Miracle-dz/UniFAR-FTUs huggingface dataset:
An Estimation of the Star Formation Rate in the Perseus Complex

We present the results of our investigation of the star-forming potential in the Perseus star-forming complex. We build on previous starless core, protostellar core, and young stellar object (YSO) catalogs from Spitzer (3.6–70 μm), Herschel (70–500 μm), and SCUBA (850 μm) observations in the literature. We place the cores and YSOs within seven star-forming clumps based on column densities greater than cm−2. We calculate the mean density and free-fall time for 69 starless cores as ∼5.55 g cm−3 and ∼0.1 Myr, respectively, and we estimate the star formation rate for the near future as ∼150 M⊙ Myr−1. According to Bonnor–Ebert stability analysis, we find that majority of starless cores in Perseus are unstable. Broadly, these cores can collapse to form the next generation of stars. We found a relation between starless cores and YSOs, where the numbers of young protostars (Class 0 + Class I) are similar to the numbers of starless cores. This similarity, which shows a one-to-one relation, suggests that these starless cores may form the next generation of stars with approximately the same formation rate as the current generation, as identified by the Class 0 and Class I protostars. It follows that if such a relation between starless cores and any YSO stage exists, the SFR values of these two populations must be nearly constant. In brief, we propose that this one-to-one relation is an important factor in better understanding the star formation process within a cloud.
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal

Language models excel at generating coherent text, and model compression techniques such as knowledge distillation have enabled their use in resource-constrained settings. However, these models can be biased in multiple ways, including the unfounded association of male and female genders with gender-neutral professions. Therefore, knowledge distillation without any fairness constraints may preserve or exaggerate the teacher model’s biases onto the distilled model. To this end, we present a novel approach to mitigate gender disparity in text generation by learning a fair model during knowledge distillation. We propose two modifications to the base knowledge distillation based on counterfactual role reversal—modifying teacher probabilities and augmenting the training set. We evaluate gender polarity across professions in open-ended text generated from the resulting distilled and finetuned GPT–2 models and demonstrate a substantial reduction in gender disparity with only a minor compromise in utility. Finally, we observe that language models that reduce gender polarity in language generation do not improve embedding fairness or downstream classification fairness.
On the non-archimedean Monge-Amp\`ere equation in mixed characteristic

Let X be a smooth projective variety over a complete discretely valued field of mixed characteristic. We solve non-archimedean Monge-Amp\`ere equations on X assuming resolution and embedded resolution of singularities. We follow the variational approach of Boucksom, Favre, and Jonsson proving the continuity of the plurisubharmonic envelope of a continuous metric on an ample line bundle on X. We replace the use of multiplier ideals in equicharacteristic zero by the use of perturbation friendly test ideals introduced by Bhatt, Ma, Patakfalvi, Schwede, Tucker, Waldron, and Witaszek building upon previous constructions by Hacon, Lamarche, and Schwede.
Solid Fuel Conversion in Dual Fluidized Bed Gasification - Modelling and Experiments

Dual fluidized bed gasification (DFBG) is the initial step towards the transformation of ligno-cellulosic materials into a raw gas, which can be further upgraded into transportation fuels, such as substitute natural gas, Fischer-Tropsch diesel, dimethyl ether, and methanol. DFBG units can be operated in two distinctly different ways, depending on whether the main product is a gas (to be refined into a transportation fuel) or heat and power (with gas as a by-product). For efficient operation in either mode, the degree of char conversion in the gasification chamber needs to be controlled and optimised. For this purpose, extensive knowledge is required regarding how the degree of char gasification is affected by different parameters. The aim of this thesis is to identify and fill key knowledge gaps regarding how different parameters influence solid fuel conversion in the gasification chamber of a DFBG unit, using a combination of laboratory-scale experiments and semi-empirical modelling. In addition, the possibility of ensuring adequate fuel conversion for either of the target modes described above is investigated. The results of the experiments presented in this thesis confirm that the laboratory-scale conditions applied in the experimental determination of reactivity data aimed at modelling fluidized bed gasification should, as much as possible, mimic the conditions of the end-scale reactor to be modelled. In particular, the effects of fuel axial mixing and of catalytic bed materials on char gasification were found to be significant. A validated semi-empirical 1D model of the gasification chamber of a DFBG unit has been formulated that: 1) accounts for the effect of fuel axial mixing on the char gasification rate; and 2) introduces a computationally efficient method for describing fuel conversion in fluidized beds. The modelling results show that the dominance of fuel convection over fuel dispersion increases with scale. Satisfactory fuel conversion is easily achieved when heat and power are the main products, with gas as a by-product. However, when the main goal is to improve the efficiency of gas production, a combination of baffles, properly chosen operational conditions, and/or the use of an active bed material is likely necessary to achieve sufficient fuel conversion.
Improving Suspension in a Quarter Car Model Test from Aero Post Rig Analysis: Performance Index

The performance of an F1 race car is greatly influenced by its aerodynamics. Race teams try to improve the vehicle performance by aiming for more levels of downforce. A huge amount of time is spent in wind tunnel and track testing. Typical wind tunnel testing is carried out in steady aerodynamic conditions and with car static configurations. However, the ride heights of a car are continuously changing in a race track because of many factors. These are, for example, the roughness and undulations of the track, braking, accelerations, direction changes, aerodynamic load variations due to varying air speed and others. These factors may induce movements on suspensions components (sprung and unsprung masses) at different frequencies and may cause aerodynamic fluctuations that vary tires grip. When the frequency of the movement of a race car is high enough the steady aerodynamic condition and the car static configurations are not fulfilled. Then, transient effects appear and the dynamics of the system changes: heave, pitch and roll transient movements of the sprung mass affect both downforce and center of pressure position. The suspension system have to cope with them, but in order for the suspension to be effective, unsteady aerodynamics must be considered. The main objective is to model the effects of unsteady aerodynamics and know really the car dynamic, with the aim of optimizing the suspension performance, improving tire grip and finally reducing lap times.
The role of post-selection in generating vortex particles of arbitrary mass, spin, and energy

There exist many methods to obtain twisted photons with a projection of orbital angular momentum onto a propagation axis. However, despite the big interest in generating massive particles with the phase vortices, the available diﬀraction techniques are only applicable to the moderately relativistic beams of electron microscopes, to cold neutrons, or non-relativistic atoms. In order to bring the matter waves physics into the high energy domain, one needs to develop alternative methods, applicable for ultrarelativistic energies and for composite particles, including ions, and nuclei. Here, we show that vortex particles of in principle arbitrary mass, spin, and energy, including muons, hadrons, nuclei, and heavy ions, can be generated during photon emission in helical undulators, via Cherenkov radiation, in collisions of charged particles with intense circularly polarized laser beams, in such scattering or annihilation processes as eµ → eµ, ep → ep, e − e + → p ¯ p , and so forth. We argue that the key element in obtaining such quantum states is the post-selection protocol due to quantum entanglement between a pair of the ﬁnal particles and it is largely not the process itself and, in contrast to the classical theory, not the trajectory of the emitting wave-packet’s centroid. The state of a ﬁnal particle – be it a photon, a proton, or a nucleus – becomes twisted if the azimuthal angle of the other particle’s momentum is weakly measured with a large error or not measured at all, which is often the case when the scattering angle is small. As a result, the requirements to the beam transverse coherence can be greatly relaxed, which enables the generation of vortex particles at accelerators and synchrotron radiation facilities, thus making them a new tool for hadronic and spin studies. This weak-measurement technique can also facilitate the development of sources of hard X-ray and γ -range twisted photons for the purposes of nuclear and particle physics.
Genetic heterogeneity of Escherichia coli strains isolated from raw milk , Minas Frescal cheese , and food handlers

From February 2004 to March 2005, 140 samples of food handlers – hands and nostrils – (92), raw milk (24), and minas frescal cheese (24) were analyzed for the presence of Escherichia coli in a dairy processing plant of Goiás State. Forty-seven E. coli strains were obtained and compared by DNA macrorestriction patterns obtained from pulsed-field gel electrophoresis following XbaI restriction in order to investigate the possible sources of cheese contaminations. Based on PFGE genotyping, one strain isolated from food the hands of a handler and five strains isolated from raw milk were identical or closely related to six strains from cheese suggesting, in these cases, the probable source of E. coli contamination in cheeses. No strain isolated from the nostrils was related to those found in cheeses or milk strains. The results showed high diversity among the strains, demonstrating a lack of predominance of an endemic clone in the dairy plant. This paper highlights the usefulness of PFGE as an epidemiological tool for determining the source of E. coli contamination in the food industry.
VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training

Pre-training video transformers on extra large-scale datasets is generally required to achieve premier performance on relatively small datasets. In this paper, we show that video masked autoencoders (VideoMAE) are data-efficient learners for self-supervised video pre-training (SSVP). We are inspired by the recent ImageMAE and propose customized video tube masking with an extremely high ratio. This simple design makes video reconstruction a more challenging self-supervision task, thus encouraging extracting more effective video representations during this pre-training process. We obtain three important findings on SSVP: (1) An extremely high proportion of masking ratio (i.e., 90% to 95%) still yields favorable performance of VideoMAE. The temporally redundant video content enables a higher masking ratio than that of images. (2) VideoMAE achieves impressive results on very small datasets (i.e., around 3k-4k videos) without using any extra data. (3) VideoMAE shows that data quality is more important than data quantity for SSVP. Domain shift between pre-training and target datasets is an important issue. Notably, our VideoMAE with the vanilla ViT can achieve 87.4% on Kinetics-400, 75.4% on Something-Something V2, 91.3% on UCF101, and 62.6% on HMDB51, without using any extra data. Code is available at https://github.com/MCG-NJU/VideoMAE.
The evolution of the rest-frame J- and H-band luminosity function of galaxies to z=3.5

We present the rest-frame J- and H-band luminosity function (LF) of field galaxies, based on a deep multi-wavelength composite sample from the MUSYC, FIRES and FIREWORKS survey public catalogues, covering a total area of 450 arcmin^2. The availability of flux measurements in the Spitzer IRAC 3.6, 4.5, 5.8, and 8 um channels allows us to compute absolute magnitudes in the rest-frame J and H bands up to z=3.5 minimizing the dependence on the stellar evolution models. We compute the LF in the four redshift bins 1.5<z<2.0, 2.0<z<2.5, 2.5<z<3.0 and 3.0<z<3.5. Combining our results with those already available at lower redshifts, we find that (1) the faint end slope is consistent with being constant up to z=3.5, with alpha=-1.05+/-0.03 for the rest-frame J band and alpha=-1.15+/-0.02 for the rest-frame H band; (2) the normalization phi* decreases by a factor of 6 between z=0 and z~1.75 and by a factor 3 between z~1.75 and z=3.25; (3) the characteristic magnitude M* shows a brightening from z=0 to z~2 followed by a slow dimming to z=3.25. We finally compute the luminosity density (LD) in both rest-frame J and H bands. The analysis of our results together with those available in the literature shows that the LD is approximately constant up to z~1, and it then decreases by a factor of 6 up to z=3.5.
COOL-LAMPS. II. Characterizing the Size and Star Formation History of a Bright Strongly Lensed Early-type Galaxy at Redshift 1.02

We present COOL J1323+0343, an early-type galaxy at z = 1.0153 ± 0.0006, strongly lensed by a cluster of galaxies at z = 0.353 ± 0.001. This object was originally imaged by DECaLS and noted as a gravitational lens by COOL-LAMPS, a collaboration initiated to find strong-lensing systems in recent public optical imaging data, and confirmed with follow-up data. With ground-based grzH imaging and optical spectroscopy from the Las Campanas Observatory and the Nordic Optical Telescope, we derive a stellar mass, metallicity, and star formation history from stellar-population synthesis modeling. The lens modeling implies a total magnification, summed over the three images in the arc, of μ ∼ 113. The stellar mass in the source plane is M * ∼ 10.64 M ⊙ and the 1σ upper limit on the star formation rate (SFR) in the source plane is SFR ∼ 3.75 × 10−2 M ⊙ yr−1 (log sSFR = −12.1 yr−1) in the youngest two age bins (0–100 Myr), closest to the epoch of observation. Our measurements place COOL J1323+0343 below the characteristic mass of the stellar mass function, making it an especially compelling target that could help clarify how intermediate-mass quiescent galaxies evolve. We reconstruct COOL J1323+0343 in the source plane and fit its light profile. This object is below the expected size evolution of an early-type galaxy at this mass with an effective radius r e ∼ 0.5 kpc. This extraordinarily magnified and bright lensed early-type galaxy offers an exciting opportunity to study the morphology and star formation history of an intermediate-mass early-type galaxy in detail at z ∼ 1.
Takeovers and (Excess) CEO Compensation

We study if a CEO’s equity-based compensation affects the expected value generation in takeovers. When the objectives of management and shareholders are more aligned, as proxied by the use of equity-based compensation, more value-maximizing acquisitions are expected. Whereas in widely-held firms the decision power is with the management, in firms with concentrated ownership the decision power may be with major blockholders. This may entail that ownership concentration and equity-based pay are substitutes. We find a strongly positive relation between equity-based compensation and cumulative abnormal announcement returns at takeovers, but this relation is eroded when dominant share blocks are held by corporations, which confirms the substitution effect. Powerful CEOs in companies with weak boards and without actively monitoring shareholders may set their own pay which could lead to excesses. We relate excess pay to how takeover decisions are received by the market, and demonstrate that excess compensation negatively affects the acquirer’s stock valuation at a takeover announcement. The market is thus able to identify firms with agency problems and is cautious in its expectations about potential value creation by means of acquisitions.
Hybrid Relay-Reflecting Intelligent Surface-Aided Covert Communications

Covert communication aims to prevent the warden from detecting the presence of communications, i.e. with a negligible detection probability. When the distance between the transmitter and the legitimate receiver is large, large transmission power is needed, which in turn increases the detection probability. Relay is an effective technique to tackle this problem, and various relaying strategies have been proposed for long-distance covert communication in these years. In this article, we first offer a tutorial on the relaying strategies utilized in covert transmission. With the emergence of reflecting intelligent surface and its application in covert communications, we propose a hybrid relay-reflecting intelligent surface (HR-RIS)-assisted strategy to further enhance the performance of covert communications, which simultaneously improves the signal strength received at the legitimate receiver and degrades that at the warden relying on optimizing both the phase and the amplitude of the HR-RIS elements. The numerical results show that the proposed HR-RIS-assisted strategy significantly outperforms the conventional RIS-aided strategy in terms of covert rate.
Spectral analysis of a mixed method for linear elasticity

The purpose of this paper is to analyze a mixed method for linear elasticity eigenvalue problem, which approximates numerically the stress, displacement, and rotation, by piecewise $(k+1)$, $k$ and $(k+1)$-th degree polynomial functions ($k\geq 1$), respectively. The numerical eigenfunction of stress is symmetric. By the discrete $H^1$-stability of numerical displacement, we prove an $O(h^{k+2})$ approximation to the $L^{2}$-orthogonal projection of the eigenspace of exact displacement for the eigenvalue problem, with proper regularity assumption. Thus via postprocessing, we obtain a better approximation to the eigenspace of exact displacement for the eigenproblem than conventional methods. We also prove that numerical approximation to the eigenfunction of stress is locking free with respect to Poisson ratio. We introduce a hybridization to reduce the mixed method to a condensed eigenproblem and prove an $O(h^2)$ initial approximation (independent of the inverse of the elasticity operator) of the eigenvalue for the nonlinear eigenproblem by using the discrete $H^1$-stability of numerical displacement, while only an $O(h)$ approximation can be obtained if we use the traditional inf-sup condition. Finally, we report some numerical experiments.
Studies on the phytochemical and antibacterial activities of aqueous and ethanol extracts of Psidium guajava and Moringa oleifera

Extracts of the leaves, bark and root of Psidium guajava as well as the leaves of Moringa oleifera were investigated for antibacterial activity against Staphylococcus aureus, Streptococcus spp, Klebsiella spp, Proteus spp and Psuedomonas spp. The disc diffusion method was adopted using extract concentrations of 10-280 mg/ml. The qualitative phytochemical compositions of both plants were studied. Phytochemical test on the extracts revealed the presence of saponins, alkaliods, tannins, flavoniods, steroids, phenol and glycosides. Minimum Inhibition concentration (MIC) was obtained by plotting logarithm of the concentrations of the extract against the squares of the zone of inhibition. The antilogarithm of the intercept gave the MIC values. Leaves extract of Moringa oleifera at 280 mg/ml showed good inhibitory effect against Streptococcus spp, comparable to synthetic antibiotics such as Ciproflox and Reflacine. Similarly, the inhibitory effect of P. guajava bark at 280 mg/ml against Klebsiella spp competed favourably with Reflacine. Extracts of P. guajava leaves, root and the synthetic drug Reflacine gave equal antimicrobial effect against Pseudomonas spp. These results indicate that extracts of P. guajava and M. oleifera can be used for the treatment of pathogenic infections caused by some bacteria.
Targeting Policy-Compliers with Machine Learning: An Application to a Tax Rebate Programme in Italy

Machine Learning (ML) can be a powerful tool to inform policy decisions. Those who are treated under a programme might have different propensities to put into practice the behaviour that the policymaker wants to incentivize. ML algorithms can be used to predict the policy-compliers; that is, those who are most likely to behave in the way desired by the policymaker. When the design of the programme is tailored to target the policy-compliers, the overall effectiveness of the policy is increased. This paper proposes an application of ML targeting that uses the massive tax rebate scheme introduced in Italy in 2014.
Relation Classification using Semantically-Enhanced Syntactic Dependency Paths – Combining Semantic and Syntactic Dependencies for Relation Classification using Long Short-Term Memory Networks

Many approaches to solving tasks in the field of Natural Language Processing (NLP) use syntactic dependency trees (SDTs) as a feature to represent the latent nonlinear structure within sentences. Recently, work in parsing sentences to graph-based structures which encode semantic relationships between words—called semantic dependency graphs (SDGs)—has gained interest. This thesis seeks to explore the use of SDGs in place of and alongside SDTs within a relation classification system based on long short-term memory (LSTM) neural networks. Two methods for handling the information in these graphs are presented and compared between two SDG formalisms. Three new relation extraction system architectures have been created based on these methods and are compared to a recent state-of-the-art LSTM-based system, showing comparable results when semantic dependencies are used to enhance syntactic dependencies, but with significantly fewer training parameters.