Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Colchicine and X-Rays on Onion Root Tips

Colchicine, the alkaloid extracted from the seed or corm of Colchicum autumnale L. , the meadow saffron, has been known for many years. Houd6 isolated this substance in 1887 as a yellow flocculent material soluble in cold water, alcohol, and chloroform. When injected into the body in small doses, it produces gastrointestinal symptoms and in some respects behaves as muscarine, pilocarpine, physostigmine, and snake venom. Lits and his associates (39) gave a more detailed account of the early uses of colchicine, to which the reader is referred. Its empirical formula is C. ,. ,H_o~NO6. According to Windhaus it has a phenanthrene nucleus, and its structural formula is expressed as follows:
Level-set percolation of the Gaussian free field on regular graphs I: regular trees

We study level-set percolation of the Gaussian free field on the infinite $d$-regular tree for fixed $d\geq 3$. Denoting by $h_\star$ the critical value, we obtain the following results: for $h>h_\star$ we derive estimates on conditional exponential moments of the size of a fixed connected component of the level set above level $h$; for $h<h_\star$ we prove that the number of vertices connected over distance $k$ above level $h$ to a fixed vertex grows exponentially in $k$ with positive probability. Furthermore, we show that the percolation probability is a continuous function of the level $h$, at least away from the critical value $h_\star$. Along the way we also obtain matching upper and lower bounds on the eigenfunctions involved in the spectral characterisation of the critical value $h_\star$ and link the probability of a non-vanishing limit of the martingale used therein to the percolation probability. A number of the results derived here are applied in the accompanying paper [AC2].
Stellar Representation of Grassmannians.

Pure quantum spin-$s$ states can be represented by $2s$ points on the sphere, as shown by Majorana in 1932 --- the description has proven particularly useful in the study of rotational symmetries of the states, and a host of other properties, as the points rotate rigidly on the sphere when the state undergoes an $SU(2)$ transformation in Hilbert space. At the same time, the Wilzcek-Zee effect, which involves the cyclic evolution of a degenerate $k$-dimensional linear subspace of the Hilbert space, and the associated holonomy dictated by Schroedinger's equation, have been proposed as a fault-tolerant mechanism for the implementation of logical gates, with applications in quantum computing. We show, in this paper, how to characterize such subspaces by Majorana-like sets of points on the sphere, that also rotate rigidly under $SU(2)$ transformations --- the construction is actually valid for arbitrary totally antisymmetric $k$-partite qudit states.
hi_class background evolution, initial conditions and approximation schemes

Cosmological datasets have great potential to elucidate the nature of dark energy and test gravity on the largest scales available to observation. Theoretical predictions can be computed with hi_class (www.hiclass-code.net), an accurate, fast and flexible code for linear cosmology, incorporating a wide range of dark energy theories and modifications to general relativity. We introduce three new functionalities into hi_class: (1) Support for models based on covariant Lagrangians, including a constraint-preserving integration scheme for the background evolution and a series of worked-out examples: Galileon, nKGB, quintessence (monomial, tracker) and Brans-Dicke. (2) Consistent initial conditions for the scalar-field perturbations in the deep radiation era, identifying the conditions under which modified-gravity isocurvature perturbations may grow faster than adiabatic modes leading to a loss of predictivity. (3) An automated quasi-static approximation scheme allowing order-of-magnitude improvement in computing performance without sacrificing accuracy for wide classes of models. These enhancements bring the treatment of dark energy and modified gravity models to the level of detail comparable to software tools restricted to standard ΛCDM cosmologies. The hi_class code is publicly available (https://github.com/miguelzuma/hi_class_public), ready to explore current data and prepare for next-generation experiments.
Proconda - Protected Control Data

Memory corruption vulnerabilities often enable attackers to take control of a target system by overwriting control-flow relevant data (such as return addresses and function pointers), which are potentially stored in close proximity of related, typically user-controlled data on the stack. In this paper, we propose ProConDa, a general approach for protecting control-flow relevant data on the stack ProConDa leverages hardware features to enforce a strict separation between control-flow relevant and regular data of programs written in non-memory-safe languages such as C. Contrary to related approaches, ProConDa does not rely on information hiding and is therefore not susceptible to several recent attacks specifically targeting information hiding as a foundation for memory isolation. We show that ProConDa enforcement is compatible with existing software by applying a software-based prototype to industry benchmarks on an ARM CPU running Linux.
Exceptional point of sixth-order degeneracy in a modified coupled-resonator optical waveguide

We demonstrate for the first time the occurrence of a sixth order exceptional point of degeneracy (EPD) in a multimode optical photonic structure by using a modified periodic coupled resonators optical waveguide (CROW), at the optical wavelength ${\lambda_e} = 1550 nm$. The 6th order EPD is obtained in a CROW without the need of loss or gain. Such EPD corresponds to a very special band edge of the periodic photonic structure where six eigenmode coalesce, so we refer to it as the 6th order degenerate band edge (6DBE). The quality factor Q of an optical cavity made of such a periodic waveguide operating near the 6DBE shows exceptional scaling with the structure length as $Q{\propto}N^7$ with $N$ being the number of unit cells in the periodic finite structure. Furthermore, we elaborate on two applications of the 6DBE: ultra-low-threshold lasers, with threshold that scales as $N^{-7}$, and highly sensitive sensors. The proposed 6DBE-CROW may also find applications in modulators, optical switches, nonlinear devices, and Q-switching cavities.
The Net Radial Flow Velocity of the Neutral Hydrogen in the Oval Distortion of NGC 4736

The net radial flow velocity of gas is an important parameter for understanding galaxy evolution. It is difficult to measure in the presence of the elliptical orbits of an oval distortion because the mathematical model describing the observed velocity is degenerate in the unknown velocity components. A method is developed in this paper that breaks the degeneracy using additional information about the angular frequency of the oval distortion. The method is applied to the neutral hydrogen in the oval distortion of NGC 4736. The neutral hydrogen is flowing inward at a mean rate of −6.1 ± 1.9 km s−1. At this rate, it takes 400 Myr, or 1.7 rotations of the oval distortion, for the neutral hydrogen to travel the 2.5 kpc from the end to the beginning of the oval distortion. The mean mass flow rate of the neutral hydrogen in this region is −0.25 ± 0.11 M⊙ yr−1, which is similar to estimates for the star formation rate reported in the literature.
The Properties of Planetesimal Collisions under Jupiter’s Perturbation and the Application to Chondrule Formation via Impact Jetting

Understanding chondrule formation provides invaluable clues about the origin of the solar system. Recent studies suggest that planetesimal collisions and the resulting impact melts are promising for forming chondrules. Given that the dynamics of planetesimals is a key in impact-based chondrule formation scenarios, we here perform direct N-body simulations to examine how the presence of Jupiter affects the properties of chondrule-forming collisions. Our results show that the absence/presence of Jupiter considerably changes the properties of high-velocity collisions whose impact velocities are higher than 2.5 km s−1. High-velocity collisions occur due to impacts between protoplanets and planetesimals for the case without Jupiter; for the case with Jupiter, the eccentricities of planetesimals are pumped up by the secular and resonant perturbations from Jupiter. We also categorize the resulting planetesimal collisions and find that most high-velocity collisions are classified as grazing ones for both cases. To examine the effect of Jupiter on chondrule formation directly, we adopt the impact-jetting scenario and compute the resulting abundance of chondrules. Our results show that for the case without Jupiter, chondrule formation proceeds in the inside-out manner, following the growth of protoplanets. If Jupiter is present, the location and timing of chondrule formation are determined by Jupiter’s eccentricity, which is treated as a free parameter in our simulations. Thus, the existence of Jupiter is the key parameter for specifying when and where chondrule formation occurs for impact-based scenarios.
Unsupervised Paraphrasing by Simulated Annealing

We propose UPSA, a novel approach that accomplishes Unsupervised Paraphrasing by Simulated Annealing. We model paraphrase generation as an optimization problem and propose a sophisticated objective function, involving semantic similarity, expression diversity, and language fluency of paraphrases. UPSA searches the sentence space towards this objective by performing a sequence of local editing. We evaluate our approach on various datasets, namely, Quora, Wikianswers, MSCOCO, and Twitter. Extensive results show that UPSA achieves the state-of-the-art performance compared with previous unsupervised methods in terms of both automatic and human evaluations. Further, our approach outperforms most existing domain-adapted supervised models, showing the generalizability of UPSA.
Compound Domain Adaptation in an Open World

Existing works on domain adaptation often assume clear boundaries between source and target domains. Despite giving rise to a clean problem formalization, such form falls short of simulating the real world where domains are compounded of interleaving and confounding factors, blurring the domain boundaries. In this work, we opt for a different problem, dubbed open compound domain adaptation (OCDA), for studying the techniques of training domain-robust models in a more realistic setting. OCDA considers a compound (unlabeled) target domain which mixes several major factors (e.g., backgrounds, lighting conditions, etc.), along with a labeled training set, in the training stage and new open domains during inference. The compound target domain can be seen as a combination of multiple traditional target domains each with its own idiosyncrasy. To tackle OCDA, we propose a class-confusion loss to disentangle the domain-dominant factors out of the data and then use them to schedule a curriculum domain adaptation strategy. Moreover, we use a memory-augmented neural network architecture to increase the network's capacity for handling previously unseen domains. Extensive experiments on digit classification, facial expression recognition, semantic segmentation, and reinforcement learning verify the effectiveness of our approach.
Weak anti-localization in spin–orbit coupled lattice systems

The quantum correction to electrical conductivity is studied on the basis of two-dimensional Wolff Hamiltonian, which is an effective model for a spin–orbit coupled (SOC) lattice system. It is shown that weak anti-localization (WAL) arises in SOC lattices, although its mechanism and properties are different from the conventional WAL in normal metals with SOC impurities. The interband SOC effect induces the contribution from the interband singlet Cooperon, which plays a crucial role for WAL in the SOC lattice. It is also shown that there is a crossover from WAL to weak localization in SOC lattices when the Fermi energy or band gap changes. The implications of the present results to Bi–Sb alloys and PbTe under pressure are discussed.
The association between self-esteem and dietary habits, nutrition, sport, gender and age among adolescents in Rijeka (Croatia)

Cilj: Utvrditi povezanosti uhranjenosti i prehrambe nih navika studenata i srednjoškolaca, ovisno o dob i i spolu, te vezu sa samopoštovanjem, zadovoljstvom iz gledom i tjelesnom aktivnoš ću. Ispitanici i metode: Istraživanje je provedeno u Rijeci 2011. /2012. godi ne na uzorku od 248 studenata (151 mladi ć i 97 djevojaka), prosje čne dobi od 20 godina i 164 srednjoškolca (120 mladi ća i 44 djevojke) u dobi od šesnaest godina. Uhranjenost ispitanika procjenjivana je na osnovi BMI (kg/m) i odgovarajućih percentilnih krivulja. Anketni list je sadržavao pitanja o prehrambenim na vikama, bavljenju sportom, zadovoljstvu vlastitim izgledom i načinu na koji se on mijenja te ljestvicu samopoštovan ja. Rezultati: Utvr đeno je da se naši ispitanici uglavnom nepravilno hrane. Me đu srednjoškolcima je 17,1% pretilih, a me đu studentima 10,2%. Mnogo je više pretilih mladi ća nego djevojaka, ali broj pretilih mladi ća pada zajedno s njihovom dobi. Može se vidjeti da su srednjoškolci tri puta nezadovoljn iji svojim izgledom u odnosu na studente, a ta razl ik je izraženije vidljiva u skupini djevojaka. Žele ći poboljšati svoj izgled srednjoškolci u odnosu na studente 2,5 puta češće koriste dijetu, dok studenti u odnosu na srednjoš kolce 1,6 puta češće kombiniraju tjelesnu aktivnost i promjene u prehrani. Zaklju čak: Na temelju uo čenih rezultata name ć se potreba intenziviranja zdravstveno-odgojnih aktivnosti. Stoga je, zajedno s postojećim programom ''Debljina je bolest – hrana može biti lijek'', zapo čela s radom ambulanta specijalizirana za prevenciju poremećaja u prehrani, u sklopu Centra za mlade – savjetovalište otvorenih vrata.
9. Fourier analytic techniques for lattice point discrepancy

Counting integer points in large convex bodies with smooth boundaries containing isolated flat points is oftentimes an intermediate case between balls (or convex bodies with smooth boundaries having everywhere positive curvature) and cubes (or convex polytopes). In this paper, we provide a detailed description of several discrepancy problems in the particular planar case where the boundary coincides locally with the graph of the function ℝ ∋ t -> |t|^γ, with γ > 2. We consider both integer points problems and irregularities of distribution problems. The above “restriction” to a particular family of convex bodies is compensated by the fact that many proofs are elementary. The paper is entirely self-contained.
Acoustomicrofluidic separation of tardigrades from raw cultures for sample preparation

Tardigrades are microscopic animals widely known for their ability to survive in extreme conditions. They are the focus of current research in the fields of taxonomy, biogeography, genomics, proteomics, development, space biology, evolution and ecology. Tardigrades, such as Hypsibius exemplaris, are being advocated as a next-generation model organism for genomic and developmental studies. The raw culture of H. exemplaris usually contains tardigrades themselves, their eggs, faeces and algal food. Experimentation with tardigrades often requires the demanding and laborious separation of tardigrades from raw samples to prepare pure and contamination-free tardigrade samples. In this paper, we propose a two-step acoustomicrofluidic separation method to isolate tardigrades from raw samples. In the first step, a passive microfluidic filter composed of an array of traps is used to remove large algal clusters in the raw sample. In the second step, a surface acoustic wave-based active microfluidic separation device is used to deflect tardigrades continuously from their original streamlines inside the microchannel and thus isolate them selectively from algae and eggs. The experimental results demonstrated the efficient separation of tardigrades, with a recovery rate of 96% and an impurity of 4% algae on average in a continuous, contactless, automated, rapid and biocompatible manner.
Deleter: Leveraging BERT to Perform Unsupervised Successive Text Compression

Text compression has diverse applications such as Summarization, Reading Comprehension and Text Editing. However, almost all existing approaches require either hand-crafted features, syntactic labels or parallel data. Even for one that achieves this task in an unsupervised setting, its architecture necessitates a task-specific autoencoder. Moreover, these models only generate one compressed sentence for each source input, so that adapting to different style requirements (e.g. length) for the final output usually implies retraining the model from scratch. In this work, we propose a fully unsupervised model, Deleter, that is able to discover an "optimal deletion path" for an arbitrary sentence, where each intermediate sequence along the path is a coherent subsequence of the previous one. This approach relies exclusively on a pretrained bidirectional language model (BERT) to score each candidate deletion based on the average Perplexity of the resulting sentence and performs progressive greedy lookahead search to select the best deletion for each step. We apply Deleter to the task of extractive Sentence Compression, and found that our model is competitive with state-of-the-art supervised models trained on 1.02 million in-domain examples with similar compression ratio. Qualitative analysis, as well as automatic and human evaluations both verify that our model produces high-quality compression.
Maximal Rigid Subalgebras of Deformations and $L^2$ Cohomology, II

In the past two decades, Sorin Popa's breakthrough deformation/rigidity theory has produced remarkable rigidity results for von Neumann algebras $M$ which can be deformed inside a larger algebra $\widetilde M \supseteq M$ by an action $\alpha: \mathbb{R} \to {\rm Aut}(\widetilde M)$, while simultaneously containing subalgebras $Q$ {\it rigid} with respect to that deformation, that is, such that $\alpha_t \to {\rm id}$ uniformly on the unit ball of $Q$ as $t \to 0$. However, it has remained unclear how to exploit the interplay between distinct rigid subalgebras not in specified relative position. We show that in fact, any diffuse subalgebra which is rigid with respect to a mixing s-malleable deformation is contained in a subalgebra which is uniquely maximal with respect to being rigid. In particular, the algebra generated by any family of rigid subalgebras that intersect diffusely must itself be rigid with respect to that deformation. The case where this family has two members was the motivation for this work, showing for example that if $G$ is a countable group with $\beta^{1}_{(2)}(G) > 0$, then $L(G)$ cannot be generated by two property $(T)$ subalgebras with diffuse intersection; however, the result is most striking when the family is infinite.
A time-dependent Hartree-Fock study of triple-alpha dynamics

Time-dependent Hartree-Fock calculations have been performed for fusion reactions of He-4 + He-4 -> Be*-8, followed by He-4 + Be*-8 . Depending on the orientation of the initial state, a linear chain vibrational state or a triangular vibration is found in 12C, with transitions between these states observed. The vibrations of the linear chain state and the triangular state occur at ~9 and 4 MeV respectively.
Group inference in high dimensions with applications to hierarchical testing

Group inference has been a long-standing question in statistics and the development of high-dimensional group inference is an essential part of statistical methods for analyzing complex data sets, including hierarchical testing, tests of interaction, detection of heterogeneous treatment effects and local heritability. Group inference in regression models can be measured with respect to a weighted quadratic functional of the regression sub-vector corresponding to the group. Asymptotically unbiased estimators of these weighted quadratic functionals are constructed and a procedure using these estimator for inference is proposed. We derive its asymptotic Gaussian distribution which allows to construct asymptotically valid confidence intervals and tests which perform well in terms of length or power. The results simultaneously address four challenges encountered in the literature: controlling coverage or type I error even when the variables inside the group are highly correlated, achieving a good power when there are many small coefficients inside the group, computational efficiency even for a large group, and no requirements on the group size. We apply the methodology to several interesting statistical problems and demonstrate its strength and usefulness on simulated and real data.
Simpler and Faster Learning of Adaptive Policies for Simultaneous Translation

Simultaneous translation is widely useful but remains challenging. Previous work falls into two main categories: (a) fixed-latency policies such as Ma et al. (2019) and (b) adaptive policies such as Gu et al. (2017). The former are simple and effective, but have to aggressively predict future content due to diverging source-target word order; the latter do not anticipate, but suffer from unstable and inefficient training. To combine the merits of both approaches, we propose a simple supervised-learning framework to learn an adaptive policy from oracle READ/WRITE sequences generated from parallel text. At each step, such an oracle sequence chooses to WRITE the next target word if the available source sentence context provides enough information to do so, otherwise READ the next source word. Experiments on German<=>English show that our method, without retraining the underlying NMT model, can learn flexible policies with better BLEU scores and similar latencies compared to previous work.
Explanation based Handwriting Verification

Deep learning system have drawback that their output is not accompanied with ex-planation. In a domain such as forensic handwriting verification it is essential to provideexplanation to jurors. The goal of handwriting verification is to find a measure of confi-dence whether the given handwritten samples are written by the same or different writer.We propose a method to generate explanations for the confidence provided by convolu-tional neural network (CNN) which maps the input image to 15 annotations (features)provided by experts. Our system comprises of: (1) Feature learning network (FLN),a differentiable system, (2) Inference module for providing explanations. Furthermore,inference module provides two types of explanations: (a) Based on cosine similaritybetween categorical probabilities of each feature, (b) Based on Log-Likelihood Ratio(LLR) using directed probabilistic graphical model. We perform experiments using acombination of feature learning network (FLN) and each inference module. We evaluateour system using XAI-AND dataset, containing 13700 handwritten samples and 15 cor-responding expert examined features for each sample. The dataset is released for publicuse and the methods can be extended to provide explanations on other verification taskslike face verification and bio-medical comparison. This dataset can serve as the basis and benchmark for future research in explanation based handwriting verification. The code is available on github.
A Particle Emitting Source From an Accelerating, Perturbative Solution of Relativistic Hydrodynamics

The quark gluon plasma is formed in heavy-ion collisions, and it can be described by solutions of relativistic hydrodynamics. In this paper we utilize perturbative hydrodynamics, where we study first order perturbations on top of a known solution. We investigate the perturbations on top of the Hubble flow. From this perturbative solution we can give the form of the particle emitting source and calculate observables of heavy-ion collisions. We describe the source function and the single-particle momentum spectra for a spherically symmetric solution.