the various dust temperatures

Generation of subnanometric platinum with high stability during transformation of a 2D zeolite into 3D

[EN] Single metal atoms and metal clusters have attracted much attention thanks to their advantageous capabilities as heterogeneous catalysts. However, the generation of stable single atoms and clusters on a solid support is still challenging. Herein, we report a new strategy for the generation of single Pt atoms and Pt clusters with exceptionally high thermal stability, formed within purely siliceous MCM-22 during the growth of a two-dimensional zeolite into three dimensions. These subnanometric Pt species are stabilized by MCM-22, even after treatment in air up to 540 degrees C. Furthermore, these stable Pt species confined within internal framework cavities show size-selective catalysis for the hydrogenation of alkenes. High-temperature oxidation-reduction treatments result in the growth of encapsulated Pt species to small nanoparticles in the approximate size range of 1 to 2 nm. The stability and catalytic activity of encapsulated Pt species is also reflected in the dehydrogenation of propane to propylene.This work was funded by the Spanish Government (Consolider Ingenio 2010-MULTICAT (CSD2009-00050) and MAT2014-52085-C2-1-P) and by the Generalitat Valenciana (Prometeo). The Severo Ochoa Program (SEV-2012-0267) is gratefully acknowledged. L.L. thanks ITQ for a contract. The authors also thank the Microscopy Service of UPV for the TEM and STEM measurements. The HAADF-HRSTEM works were conducted in the Laboratorio de Microscopias Avanzadas (LMA) at the Instituto de Nanociencia de Aragon (INA)-Universidad de Zaragoza (Spain), a Spanish ICTS National Facility. Some of the research leading to these results has received funding from the European Union Seventh Framework Program under Grant Agreement 312483-ESTEEM2 (Integrated Infrastructure Initiative-I3). 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Development of an fMRI-based communication protocol for unresponsive patients

Recent studies using functional magnetic resonance imaging (fMRI) have reported that a subset ofpatients suffering from Unresponsive Wakefulness Syndrome (UWS, or vegetative state) were able toreliably follow instructions and perform mental imagery or attention tasks. Based on these finding,efforts were directed towards developing a communication protocol based on command-following.However, only a handful of UWS patients managed to communicate successfully. The current studyaims to develop an fMRI-based communication protocol using simple motor commands (imaginemoving right hand and left foot). A single volunteer took part in the experiment. While inside thescanner, the participant was first instructed to imagine moving their right hand or left foot(command-following). The participant then answered a series of binary questions using motor imagery– imagine moving right hand to indicate ‘Yes’ and imagine moving left foot to indicate ‘No’. Overall,the results showed that the protocol can successfully decode a healthy participant’s answers to allquestions correctly. While promising, the protocol must be tested on actual UWS patients to validate its effectiveness