Miracle-dz/UniFAR-FTUs huggingface dataset:
Growth of a Protostar and a Young Circumstellar Disk with a High Mass-Accretion Rate onto the Disk

The growing process of both a young protostar and a circumstellar disk is investigated. Viscous evolution of a disk around a single star is considered with a model where a disk increases its mass by dynamically accreting envelope and simultaneously loses its mass via viscous accretion onto the central star. We focus on the circumstellar disk with high mass accretion rate onto the disk $\dot{M}=8. 512c_{\rm s}^3/G$ as a result of dynamical collapse of rotating molecular cloud core. We study the origin of the surface density distribution and the origin of the disk-to-star mass ratio by means of numerical calculations of unsteady viscous accretion disk in one-dimensional axisymmetric model. It is shown that the radial profiles of the surface density $\Sigma$, azimuthal velocity $v_{\phi}$, and mass accretion rate $\dot{M}$ in the inner region approach to the quasi-steady state. Profile of the surface density distribution in the quasi-steady state is determined as a result of angular momentum transport rather than its original distribution of angular momentum in the cloud core. It is also shown that the disk mass becomes larger than the central star in the long time limit as long as temporary constant mass flux onto the disk is assumed. After the mass infall rate onto the disk declines owing to the depletion of the parent cloud core, the disk-to-star mass ratio $M_{\rm disk}/M_*$ decreases. The disk-to-star mass ratio becomes smaller than unity after $t> 10^5 \rm yr$ and $t>10^6 \rm yr$ from the beginning of the accretion phase in the case with $\alpha_0 =1 {\rm and} 0.1$, respectively, where $\alpha_0 $ is the constant part of viscous parameter. In the case with $\alpha_0 \leq 10^{-2}$, $M_{\rm disk}/M_*$ is still larger than unity at $2 \rm Myr$ from the beginning of the accretion phase.
SUPERNOVA LIGHT CURVES POWERED BY YOUNG MAGNETARS

We show that energy deposited into an expanding supernova remnant by a highly magnetic (B ∼ 5 × 1014 G) neutron star spinning at an initial period of Pi ≈ 2–20 ms can substantially brighten the light curve. For magnetars with parameters in this range, the rotational energy is released on a timescale of days to weeks, which is comparable to the effective diffusion time through the supernova remnant. The late time energy injection can then be radiated without suffering overwhelming adiabatic expansion losses. The magnetar input also produces a central bubble that sweeps ejecta into an internal dense shell, resulting in a prolonged period of nearly constant photospheric velocity in the observed spectra. We derive analytic expressions for the light curve rise time and peak luminosity as a function of B and Pi, and the properties of the supernova ejecta that allow for direct inferences about the underlying magnetar in bright supernovae. We perform numerical radiation hydrodynamic calculations of a few specific instances and compare the resulting light curves to observed events. Magnetar birth is likely to impact more than a few percent of all core-collapse supernovae, and may naturally explain some of the brightest events ever seen (e.g., SN 2005ap and SN 2008es) at L ≳ 1044 ergs s−1.
Decomposition methods for quadratic zero-one programming

The quadratic 0-1 programmingwith linear constraints (QP) is a general class of optimization problems that includes many combinatorial optimization problems. The Quadratic Assignment Problem (QAP), Quadratic Traveling Salesman Problem (QTSP), Graph Partitioning, Quadratic Knapsack Problem (QKP) and Quadratic Minimum Spanning Tree Problem (QMSTP) are among the well-known particular cases of the QP which arise in a variety of real-world applications. Since in general the QP is an NP-hard non-linear optimization problem, usually a problem reformulation is considered so that a computationally inexpensive bound on the optimal objective function value is obtained. In the first part of this thesis the most important solution methods for the QP are studied. These solution methods are divided into two main groups: Reformulation-Relaxation approaches (RR), and Reformulation-Decomposition approaches (RD). It is discussed how one can reformulate and solve the problem taking into account the problem structure. In the second part of the thesis, different RR and RD approaches are developed to four classical combinatorial optimization problems including QAP, QTSP, QMSTP, and Quadratic Shortest Path problem (QSP). As for the QAP, new compact reformulations are presented for the general case, and different decomposition strategies are developed for two special cases of the problem. The QTSP is another special case of QPs that is studied and analyzed in the spirit of the reformulation-decomposition. More precisely an extended Linear Programming formulation that contains a variable for each cycle in the graph is presented. Since the number of cycles is exponential in the graph size, the new formulation is solved via Column Generation approach. In the context of QMSTP, new bounding procedures based on a novel reformulation scheme and some new mixed 0-1 linear formulations are proposed. The efficiency of the proposed bounds is comprehensively discussed and some efficient dual-ascent algorithms to derive the new bounds are developed. Finally, quadratic shortest path problem is introduced as a novel QP. The NP-hardness of the problem is proved, and some bounding techniques for the problem are presented.
Lean, Green, and Lifetime Maximizing Sensor Deployment on a Barrier

Lean, Green, and Lifetime Maximizing Mobile Sensor Deployment on a Barrier by Peter Michael Terlecky Advisor: Amotz Bar-Noy Mobile sensors are located on a barrier represented by a line segment, and each sensor has a single energy source that can be used for both moving and sensing. Sensors may move once to their desired destinations and then coverage/communication is commenced. The sensors are collectively required to cover the barrier or in the communication scenario set up a chain of communication from endpoint to endpoint. A sensor consumes energy in movement in proportion to distance traveled, and it expends energy per time unit for sensing in direct proportion to its radius raised to a constant exponent. The first focus is of energy efficient coverage. A solution is sought which minimizes the sum of energy expended by all sensors while guaranteeing coverage for a predetermined amount of time. The objective of minimizing the maxi-
New Electrodynamics of Pulsars

We have recently proposed that Force-Free Electrodynamics (FFE) does not apply to pulsars -- pulsars should be described by the high-conductivity limit of Strong-Field Electrodynamics (SFE), which predicts an order-unity damping of the Poynting flux, while FFE postulates zero damping. The strong damping result has not been accepted by several pulsar experts, who claim that FFE basically works and the Poynting flux damping can be arbitrarily small. Here we consider a thought experiment -- cylindrical periodic pulsar. We show that FFE is incapable of describing this object, while SFE predictions are physically plausible. The intrinsic breakdown of FFE should mean that the FFE description of the singular current layer (the only region of magnetosphere where FFE and the high-conductivity SFE differ) is incorrect. Then the high-conductivity SFE should be the right theory for real pulsars too, and the pure-FFE description of pulsars should be discarded.
Supermassive Dark Stars: Detectable in JWST and HST

The first stars to form in the history of the universe may have been powered by dark matter annihilation rather than by fusion. This new phase of stellar evolution may have lasted millions to billions of years. These dark stars can grow to be very large, > 10^5 solar masses, and are relatively cool (~10^4 K). They are also very bright, being potentially detectable in the upcoming James Webb Space Telescope or even the Hubble Space Telescope. Once the dark matter runs out, the dark stars have a short fusion phase, before collapsing into black holes (BH). The resulting BH could serve as seeds for the (unexplained) supermassive black holes at high redshift and at the centers of galaxies.
Depression Recognition in Social Media based on Symptoms' Detection

: Depression is a common mental disorder that affects millions of people around the world. Recently, several methods have been proposed that detect people suffering from depression by analyzing their language patterns in social media. These methods show competitive results, but most of them are opaque and lack of explainability. Motivated by these problems, and inspired by the questionnaires used by health professionals for its diagnosis, in this paper we propose an approach for the detection of depression based on the identification and accumulation of evidence of symptoms through the users’ posts. Results in a benchmark collection are encouraging, as they show a competitive performance with respect to state-of-the-art methods. Furthermore, taking advantage of the approach’s properties, we outline what could be a support tool for healthcare professionals for analyzing and monitoring depression behaviors in social networks.
Evaluation of call centre conversations based on a high-level symbolic representation

We present a demo that illustrates the performance of our system to analyse and evaluate call centre conversations. Our solution can be used at different stages of the quality feedback loop. The high-level symbolic representation developed on the context-based intent recognition core module allows for detecting fine-grained reasons for quality assurance problems and going in-depth qualitative analysis of how agents and customers interact. We illustrate the evaluation and insights of real-life conversations provided by a Belgian call centre. Participants can interact with the demo by playing with call annotation, recommendations, and diverse parameters.
Biomedical entities recognition in Spanish combining word embeddings

: This is a summary of the Ph.D. thesis written by Pilar L´opez ´Ubeda at Universidad de Ja´en under the supervision of PhD. M. Teresa Mart´ın Valdivia, Ph.D. L. Alfonso Ure˜na L´opez and PhD. Manuel Carlos D´ıaz Galiano. The defense was held in Ja´en on April 22, 2021. The doctoral committee was integrated by PhD. Rafael Mu˜noz Guillena from Universidad de Alicante, PhD. Paloma Mart´ınez Fern´andez from Universidad Carlos III de Madrid, and Manuel Montes y G´omez from National Institute of Astrophysics, Optics and Electronics (Mexico). The thesis obtained the grade of Summa Cum Laude and the international mention.
A tale twice told: the luminosity profiles of the Sagittarius tails

The Sagittarius (Sgr) dwarf galaxy is the archetype of a tidally disrupting system. Both leading and trailing tails can be observed across at least 180° of the sky and measurements of their luminosity density profiles have recently become available. Using numerical simulations, we explore the factors that control the appearance of such profiles. We use two possible models for the Sgr progenitor. The first is a one-component Plummer model, which may represent either a dark matter free progenitor, or one in which pre-existing dark matter has already been largely stripped. The second is a two-component model in which the stars are represented by a Hernquist sphere embedded in a cosmologically modish Navarro–Frenk–White dark halo. Disruption of the models in the Milky Way galaxy provides us with two tellings of the tale of the formation of the Sgr stream. The initial disintegration of the baryons proceeds more slowly for the two-component models because of the protective cocoon of dark matter. Once this has been stripped, though, matters proceed apace. In both cases, the profiles after ∼6 pericentric passages provide good matches to the observational data, but the tails are more extended for the two-component models. The leading and trailing tails are symmetric at apocentre or pericentre. At other orbital phases, asymmetries are present, as tails are compressed as they approach apocentre and stretched out as they approach pericentre. There may exist density enhancements corresponding to such pile-ups which may be observable in current survey data. We re-visit the calculation of Niederste-Ostholt et al. and slightly revise upwards the luminosity of the Sgr progenitor to 9.9–14.4 × 107 L⊙ based on insights from the simulations.
Tropical enumeration of curves in blowups of the projective plane

We describe a method for recursively calculating Gromov-Witten invariants of all blowups of the projective plane. This recursive formula is different from the recursive formulas due to G\"ottsche and Pandharipande in the zero genus case, and Caporaso and Harris in the case of no blowups. We use tropical curves and a recursive computation of Gromov-Witten invariants relative a normal crossing divisor.
Voice Puppetry with FastPitch

Affective speech synthesis is an active research area, but recent approaches usually lack the full, fine-grained controllabil-ity to produce utterances with any exact affect intended by the user. We propose a puppetry tool based on FastPitch to help model output convey any required suprasegmental meanings. Users can choose any trained FastPitch model, and which features should be mimicked, making the approach fine-grained and language-independent.
Burmese Sentiment Analysis Based on Transfer Learning

Using a rich resource language to classify sentiments in a language with few resources is a popular subject of research in natural language processing. Burmese is a low-resource language. In light of the scarcity of labeled training data for sentiment classification in Burmese, in this study, we propose a method of transfer learning for sentiment analysis of a language that uses the feature transfer technique on sentiments in English. This method generates a cross-language word-embedding representation of Burmese vocabulary to map Burmese text to the semantic space of English text. A model to classify sentiments in English is then pre-trained using a convolutional neural network and an attention mechanism, where the network shares the model for sentiment analysis of English. The parameters of the network layer are used to learn the cross-language features of the sentiments, which are then transferred to the model to classify sentiments in Burmese. Finally, the model was tuned using the labeled Burmese data. The results of the experiments show that the proposed method can significantly improve the classification of sentiments in Burmese compared to a model trained using only a Burmese corpus.
GAN-Based Local Lightness-Aware Enhancement Network for Underexposed Images

Uneven light in real-world causes visual degradation for underexposed regions. For these regions, insufficient consideration during enhancement procedure will result in over-/under-exposure, loss of details and color distortion. Confronting such challenges, an unsupervised low-light image enhancement network is proposed in this paper based on the guidance of the unpaired low-/normal-light images. The key components in our network include super-resolution module (SRM), a GAN-based low-light image enhancement network (LLIEN), and denoising-scaling module (DSM). The SRM improves the resolution of the low-light input images before illumination enhancement. Such design philosophy improves the effectiveness of texture details preservation by operating in high-resolution space. Subsequently, local lightness attention module in LLIEN effectively distinguishes unevenly illuminated areas and puts emphasis on low-light areas, ensuring the spatial consistency of illumination for locally underexposed images. Then, multiple discriminators, i.e., global discriminator, local region discriminator, and color discriminator performs assessment from different perspectives to avoid over-/under-exposure and color distortion, which guides the network to generate images that in line with human aesthetic perception. Finally, the DSM performs noise removal and obtains high-quality enhanced images. Both qualitative and quantitative experiments demonstrate that our approach achieves favorable results, which indicates its superior capacity on illumination and texture details restoration.
A Semantic-Proximity Term-Weighting Scheme for Aspect Category Detection

: Aspect category detection is a subtask of aspect-level sentiment analysis, which aims at identifying the aspect categories present in an opinion. It is a diﬃcult task because the category must be inferred from the terms of the opinion, and also because each opinion may include judgments for more than one aspect category. In recent years, the use of attention mechanisms has improved performance in diﬀerent tasks, allowing the identiﬁcation and prioritization of terms that mostly contribute to the classiﬁcation. However, in multi-label problems, such as aspect category detection, diﬀerent terms must be selected based on each category, which is a drawback for these models. Motivated by the same idea of identifying and highlighting the importance of terms, this paper proposes a weighing scheme that emphasizes terms in an opinion based on their semantic proximity to each aspect category. The proposed scheme has been evaluated on diﬀerent SemEval datasets, demonstrating its eﬀectiveness in this multi-label scenario. Moreover, it can be applied in scenarios with limited training data and can be combined with diﬀerent classiﬁcation models, including deep neural networks.
Exploiting user-frequency information for mining regionalisms in Argentinian Spanish from Twitter

: The task of detecting regionalisms (expressions or words used in certain regions) has traditionally relied on the use of questionnaires and surveys, heavily depending on the expertise and intuition of the surveyor. The emergence of social media and microblogging services has produced an unprecedented wealth of content (mainly informal text generated by users), opening new opportunities for linguists to extend their studies of language variation. Previous work on the automatic detection of regionalisms depended mostly on word frequencies. In this work, we present a novel metric based on Information Theory that incorporates user frequency. We tested this metric on a corpus of Argentinian Spanish tweets in two ways: via manual annotation of the relevance of the retrieved terms, and also as a feature selection method for geolocation of users. In either case, our metric outperformed other techniques based on word frequency, suggesting that measuring the amount of users that use a word is an informative feature. This tool has helped lexicographers discover several unregistered words of Argentinian Spanish, as well as diﬀerent meanings assigned to registered words.
Enhanced ferromagnetic and metal insulator transition in Sm0.55Sr0.45MnO3 thin films: Role of oxygen vacancy induced quenched disorder

Effect of quenched disorder (QD) caused by oxygen vacancy (OV) and substrate induced inhomogeneous compressive strain, on the magnetic and transport properties of oriented polycrystalline Sm0.55Sr0. 45MnO3 thin films is investigated. QD is related intimately to the ordering/disordering of the OVs and controls the paramagnetic-ferromagnetic/insulator-metal transition. OV ordered films show enhanced TC/TIM∼165 K, which is depressed by oxygen annealing. OV disordering realized by quenching reduces TC/TIM. The first order IM transition observed in SSMO single crystals is transformed into nonhysteretic and continuous one in the OV ordered films. QD appears to be diluted by OV disorder/annihilation and results in stronger carrier localization.
Local Extrema in Quantum Chaos

We numerically investigate the distribution of extrema of 'chaotic' Laplacian eigenfunctions on two-dimensional manifolds. Our contribution is two-fold: (a) we count extrema on grid graphs with a small number of randomly added edges and show the behavior to coincide with the 1957 prediction of Longuet-Higgins for the continuous case and (b) compute the regularity of their spatial distribution using \textit{discrepancy}, which is a classical measure from the theory of Monte Carlo integration. The first part suggests that grid graphs with randomly added edges should behave like two-dimensional surfaces with ergodic geodesic flow; in the second part we show that the extrema are more regularly distributed in space than the grid $\mathbb{Z}^2$.
Total Knee Replacement Epidemiology in a Single Secondary Hospital Before and After the COVID-19 Pandemic: A descriptive Comparative Study

Background: The purposes of this study were (1) to describe the characteristics of patients underwent TKR during COVID-19 Pandemic and (2) to compare the demographic of patients underwent TKR before and after COVID-19 Pandemic in St. Carolus Hospital, Jakarta, Indonesia. Methods: Data were extracted from January 2016 to December 2020 from the annual reports of arthroplasty registry (single surgeon). Patient demographic data were collected (Gender, age, comorbidity). Post-operative characteristics were defined as: (1) Length of hospitalization (days); (2) Complication rate (%); (3) Revision event (%). The complication rate included: (1) Deep vein thrombosis; (2) Prosthetic joint infection; (3) Periprosthetic fracture. The above parameters were compared before and after the COVID-19 Pandemic. Result: A total of 730 primary TKR procedures (12.3 cases per month) were performed from January 2016 to February 2020, meanwhile there were 54 primary TKR (6 cases per month) done in 9 months after COVID-19 Pandemic from March 2020 to December 2020. The lowest case monthly after the COVID-19 Pandemic was found on April 2020 (1 case per month), on the other hand, the highest case monthly was found on December 2020 (14 cases per month). The complication rate decreased from the Pre
Modification of the phase structure of blackD6branes in a canonical ensemble and its origin

It is well known that charged black $Dp$ branes of type II string theory share a universal phase structure of van der Waals$-$Maxwell liquid-gas type except $D5$ and $D6$ branes. Interestingly, the phase structure of $D5$ and $D6$ branes can be changed to the universal form with the inclusion of particular delocalized charged lower-dimensional branes. For $D5$ branes one needs to introduce delocalized $D1$ branes, and for $D6$ branes, one needs to introduce delocalized $D0$ branes to obtain the universal structure. In a previous paper [J. High Energy Phys. {\bf 04} (2013) 100] Lu with Wei study the phase structure of black $D6$ branes with the introduction of delocalized $D0$ branes in a special case when their charges are equal and the dilaton charge vanishes. In this paper, we look at the phase structure of the black $D6/D0$ system with the generic values of the parameters, which makes the analysis more involved but the structure more rich. We also provide reasons why the respective modifications of the phase structures to the universal form for the black $D5$ and $D6$ branes occur when specific delocalized lower-dimensional branes are introduced.