Miracle-dz/UniFAR-FTUs huggingface dataset:
On general position sets in Cartesian grids

The general position number ${\rm gp}(G)$ of a connected graph $G$ is the cardinality of a largest set $S$ of vertices such that no three pairwise distinct vertices from $S$ lie on a common geodesic; such sets are refereed to as gp-sets of $G$. A formula for the number of gp-sets in $P_r \,\square\, P_s$, $r,s\ge 2$, is determined. The general position number of cylinders $P_r \,\square\, C_s$ is deduced, while ${\rm gp}(C_r \,\square\, C_s)$ is bounded from the below by $6$, whenever $r\ge s \neq 4$ and $r\ge 6$. It is proved that ${\rm gp}(P_{\infty} \,\square\, P_{\infty} \,\square\, P_{\infty}) \ge 14$. A probabilistic lower bound on the general position number of Hamming graphs and of Cartesian graph powers is also achieved.
Spam: the plague of junk E-mail

In a sketch on the British comedy show Monty Python's Flying Circus, a group of Vikings in a cafe sing loudly about Spam (the luncheon meat), drowning out the conversation of other diners. On the Internet, the word spam is used to mean intrusive messages, most of them commercial, that can overwhelm discussion groups and E-mail in-boxes. If you've ever posted a message on Usenet, put your E-mail address on a Web page, or even subscribed to an E-mail discussion list that wasn't configured to conceal its subscribers' addresses, chances are good that you've received unsolicited bulk E-mail, the type of spam that's generating the most controversy nowadays. Such junk E-mail is used by businesses that don't care about their reputations, so it advertises mainly questionable medical products, get-rich-quick schemes, pornography, and the like, as well as spamming software and address lists. Once you've been put on a spammer's list, it's almost impossible to get off, and the spam is likely to multiply.
Solving Quantum Random Walker Using Steepest Entropy Ascent Ansatz: A Pathway Towards Typicality

We apply the formalism of Steepest Entropy Ascent (SEA) ansatz on the robust model of Quantum Random Walk (QRW). By doing so, we arrive at the resolution of the origin of typicality (or Eigenstate Thermalization Hypothesis (ETH)) and Many Body Localization (MBL) dichotomy, a clear understanding of which still hides in ambiguity. We shed some light on this through our novel approach using detailed analytical and numerical calculations. The results are indicative of bridging the lacuna between the two contesting philosophies of SEA and ETH/MBL.
A statistically significant lack of debris discs in medium separation binary systems

We compile a sample of 341 binary and multiple star systems with the aim of searching for and characterizing Kuiper belt-like debris discs. The sample is assembled by combining several smaller samples studied in previously published work with targets from two unpublished Herschel surveys. We find that 38 systems show excess emission at 70 or 100 $\mu$m suggestive of a debris disc. While nine of the discs appear to be unstable to perturbations from their host binary based on a simple analysis of their inferred radii, we argue that the evidence for genuine instability is not strong, primarily because of uncertainty in the true disc radii, uncertainty in the boundaries of the unstable regions, and orbital projection effects. The binary separation distributions of the disc-bearing and disc-free systems are different at a confidence level of $99.4{{\ \rm per\ cent}}$, indicating that binary separation strongly influences the presence of detectable levels of debris. No discs are detected for separations between ∼25 and 135 au; this is likely a result of binaries whose separations are comparable with typical disc radii clearing out their primordial circumstellar or circumbinary material via dynamical perturbations. The disc detection rate is $19^{+5}_{-3}{{\ \rm per\ cent}}$ for binaries wider than 135 au, similar to the published results for single stars. Only $8^{+2}_{-1}{{\ \rm per\ cent}}$ of systems with separations below 25 au host a detectable disc, which may suggest that planetesimal formation is inhibited in binaries closer than a few tens of au, similar to the conclusions of studies of known planet-hosting binaries.
Joint Learning of Multiple Image Restoration Tasks

Convolutional neural networks have recently been successfully applied to the problems of restoring clean images from their degraded versions. Most studies have designed and trained a dedicated network for each of many image restoration tasks, such as motion blur removal, rain-streak removal, haze removal, etc. In this paper, we show that a single network having a single input and multiple output branches can solve multiple image restoration tasks. This is made possible by improving the attention mechanism and an internal structure of the basic blocks used in the dual residual networks, which was recently proposed and shown to work well for a number of image restoration tasks by Liu et al. Experimental results show that the proposed approach achieves a new state-of-the-art performance on haze removal (both in PSNR/SSIM) and JPEG artifact removal (in SSIM). To the authors' knowledge, this is the first report of successful multi-task learning on diverse image restoration tasks.
Hillview: A trillion-cell spreadsheet for big data

Hillview is a distributed spreadsheet for browsing very large datasets that cannot be handled by a single machine. As a spread-sheet, Hillview provides a high degree of interactivity that permits data analysts to explore information quickly along many dimensions while switching visualizations on a whim. To provide the required responsiveness, Hillview introduces visualization sketches, or vizketches , as a simple idea to produce compact data visualizations. Vizketches combine algorithmic techniques for data summarization with computer graphics principles for efficient rendering. While simple, vizketches are effective at scaling the spreadsheet by parallelizing computation, reducing communication, providing progressive visualizations, and offering precise accuracy guarantees. Using Hillview running on eight servers, we can navigate and visualize datasets of tens of billions of rows and trillions of cells, much beyond the published capabilities of competing systems.
Near-optimal Bayesian Solution For Unknown Discrete Markov Decision Process.

We tackle the problem of acting in an unknown finite and discrete Markov Decision Process (MDP) for which the expected shortest path from any state to any other state is bounded by a finite number $D$. An MDP consists of $S$ states and $A$ possible actions per state. Upon choosing an action $a_t$ at state $s_t$, one receives a real value reward $r_t$, then one transits to a next state $s_{t+1}$. The reward $r_t$ is generated from a fixed reward distribution depending only on $(s_t, a_t)$ and similarly, the next state $s_{t+1}$ is generated from a fixed transition distribution depending only on $(s_t, a_t)$. The objective is to maximize the accumulated rewards after $T$ interactions. In this paper, we consider the case where the reward distributions, the transitions, $T$ and $D$ are all unknown. We derive the first polynomial time Bayesian algorithm, BUCRL{} that achieves up to logarithm factors, a regret (i.e the difference between the accumulated rewards of the optimal policy and our algorithm) of the optimal order $\tilde{\mathcal{O}}(\sqrt{DSAT})$. Importantly, our result holds with high probability for the worst-case (frequentist) regret and not the weaker notion of Bayesian regret. We perform experiments in a variety of environments that demonstrate the superiority of our algorithm over previous techniques. Our work also illustrates several results that will be of independent interest. In particular, we derive a sharper upper bound for the KL-divergence of Bernoulli random variables. We also derive sharper upper and lower bounds for Beta and Binomial quantiles. All the bound are very simple and only use elementary functions.
SynthCity: A large scale synthetic point cloud

With deep learning becoming a more prominent approach for automatic classification of three-dimensional point cloud data, a key bottleneck is the amount of high quality training data, especially when compared to that available for two-dimensional images. One potential solution is the use of synthetic data for pre-training networks, however the ability for models to generalise from synthetic data to real world data has been poorly studied for point clouds. Despite this, a huge wealth of 3D virtual environments exist which, if proved effective can be exploited. We therefore argue that research in this domain would be of significant use. In this paper we present SynthCity an open dataset to help aid research. SynthCity is a 367.9M point synthetic full colour Mobile Laser Scanning point cloud. Every point is assigned a label from one of nine categories. We generate our point cloud in a typical Urban/Suburban environment using the Blensor plugin for Blender.
A Knowledge-based Filtering Story Recommender System for Theme Lovers with an Application to the Star Trek Television Franchise

Collaborative filtering based recommender systems have proven to be extremely successful in settings where user preference data on items is abundant. However, collaborative filtering algorithms are hindered by their weakness against the item cold-start problem and general lack of interpretability. Ontology-based recommender systems exploit hierarchical organizations of users and items to enhance browsing, recommendation, and profile construction. While ontology-based approaches address the shortcomings of their collaborative filtering counterparts, ontological organizations of items can be difficult to obtain for items that mostly belong to the same category (e.g., television series episodes). In this paper, we present an ontology-based recommender system that integrates the knowledge represented in a large ontology of literary themes to produce fiction content recommendations. The main novelty of this work is an ontology-based method for computing similarities between items and its integration with the classical Item-KNN (K-nearest neighbors) algorithm. As a study case, we evaluated the proposed method against other approaches by performing the classical rating prediction task on a collection of Star Trek television series episodes in an item cold-start scenario. This transverse evaluation provides insights into the utility of different information resources and methods for the initial stages of recommender system development. We found our proposed method to be a convenient alternative to collaborative filtering approaches for collections of mostly similar items, particularly when other content-based approaches are not applicable or otherwise unavailable. Aside from the new methods, this paper contributes a testbed for future research and an online framework to collaboratively extend the ontology of literary themes to cover other narrative content.
Pediatric Respirology and Critical Care Medicine

ing and indexing information The journal is registered with the following abstracting partners: Baidu Scholar, CNKI (China National Knowledge Infrastructure), EBSCO Publishing’s Electronic Databases, Exlibris – Primo Central, Google Scholar, Hinari, Infotrieve, National Science Library, Netherlands ISSN center, ProQuest, TdNet, Wanfang Data. Information for authors The journal does not charge for submission, processing or publication of manuscripts and even for color reproduction of photographs. Please check http://www.prccm. org/ contributors.asp for details. All manuscripts must be submitted online at http://www.journalonweb. com/prcm. Advertising policies The journal accepts display and classified advertising. Frequency discounts and special positions are available. Inquiries about advertising should be sent to Medknow Publications, advertise@medknow.com. The journal reserves the right to reject any advertisement considered unsuitable according to the set policies of the journal. The appearance of advertising or product information in the various sections in the journal does not constitute an endorsement or approval by the journal and/or its publisher of the quality or value of the said product or of claims made for it by its manufacturer.
The Last Stages of Second Language Acquisition: Linguistic Evidence from Academic Writing by Advanced Non-Native English Speakers

Second Language Acquisition (SLA) researchers have yet to map the developmental stages language learners go through as they approach the target language. In studies of ESL writing, the term “advanced learner” has been applied indiscriminately to learners ranging from freshman ESL composition to graduate students (Bardovi-Harlig and Bofman, 1989; Chaudron and Parker, 1990; Connor and Mayberry, 1996; Hinkel, 1997, 2003). There is a need to examine the advanced stages of SLA in order to refine SLA theories and pedagogical approaches. A corpus of texts written by eleven graduate students in applied linguistics who are non-native-English speakers from several linguistic backgrounds was analyzed to determine the texts’ lexical, morphological, and syntactic fluency, accuracy, and complexity. A sub-corpus of papers by seven native-English-speaking peers was used for comparison. The texts were sit-down and take-home examinations written in a doctoral program at the end of the first semester and three years later. Surveys and interviews were conducted to supplement the corpus with ethnographic data. This dissertation defines data-based criteria that distinguish four quantitatively and qualitatively distinct developmental stages: the advanced, highly advanced, nearnative, and native-like stages. Advanced learners make more frequent and varied errors (with articles, prepositions, plural and possessive markers, agreement and anaphors), which can be explained by linguistic transfer. Native-like writers make few errors that can be explained by overgeneralization of conventions from informal English and working memory limitations (just like native speakers’ errors). Throughout the four
Frequency calibration of the system clock of passive wireless microsystems

This thesis presents a theoretical and simulated study of frequency calibration of the system clock of passive wireless microsystems. The proposed frequency calibration technique achieves ultra-low power, high fre- quency accuracy, and fast calibration of the frequency of a local oscillator in a passive wireless microsystem using a frequency-locked loop (FLL). A new integrating frequency dif- ference detector (iFDD) that senses the frequency difference between the local oscillator and a reference clock is also proposed. The iFDD is implemented using a switched-capacitor network with two integrating paths. The FLL is composed of a logic-control block for gen- eration of clock signals, the iFDD, and a relaxation voltage-controlled oscillator. A detailed analysis of the characteristics of the iFDD in the time and frequency domains is presented. The loop dynamics of the FLL is also investigated. The proposed FLL is implemented in IBM 0.13-µm, 1.2 V CMOS technology and is validated through simulations using Spectre APS.
CONSTRAINTS ON MARTIAN CLIMATE HISTORY FROM ICY IMPACT CRATERS

Subsurface ice is one of the major H 2O reservoirs on Mars [1] and plays a significant role in the long-term water cycle. Its overall geographic distribution and burial depth, as measured with neutron spectroscopy [2, 3, 4, 5], is consistent with the assumption that the vapor concentration at the ice and in the atmosphere have equilibrated [6, 7, 8]. On a zonal average, subsurface ice is expected poleward of about ±55◦ latitude on both hemispheres. However, in a surprise discovery, ice was found excavated by very recent impacts at latitudes 43◦–56◦N [9, 10]. These icy impact craters are further equatorward than the equilibrium geographic boundary of the subsurface ice, unless an atmospheric humidity higher than today’s is assumed. Here, we explore what constraints the presence of almost pure ice as far equatorward as 43◦N places on the climate history, based on simulations of the retreat of subsurface ice. Progress in subsurface ice modeling [11, 12] enables us to not only determine the equilibrium distribution but follow the evolution of the ice in response to temperature and climate change caused by orbital variations (Milankovitch cycles).
A Multi-Dimensional Theoretical Framework to Support the Learning Needs of Medical Specialists

The Royal Australasian College of Physicians (RACP) is the professional medical College of over 17,000 physicians and 8,000 trainee physicians (medical specialists), in Australia and New Zealand. Due to the complex and applied nature of the medical profession, continuous learning is an absolute priority which involves specific challenges, such as the constantly evolving state of knowledge and the extensive diversity of the scope of practice of different specialties. The College operates in a fastpaced environment, characterised by profound change, driven by rapid advances in medical knowledge, shifts in patterns of disease, new technologies, and changing regulatory frameworks. Medical specialists mainly learn on the job in teaching hospital settings. This learning practice is situated in a specific context (hospital hierarchy, high level of responsibility while still in training, long working hours, etc.) that affects learning processes. To provide effective learning opportunities in such a complex environment, the College has developed a research-based conceptual multi-dimensional framework comprising four components: social learning, learning by doing, experiential learning and reflective practice. The framework has been applied to the design and development of the online learning resources the College produces every year. Its effectiveness is being regularly evaluated using pre and post course evaluation that indicates excellent level of users’ satisfaction.
On Keyframe Positioning for Pose Graphs Applied to Visual SLAM

In this work, a new method is introduced for localization and keyframe identification to solve a Simultaneous Localization and Mapping (SLAM) problem. The proposed approach is based on a dense spherical acquisition system that synthesizes spherical intensity and depth images at arbitrary locations. The images are related by a graph of 6 degrees-of-freedom (DOF) poses which are estimated through spherical registration. A direct image-based method is provided to estimate pose by using both depth and color information simultaneously. A new keyframe identification method is proposed to build the map of the environment by using the covariance matrix between raletive 6 DOF poses, which is basically the uncertainty of the estimated pose. This new approach is shown to be more robust than an error-based keyframe identification method. Navigation using the maps built from our method also gives less trajectory error than using maps from other methods.
Studying the optimal height of the EFSM equivalent for testing telecommunication protocols

The paper presents experimental results on the optimal height of the EFSM equivalent for deriving high quality tests for telecommunication protocols. The EFSM model is a widely used finite state model, and its l-equivalent is an FSM which behavior is equivalent to the initial EFSM for each input sequence of the length l or less. The l-equivalent is known to be more suitable for test derivation than the initial EFSM and thus, it is often used as the specification EFSM for this purpose. In this paper, test derivation the l-equivalent has been derived for the following protocols: POP 3, SMTP, TIME, DCCP, TCP. EFSM models have been extracted from the corresponding RFC specifications, and mutation testing techniques have been utilized in order to estimate the fault coverage of the test suites which correspond to a transition tour of a corresponding l-equivalent. Experimental results clearly show that even when the height l of the l-equivalent is low, and moreover, equals two, many functional faults can be detected in the protocol implementation. Keywords—EFSM, l-equivalent, testing, telecommunication
Cahier 06-2003 FINITE-SAMPLE DIAGNOSTICS FOR MULTIVARIATE REGRESSIONS WITH APPLICATIONS TO LINEAR ASSET PRICING MODELS

In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR) with applications to asset pricing models. We focus on departures from the assumption of i.i. d. errors assumption, at univariate and multivariate levels, with Gaussian and non-Gaussian (including Student t) errors. The univariate tests studied extend existing exact procedures by allowing for unspecified parameters in the error distributions (e.g., the degrees of freedom in the case of the Student t distribution). The multivariate tests are based on properly standardized multivariate residuals to ensure invariance to MLR coefficients and error covariances. We consider tests for serial correlation, tests for multivariate GARCH and sign-type tests against general dependencies and asymmetries. The procedures proposed provide exact versions of those applied in Shanken (1990) which consist in combining univariate specification tests. Specifically, we combine tests across equations using the MC test procedure to avoid Bonferroni-type bounds. Since non-Gaussian based tests are not pivotal, we apply the “maximized MC” (MMC) test method [Dufour (2002)], where the MC p-value for the tested hypothesis (which depends on nuisance parameters) is maximized (with respect to these nuisance parameters) to control the test’s significance level. The tests proposed are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995. Our empirical results reveal the following. Whereas univariate exact tests indicate significant serial correlation, asymmetries and GARCH in some equations, such effects are much less prevalent once error cross-equation covariances are accounted for. In addition, significant departures from the i.i. d. hypothesis are less evident once we allow for non-Gaussian
A numerical alignment error estimation for the SPring-8-II

Alignment errors for entire accelerator components of the SPring-8-II configuration are numerically estimated and confirmed to satisfy required allowable errors. Necessity of realignment are also discussed tracking both estimated observation coordinates and relative errors of neighboring two common girders based on ground deformation trends of SPring-8. Furthermore, a verification of the ATLlaw application for variations of the current storage ring level is briefly introduced and discussed.
Can Participants Estimate Program Impacts ? Evidence from a Labor Market Intervention

We test whether participants in two labor market interventions hold accurate beliefs about program impacts, exploiting a randomized evaluation to compare participants’ beliefs to intent-to-treat estimates. We provide a framework for comparing methods of belief elicitation and identifying potential biases. We find the program participants do a poor job of estimating their own counterfactual (probabilistic) outcomes. However, we extend the existing set of best practices by demonstrating that participants are quite good at estimating average treatment impacts on the population once behavioral biases are taken into account.