Miracle-dz/UniFAR-FTUs huggingface dataset:
The MOSDEF Survey: Untangling the Emission-line Properties of $z\sim 2.3$ Star-forming Galaxies

We analyze the rest-optical emission-line spectra of $z\sim2.3$ star-forming galaxies in the complete MOSFIRE Deep Evolution Field (MOSDEF) survey. In investigating the origin of the well-known offset between the sequences of high-redshift and local galaxies in the [O III]5008/H$\beta$ vs. [N II]6585/H$\alpha$ ("[N II] BPT") diagram, we define two populations of $z\sim2.3$ MOSDEF galaxies. These include the "high" population that is offset towards higher [O III]5008/H$\beta$ and/or [N II]6585/H$\alpha$ with respect to the local SDSS sequence and the "low" population that overlaps the SDSS sequence. These two groups are also segregated within the [O III]5008/H$\beta$ vs. [S II]6718,6733/H$\alpha$ and the [O III]4960,5008/[O II]3727,3730 (O$_{32}$) vs. ([O III]4960,5008+[O II]3727,3730)/H$\beta$ (R$_{23}$) diagram, which suggests qualitatively that star-forming regions in the more offset galaxies are characterized by harder ionizing spectra at fixed nebular oxygen abundance. We also investigate many galaxy properties of the split sample and find that the "high" sample is on average smaller in size and less massive, but has higher specific star-formation rate and star-formation-rate surface density values and is slightly younger compared to the "low" population. From Cloudy+BPASS photoionization models, we estimate that the "high" population has a lower stellar metallicity (i.e., harder ionizing spectrum) but slightly higher nebular metallicity and higher ionization parameter compared to the "low" population. While the "high" population is more $\alpha$-enhanced (i.e., higher $\alpha$/Fe) than the "low" population, both samples are significantly more $\alpha$-enhanced compared to local star-forming galaxies with similar rest-optical line ratios. These differences must be accounted for in all high-redshift star-forming galaxies -- not only those "offset" from local excitation sequences.
The star formation properties of the observed and simulated AGN Universe: BAT versus EAGLE

In this paper, we present data from 72 low-redshift, hard X-ray selected active galactic nucleus (AGN) taken from the Swift–BAT 58 month catalogue. We utilize spectral energy distribution fitting to the optical to infrared photometry in order to estimate host galaxy properties. We compare this observational sample to a volume- and flux-matched sample of AGN from the Evolution and Assembly of GaLaxies and their Environments (EAGLE) hydrodynamical simulations in order to verify how accurately the simulations can reproduce observed AGN host galaxy properties. After correcting for the known +0.2 dex offset in the SFRs between EAGLE and previous observations, we find agreement in the star formation rate (SFR) and X-ray luminosity distributions; however, we find that the stellar masses in EAGLE are 0.2–0.4 dex greater than the observational sample, which consequently leads to lower specific star formation rates (sSFRs). We compare these results to our previous study at high redshift, finding agreement in both the observations and simulations, whereby the widths of sSFR distributions are similar (∼0.4–0.6 dex) and the median of the SFR distributions lie below the star-forming main sequence by ∼0.3–0.5 dex across all samples. We also use EAGLE to select a sample of AGN host galaxies at high and low redshift and follow their characteristic evolution from z = 8 to z = 0. We find similar behaviour between these two samples, whereby star formation is quenched when the black hole goes through its phase of most rapid growth. Utilizing EAGLE we find that 23 per cent of AGN selected at z ∼ 0 are also AGN at high redshift, and that their host galaxies are among the most massive objects in the simulation. Overall, we find EAGLE reproduces the observations well, with some minor inconsistencies (∼0.2 dex in stellar masses and ∼0.4 dex in sSFRs).
Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance

Spiking neural network (SNN) is promising but the development has fallen far behind conventional deep neural networks (DNNs) because of difficult training. To resolve the training problem, we analyze the closed-form input-output response of spiking neurons and use the response expression to build abstract SNN models for training. This avoids calculating membrane potential during training and makes the direct training of SNN as efficient as DNN. We show that the nonleaky integrate-and-fire neuron with single-spike temporal-coding is the best choice for direct-train deep SNNs. We develop an energy-efficient phase-domain signal processing circuit for the neuron and propose a direct-train deep SNN framework. Thanks to easy training, we train deep SNNs under weight quantizations to study their robustness over low-cost neuromorphic hardware. Experiments show that our direct-train deep SNNs have the highest CIFAR-10 classification accuracy among SNNs, achieve ImageNet classification accuracy within 1% of the DNN of equivalent architecture, and are robust to weight quantization and noise perturbation.
Physical parameters of active galactic nuclei derived from properties of the jet geometry transition region

We use the observed jet boundary transition from parabolic to conical shape, which was earlier discovered as possibly a common effect in active galactic nuclei, to estimate a black hole, a jet and an ambient medium parameters. We explained earlier the geometry transition as a consequence of a change in the jet inner properties: a transition from a magnetically dominated to an equipartition regime. This interpretation allows us to estimate a black hole spin, a black hole mass and an ambient pressure amplitude, using the observed jet shape break position and the jet width at the transition point for 11 active galactic nuclei. The black hole spin values obtained using our method are consistent with the lower estimates for the sources with redshift $z<2$ from the spin evolution modelling. We find that the method of a black hole mass determination based on the relation between the broad-line region size and its luminosity may underestimate masses of the sources with large jet viewing angles. We propose a new method for the black hole mass determination, with the obtained masses being in interval $10^8-10^{10}\;M_{\odot}$. The range of the values of the ambient pressure amplitude points to the uniform medium conditions for the sources in our sample, with a tentative indication of higher pressure around FRII sources.
Facial Expression Retargeting From Human to Avatar Made Easy

Facial expression retargeting from humans to virtual characters is a useful technique in computer graphics and animation. Traditional methods use markers or blendshapes to construct a mapping between the human and avatar faces. However, these approaches require a tedious 3D modeling process, and the performance relies on the modelers’ experience. In this article, we propose a brand-new solution to this cross-domain expression transfer problem via nonlinear expression embedding and expression domain translation. We first build low-dimensional latent spaces for the human and avatar facial expressions with variational autoencoder. Then we construct correspondences between the two latent spaces guided by geometric and perceptual constraints. Specifically, we design geometric correspondences to reflect geometric matching and utilize a triplet data structure to express users’ perceptual preference of avatar expressions. A user-friendly method is proposed to automatically generate triplets for a system allowing users to easily and efficiently annotate the correspondences. Using both geometric and perceptual correspondences, we trained a network for expression domain translation from human to avatar. Extensive experimental results and user studies demonstrate that even nonprofessional users can apply our method to generate high-quality facial expression retargeting results with less time and effort.
FATNN: Fast and Accurate Ternary Neural Networks*

Ternary Neural Networks (TNNs) have received much attention due to being potentially orders of magnitude faster in inference, as well as more power efficient, than full-precision counterparts. However, 2 bits are required to encode the ternary representation with only 3 quantization levels leveraged. As a result, conventional TNNs have similar memory consumption and speed compared with the standard 2-bit models, but have worse representational capability. Moreover, there is still a significant gap in accuracy between TNNs and full-precision networks, hampering their deployment to real applications. To tackle these two challenges, in this work, we first show that, under some mild constraints, computational complexity of the ternary inner product can be reduced by 2×. Second, to mitigate the performance gap, we elaborately design an implementation-dependent ternary quantization algorithm. The proposed framework is termed Fast and Accurate Ternary Neural Networks (FATNN). Experiments on image classification demonstrate that our FATNN surpasses the state-of-the-arts by a significant margin in accuracy. More importantly, speedup evaluation compared with various precision is analyzed on several platforms, which serves as a strong benchmark for further research. Source code and models are available at: https://github.com/MonashAI/QTool
EMBRYONIC DEVELOPMENT IN POECILIID FISHES

In poeciliid fishes the embryos are retained within the ovarian follicles until parturition. When the dry weight of the intact follicle is determined at various stages of development, no significant weight change can be demonstrated in the 18 species studied. This is in marked contrast to the situation in a truly ovoviviparous fish where one-third of the initial weight of the egg is used for maintenance during development. Accordingly, it is concluded that all of the species studied receive nourishment from the mother and hence are not ovoviviparous in the strict sense of the word. Furthermore, they apparently receive only as much nutriment, quantitatively at least, as they require for their maintenance metabolism. Some limiting mechanism must be operating, but its nature is not known. This situation is contrasted with that in Heterandria formosa and Aulophallus elongatus, members of the family which have developed nearly complete dependence on the mother for nourishment during development.
The Refractory Period Matters: Unifying Mechanisms of Macroscopic Brain Waves

Abstract The relationship between complex brain oscillations and the dynamics of individual neurons is poorly understood. Here we utilize maximum caliber, a dynamical inference principle, to build a minimal yet general model of the collective (mean field) dynamics of large populations of neurons. In agreement with previous experimental observations, we describe a simple, testable mechanism, involving only a single type of neuron, by which many of these complex oscillatory patterns may emerge. Our model predicts that the refractory period of neurons, which has often been neglected, is essential for these behaviors.
Fate of stellar bars in minor merger of galaxies

Minor merger of galaxies are common during the evolutionary phase of galaxies. Here, we investigate the dynamical impact of a minor merger (mass ratio 1:10) event on the final fate of a stellar bar in the merger remnant. To achieve that, we choose a set of minor merger models from the publicly available GalMer library of galaxy merger simulations. The models differ in terms of their orbital energy, orientation of the orbital spin vector, and morphology of the satellite galaxy (discy/spheroidal). We demonstrate that the central stellar bar, initially present in the host galaxy, undergoes a transient bar amplification phase after each pericentre passage of the satellite; in concordance with past studies of bar excitation due to tidal encounter. However, once the merger happens, the central stellar bar weakens substantially, followed by a complete destruction of the bar in merger remnant for some models. The accumulation of satellite's stars in the central region of merger remnant plays a key role in the bar weakening/destruction process; causing a net increase in the central mass concentration as well as in the specific angular momentum content. We find that the efficiency of mass accumulation from the satellite in the central parts of merger remnants depends on the orbital parameters as well as on the satellite's morphology. Consequently, different minor merger models display different degrees of bar weakening/destruction (partial or complete) event. This demonstrates that minor merger of galaxies is a plausible avenue for bar weakening/destruction in disc galaxies.
Charmed and ϕ meson decay constants from 2+1-flavor lattice QCD

On a lattice with 2+1-flavor dynamical domain-wall fermions at the physical pion mass, we calculate the decay constants of $D_{s}^{(*)}$, $D^{(*)}$ and $\phi$. The lattice size is $48^3\times96$, which corresponds to a spatial extension of $\sim5.5$ fm with the lattice spacing $a\approx 0.114$ fm. For the valence light, strange and charm quarks, we use overlap fermions at several mass points close to their physical values. Our results at the physical point are $f_D=213(5)$ MeV, $f_{D_s}=249(7)$ MeV, $f_{D^*}=234(6)$ MeV, $f_{D_s^*}=274(7)$ MeV, and $f_\phi=241(9)$ MeV. The couplings of $D^*$ and $D_s^*$ to the tensor current ($f_V^T$) can be derived, respectively, from the ratios $f_{D^*}^T/f_{D^*}=0.91(4)$ and $f_{D_s^*}^T/f_{D_s^*}=0.92(4)$, which are the first lattice QCD results. We also obtain the ratios $f_{D^*}/f_D=1.10(3)$ and $f_{D_s^*}/f_{D_s}=1.10(4)$, which reflect the size of heavy quark symmetry breaking in charmed mesons. The ratios $f_{D_s}/f_{D}=1.16(3)$ and $f_{D_s^*}/f_{D^*}=1.17(3)$ can be taken as a measure of SU(3) flavor symmetry breaking.
Species Diversity of Benthic Macroinvertebrates in a Stream Receiving Domestic and Oil Refinery Effluents

A study was made of physicochemical conditions and benthic macroinvertebrate community structure in a stream receiving domestic and oil refinery effluents. Measures derived from information theory, diversity per individual and redundancy, were found to be more precise measures of stream conditions as reflected by benthic macroinvertebrate populations than traditional methods.
Towards Unsupervised Crowd Counting via Regression-Detection Bi-knowledge Transfer

Unsupervised crowd counting is a challenging yet not largely explored task. In this paper, we explore it in a transfer learning setting where we learn to detect and count persons in an unlabeled target set by transferring bi-knowledge learnt from regression- and detection-based models in a labeled source set. The dual source knowledge of the two models is heterogeneous and complementary as they capture different modalities of the crowd distribution. We formulate the mutual transformations between the outputs of regression- and detection-based models as two scene-agnostic transformers which enable knowledge distillation between the two models. Given the regression- and detection-based models and their mutual transformers learnt in the source, we introduce an iterative self-supervised learning scheme with regression-detection bi-knowledge transfer in the target. Extensive experiments on standard crowd counting benchmarks, ShanghaiTech, UCF_CC_50, and UCF_QNRF demonstrate a substantial improvement of our method over other state-of-the-arts in the transfer learning setting.
Enhancement of the Start-Up Time for Microliter-Scale Microbial Fuel Cells (µMFCs) via the Surface Modification of Gold Electrodes

Microbial Fuel Cells (MFCs) are biological fuel cells based on the oxidation of fuels by electrogenic bacteria to generate an electric current in electrochemical cells. There are several methods that can be employed to improve their performance. In this study, the effects of gold surface modification with different thiol molecules were investigated for their implementation as anode electrodes in micro-scale MFCs (µMFCs). Several double-chamber µMFCs with 10.4 µL anode and cathode chambers were fabricated using silicon-microelectromechanical systems (MEMS) fabrication technology. µMFC systems assembled with modified gold anodes were operated under anaerobic conditions with the continuous feeding of anolyte and catholyte to compare the effect of different thiol molecules on the biofilm formation of Shewanella oneidensis MR-1. Performances were evaluated using polarization curves, Electrochemical Impedance Spectroscopy (EIS), and Scanning Electron Microcopy (SEM). The results showed that µMFCs modified with thiol self-assembled monolayers (SAMs) (cysteamine and 11-MUA) resulted in more than a 50% reduction in start-up times due to better bacterial attachment on the anode surface. Both 11-MUA and cysteamine modifications resulted in dense biofilms, as observed in SEM images. The power output was found to be similar in cysteamine-modified and bare gold µMFCs. The power and current densities obtained in this study were comparable to those reported in similar studies in the literature.
The Entrepreneur’s Psychological Capital, Creative Innovation Behavior, and Enterprise Performance

In order to analyze the relationship between entrepreneur psychological capital, creative innovation behavior, and enterprise performance based on the actual situation of Chinese enterprises and provide a theoretical basis for the application of entrepreneur psychological capital in enterprise innovation and performance development, in this study, 536 entrepreneurs from 517 enterprises in different fields in Anhui region were selected, and a questionnaire survey on the psychological capital of entrepreneurs, creative innovation behaviors, and corporate performance was conducted. A hypothesis model of the relationship between entrepreneur’s psychological capital, creative innovation behavior, and enterprise performance was constructed. The correlation between entrepreneur’s psychological capital, creative innovation behavior, and enterprise performance and the intermediation of creative innovation behavior were analyzed using multiple-regression model and structural equation model. The results show that there is a significant positive correlation between dimensions of self-efficacy (regression coefficient = 0.682, p = 0.000), toughness (regression coefficient = 0.526, p = 0.000), and enterprise performance; there is a significant positive correlation between the dimensions of optimism (regression coefficient = 0.471, p = 0.003), hope (regression coefficient = 0.590, p = 0.006), and enterprise performance; there is a significant positive correlation between entrepreneurs’ technological innovation behavior (regression coefficient = 0.506, p = 0.000), business innovation behavior (regression coefficient = 0.562, p = 0.000), and enterprise performance; there is a significant positive correlation between entrepreneurial relationship acquisition behavior (regression coefficient = 0.632, p = 0.004) and enterprise performance. Taking entrepreneurs’ creative innovation behavior as the intermediary variable, the authors conclude that the dimensions of entrepreneurs’ self-efficacy, hope, optimism, toughness, and the standardized path coefficient of enterprise performance are significantly reduced; through the analysis of structural equation model, it is found that the fitting index of the model of entrepreneur’s psychological capital, creative innovation behavior, and enterprise performance meets the fitting standard, which shows that both the psychological capital and the creative innovation behavior of entrepreneurs can promote the improvement of enterprise performance. Entrepreneur’s creative innovation behavior plays an intermediary effect in the positive influence of entrepreneur’s psychological capital on enterprise performance.
THE SYSTEMATIC POSITION OF EUPHRONIA, WITH COMMENTS ON THE POSITION OF BALANOPS : AN ANALYSIS BASED ON RBCL SEQUENCE DATA

Euiphronia has been variously allied with the Trigoniaceae and Vochysiaceae, but morpho- logical data have been unable to indicate an unequivocal position for this distinctive genus. Molecular sequence data place Euphronia as sister to the Chrysobalanaceae, in a clade that also includes Dichapeta- laceae and Trigoniaceae. A review of morphological, anatomical, and phytochemical data failed to turn up any apparent synapomorphies relating Euphronia to the other taxa in the clade. Nonetheless, these data do not clearly indicate any alternative taxonomic position, thus the placement indicated by the molecular data should be accepted at this time. Another genus of uncertain affinities, Balanops, is also a member of this clade, falling as sister to the rest of the taxa. We suggest that both Euphronia and Balanops be recognized as monotypic families.
Regulated Iron Siderophore Production of the Halophilic Archaeon Haloferax volcanii

Iron is part of many redox and other enzymes and, thus, it is essential for all living beings. Many oxic environments have extremely low concentrations of free iron. Therefore, many prokaryotic species evolved siderophores, i.e., small organic molecules that complex Fe3+ with very high affinity. Siderophores of bacteria are intensely studied, in contrast to those of archaea. The haloarchaeon Haloferax volcanii contains a gene cluster that putatively encodes siderophore biosynthesis genes, including four iron uptake chelate (iuc) genes. Underscoring this hypothesis, Northern blot analyses revealed that a hexacistronic transcript is generated that is highly induced under iron starvation. A quadruple iuc deletion mutant was generated, which had a growth defect solely at very low concentrations of Fe3+, not Fe2+. Two experimental approaches showed that the wild type produced and exported an Fe3+-specific siderophore under low iron concentrations, in contrast to the iuc deletion mutant. Bioinformatic analyses revealed that haloarchaea obtained the gene cluster by lateral transfer from bacteria and enabled the prediction of enzymatic functions of all six gene products. Notably, a biosynthetic pathway is proposed that starts with aspartic acid, uses several group donors and citrate, and leads to the hydroxamate siderophore Schizokinen.
The Disengagement of Visual Attention: An Eye-Tracking Study of Cognitive Impairment, Ethnicity and Age

Various studies have shown that Alzheimer’s disease (AD) is associated with an impairment of inhibitory control, although we do not have a comprehensive understanding of the associated cognitive processes. The ability to engage and disengage attention is a crucial cognitive operation of inhibitory control and can be readily investigated using the “gap effect” in a saccadic eye movement paradigm. In previous work, various demographic factors were confounded; therefore, here, we examine separately the effects of cognitive impairment in Alzheimer’s disease, ethnicity/culture and age. This study included young (N = 44) and old (N = 96) European participants, AD (N = 32), mildly cognitively impaired participants (MCI: N = 47) and South Asian older adults (N = 94). A clear reduction in the mean reaction times was detected in all the participant groups in the gap condition compared to the overlap condition, confirming the effect. Importantly, this effect was also preserved in participants with MCI and AD. A strong effect of age was also evident, revealing a slowing in the disengagement of attention during the natural process of ageing.
Stricture Following Esophageal Reconstruction

Owing to varying clinical definitions of anastomotic stricture following esophageal reconstruction, its reported incidence rate varies from 10% to 56%. Strictures adversely impact patients’ quality of life. Risk factors, such as the anastomosis method, leakage, ischemia, neoadjuvant chemoradiotherapy, and underlying disease have been mentioned, but conflicting information has been reported. Balloon dilation is regarded as a safe and effective treatment method for patients with benign anastomotic strictures. Reoperations are seldom required. The etiology and management of anastomotic strictures are reviewed in this article.