Miracle-dz/UniFAR-FTUs huggingface dataset:
Implicit Generative Modeling for Efficient Exploration

Efficient exploration remains a challenging problem in reinforcement learning, especially for those tasks where rewards from environments are sparse. A commonly used approach for exploring such environments is to introduce some "intrinsic" reward. In this work, we focus on model uncertainty estimation as an intrinsic reward for efficient exploration. In particular, we introduce an implicit generative modeling approach to estimate a Bayesian uncertainty of the agent's belief of the environment dynamics. Each random draw from our generative model is a neural network that instantiates the dynamic function, hence multiple draws would approximate the posterior, and the variance in the future prediction based on this posterior is used as an intrinsic reward for exploration. We design a training algorithm for our generative model based on the amortized Stein Variational Gradient Descent. In experiments, we compare our implementation with state-of-the-art intrinsic reward-based exploration approaches, including two recent approaches based on an ensemble of dynamic models. In challenging exploration tasks, our implicit generative model consistently outperforms competing approaches regarding data efficiency in exploration.
Regular Turán numbers and some Gan–Loh–Sudakov‐type problems

Motivated by a Gan–Loh–Sudakov‐type problem, we introduce the regular Turán numbers, a natural variation on the classical Turán numbers where we restrict ourselves to the class of regular graphs. Among other results, we prove a striking supersaturation version of Mantel's theorem in the case of a regular host graph of odd order. We also characterize the graphs for which the regular Turán numbers behave classically or otherwise.
Optimization of power broadening in optically detected magnetic resonance of defect spins in silicon carbide

Defect spins in silicon carbide have become promising platforms with respect to quantum information processing and quantum sensing. Indeed, the optically detected magnetic resonance (ODMR) of defect spins is the cornerstone of the applications. In this work, we systematically investigate the contrast and linewidth of laser-and microwave power-dependent ODMR with respect to ensemble-divacancy spins in silicon carbide at room temperature. The results suggest that magnetic field sensing sensitivity can be improved by a factor of 10 for the optimized laser and microwave power range. The experiment will be useful for the applications of silicon carbide defects in quantum information processing and ODMR-dependent quantum sensing.
Rethinking deep active learning: Using unlabeled data at model training

Active learning typically focuses on training a model on few labeled examples alone, while unlabeled ones are only used for acquisition. In this work we depart from this setting by using both labeled and unlabeled data during model training across active learning cycles. We do so by using unsupervised feature learning at the beginning of the active learning pipeline and semi-supervised learning at every active learning cycle, on all available data. The former has not been investigated before in active learning, while the study of latter in the context of deep learning is scarce and recent findings are not conclusive with respect to its benefit. Our idea is orthogonal to acquisition strategies by using more data, much like ensemble methods use more models. By systematically evaluating on a number of popular acquisition strategies and datasets, we find that the use of unlabeled data during model training brings a spectacular accuracy improvement in image classification, compared to the differences between acquisition strategies. We thus explore smaller label budgets, even one label per class.
Binary population synthesis models for core-collapse gamma-ray burst progenitors

Long-duration gamma-ray bursts (GRBs) are understood to be the final fate for a subset of massive, stripped envelope, rapidly rotating stars. Beyond this, our knowledge of the progenitor systems is limited. Using the Binary Population and Spectral Synthesis (bpass) stellar evolution models, we investigate the possibility that some massive stars in binaries can maintain the angular momentum required for jet production, while still loosing their outer envelope through winds or binary interactions. We find that a total hydrogen mass of MH < 5 × 10−4 M⊙ and a helium ejecta mass fraction of FHe < 0.20 provide the best thresholds for the supernova type II/Ibc and Ib/Ic divisions, respectively. Tidal interactions in binaries are accounted for by applying a tidal algorithm to post-process the stellar evolution models output by bpass. We show that the observed volumetric GRB rate evolution can be recreated using two distinct pathways and plausible distributions for burst parameters. In the first pathway, stars are spun up by mass accretion into a quasi-homogeneous state. In the second, tides maintain rotation where otherwise the star would spin-down. Both lead to type Ic supernova progenitors, and a metallicity distribution consistent with the GRB host galaxy population. The inferred core angular momentum threshold for jet production is consistent with theoretical requirements for collapsars, given the assumptions made in our model. We can therefore reproduce several aspects of core-collapse supernova/GRB observation and theory simultaneously. We discuss the predicted observable properties of GRB progenitors and their surviving companions.
Principal Stratification for Advertising Experiments

Advertising experiments often suffer from noisy responses making precise estimation of the average treatment effect (ATE) and evaluating ROI difficult. We develop a principal stratification model that improves the precision of the ATE by dividing the customers into three strata -- those who buy regardless of ad exposure, those who buy only if exposed to ads and those who do not buy regardless. The method decreases the variance of the ATE by separating out the typically large share of customers who never buy and therefore have individual treatment effects that are exactly zero. Applying the procedure to 5 catalog mailing experiments with sample sizes around 140,000 shows a reduction of 36-57% in the variance of the estimate. When we include pre-randomization covariates that predict stratum membership, we find that estimates of customers' past response to similar advertising are a good predictor of stratum membership, even if such estimates are biased because past advertising was targeted. Customers who have not purchased recently are also more likely to be in the "never purchase" stratum. We provide simple summary statistics that firms can compute from their own experiment data to determine if the procedure is expected to be beneficial before applying it.
The Acceleration and Confinement of Energetic Electrons by a Termination Shock in a Magnetic Trap: An Explanation for Nonthermal Loop-top Sources during Solar Flares

Nonthermal loop-top sources in solar flares are the most prominent observational signatures that suggest energy release and particle acceleration in the solar corona. Although several scenarios for particle acceleration have been proposed, the origin of the loop-top sources remains unclear. Here we present a model that combines a large-scale magnetohydrodynamic simulation of a two-ribbon flare with a particle acceleration and transport model for investigating electron acceleration by a fast-mode termination shock (TS) at the loop top. Our model provides spatially resolved electron distribution that evolves in response to the dynamic flare geometry. We find a concave-downward magnetic structure located below the flare TS, induced by the fast reconnection downflows. It acts as a magnetic trap to confine the electrons at the loop top for an extended period of time. The electrons are energized significantly as they cross the shock front, and eventually build up a power-law energy spectrum extending to hundreds of kiloelectron volts. We suggest that this particle acceleration and transport scenario driven by a flare TS is a viable interpretation for the observed nonthermal loop-top sources.
Implicit Regularization of Normalization Methods

Normalization methods such as batch normalization are commonly used in overparametrized models like neural networks. Here, we study the weight normalization (WN) method (Salimans & Kingma, 2016) and a variant called reparametrized projected gradient descent (rPGD) for overparametrized least squares regression and some more general loss functions. WN and rPGD reparametrize the weights with a scale $g$ and a unit vector such that the objective function becomes \emph{non-convex}. We show that this non-convex formulation has beneficial regularization effects compared to gradient descent on the original objective. We show that these methods adaptively regularize the weights and \emph{converge with exponential rate} to the minimum $\ell_2$ norm solution (or close to it) even for initializations \emph{far from zero}. This is different from the behavior of gradient descent, which only converges to the min norm solution when started at zero, and is more sensitive to initialization. Some of our proof techniques are different from many related works; for instance we find explicit invariants along the gradient flow paths. We verify our results experimentally and suggest that there may be a similar phenomenon for nonlinear problems such as matrix sensing.
Brain reaction times: Linking individual and collective behaviour through Physics modelling

An individual's reaction time data to visual stimuli have usually been represented in Experimental Psychology by means of an ex-Gaussian function (EGF). In most previous works, researchers have mainly aimed at finding a meaning for the parameters of the EGF function in relation to psychological phenomena. We will focus on interpreting the reaction times (RTs) of a group of individuals rather than a single person's RT, which is relevant for the different contexts of social sciences. In doing so, the same model as for the Ideal Gases (IG) (an inanimate system of non-interacting particles) emerges from the experimental RT data. Both systems are characterised by a collective parameter which is k_BT in the case of the system of particles and what we have called life span parameter for the system of brains. Similarly, we came across a Maxwell-Boltzmann-type distribution for the system of brains which provides a natural and more complete characterisation of the collective time response than has ever been provided before. Thus, we are able to know about the behaviour of a single individual in relation to the coetaneous group to which they belong and through the application of a physical law. This leads to a new entropy-based methodology for the classification of the individuals forming the system which emerges from the physical law governing the system of brains. To the best of our knowledge, this is the first work in the literature reporting on the emergence of a physical theory (IG) from human RT experimental data.
Inter-layer Collision Networks

Deeper neural networks are hard to train. Inspired by the elastic collision model in physics, we present a universal structure that could be integrated into the existing network structures to speed up the training process and eventually increase its generalization ability. We apply our structure to the Convolutional Neural Networks(CNNs) to form a new structure, which we term the "Inter-layer Collision" (IC) structure. The IC structure provides the deeper layer a better representation of the input features. We evaluate the IC structure on CIFAR10 and Imagenet by integrating it into the existing state-of-the-art CNNs. Our experiment shows that the proposed IC structure can effectively increase the accuracy and convergence speed.
A topological dynamical system with two different positive sofic entropies

A sofic approximation to a countable group is a sequence of partial actions on finite sets that asymptotically approximates the action of the group on itself by left-translations. A group is sofic if it admits a sofic approximation. Sofic entropy theory is a generalization of classical entropy theory in dynamics to actions by sofic groups. However, the sofic entropy of an action may depend on a choice of sofic approximation. All previously known examples showing this dependence rely on degenerate behavior. This paper exhibits an explicit example of a mixing subshift of finite type with two different positive sofic entropies. The example is inspired by statistical physics literature on 2-colorings of random hyper-graphs.
Constrained R-Cnn: A General Image Manipulation Detection Model

Recently, deep learning-based models have exhibited remarkable performance for image manipulation detection. However, most of them suffer from poor universality of handcrafted or predetermined features. Meanwhile, they only focus on manipulation localization and overlook manipulation classification. To address these issues, we propose a coarse-to-fine architecture named Constrained R-CNN for complete and accurate image forensics. First, the learnable manipulation feature extractor learns a unified feature representation directly from data. Second, the attention region proposal network effectively discriminates manipulated regions for the next manipulation classification and coarse localization. Then, the skip structure fuses low-level and high-level information to refine the global manipulation features. Finally, the coarse localization information guides the model to further learn the finer local features and segment out the tampered region. Experimental results show that our model achieves state-of-the-art performance. Especially, the F1 score is increased by 28.4%, 73.2%, 13.3% on the NIST16, COVERAGE, and Columbia dataset.
Sets in $\mathbb{R}^d$ determining $k$ taxicab distances

We address an analog of a problem introduced by Erd\H{o}s and Fishburn, itself an inverse formulation of the famous Erd\H{o}s distance problem, in which the usual Euclidean distance is replaced with the metric induced by the $\ell^1$-norm, commonly referred to as the $\textit{taxicab metric}$. Specifically, we investigate the following question: given $d,k\in \mathbb{N}$, what is the maximum size of a subset of $\mathbb{R}^d$ that determines at most $k$ distinct taxicab distances, and can all such optimal arrangements be classified? We completely resolve the question in dimension $d=2$, as well as the $k=1$ case in dimension $d=3$, and we also provide a full resolution in the general case under an additional hypothesis.
Base-neutralizing capacity of Finnish mineral soils

The base-neutralizing capacity, BMC, (OHas meq kg -1 needed to raise soil pH to 7), was determined graphically from curves obtained in KOH titration (at a constant ionic strength of I = 0.1). In 84 soil samples, BMC, amounted to 0—316 meq kg-1 , being highest in the heavy clay soils and lowest in the non-clay soils. In different textural groups, BMC, seemed most markedly to be dependent on the initial soil pH, followed by organic C or oxalate soluble Al, in the coarser clays also on clay content. The results evidence that in determination of lime requirement, attention should be paid to the capacity of soil acidity. In routine soil testing, detailed lime recommendations for various soil types are needed. Index words: base-neutralizing capacity, soil acidity, titration, pH-buffering, lime requirement, soil testing
Determinants of contraceptive use in Orissa: An analysis from National Family Health Survey III.

This paper attempts to study the differentials of contraceptive use by women’s background characteristics and determinants by using data from National Family Health Survey III conducted during 2005-06 for Orissa. Also data have been drawn from Family Welfare Year Book 2001. Both bi-variate and multivariate analysis have been used in the present study. The various predictor variables used in the analysis were caste religion women’s educational level place of residence wealth index of the household work status of women number of living sons age at marriage marital duration whether experienced infant death and exposure to mass media. The findings revealed that only one-third of the women with one child use contraception in Orissa. Such proportion goes to 60 per cent 73 per cent and 60 per cent for women with two three and more than three living children respectively. The analysis indicate that spacing is not very common but most of the contraceptive’s use are for limiting family size. Educational levels of women sex preference marital duration infant death and exposure to mass media have a significant effect on the use of contraception. Therefore these aspects may be given due attention while framing family planning programme and efforts should be made to make people aware of the benefit of small family norm.
Effect of supplementing bypass fat on the performance of buffalo calves

The experiment was conducted to assess the effect of bypass fat supplementation on growth and nutrient utilization in calves. Female Murrah buffalo calves (15; 6–8 m old of 109.7±7.6 kg BW) divided into three similar groups were fed wheat straw, chaffed green oat fodder and concentrate mixture in 15:35:50 ratio (on DM basis) control, supplemented with commercial bypass fat @ 2.5(T1) or 4 (T2) per cent of DMI for 90 days. ADG was higher (P<0.05) in T1 by 23.90 per cent over that of control. The digestibility of EE were higher (P<0.05) by 9.44 and 11.89%, in T1 and T2 groups over that of control while no effect was recorded on the digestibility of other nutrients. Feed conversion ratio was improved (P<0.05) by 20.70 per cent in T1 group over that of control. Blood cholesterol, triglycerides and NEFA concentrations were also increased (P<0.05) on bypass fat supplementation. It was concluded that supplementation of bypass fat at 2.5% of DMI increased the average daily gain and feed conversion ratio in female buffalo calves. There was no adverse effect of feeding bypass fat on nutrient utilization.
Medical Utilization and Cost in Patients with Overlap Syndrome of Chronic Obstructive Pulmonary Disease and Asthma

Background: Little information is available regarding medical utilization and cost in patients with overlap syndrome of COPD and asthma. Purpose: To analyze medical utilization and cost in patients with overlap syndrome and to compare them to COPD patients without asthma. Methods: Using the 2009 Korean National Health Insurance (NHI) database, COPD patients were identified. Medical utilization and costs were also analyzed. Results: Of a total of 185,147 patients identified with COPD, 101,004 patients were classified with overlap syndrome of COPD and asthma and 84,143 patients with COPD without asthma. In 2009, the percentages of ER visits, admissions, and ICU admissions were 14.6%, 30.5%, and 0.5%, respectively, in the patients with overlap syndrome group and 5.0%, 14.1%, and 0.2%, respectively, in the COPD patients without asthma group (P＜0.05 for all comparisons). The cost of medical utilization was 790±71 US dollars per person and 3,373±4,628 dollars per person for outpatient and inpatient services, respectively, in the patients with overlap syndrome and 413±512 and 3,010±5,013, respectively, in the COPD patients without asthma (P＜0.05 for all comparisons). Multiple linear regression showed that age, sex, overlap syndrome, and hospitalization in the last year were significant factors affecting medical utilization and cost. Conclusions: In patients with overlap syndrome, both medical utilization and cost were higher than in COPD patients without.
Strategies in alcohol, tobacco and drug education.

This report is an attempt to give a review of some preventive health education strategies that have been used in other countries in the areas of smoking, alcohol and , drug education. It does not purport to be exhaustive, and in fact, the difficulties of getting material from abroad during the postal strike may have led to the omission of some useful material. It is hoped, however, that it will be of help as an initial reference work for those who will be doing further work in any of these areas.
Atmospheric Measurement Techniques Sky cover from MFRSR observations

The diffuse all-sky surface irradiances measured at two nearby wavelengths in the visible spectral range and their modeled clear-sky counterparts are the main components of a new method for estimating the fractional sky cover of different cloud types, including cumuli. The performance of this method is illustrated using 1-min resolution data from a ground-based Multi-Filter Rotating Shadowband Radiometer (MFRSR). The MFRSR data are collected at the US Department of Energy Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site during the summer of 2007 and represent 13 days with cumuli. Good agreement is obtained between estimated values of the fractional sky cover and those provided by a well-established independent method based on broadband observations.
1 Rules for the governance of coastal and marine ecosystem services : An evaluative 1 framework based on the IAD framework 2

There is an increasing need for a comprehensive institutional understanding pertaining to 4 ecosystem services (ESs) in coastal and marine fields. This paper develops a systematic 5 framework to inform coastal and marine governance about the integration of ES concepts. 6 First, as a theoretical basis, we analyze the generic rules that are part of the Institutional 7 Analysis and Development (IAD) framework. Second, by an extensive literature review, we 8 formulate a set of ES-specific rules and develop an evaluative framework for coastal and 9 marine governance. Third, we examine this evaluative framework in a specific action situation, 10 namely coastal strategic planning concerning Qingdao, China. Results from the literature 11 review and the case study reveal that when designing ES-specific rules for coastal and marine 12 governance, there are several socio-spatial and economic aspects that should be taken into 13 account: (1) conceive of stakeholders as ES users, (2) capture the effect of ecological scaling, 14 (3) understand ES interactions and clarify indirect impacts and causalities, (4) account for ES 15 values, and (5) draw on economic choices for use rights to deal with ES issues. 16