Miracle-dz/UniFAR-FTUs huggingface dataset:
SOCKS: A Stochastic Optimal Control and Reachability Toolbox Using Kernel Methods

We present SOCKS, a data-driven stochastic optimal control toolbox based in kernel methods. SOCKS is a collection of data-driven algorithms that compute approximate solutions to stochastic optimal control problems with arbitrary cost and constraint functions, including stochastic reachability, which seeks to determine the likelihood that a system will reach a desired target set while respecting a set of pre-defined safety constraints. Our approach relies upon a class of machine learning algorithms based in kernel methods, a nonparametric technique which can be used to represent probability distributions in a high-dimensional space of functions known as a reproducing kernel Hilbert space. As a nonparametric technique, kernel methods are inherently data-driven, meaning that they do not place prior assumptions on the system dynamics or the structure of the uncertainty. This makes the toolbox amenable to a wide variety of systems, including those with nonlinear dynamics, black-box elements, and poorly characterized stochastic disturbances. We present the main features of SOCKS and demonstrate its capabilities on several benchmarks.
SummaReranker: A Multi-Task Mixture-of-Experts Re-ranking Framework for Abstractive Summarization

Sequence-to-sequence neural networks have recently achieved great success in abstractive summarization, especially through fine-tuning large pre-trained language models on the downstream dataset. These models are typically decoded with beam search to generate a unique summary. However, the search space is very large, and with the exposure bias, such decoding is not optimal. In this paper, we show that it is possible to directly train a second-stage model performing re-ranking on a set of summary candidates. Our mixture-of-experts SummaReranker learns to select a better candidate and consistently improves the performance of the base model. With a base PEGASUS, we push ROUGE scores by 5.44% on CNN- DailyMail (47.16 ROUGE-1), 1.31% on XSum (48.12 ROUGE-1) and 9.34% on Reddit TIFU (29.83 ROUGE-1), reaching a new state-of-the-art. Our code and checkpoints will be available at https://github.com/ntunlp/SummaReranker.
The stable cooperations of Morava $K$-Theory and the fiber product of automorphism groups of formal group laws

There are many previous studies on the Hopf algebra $K(n)_*(K(n))$, the stable cooperations of $n$th Morava $K$-theory at an odd prime. Whereas the main part of $K(n)_*(K(n))$ corepresents the group-valued functor consisting of strict automorphisms of the Honda formal group law of height $n$, relations between the whole structure of $K(n)_*(K(n))$ including the exterior part and formal group laws have not been investigated well. Firstly, we constitute a functor $C(-)$ which is given by the fiber product of two natural homomorphism between subgroups of automorphisms of formal group laws, and the Hopf algebra $C_*$ corepresenting $C(-)$. Next, we construct a Hopf algebra homomorphism $\kappa^*:C_*\to K(n)_*(K(n))$ naturally. To relate $C_*$ to $K(n)_*(K(n))$, we use stable comodule algebras which are introduced by Boardman. From the algebra structure of $K(n)_*(K(n))$ which is given by W\"urgler and Yagita, we see that $\kappa^*$ is an isomorphism. Since we formulate $C_*$ by using formal group laws, the isomorphism $\kappa^*$ clarifies relationship between the Hopf algebra structure of $K(n)_*(K(n))$ including the exterior algebra part and formal group laws.
Dark energy survey year 3 results: cosmological constraints from the analysis of cosmic shear in harmonic space

We present cosmological constraints from the analysis of angular power spectra of cosmic shear maps based on data from the first three years of observations by the Dark Energy Survey (DES Y3). Our measurements are based on the pseudo-Cℓmethod and complement the analysis of the two-point correlation functions in real space, as the two estimators are known to compress and select Gaussian information in different ways, due to scale cuts. They may also be differently affected by systematic effects and theoretical uncertainties, making this analysis an important cross-check. Using the same fiducial ΛCDMmodel as in the DES Y3 real-space analysis, we find ${S_8 \equiv \sigma _8 \sqrt{\Omega _{\rm m}/0.3} = 0.793^{+0.038}_{-0.025}}$, which further improves to S8 = 0.784 ± 0.026 when including shear ratios. This result is within expected statistical fluctuations from the real-space constraint, and in agreement with DES Y3 analyses of non-Gaussian statistics, but favors a slightly higher value of S8, which reduces the tension with the Planck2018 constraints from 2.3 σ in the real space analysis to 1.5 σ here. We explore less conservative intrinsic alignments models than the one adopted in our fiducial analysis, finding no clear preference for a more complex model. We also include small scales, using an increased Fourier mode cut-off up to kmax = 5 h Mpc−1, which allows to constrain baryonic feedback while leaving cosmological constraints essentially unchanged. Finally, we present an approximate reconstruction of the linear matter power spectrum at present time, found to be about 20 per cent lower than predicted by Planck2018, as reflected by the lower S8 value.
Defending From Physically-Realizable Adversarial Attacks Through Internal Over-Activation Analysis

This work presents Z-Mask, an effective and deterministic strategy to improve the adversarial robustness of convolutional networks against physically-realizable adversarial attacks. The presented defense relies on specific Z-score analysis performed on the internal network features to detect and mask the pixels corresponding to adversarial objects in the input image. To this end, spatially contiguous activations are examined in shallow and deep layers to suggest potential adversarial regions. Such proposals are then aggregated through a multi-thresholding mechanism. The effectiveness of Z-Mask is evaluated with an extensive set of experiments carried out on models for semantic segmentation and object detection. The evaluation is performed with both digital patches added to the input images and printed patches in the real world. The results confirm that Z-Mask outperforms the state-of-the-art methods in terms of detection accuracy and overall performance of the networks under attack. Furthermore, Z-Mask preserves its robustness against defense-aware attacks, making it suitable for safe and secure AI applications.
Hydrogen phase-IV characterization by full account of quantum anharmonicity

We devise a framework to compute accurate phonons in molecular crystals even in case of strong quantum anharmonicity. Our approach is based on the calculation of the static limit of the phononic Matsubara Green’s function from path integral molecular dynamics simulations. Our method enjoys a remarkably low variance, which allows one to compute accurate phonon frequencies after a few picoseconds of nuclear dynamics, and it is further stabilized by the use of appropriate constrained displacement operators. We applied it to solid hydrogen at high pressure. For phase III, our predicted infrared (IR) and Raman active vibrons agree very well with experiments. We then characterize the crystalline symmetry of phase IV by direct comparison with vibrational data and we determine the character and isotopic shift of its Raman and IR vibron peaks.
Logical shadow tomography: Efficient estimation of error-mitigated observables

We introduce a technique to estimate error-mitigated expectation values on noisy quantum computers. Our technique performs shadow tomography on a logical state to produce a memory-eﬃcient classical reconstruction of the noisy density matrix. Using eﬃcient classical post-processing, one can mitigate errors by projecting a general nonlinear function of the noisy density matrix into the codespace. The subspace expansion and virtual distillation can be viewed as special cases of the new framekwork. We show our method is favorable in the quantum and classical resources overhead. Relative to subspace expansion which requires O (cid:0) 2 N (cid:1) samples to estimate a logical Pauli observable with [[ N, k ]] error correction code, our technique requires only O (cid:0) 4 k (cid:1) samples. Relative to virtual distillation, our technique can compute powers of the density matrix without additional copies of quantum states or quantum memory. We present numerical evidence using logical states encoded with up to sixty physical qubits and show fast convergence to error-free expectation values with only 10 5 samples under 1% depolarizing noise.
Few-shot Controllable Style Transfer for Low-Resource Multilingual Settings

Style transfer is the task of rewriting a sentence into a target style while approximately preserving content. While most prior literature assumes access to a large style-labelled corpus, recent work (Riley et al. 2021) has attempted “few-shot” style transfer using only 3-10 sentences at inference for style extraction. In this work we study a relevant low-resource setting: style transfer for languages where no style-labelled corpora are available. We notice that existing few-shot methods perform this task poorly, often copying inputs verbatim. We push the state-of-the-art for few-shot style transfer with a new method modeling the stylistic difference between paraphrases. When compared to prior work, our model achieves 2-3x better performance in formality transfer and code-mixing addition across seven languages. Moreover, our method is better at controlling the style transfer magnitude using an input scalar knob. We report promising qualitative results for several attribute transfer tasks (sentiment transfer, simplification, gender neutralization, text anonymization) all without retraining the model. Finally, we find model evaluation to be difficult due to the lack of datasets and metrics for many languages. To facilitate future research we crowdsource formality annotations for 4000 sentence pairs in four Indic languages, and use this data to design our automatic evaluations.
Image Translation using Texture Co-occurrence and Spatial Self-Similarity for Texture Debiasing

Classification models trained on datasets with texture bias usually perform poorly on out-of-distribution samples since biased representations are embedded into the model. Recently, various debiasing methods have attempted to disentangle biased representations, but discarding texture biased features without altering other relevant information is still a challenging task. In this paper, we propose a novel texture debiasing approach to generate additional training images using the content of a source image and the texture of a target image with a different semantic label to explicitly mitigate texture biases when training a classifier. Our model ensures texture similarity between the target and generated images via a texture co-occurrence loss while preserving the content details from the source image with a spatial self-similarity loss. Both the generated and original training images are combined to train an improved classifier that is robust against inconsistent texture bias representations. We employ five datasets with known texture biases to demonstrate the ability of our method to mitigate texture bias. In all cases, our method outperformed existing state-of-the-art methods.
The Democratic Returns of Pluralism in Autocracy: Opposition Representation and Local Development in Cambodia’s Commune Councils

The proliferation of “competitive authoritarian” regimes has rendered the participation of legal opposition parties commonplace in authoritarian elections, legislatures, and sub-national councils, yet we know little about how the opposition’s participation in these institutions affects how they function and the outcomes they produce. In this paper, I consider three mechanisms through which the opposition party’s participation in local authoritarian institutions might “matter” for public goods delivery: by increasing political competition, by conferring oversight authority to opposition politicians, and by increasing opposition representation in local political institutions. Drawing from the democratic literature on the effects of pluralism and competition on corruption, I theorize that there are reasons to expect increased opposition participation in local institutions to translate to better governance in each case. I test my hypotheses using three distinct research designs, making use of original data from over 16,000 contracts for commune infrastructure projects in Cambodia’s 1633 elected commune councils and a novel close-elections regression discontinuity design in a proportional representation setting. I find evidence that increased political competition alone fails to lead to improvements in governance; however, increases in the opposition’s share of seats in local institutions leads to significant increases in the number of bidders in competitive procurement and decreases in the price at which contracts are secured. The findings suggest that opposition parties’ participation in local political institutions can have important effects on authoritarian governance, even where the prospects for an outright opposition victory remain low. ∗Department of Political Science, Duke University. I would like to thank Eddy Malesky, Erik Wibbels, Melanie Manion, Emily Myers, Viola Rothschild, and Griffin Riddler for their invaluable feedback on several iterations of this paper. I would also like to thank Diego Romero and participants in the DevLab@Duke Fall 2020 workshop series for their comments and suggestions. “A full description of the opportunities available for participation and contestation with a country surely requires one to say something about the opportunities available within subnational units. ” – Robert Dahl, Polyarchy (1972)
COVID-19 and Regional Solutions for Mitigating the Risk of Small and Medium-sized Enterprise Finance in ASEAN Member States

One of the significant challenges small and medium-sized enterprises (SMEs) face is their difficulty in accessing finance. One way to reduce the risk of lending to SMEs is through the credit guarantee scheme (CGS). In this paper, we assess the determining factors of the optimal credit guarantee ratio for the banking industry in four Association of Southeast Asian Nations (ASEAN) countries, namely Indonesia, Singapore, the Philippines, and Malaysia, by employing statistical techniques and econometric models. The empirical findings prove that the loan default ratio (nonperforming loan/loan, or NPL/L) is the optimal credit guarantee ratio’s main determining factor. Our empirical findings confirm that in the ASEAN region, to help SMEs survive in the emergency stage of COVID-19, the credit guarantee ratio needs to be increased. Gradually, when moving to the new normal stage, the ratio needs to be lessened. Our results show that the credit guarantee ratio should vary for different countries based on the macroeconomic climate and also for each bank or, in other words, for banks with similar financial soundness. Governments should give a higher guarantee ratio to sound banks, whilst less healthy banks should receive a lower guarantee ratio. The study also provides policy recommendations for establishing a regional credit guarantee scheme in ASEAN to promote regional economic cooperation at the SME level for greater economic integration.
Relation of ASC and IL-1beta with neurocog- nitive parameters in patients with Obsessive-Compulsive Disorder Relation of ASC and IL-1beta with neurocognitive parameters in patients with Obsessive-Compulsive Disorder

Objective: It is now well accepted that inflammatory processes play a role in the etiopathogenesis of psychiatric disorders. NLRP3 inflammasome, which is formed by the combination of NLRP3, ASC and Caspase-1 proteins, and its activator NEK7, takes part in these processes. In this study, we aimed to investigate the relationship between inflammatory markers (i.e. IL-1β, IL-18, NLRP3 inflammasome protein levels) and cognitive functions in patients with obsessive compulsive disorder (OCD). Method: Forty-two patients between the ages of 18-45 who were diagnosed with OCD were included in the study. Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I), Yale-Brown Obsessive Compulsive Scale (Y-BOCS), and Hamilton Depression Scale (HAMD) were used for clinical evaluations. In order to evaluate cognitive functions, Trail Making Test (TMT), Berg Card Sorting Test and Category Fluency Test were applied. IL1β and IL-18 cytokine levels were determined by the ELISA method; measurement of the protein amounts of NLRP3, Caspase-1, ASC and NEK7 were performed by Western blotting. Results: Serum IL-1beta was negatively correlated with TMT (B-A) (rs=-.36, p= 0.019). Similarly, ASC was negatively correlated with TMT-B and TMT (B-A) (rs=-.38, p= 0.03; rs=-0.36, p = 0.04, respectively). However, no statistically significant relationship was found between other inflammatory parameters (NLRP3, Caspase-1, and IL-18) and neurocognitive tests. Discussion: Our results indicate that some aspects of neurocognitive impairment in patients with OCD might be related to neuroinflammatory processes, with implications for our understanding of the pathogenesis of OCD.
Evaluation of Sperm DNA Fragmentation using TUNEL Assay in Different Animal Species

| The studies of spermatozoa DNA fragmentation at the level of different animal species are very limited. This study examined the sperm DNA fragmentation in several animal species (bulls, chickens, and mice) by utilizing terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) assay. This study used a total of 24 different semen samples of Peranakan Ongole (PO bulls) or Ongole grade bull, chickens (KUB Chicken), and mice. Eight semen samples each were collected by three different methods. Semen samples of Peranakan Ongole (PO) bull were collected by artificial vagina method, semen samples of Kampung Unggul Balitnak (KUB) chicken were collected by abdominal massage method, and semen samples of mice were collected by epididymal collection method. Evaluation rate included the motility (%), viability (%) by eosin-nigrosine staining method, membrane integrity (%) by hypo-osmotic swelling test (HOST) method and sperm DNA fragmentation (%) by the TUNEL assay method. The results showed mice had the highest DNA fragmentation rates as compared to others species under study, while bull semen samples showed the lowest rates of DNA fragmentation. Significant differences in mice semen could be affected by the quality of chromatin. The TUNEL method might not effectively interpret the chicken semen samples better than the bulls and mice. However, sperm DNA fragmentation can be used to determine semen quality comprehensively based on the rates of DNA damage.
Q A ] 1 4 M ar 2 02 2 Classification of 2-term L ∞-algebras

We classify all 2-term L∞-algebras up to isomorphism. We show that such L∞-algebras are classified by a Lie algebra, a vector space, a representation (all up to isomorphism) and a cohomology class of the corresponding Lie algebra cohomology.
Ascidian metamorphosis

Solitary ascidians have a long legacy as model organisms for investigating developmental mechanisms because of the simplicity of their embryogenesis and their basal phylogenetic position within the chordates (Berrill, 1929; Cameron et al., 2000; Conklin, 1905; Jeffery and Swalla, 1997; Kowalevsky, 1866; Satoh, 1994). The chordate traits that unite ascidians with the cephalochordates and vertebrates include the larval notochord and dorsal nerve cord (Fig. 1A), as well as the adult pharyngeal gill slits and endostyle (Fig. 1B) (Jeffery and Swalla, 1997). Recent investigations of ascidian development have focused almost exclusively on embryogenesis (Di Gregorio et al., 2001; Hotta et al., 2000; Jeffery and Swalla, 1997; Nishida and Sawada, 2001; Satoh, 1994). However, the majority of ascidian development, including the differentiation of the adult endoderm, body wall musculature, heart, blood cells and nervous system takes place during metamorphosis (Cloney, 1978; Hinman et al., 2000, Jeffery and Swalla, 1997; Satoh, 1994). The metamorphosis of solitary ascidian tadpole larvae into sessile filter-feeding juveniles can be divided into two phases: a rapid settlement reaction followed by a prolonged period of juvenile differentiation. The initial settlement phase of ascidian metamorphosis has been thoroughly characterized by Cloney (Cloney, 1978; Cloney, 1982). After a rapid embryogenesis lasting 8-48 hours, solitary ascidian larvae hatch and swim within the plankton for a variable period of a few hours to five days. Solitary ascidian larvae have a well-developed tail including the notochord, dorsal neural tube as well as a larval CNS including an otolith and ocellus (Jeffery and Swalla, 1997) (Fig. 1A). However, they possess only rudimentary adult s ructures, including a single-layered endothelial rudiment of the gut and a pocket of trunk mesenchyme that will form the adult mesoderm (Hirano and Nishida, 1997) (Fig. 1B). Initially, hatched larvae are unable to respond to either natural or artificial settlement cues. Within a discrete, speciesspecific number of hours after hatching, larvae become competent to respond to settlement cues and commence a series of rapid morphological changes (Degnan et al., 1997). Within the first 20 minutes of settlement, the papillae facilitate initial attachment, the tail is rapidly resorbed and the trunk 4739 Development 129, 4739-4751 (2002) Printed in Great Britain © The Company of Biologists Limited 2002 DEV5984
www.ssoar.info A small-scale randomized controlled trial of the revised new forest parenting programme for preschoolers with attention deficit hyperactivity disorder

The revised new forest parenting programme (NFPP) is an 8-week psychological intervention designed to treat ADHD in preschool children by targeting, amongst other things, both underlying impairments in self-regulation and the quality of mother–child interactions. Forty-one children were randomized to either the revised NFPP or treatment as usual conditions. Outcomes were ADHD and ODD symptoms measured using questionnaires and direct observation, mothers’ mental health and the quality of mother–child interactions. Effects of the revised NFPP on ADHD symptoms were large (effect size [1) and significant and effects persisted for 9 weeks post-intervention. Effects on ODD symptoms were less marked. There were no improvements in maternal mental health or parenting behavior during mother–child interaction although there was a drop in mothers’ negative and an increase in their positive comments during a 5-min speech sample. The small-scale trial, although limited in power and generalizability, provides support for the efficacy of the revised NFPP. The findings need to be replicated in a larger more diverse sample.
Thermodynamic Re-Assessment of the Ternary System Ni-Sn-Zn using a four-sublattice model and supported by first-principles calculations

Abstract In this paper CALPHAD (CALculation of PHAse Diagram) method was used for thermodynamic reevaluation of the ternary Ni-Sn-Zn system. The fcc_A1/Ni3Sn2-L12 disordered/ordered transition was described using a four-sublattice model. In CALPHAD modeling therefore, the enthalpies of formation of the ternary compounds (τ1, τ2, and τ4) and end-members of the phases at 0 K are essential input thermodynamic parameter in the Ni-Sn-Zn ternary system. Which is computed via first-principles calculations? In the Ni-Sn-Zn ternary system, it was clarified that the ordered Ni-Sn-Zn phase is formed from the liquid phase with the addition of Zn. An optimal set of thermodynamic parameters for the Ni-SnZn system was obtained by taking into consideration of the experimental data from the literature and theoretic values from the present first-principles calculations. Assessments between the calculated and measured phase diagrams signposted, that nearly all the consistent experimental information was agreeably accounted for by the present modeling.