Miracle-dz/UniFAR-FTUs huggingface dataset:
Morphological generalization in bilingual language production: Age of acquisition determines variability

ABSTRACT Morphological variability in bilingual language production is widely attested. Producing inflected words has been found to be less reliable and consistent in bilinguals than in first-language (functionally monolingual) L1 speakers, even for bilingual speakers at advanced proficiency levels. The sources for these differences are not well understood. The current study presents a detailed investigation of morphological generalization processes in bilingual speakers’ language production. We examined past participle formation of German using an elicited-production experiment containing nonce verbs with varying degrees of similarity to existing verbs testing a large group of bilingual Turkish/German speakers relative to L1 German speakers. We compared similarity-based lexical extensions with generalizations of morphological rules. The results show that rule-based generalizations are used less often and more variably within the bilingual group than within the L1 group. Our results also show a selective effect of age of acquisition on the bilingual speakers’ morphological generalizations.
Non-Hermitian topology of spontaneous magnon decay

Spontaneous magnon decay is a generic feature of the magnetic excitations of anisotropic magnets and isotropic magnets with noncollinear order. In this Rapid Communication, we argue that the effect of interactions on one-magnon states can, under many circumstances, be treated in terms of an effective, energy-independent, non-Hermitian Hamiltonian for the magnons. In the vicinity of Dirac or Weyl touching points, we show that the spectral function has a characteristic anisotropy arising from topologically protected exceptional points or lines in the non-Hermitian spectrum. Such features can, in principle, be detected using inelastic neutron scattering or other spectroscopic probes. We illustrate this physics through a concrete example: a honeycomb ferromagnet with Dzyaloshinskii-Moriya exchange. We perform interacting spin-wave calculations of the structure factor and spectral function of this model, showing good agreement with results from a simple effective non-Hermitian model for the splitting of the Dirac point. Finally, we argue that the zoo of known topological protected magnon band structures may serve as a nearly ideal platform for realizing and exploring non-Hermitian physics in solid-state systems.
General relativistic time dilation and increased uncertainty in generic quantum clocks

The theory of relativity associates a proper time with each moving object via its world line. In quantum theory however, such well-defined trajectories are forbidden. After introducing a general characterisation of quantum clocks, we demonstrate that, in the weak-field, low-velocity limit, all "good" quantum clocks experience time dilation as dictated by general relativity when their state of motion is classical (i.e. Gaussian). For nonclassical states of motion, on the other hand, we find that quantum interference effects may give rise to a significant discrepancy between the proper time and the time measured by the clock. We also show how ignorance of the clock's state of motion leads to a larger uncertainty in the time measured by the clock --- a consequence of entanglement between the clock time and its center-of-mass degrees of freedom. We demonstrate how this lost precision can be recovered by performing a measurement of the clock's state of motion alongside its time reading.
Anisotropic hydrodynamic modeling of 200 GeV Au-Au collisions

We compare phenomenological results from 3+1d quasiparticle anisotropic hydrodynamics (aHydroQP) with experimental data collected in RHIC 200 GeV Au-Au collisions. We present comparisons of identified particle spectra in different centrality clases, charged particle multiplicity versus pseudorapidity, identified particle multiplicity versus centrality across a wide range of particle species, identified particle elliptic flow versus transverse momentum, and charged particle elliptic flow as a function of transverse momentum and rapidity. We use the same aHydroQP and hadronic production/feed down codes that were used previously to describe LHC 2.76 TeV data. The aHydroQP hydrodynamic model includes the effects of both shear and bulk viscosities in addition to an infinite number of transport coefficients computed self-consistently in the relaxation time approximation. To convert to the final state hadrons, we use anisotropic Cooper-Frye freeze-out performed on a fixed-energy-density hypersurface and compute the production/feed down using a customized version of Therminator 2. We find good agreement with many heavy-ion collision observables using only smooth Glauber initial conditions parameterized by an initial central temperature of T_0 = 455 MeV, a constant shear viscosity to entropy density ratio eta/s= 0.179, and a switching (freeze-out) temperature of T_FO=130 MeV.
An End-to-End Baseline for Video Captioning

Building correspondences across different modalities, such as video and language, has recently become critical in many visual recognition applications, such as video captioning. Inspired by machine translation, recent models tackle this task using an encoder-decoder strategy. The (video) encoder is traditionally a Convolutional Neural Network (CNN), while the decoding (for language generation) is done using a Recurrent Neural Network (RNN). Current state-of-the-art methods, however, train encoder and decoder separately. CNNs are pretrained on object and/or action recognition tasks and used to encode video-level features. The decoder is then optimised on such static features to generate the video's description. This disjoint setup is arguably sub-optimal for input (video) to output (description) mapping. In this work, we propose to optimise both encoder and decoder simultaneously in an end-to-end fashion. In a two-stage training setting, we first initialise our architecture using pre-trained encoders and decoders -- then, the entire network is trained end-to-end in a fine-tuning stage to learn the most relevant features for video caption generation. In our experiments, we use GoogLeNet and Inception-ResNet-v2 as encoders and an original Soft-Attention (SA-) LSTM as a decoder. Analogously to gains observed in other computer vision problems, we show that end-to-end training significantly improves over the traditional, disjoint training process. We evaluate our End-to-End (EtENet) Networks on the Microsoft Research Video Description (MSVD) and the MSR Video to Text (MSR-VTT) benchmark datasets, showing how EtENet achieves state-of-the-art performance across the board.
The Influence of Land Use Change on Key Ecosystem Services and Their Relationships in a Mountain Region from Past to Future (1995–2050)

The ecosystem services (ESs) provided by mountain regions can bring about benefits to people living in and around the mountains. Ecosystems in mountain areas are fragile and sensitive to anthropogenic disturbance. Understanding the effect of land use change on ESs and their relationships can lead to sustainable land use management in mountain regions with complex topography. Chongqing, as a typical mountain region, was selected as the site of this research. The long-term impacts of land use change on four key ESs (i.e., water yield (WY), soil conservation (SC), carbon storage (CS), and habitat quality (HQ)) and their relationships were assessed from the past to the future (at five-year intervals, 1995–2050). Three future scenarios were constructed to represent the ecological restoration policy and different socioeconomic developments. From 1995 to 2015, WY and SC experienced overall increases. CS and HQ increased slightly at first and then decreased significantly. A scenario analysis suggested that, if the urban area continues to increase at low altitudes, by 2050, CS and HQ are predicted to decrease moderately. However, great improvements in SC, HQ, and CS are expected to be achieved by the middle of the century if the government continues to make efforts towards vegetation restoration on the steep slopes.
Architecture specification of parametric component-based systems

In this paper we are interested in the modelling of parametric component-based systems, and more precisely in the specification of their architectures. The topology of parametric systems is described by architectures which characterize the permissible interactions among their components. We introduce an extended first-order interaction logic which serves as a specification language for architectures of parametric component-based systems. In comparison to other logical characterizations of parametric systems, studied so far, our logic effectively describes the order of execution of interactions which is a main feature in several important architectures. We state complexity and decidability results for extended first-order interaction logic formulas, and provide several examples of formulas describing well-known architectures.
Dynamical Constraints on Mercury’s Collisional Origin

Of the solar system’s four terrestrial planets, the origin of Mercury is perhaps the most mysterious. Modern numerical simulations designed to model the dynamics of terrestrial planet formation systematically fail to replicate Mercury, which possesses just 5% of the mass of Earth and the highest orbital eccentricity and inclination among the planets. However, Mercury’s large iron-rich core and low volatile inventory stand out among the inner planets, and seem to imply a violent collisional origin. Because most algorithms used for simulating terrestrial accretion do not consider the effects of collisional fragmentation, it has been difficult to test these collisional hypotheses within the larger context of planet formation. Here, we analyze a large suite of terrestrial accretion models that account for the fragmentation of colliding bodies. We find that planets with core mass fractions boosted as a result of repeated hit-and-run collisions are produced in 90% of our simulations. While many of these planets are similar to Mercury in mass, they rarely lie on Mercury-like orbits. Furthermore, we perform an additional batch of simulations designed to specifically test the single giant impact origin scenario. We find less than a 1% probability of simultaneously replicating the Mercury–Venus dynamical spacing and the terrestrial system’s degree of orbital excitation after such an event. While dynamical models have made great strides in understanding Mars’ low mass, their inability to form accurate Mercury analogs remains a glaring problem.
Detailed dust modelling in the L-Galaxies semi-analytic model of galaxy formation

We implement a detailed dust model into the L-Galaxies semi-analytical model which includes: injection of dust by type II and type Ia supernovae (SNe) and AGB stars; grain growth in molecular clouds; and destruction due to supernova-induced shocks, star formation, and reheating. Our grain growth model follows the dust content in molecular clouds and the inter-cloud medium separately, and allows growth only on pre-existing dust grains. At early times, this can make a significant difference to the dust growth rate. Above z ∼ 8, type II SNe are the primary source of dust, whereas below z ∼ 8, grain growth in molecular clouds dominates, with the total dust content being dominated by the latter below z ∼ 6. However, the detailed history of galaxy formation is important for determining the dust content of any individual galaxy. We introduce a fit to the dust-to-metal (DTM) ratio as a function of metallicity and age, which can be used to deduce the DTM ratio of galaxies at any redshift. At z ≲ 3, we find a fairly flat mean relation between metallicity and the DTM, and a positive correlation between metallicity and the dust-to-gas (DTG) ratio, in good agreement with the shape and normalization of the observed relations. We also match the normalization of the observed stellar mass–dust mass relation over the redshift range of 0–4, and to the dust mass function at z = 0. Our results are important in interpreting observations on the dust content of galaxies across cosmic time, particularly so at high redshift.
Racial Disparities in Housing Returns

We identify the existence of a racial gap in housing returns that is an order of magnitude larger than disparities arising from housing costs alone. The returns gap is driven almost entirely by differences in distressed home sales (i.e. foreclosures and short sales). Black and Hispanic homeowners are both more likely to experience a distressed sale and to live in neighborhoods where distressed sales carry larger foreclosure discounts. Higher rates of distressed sales among minorities are driven by pre-existing differences in economic stability and neighborhood sorting. Black and Hispanic homeowners are more likely to default in response to increases in monthly payments, consistent with racial differences in liquid wealth holdings playing a key role in creating the observed disparities. We use quasi-experimental variation in the receipt of mortgage modifications to show that policies that encourage lenders to modify loans when homeowners can no longer afford their mortgages can mitigate gaps in housing returns, particularly if they are targeted towards minority homeowners or neighborhoods.
Early Time Light Curves of 18 Bright Type Ia Supernovae Observed with TESS

We present early time light curves of 18 Type Ia supernovae observed in the first six sectors of TESS data. Nine of these supernovae were discovered by ASAS-SN, four by ATLAS, four by ZTF, and one by \textit{Gaia}. For eight of these objects with sufficient dynamic range ($>$3.0 mag from detection to peak), we fit power law models and search for signatures of companion stars. Most of our sources are consistent with fireball models where the flux increases $\propto t^2$, while two display a flatter rise with flux $\propto t$. We do not find any obvious evidence for additional structure such as multiple power law components in the early rising light curves. Assuming a favorable viewing angle, we place conservative upper limits on the radii of any companion stars of less than 25 R$_\odot$ for six supernovae and less than 4 R$_\odot$ for 4 supernovae. If such systems are commonplace, the odds of non-detection in this sample are 38\% for companions $\gtrsim$25\,R$\odot$ and 52\% for companions $\gtrsim$4\,R$\odot$. Based on the examples in this work, we expect that TESS will either detect emission from a dwarf companion during its initial two year survey, or place stringent limits on single-degenerate progenitor models.
Weight Estimation of Asian Sea Bass (Lates calcarifer) Comparing Whole Body with and without Fins using Computer Vision Technique

An optimal model to evaluate the weight of the whole body of Asian sea bass with and without fins was generated using computer vision image processing techniques. Image data of 25 fish randomly selected were collected every week for one month. The data were divided into two sets by means of a 40 - 60 % split-test, 40 % (10 fish; 100 images) were used as training data and 60 % (15 fish; 150 images) were used as out-samples or validation data. The model using fish images without fins gave a higher average and total coefficient of determination (N150R2 = 0.77 ± 0.10, N600R2 = 0.96) than using images with fins (N150R2 = 0.24 ± 0.20, N600R2 0.63). Errors as root mean square error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE), maximum absolute error (MXAE), and maximum relative error (MXRE) were compared using mathematical models. Results showed that the model using fish images without fins recorded fewer errors, with average values of 9.19 ± 3.74 g, 6.06 ± 3.64 g, 5.18 ± 3.08 %, 8.87 ± 3.26 g and 0.12 ± 0.12 %, respectively compared with fish images with fins at 12.35 ± 4.45 g, 11.26 ± 3.61 g, 9.69 ± 2.94 %, 11.50 ± 4.71 g and 0.14 ± 0.11 %, respectively. Comparison between models, with and without fins, and normal manual measurement methods found no statistically significant differences (P > 0.05). Therefore, this technique may be applied for weight estimation in real pond conditions to give advantages of reduced time, stress and injury, with minimal interference in fish feeding compared to physical capture and weighing. HIGHLIGHTS 2D Computer vision techniques can be applied for fish weight estimation Fish images without fins show better results than those of with fins The advantages of this technique are reduced time, stress and injury compared to physical capture and weighing Step toward development of an automatic fish weight monitoring when the fish is swimming freely in the water GRAPHICAL ABSTRACT
Impact of Internal Integration, Supply Chain Partnership, Supply Chain Agility, and Supply Chain Resilience on Sustainable Advantage

The global order has suddenly changed due to the COVID-19 pandemic. Many countries, including Indonesia, have applied lockdown policies to stop the spread of COVID-19. Lockdown policies have disrupted the supply of raw materials and the demand for finished goods. The manufacturing industry is one of the sectors that has suffered most in this situation, and they have struggled to reconfigure their internal and external supply chain network and partnership. This study examined the impact of internal integration, supply chain partnership, supply chain agility, and supply chain resilience on sustainable advantage. The participants of this study were from manufacturing companies in Indonesia. For data collection, a questionnaire was used, with a five-point Likert scale to obtain the respondents’ opinions. Using Google Form link, the questionnaire was distributed via email and the WhatsApp social media application to the predetermined set of manufacturing companies. Respondents filled out 672 questionnaires, and 456 respondents (corresponding to 67.86%) filled it out correctly and were considered valid for further analysis. Partial least squares (PLS) regression was used to analyze the data using the SmartPLS software version 3.3. The results supported all nine hypotheses proposed. Internal integration through interdepartmental data sharing affects supply chain (SC) partnerships, SC agility, and SC resilience. Moreover, SC partnerships, through the on-time delivery of materials and by coping with changing demand, improve SC agility, SC resilience, and sustainable advantages. SC agility, in keeping the production process running normally and regulating the production capacity, affects SC resilience and sustainable advantage. SC resilience improves sustainable advantage by providing timely product delivery and reliable sales volumes in pandemic conditions. These results provide insights for managers into enhancing the sustainable advantage by improving supply chain agility, supply chain resilience, and supply chain partnerships. This study could contribute and extend the acceptance of previous studies in the context of the manufacturing industry.
Backtracking gradient descent method for general $C^1$ functions, with applications to Deep Learning

While Standard gradient descent is one very popular optimisation method, its convergence cannot be proven beyond the class of functions whose gradient is globally Lipschitz continuous. As such, it is not actually applicable to realistic applications such as Deep Neural Networks. In this paper, we prove that its backtracking variant behaves very nicely, in particular convergence can be shown for all Morse functions. The main theoretical result of this paper is as follows. Theorem. Let $f:\mathbb{R}^k\rightarrow \mathbb{R}$ be a $C^1$ function, and $\{z_n\}$ a sequence constructed from the Backtracking gradient descent algorithm. (1) Either $\lim _{n\rightarrow\infty}||z_n||=\infty$ or $\lim _{n\rightarrow\infty}||z_{n+1}-z_n||=0$. (2) Assume that $f$ has at most countably many critical points. Then either $\lim _{n\rightarrow\infty}||z_n||=\infty$ or $\{z_n\}$ converges to a critical point of $f$. (3) More generally, assume that all connected components of the set of critical points of $f$ are compact. Then either $\lim _{n\rightarrow\infty}||z_n||=\infty$ or $\{z_n\}$ is bounded. Moreover, in the latter case the set of cluster points of $\{z_n\}$ is connected. Some generalised versions of this result, including an inexact version, are included. Another result in this paper concerns the problem of saddle points. We then present a heuristic argument to explain why Standard gradient descent method works so well, and modifications of the backtracking versions of GD, MMT and NAG. Experiments with datasets CIFAR10 and CIFAR100 on various popular architectures verify the heuristic argument also for the mini-batch practice and show that our new algorithms, while automatically fine tuning learning rates, perform better than current state-of-the-art methods such as MMT, NAG, Adagrad, Adadelta, RMSProp, Adam and Adamax.
The Quintuplet Cluster: Extended Structure and Tidal Radius

The Quintuplet star cluster is one of only three known young (<10 Myr) massive (M > 104 M⊙) clusters within ∼100 pc of the Galactic center (GC). In order to explore star cluster formation and evolution in this extreme environment, we analyze the Quintuplet’s dynamical structure. Using the HST WFC3-IR instrument, we take astrometric and photometric observations of the Quintuplet covering a 120″ × 120″ field of view, which is 19 times larger than those of previous proper-motion studies of the Quintuplet. We generate a catalog of the Quintuplet region with multiband, near-infrared photometry, proper motions, and cluster membership probabilities for 10,543 stars. We present the radial density profile of 715 candidate Quintuplet cluster members with M ≳ 4.7 M⊙ out to 3.2 pc from the cluster center. A 3σ lower limit of 3 pc is placed on the tidal radius, indicating the lack of a tidal truncation within this radius range. Only weak evidence for mass segregation is found, in contrast to the strong mass segregation found in the Arches cluster, a second and slightly younger massive cluster near the GC. It is possible that tidal stripping hampers a mass segregation signature, though we find no evidence of spatial asymmetry. Assuming that the Arches and Quintuplet clusters formed with comparable extent, our measurement of the Quintuplet’s comparatively large core radius of pc provides strong empirical evidence that young massive clusters in the GC dissolve on a several-megayear timescale.
HERBS II: Detailed chemical compositions of Galactic bulge stars

This work explores the detailed chemistry of the Milky Way bulge using the HERMES spectrograph on the Anglo-Australian Telescope. Here, we present the abundance ratios of 13 elements for 832 red giant branch and clump stars along the minor bulge axis at latitudes b = −10○, − 7.5○, and −5○. Our results show that none of the abundance ratios vary significantly with latitude. We also observe disc-like [Na/Fe] abundance ratios, which indicate that the bulge does not contain helium-enhanced populations as observed in some globular clusters. Helium enhancement is therefore not the likely explanation for the double red-clump observed in the bulge. We confirm that bulge stars mostly follow abundance trends observed in the disc. However, this similarity is not confirmed across all elements and metallicity regimes. The more metal-poor bulge population at [Fe/H] ≲ − 0.8 is enhanced in the elements associated with core collapse supernovae (SNeII). In addition, the [La/Eu] abundance ratio suggests higher r-process contribution, and likely higher star formation in the bulge compared to the disc. This highlights the complex evolution in the bulge, which should be investigated further, both in terms of modelling; and with additional observations of the inner Galaxy.