Miracle-dz/UniFAR-FTUs huggingface dataset:
Probing the Dependence of the Intergalactic Medium on Large-scale Environment Using the Low-redshift Lyα Forest

We examine the statistics of the low-redshift Lyα forest in a cosmological hydrodynamic simulation using adaptive mesh refinement that has sufficient volume to include distinct large-scale environments. We compare our H i column density distribution of absorbers both with recent work and between two highly refined regions of our simulation: a large-scale overdensity and a large-scale underdensity (on scales of approximately 20 Mpc). We recover the average results presented by Kollmeier et al. using different simulation methods. We further break down these results as a function of environment to examine the detailed dependence of absorber statistics on large-scale density. We find that the slope of the H i column density distribution (CDD) in the range ≤ /cm−2 ≤ depends on environment such that the slope becomes steeper for higher environmental density, and this difference reflects distinct physical conditions of the intergalactic medium (IGM) on these scales. We track this difference to the different temperature structures of filaments in varying environments. Specifically, filaments in the overdensity are hotter, and correspondingly are composed of gas with lower H i fractions than those in underdense environments. Our results highlight that in order to understand the physics driving the H i CDD, we need not only improved accounting of the sources of ionizing UV photons, but also a clearer picture of the physical conditions of the IGM and how it may vary as a function of large-scale environment.
Slab‐ and height‐resolving models of the tropical cyclone boundary layer. Part II: Why the simulations differ

Depth‐averaged, or slab, models of the tropical cyclone boundary layer have had important practical uses in engineering design and climatological risk‐assessment studies and as components of tropical cyclone potential‐intensity models. In Part I of this article, such models were compared with a fully height‐resolving model, and it was shown that there are substantial differences in the simulations. This second part determines the reasons for these differences. The main tool used is a new model, which parametrizes the vertical structure of the boundary layer and thereby allows more accurate calculation of the surface drag and nonlinear terms. It is more accurate than the slab model, but of similar computational cost. This model, and hybrids of it and the slab model, are used to determine the consequences of the approximations in slab models. It was indicated in Part I and is confirmed here that the excessively strong inflow and too great departure of the boundary‐layer mean winds from gradient balance in the slab model are due to excessive surface drag. The tendency of slab models to produce quasi‐inertial oscillations is shown to be due to the inaccurate treatment of the vertically averaged nonlinear terms in the momentum equations. In particular, these oscillations are shown not to be due to the improper specification of the upper boundary condition as has recently been argued by Smith and Vogl. The considerable deficiencies of slab models of the tropical cyclone boundary layer are therefore inherent to their formulation. It is further shown that the dynamics leading to supergradient flow are different in the slab model and in the height‐resolving model. The possible uses of linearized versions of the slab model are briefly considered. Copyright © 2010 Royal Meteorological Society
Seismological Analysis of the Stars γ Serpentis and ι Leonis: Stellar Parameters and Evolution

In order to assess the information that will be available from targets of the Microvariability and Oscillations of Stars (MOST) satellite, we explore the possible evolutionary status and perform preliminary seismological analysis of two targets: the stars γ Ser and ι Leo, which show solar-like oscillations. Taking into account the astrometric observational constraints on the stars, we find that γ Ser is in the main-sequence phase of evolution, while ι Leo has two distinct solutions that match well with observations: main-sequence models and post-main-sequence models. The evolutionary tracks cover the following ranges of mass and initial metallicity: γ Ser, 1.15-1.20 M☉ and Z = 0.0135 ± 0.003; ι Leo, 1.62-1.70 M☉ and Z = 0.024 ± 0.002 (for values of the Galactic helium enrichment ratio ΔY/ΔZ in the range 0-2). By combining stellar models with observational constraints, we determine age ranges of 3.2 ± 0.6 Gyr for γ Ser and 1.7 ± 0.2 Gyr for ι Leo. The results show that the masses and ages of the stars are very sensitive to metallicity and evolutionary phase. Furthermore, we find that models with overshooting from a convective core predict a larger age for a given mass. Finally, we discuss future prospects for constraining stellar models with the help of asteroseismic observations.
Rostrum morphology and feeding strategy of the baleen whale indicate that right whales and pygmy right whales became skimmers independently

Baleen whales have lost their functional teeth and begun to use their baleen plates to feed on small prey. Modern baleen whales exhibit different types of feeding strategies, such as lunging, skimming and so on. The evolution of feeding strategy in the Chaeomysticeti is an important step in considering niche partitioning and diversification, feeding efficiency and gigantism, and evolution and extinction. This study analyses the rostrum morphology to test the hypothesis that specific rostral morphologies facilitate special feeding strategies, using modern species and their observed feeding strategies. By this means, the convergence of rostral morphology can be recognized in the closest groups in the morphospace. As a result, the two linages (Balaenidae and Caperea marginata) are recognized to have convergent rostral morphology. In addition, an early member of the Chaeomysticeti, Yamatocetus canaliculatus, and most fossil species are plotted in or close to the cluster of lunge feeders. The original feeding strategy of the Chaeomysticeti could be more similar to lunge feeding than to skim feeding. Fossil relatives of the two linages showing transitional conditions indicate that they shifted to skim feeding independently. The evolution of the feeding strategy of the Chaeomysticeti is possibly more complex than that was thought.
An STP-HSI index method for urban built-up area extraction based on multi-source remote sensing data

A change in an urban built-up area can reflect the process of urbanization and the development of a city. At present, multi-source remote sensing data extraction of built-up areas based on the human settlement index (HSI) has achieved relatively good results but the existence of noise, such as light spillover in the night-time light remote sensing data, seriously affects the accuracy of the HSI. In this paper, a high-precision human settlement index (STP-HSI) method based on spatio-temporal remote sensing and point-of-interest (POI) data is presented to improve the classification accuracy in urban built-up areas extractions. First, to correct light spillover, a new night-time light index the fuzzy c-means spatio-temporal point (FCM-STP) based on fuzzy c-means clustering is proposed, which integrates the spatio-temporal characteristics and uses night light video imaging data from Luojia-1 and POI data. Then, based on the FCM-STP index, the HSI is updated to the STP-HSI index. Finally, a random forest algorithm is used to extract the urban built-up areas, and the random forest feature database is composed of normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI) and STP-HSI index features and texture features. To develop and evaluate the accuracy of the new method for built-up areas extraction with multi-source data, three test sites located in the cities of China (Guangzhou, Xiamen and Nanjing) are used. The experimental results show that our method outperforms the single-source multi-spectral (Landsat 8) data extraction results, the overall accuracy is improved by up to 7.52%, and the kappa coefficient is improved by up to 14%. Compared with the HSI index, the maximum contribution rates of the STP-HSI increased by 25.74%. These experimental results show that the method in this paper is feasible.
A Comment on: Migrating silver eels return from the sea to the river of origin after a false start (2021) by Tambets M et al.

A recently published study [1] investigated the downstream migration of stocked origin silver-stage European eels ( Anguilla anguilla ) and demonstrated that some individuals return from the sea to the river of origin. The authors argue that eels make a ‘ false start ’ , which they interpret as ‘ sophisticated strategy ’ and ‘ impor-tant addition to the description of the plastic behaviour of eel ’ [1, p. 6]. Eels are indeed very plastic in their behaviour [2], and therefore, the return migration to rivers is plausible. This might be especially so because similar movements to freshwater have been observed in silver-stage American eels ( Anguilla rostrata ), which were otherwise estuary residents according to their otolith chemistry pro-files [3,4]. However, here were argue that the interpretations and conclusions of Tambets et al . [1] might be premature in the case of European eel, because of an artefact stemming from a peculiar study design. We also provide arguments to support an alternative interpretation for the observed results. In traditional studies
Integration through transients for inelastic hard sphere fluids

The Integration Through Transients (ITT) formalism provides a kinetic theory to go beyond the linear response regime of low density and shear rate. Its main advantage is to express observables under shear as expectation values in the quiescent system. Here we show that the quiescent fluid does not have to be in thermal equilibrium. Considering a fluidized granular medium under shear, we introduce a granular ITT formalism (gITT) providing quantitative predictions for the flow curves that reflect the rich phenomenology of granular fluids.
Particle–particle drag force in inertial bidisperse gas–particle suspensions

Abstract Particle-resolved direct numerical simulations are employed to investigate the particle–particle drag force in the bidisperse gas–particle suspensions where the particles are smooth and the single-particle velocity distribution function is Maxwellian. The particle Reynolds number ranges from 6.7 to 123.8, and in this range the particle inertia is high enough that the lubrication force is not essential. It is found that the relation derived by the kinetic theory of granular flow (KTGF) highly overestimates the particle–particle drag force. This is because the pre-collision velocities of colliding particles are not completely uncorrelated with each other. From the time sequence of collision events, it is observed that the particle pair that has just collided will probably collide again after a short time due to the restriction of the particle motion in dense suspensions. Since the post-collision velocities of the first collision cannot relax entirely in such a short time, the relative velocity before the subsequent collision is statistically smaller than the domain-averaged relative velocity. Consequently, the particle–particle drag force is over-predicted when the domain-averaged relative velocity is used. For this reason, this work assumes that the particle–particle drag force is determined by the relative velocity within a local region near large particles. When the local region is set to be the spherical shells centred on the centres of large particles and with an outer radius of a mean free path of small particles, the KTGF-based relation can reasonably predict the particle–particle drag force.
The unsteady wake transition behind a wall-mounted large-depth-ratio prism

Abstract The wake of a long rectangular wall-mounted prism is investigated at Reynolds numbers of $Re=250\unicode{x2013}1200$ by directly solving the Navier–Stokes equations. The aim of this study was to examine the unsteady transition mechanism in the wake of a large-depth-ratio (streamwise length to width) prism as well as to characterize the unsteady wake evolution at low Reynolds numbers. The results highlighted that increasing Reynolds number significantly altered the dominance of upwash and downwash flows in the time-averaged flow and changed the characteristics of coherent structures, including their size, dominant frequency and interaction with other structures in the flow. The wake is, therefore, categorized into three regimes within the transition process: steady regime at $Re \leq 625$, regular unsteady regime at $625 < Re < 750$ and irregular unsteady regime at $Re \geq 750$. Particularly, the wake started to exhibit unsteady features at $Re=625\unicode{x2013}650$, which transitioned to an early irregular unsteady wake topology at $Re=750$. At $Re \geq 675$, horseshoe vortices transformed to vortex loops. There were hairpin-like structures formed on the upper and side faces of the long prism. The results further indicated that the transition to unsteadiness is attributed to separated leading-edge shear-layer instabilities and interactions of the shear layer with the horseshoe structures. The wake was more complex due to the interactions of multiple coherent structures in the flow, which resulted in a multiple-periodicity wake system. A skeleton model is proposed for a large-depth-ratio prism, to incorporate details of the unsteady flow features and specify various flow coherent structures at low Reynolds numbers.
Zinc deficiency among pregnant women around Lake Awasa, Hawassa City, Ethiopia: a cross-sectional analysis

Abstract Zinc deficiency (ZD) during pregnancy has far-reaching consequences on the mother, fetus and subsequent child survival. Therefore, the present study aimed to assess the prevalence and associated factors of ZD among pregnant women around Lake Awasa, Hawassa City, Ethiopia. To this end, a facility-based cross-sectional study was conducted on 333 randomly sampled pregnant women from 08 April to 08 May 2021. The socio-economic, dietary intake, water, sanitation and hygiene, obstetric, and maternal health data were collected through face-to-face interviews. Moreover, on-spot blood and stool samples were taken. Descriptive statistics and binary and multivariable logistic regression analysis were conducted. The prevalence of ZD was 58⋅6 % (95 % CI 53⋅31, 63⋅89). The poorest (AOR = 3⋅28; 95 % CI 1⋅26, 8⋅50) and poor (AOR = 2⋅93; 95 % CI 1⋅14, 7⋅54) wealth quintiles, four of more family size (AOR = 1⋅84, 95 % CI 1⋅10, 3⋅35), poor dietary diversity (AOR = 4⋅11; 95 % CI 2⋅11, 7⋅62), not eating snacks (AOR = 3⋅40; 95 % CI 1⋅42, 8⋅15), not consuming fish (AOR = 3⋅53; 95 % CI 1⋅65, 7⋅56) and chicken (AOR = 2⋅53; 95 % CI 1⋅31, 4⋅88) at least once a month, and intestinal parasitic infection (AOR = 2⋅78; 95 % CI 1⋅52, 5⋅08) predicted zinc deficiency. In conclusion, ZD is a public health problem among pregnant women around Lake Awasa. The present study demonstrated that poor socio-economic status, large family size, poor nutritional practices and intestinal parasitic infection determine the zinc status in the present study area. The findings suggest the need for further analysis to deepen the understanding about ZD and consideration of livelihood in interventions to prevent and control ZD among pregnant women in Hawassa City, Ethiopia.
Polling Systems with Periodic Server Routeing in Heavy Traffic: Distribution of the Delay

We consider polling systems with mixtures of exhaustive and gated service in which the server visits the queues periodically according to a general polling table. We derive exact expressions for the steady-state delay incurred at each of the queues under standard heavy-traffic scalings. The expressions require the solution of a set of only M - N linear equations, where M is the length of the polling table and N is the number of queues, but are otherwise explicit. The equations can even be expressed in closed form for several routeing schemes commonly used in practice, such as the star and elevator visit order, in a general parameter setting. The results reveal a number of asymptotic properties of the behavior of polling systems. In addition, the results lead to simple and fast approximations for the distributions and the moments of the delay in stable polling systems with periodic server routeing. Numerical results demonstrate that the approximations are highly accurate for medium and heavily loaded systems.
Unsupervised Single Document Abstractive Summarization using Semantic Units

In this work, we study the importance of content frequency on abstractive summarization, where we define the content as “semantic units. ” We propose a two-stage training framework to let the model automatically learn the frequency of each semantic unit in the source text. Our model is trained in an unsupervised manner since the frequency information can be inferred from source text only. During inference, our model identifies sentences with high-frequency semantic units and utilizes frequency information to generate summaries from the filtered sentences. Our model performance on the CNN/Daily Mail summarization task outperforms the other unsupervised methods under the same settings. Furthermore, we achieve competitive ROUGE scores with far fewer model parameters compared to several large-scale pre-trained models. Our model can be trained under low-resource language settings and thus can serve as a potential solution for real-world applications where pre-trained models are not applicable.
FPC: Fine-tuning with Prompt Curriculum for Relation Extraction

The current classification methods for relation extraction (RE) generally utilize pre-trained language models (PLMs) and have achieved superior results. However, such methods directly treat relation labels as class numbers, therefore they ignore the semantics of relation labels. Recently, prompt-based fine-tuning has been proposed and attracted much attention. This kind of methods insert templates into the input and convert the classification task to a (masked) language modeling problem. With this inspiration, we propose a novel method Fine-tuning with Prompt Curriculum (FPC) for RE, with two distinctive characteristics: the relation prompt learning, introducing an auxiliary prompt-based fine-tuning task to make the model capture the semantics of relation labels; the prompt learning curriculum, a fine-tuning procedure including an increasingly difficult task to adapt the model to the difficult multi-task setting. We have conducted extensive experiments on four widely used RE benchmarks under fully supervised and low-resource settings. The experimental results show that FPC can significantly outperform the existing methods and obtain the new state-of-the-art results.
Transfer Learning for Humor Detection by Twin Masked Yellow Muppets

Humorous texts can be of different forms such as punchlines, puns, or funny stories. Existing humor classification systems have been dealing with such diverse forms by treating them independently. In this paper, we argue that different forms of humor share a common background either in terms of vocabulary or constructs. As a consequence, it is likely that classification performance can be improved by jointly tackling different humor types. Hence, we design a shared-private multitask architecture following a transfer learning paradigm and perform experiments over four gold standard datasets. Empirical results steadily confirm our hypothesis by demonstrating statistically-significant improvements over baselines and accounting for new state-of-the-art figures for two datasets.
Demographic-Aware Language Model Fine-tuning as a Bias Mitigation Technique

BERT-like language models (LMs), when exposed to large unstructured datasets, are known to learn and sometimes even amplify the biases present in such data. These biases generally reflect social stereotypes with respect to gender, race, age, and others. In this paper, we analyze the variations in gender and racial biases in BERT, a large pre-trained LM, when exposed to different demographic groups. Specifically, we investigate the effect of fine-tuning BERT on text authored by historically disadvantaged demographic groups in comparison to that by advantaged groups. We show that simply by fine-tuning BERT-like LMs on text authored by certain demographic groups can result in the mitigation of social biases in these LMs against various target groups.
IndoRobusta: Towards Robustness Against Diverse Code-Mixed Indonesian Local Languages

Significant progress has been made on Indonesian NLP. Nevertheless, exploration of the code-mixing phenomenon in Indonesian is limited, despite many languages being frequently mixed with Indonesian in daily conversation. In this work, we explore code-mixing in Indonesian with four embedded languages, i.e., English, Sundanese, Javanese, and Malay; and introduce IndoRobusta, a framework to evaluate and improve the code-mixing robustness. Our analysis shows that the pre-training corpus bias affects the model's ability to better handle Indonesian-English code-mixing when compared to other local languages, despite having higher language diversity.
Compositionality as an Analogical Process: Introducing ANNE

Usage-based constructionist approaches consider language a structured inventory of constructions, form-meaning pairings of different schematicity and complexity, and claim that the more a linguistic pattern is encountered, the more it becomes accessible to speakers. However, when an expression is unavailable, what processes underlie the interpretation? While traditional answers rely on the principle of compositionality, for which the meaning is built word-by-word and incrementally, usage-based theories argue that novel utterances are created based on previously experienced ones through analogy, mapping an existing structural pattern onto a novel instance. Starting from this theoretical perspective, we propose here a computational implementation of these assumptions. As the principle of compositionality has been used to generate distributional representations of phrases, we propose a neural network simulating the construction of phrasal embedding as an analogical process. Our framework, inspired by word2vec and computer vision techniques, was evaluated on tasks of generalization from existing vectors.
Combining Argumentation Structure and Language Model for Generating Natural Argumentative Dialogue

Argumentative dialogue is an important process where speakers discuss a specific theme for consensus building or decision making. In previous studies for generating consistent argumentative dialogue, retrieval-based methods with hand-crafted argumentation structures have been used. In this study, we propose a method to generate natural argumentative dialogues by combining an argumentation structure and language model. We trained the language model to rewrite a proposition of an argumentation structure on the basis of its information, such as keywords and stance, into the next utterance while considering its context, and we used the model to rewrite propositions in the argumentation structure. We manually evaluated the generated dialogues and found that the proposed method significantly improved the naturalness of dialogues without losing consistency of argumentation.