Miracle-dz/UniFAR-FTUs huggingface dataset:
Elsevier instructions for the preparation of a 2-column format camera-ready paper in L A TEX

We present new results for the τ hadronic spectral functions analysis using data accumulated by the ALEPH detector at LEP during the years 1991–94. In addition to the vector spectral function, the axial-vector spectral function and, separately, the τ − → 2 π − π + ν τ as well as the τ − → π − 2 π 0 ν τ spectral functions are determined from their respective unfolded, i.e. , physical invariant mass spectra. The spectral functions are applied to QCD chiral sum rules in order to extract information about saturation at the τ mass scale. Using the the semi-leptonic τ decay rate for vector and axial-vector currents in addition to spectral moments, we obtain precise measurements of the strong coupling constant α s ( M τ ) and the contributing non-perturbative power terms. The evolution to the Z mass yields α s ( M Z ) =0.1219 ± 0.0019.
Modeling Pixel Level Error in Fine-Resolution Digital Elevation Models: A Regression-Based Approach

The morphological method is a powerful technique for identifying distributed changes in the earth’s surface due to physical processes. This technique is typically conducted in a geographic information system by differencing digital elevation models (DEMs) derived from repeat topographic surveys. To infer meaningful interpretations from the resulting DEM of difference (DoD), real topographic change must be distinguished from spurious change attributable to error in the component DEMs. To aid in this process, this thesis presents and evaluates a new approach for modeling pixel level error in fine-resolution DEMs. The approach uses regression-based methods for modeling pixel level DEM error in a manner that is compatible with the Level of Detection technique for integrating error into DoDs. It addresses potential shortcomings of previous studies related to: (1) the assumption of normality for pixel level DEM errors; (2) the scale-dependence of the predictive relationship between local topographic roughness (LTR) and DEM error; and (3) the spatial autocorrelation of DEM error. The modeling approach is prototyped using two terrestrial laser scanning (TLS) datasets from a braided river valley. Distributions of pixel level errors are found to be predominantly nonnormal and a new measure for summarizing asymmetric error distributions is introduced. Ordinary least squares (OLS) and spatial lag (SL) regression are then used to model DEM errors as a function of LTR calculated at three different radii, producing six regression models for each TLS dataset. The regression models are then evaluated based on model fit (i.e., Akaike’s
Proceedings of the Sixth International Workshop on Web Caching and Content Distribution

We investigate the stream merging problem for mediaon-demand servers. Clients requesting media from the server arrive by a Poisson process, and delivery to the clients starts immediately. Clients are prepared to receive up to two streams at any time, one or both being fed into a bu er cache. A multicast mechanism exists that allows multiple clients to receive the same stream. We present an on-line algorithm, the dyadic stream merging algorithm, whose recursive structure allows us to derive a tight asymptotic bound on stream merging performance. In particular, let be the request arrival rate, and let L be the xed media length. Then the long-time ratio of the expected total stream length under the dyadic algorithm to that under an algorithm with no merging is asymptotically equal to 3 log L 2 L . Furthermore, we establish the near-optimality of the dyadic algorithm by comparisons with experimental results obtained for an optimal algorithm constructed as a dynamic program. The dyadic algorithm and the best on-line algorithm of those recently proposed di er by less than a percent in their comparison with an o -line optimal algorithm. Finally, the worst-case performance of our algorithm is shown to be no worse than that of earlier algorithms. Thus, the dyadic algorithm appears to be the rst near optimal algorithm that admits a rigorous average-case analysis.
Proceedings of the Sixth International Workshop on Web Caching and Content Distribution

Recently the Internet has witnessed the emergence of content distribution networks (CDNs). In this paper we study the problem of optimally replicating objects in CDN servers. In our model, each Internet Au-tonomous System (AS) is a node with (cid:12)nite storage capacity for replicating objects. The optimization problem is to replicate objects so that when clients fetch objects from the nearest CDN server with the requested object, the average number of ASs traversed is minimized. We formulate this problem as a combinatorial optimization problem. We show that this optimization problem is NP complete. We develop four natural heuristics and compare them numerically using real Internet topology data. We (cid:12)nd that the best results are obtained with heuristics that have all the CDN servers cooperating in making the replication decisions. We also develop a model for studying the bene(cid:12)ts of co-operation between nodes, which provides insight into peer-to-peer content distribution.
First Observation of the Decay B

The properties of the orbitally excited (L 1⁄4 1) Bs states are studied by using 1:0 fb 1 of pp collisions at ffiffi s p 1⁄4 7 TeV collected with the LHCb detector. The first observation of the B s2ð5840Þ meson decaying to B þK is reported, and the corresponding branching fraction measured relative to the BþK decay mode. The Bs1ð5830Þ ! B þK decay is observed as well. The width of the B s2ð5840Þ state is measured for the first time, and the masses of the two states are determined with the highest precision to date. The observation of the B s2ð5840Þ ! B þK decay favors the spin-parity assignment J 1⁄4 2þ for the B s2ð5840Þ meson. In addition, the most precise measurement of the mass difference mðB þÞ mðBþÞ 1⁄4 45:01 0:30ðstatÞ 0:23ðsystÞ MeV=c is obtained.
On Computation of Performance Bounds of Optimal Index Assignment

Channel-optimized index assignment of source codewords is arguably the simplest way of improving transmission error resilience, while keeping the source and/or channel codes intact. But optimal design of index assignment is an instance of quadratic assignment problem (QAP), one of the hardest optimization problems in the NP-complete class. In this paper we make a progress in the research of index assignment optimization. We apply some recent results of QAP research to compute the strongest lower bounds so far for channel distortion of BSC among all index assignments. The strength of the resulting lower bounds is validated by comparing them against the upper bounds produced by heuristic index assignment algorithms.
How to rank with few errors: A PTAS for Weighted Feedback Arc Set on Tournaments

Suppose you ran a chess tournament, everybody played everybody, and you wanted to use the results to rank everybody. Unless you were really lucky, the results would not be acyclic, so you could not just sort the players by who beat whom. A natural objective is to find a ranking that minimizes the number of upsets, where an upset is a pair of players where the player ranked lower on the ranking beats the player ranked higher. This is the NP-hard minimum feedback arc set (FAS) problem on tournaments. Our main result is a polynomial time approximation scheme (PTAS) for this problem. A simple weighted generalization gives a PTAS for Kemeny-Young rank aggregation. Electronic Colloquium on Computational Complexity, Report No. 144 (2006)
Quantum hydrogen-bond symmetrization in the superconducting hydrogen sulfide 1 system

Ion Errea, Matteo Calandra, Chris J. Pickard, Joseph R. Nelson, Richard J. 3 Needs, Yinwei Li, Hanyu Liu, Yunwei Zhang, Yanming Ma, and Francesco Mauri 4 Fisika Aplikatua 1 Saila, EUITI Bilbao, University of the Basque Country (UPV/EHU), 5 Rafael Moreno “Pitxitxi” Pasealekua 3, 48013 Bilbao, Basque Country, Spain 6 Donostia International Physics Center (DIPC), Manuel Lardizabal pasealekua 4, 7 20018 Donostia/San Sebastián, Basque Country, Spain 8 IMPMC, UMR CNRS 7590, Sorbonne Universités UPMC Univ. Paris 06, 9 MNHN, IRD, 4 Place Jussieu, F-75005 Paris, France 10 4 Department of Materials Science & Metallurgy, University of Cambridge, 11 27 Charles Babbage Road, Cambridge CB3 0FS, UK 12 Theory of Condensed Matter Group, Cavendish Laboratory, 13 J J Thomson Avenue, Cambridge CB3 0HE, UK 14 School of Physics and Electronic Engineering, Jiangsu Normal University, Xuzhou 221116, People’s Republic of China 15 7 Geophysical Laboratory, Carnegie Institution of Washington, Washington D.C. 20015, USA 16 State Key Laboratory of Superhard Materials, Jilin University, 17 Changchun 130012, People’s Republic of China and 18 9 Dipartimento di Fisica, Università di Roma La Sapienza, Piazzale Aldo Moro 5, I-00185 Roma, Italy 19
Weak decay of hypernuclei

The nonmesonic weak decay of light Λ hypernuclei is investigated in a shell model framework. The strangeness-changing weak ΛN → N N transition potential is constructed by including the exchange of the pseudoscalar mesons π, K, η as well as the vector mesons ρ, ω, and K*, whose weak coupling constants are obtained from soft meson theorems and SU(6)w. The transition matrix element includes a realistic ΛN short-range correlation function that is based on the Nijmegen Y N-potential. The total decay rate and the proton asymmetry, which represents a measure of the parity-violating to parity-conserving amplitudes, are in agreement with present experimental errors while the neutron- to proton-induced ratio is underestimated by more than a factor of two. In general, the observables are found to be dominated by the pion-exchange mechanism since the contributions of heavier mesons are suppressed by form factors and short-range correlations.
24 μm Detections of Circum(sub)stellar Disks in IC 348: Grain Growth and Inner Holes?

We present observations of six late-type members of the young cluster IC 348 detected at 24 μm with the Multiband Imaging Photometer for Spitzer (MIPS). At least four of the objects are probably substellar. Combining these data with ground-based optical and near-infrared photometry and complementary observations with the Infrared Array Camera (IRAC), we have modeled the spectral energy distributions using detailed models of irradiated accretion disks. We are able to fit the observations with models using a range of maximum grain sizes from ISM-type dust to grains as large as 1 mm. Two objects show a lack of excess emission at wavelengths shortward of 5.8-8 μm but significant excess at longer wavelengths, indicative of large optically thin or evacuated inner holes. Our models indicate an inner hole of radius ~0.5-0.9 AU for the brown dwarf L316; this is the first brown dwarf with evidence for an AU-scale inner disk hole. We examine several possible mechanisms for the inner disk clearing in this case, including photoevaporation and planet formation.
Energy in the 2001 Dairy NRC: Understanding the System

The purpose of this paper is to review the energy system in the 7th Edition of the Nutrient Requirements of Dairy Cattle (NRC-2001). In evaluating the energy system, both animal requirements and the supply of energy (feeds) must be considered. Previous editions of the Dairy NRC were found to have energy supplied from feeds or input energy 5 to 7% greater than energy output (Weiss, 1998). A fundamental law in thermodynamics states energy is neither created nor destroyed, but can be changed in form. Thus, the goal of the NRC-2001 was to update the energy system and make the system balanced, i.e. energy input should equal output. Also, in previous editions of the Dairy NRC, the dietary nutrient requirements were static and did not account for animal or feedstuff variations that could affect the requirement or supply of nutrients. The NRC-2001 relies heavily on a computer model to dynamically predict dietary nutrient requirements. The dietary energy requirements in the NRC 2001 consider feedstuff digestion dynamics as well as the energy requirements for maintenance, growth, lactation, reproductive status and activity of the animal. This paper will primarily focus on energy as related to the lactating cow.
Two of the three Nobel Prize winners in Chemistry of the year 2017 and 26 fellow experts in the field of electron microscopy (EM) as employed in structural biology

A geometric form of information theory allows for reasonable, i.e. probabilistic, evidence-ranking based, and generalized noise-level dependent, classifications of the crystallographic and quasicrystallographic symmetries in noisy digital images. Such classifications are based solely on the image pixel intensity values, justifiable assumptions about the aggregate distribution of generalized noise in the images, asymptotic extrapolations to zero-noise images, and rational symmetry model selections with maximized predictive accuracy in the presence of both symmetry-inclusion relations and pseudo-symmetries. Preferring a well developed geometric form of information theory over a theoretically possible geometric-Bayesian approach for these classifications is the only subjective choice made. Using digital data planes and assuming approximately Gaussian distributed generalized noise, reasonable crystallographic and quasicrystallographic symmetry classifications can be made for noisy images from both scanning probe and transmission electron microscopes. A binary type classification of structurally very similar materials into either a quasicrystal or one of its rational/crystalline approximants based on the approximate point symmetries in their noisy digital images is proposed here for the first time.
Simple Image Description Generator via a Linear Phrase-based Model

Generating a novel textual description of an image is an interesting problem that connects computer vision and natural language processing. In this paper, we present a simple model that is able to generate descriptive sentences given a sample image. This model has a strong focus on the syntax of the descriptions. We train a purely bilinear model that learns a metric between an image representation (generated from a previously trained Convolutional Neural Network) and phrases that are used to described them. The system is then able to infer phrases from a given image sample. Based on caption syntax statistics, we propose a simple language model that can produce relevant descriptions for a given test image using the phrases inferred. Our approach, which is considerably simpler than state-of-the- art models, achieves comparable results on the recently release Microsoft COCO dataset.
01 50 4 v 1 3 0 Ja n 20 02 Black Holes in Galactic Nuclei : the Promise and the Facts

It has long been suspected that Active Galactic Nuclei are powered by accretion of matter onto massive black holes and this belief implies their presence in the nuclei of most nearby galaxies as ”relics” of past activity. Just a few years ago this was considered a paradigm but, recently, new ground-based and Hubble Space Telescope observations are producing a breakthrough in our knowledge on massive black holes. I will review the evidence for the existence of black holes in galactic nuclei and how their presence is related to host galaxy properties and AGN activity. 0.1 A Brief Historical Introduction In November 1783 John Michell presented to the Royal Society his idea of a dark star, a star so massive that the escape velocity from its surface is larger than the speed of light. Combining the corpuscolary theory of light with Newton’s theory of gravitation, he found that a star with the same density as the Sun but escape velocity equal to c would have radius R = 486 R⊙ and mass M = 1.2 × 10 8 M⊙. Michell also pointed out that, although dark stars are invisible, their presence could be inferred from the motion of other luminous bodies orbiting around them. Similar ideas were independently presented in 1796 by Laplace in his ”Exposition du système du monde”. In 1916 Karl Schwarzschild presented his exact solution of Einstein field equations deriving the well-known Schwarzschild radius which Michell had exactly determined although starting from wrong assumptions. The term black hole, which is now commonly used, was not coined until 1967 by John Wheeler and the first observational evidence for the existence of a black hole was given in the early 70s by the observations of the binary X-ray source Cygnus X-1. The discovery of quasars with their enormous energy output from small volumes of space suggested that they were powered by accretion of matter onto very massive black holes residing in galactic nuclei [29]. The first observational evidence was found in the galaxy M87 whose nucleus seemed to host a 5×10 M⊙ black hole [44]. The supermassive black holes (hereafter BHs) hosted in galactic nuclei, with masses in the range 10 − 10 M⊙, are the topic of this review. Observational evidences for the existence of BHs in galactic nuclei up to the early ’90s are summarized in a review
Gene-Based Modeling of Methane Oxidation in Coastal Sediments: Constraints on the Efficiency of the Microbial Methane Filter

Methane is a powerful greenhouse gas that is produced in large quantities in marine sediments. Microbially mediated oxidation of methane in sediments, when in balance with methane production, prevents the release of methane to the overlying water. Here, we present a gene-based reactive transport model that includes both microbial and geochemical dynamics and use it to investigate whether the rate of growth of methane oxidizers in sediments impacts the efficiency of the microbial methane filter. We focus on iron- and methane-rich coastal sediments and, with the model, show that at our site, up to 10% of all methane removed is oxidized by iron and manganese oxides, with the remainder accounted for by oxygen and sulfate. We demonstrate that the slow growth rate of anaerobic methane-oxidizing microbes limits their ability to respond to transient perturbations, resulting in periodic benthic release of methane. Eutrophication and deoxygenation decrease the efficiency of the microbial methane filter further, thereby enhancing the role of coastal environments as a source of methane to the atmosphere.
Fast Recognition of birds in offshore wind farms based on an improved deep learning model

The safety of wind turbines is a prerequisite for the stable operation of offshore wind farms. However, bird damage poses a direct threat to the safe operation of wind turbines and wind turbine blades. In addition, millions of birds are killed by wind turbines every year. In order to protect the ecological environment and maintain the safe operation of offshore wind turbines, and to address the problem of the low detection capability of current target detection algorithms in low-light environments such as at night, this paper proposes a method to improve the network performance by integrating the CBAM attention mechanism and the RetinexNet network into YOLOv5. First, the training set images are fed into the YOLOv5 network with integrated CBAM attention module for training, and the optimal weight model is stored. Then, low-light images are enhanced and denoised using Decom-Net and Enhance-Net, and the accuracy is tested on the optimal weight model. In addition, the k-means++ clustering algorithm is used to optimise the anchor box selection method, which solves the problem of unstable initial centroids and achieves better clustering results. Experimental results show that the accuracy of this model in bird detection tasks can reach 87.40%, an increase of 21.25%. The model can detect birds near wind turbines in real time and shows strong stability in night, rainy and shaky conditions, proving that the model can ensure the safe and stable operation of wind turbines.
Determination of Solar Neutrino Oscillation Parameters using 1496 Days of Super-Kamiokande-I Data

A number of different fits to solar neutrino mixing and mass square difference were performed using 1496 days of Super-Kamiokande-I’s solar neutrino data. These data select two allowed areas at large neutrino mixing when combined with either the solar B flux prediction of the standard solar model or the SNO interaction rate measurements. A global fit combining SK data with the solar neutrino interaction rates measured by Homestake, SNO, Gallex/GNO and SAGE prefers a single allowed area, the Large Mixing Angle solution, at the 98.9% confidence level. The mass square difference between the two mass eigenstates ranges from about to eV , while the mixing angle is in the range of 0.25–0.65.
A Comparison between NDVI and SAVI for Vegetation Spatial Information Retrieval Based on ASTER Images:A Case Study of Huadu District,Guangzhou

Vegetation index is one of the important indexes to monitor the information of land cover,and to describe the diversity of the ecosystem types.It is significant to evaluate the vegetation cover and the growing conditions of vegetation with qualitative and quantitative method.Based on the remote sensing images of ASTER,the computative formulas of normalized difference vegetation index(NDVI) and soil-adjusted vegetation index(SAVI) are written by IDL language;then,the remote images processed by the two methods are classified by K-Means method;and then the information of vegetation is extracted.The results indicate that:NDVI images reflect well the information of land cover as a whole,and are able to distinguish quantitatively the vegetation from non-vegetation,they are fit for investigation of a great area;SAVI images give much emphasis to the information of inner difference of the vegetation as they magnify the extracted spatial information of the vegetation to a certain extent,so they can provide significant references for the information extraction of different vegetation type.
Image-to-image Neural Network for Addition and Subtraction of a Pair of Not Very Large Numbers

Looking back at the history of calculators, one can see that they become less functional and more computationally expensive over time. A modern calculator runs on a personal computer and is drawn at 60 fps only to help us click a few digits with a mouse pointer. A search engine is often used as a calculator, which means that nowadays we need the Internet just to add two numbers. In this paper, we propose to go further and train a convolutional neural network that takes an image of a simple mathematical expression and generates an image of an answer. This neural calculator works only with pairs of double-digit numbers and supports only addition and subtraction. Also, sometimes it makes mistakes. We promise that the proposed calculator is a small step for man, but one giant leap for mankind.
Peerus Review: a tool for scientific experts finding

We propose a tool for experts finding applied to academic data generated by the start-up DSRT in the context of its application Peerus. A user may submit the title, the abstract and optionnally the authors and the journal of publication of a scientific article and the application then returns a list of experts, potential reviewers of the submitted article. The retrieval algorithm is a voting system based on a language modeling technique trained on several millions of scientific papers.