Miracle-dz/UniFAR-FTUs huggingface dataset:
Atomic-scale quantification of charge densities in two-dimensional materials

Knut Müller-Caspary,1,2,3,* Martial Duchamp,3,4 Malte Rösner,5,6,7 Vadim Migunov,3 Florian Winkler,3 Hao Yang,7 Martin Huth,8 Robert Ritz,8 Martin Simson,8 Sebastian Ihle,8 Heike Soltau,8 Tim Wehling,5,6 Rafal E. Dunin-Borkowski,3 Sandra Van Aert,1 and Andreas Rosenauer2 1EMAT, Universiteit Antwerpen, Groenenborgerlaan 171, B-2020 Antwerpen, Belgium 2IFP, Universität Bremen, Otto-Hahn-Allee 1, 28359 Bremen, Germany 3Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons and Peter Grünberg Institute, Forschungszentrum Jülich, 52425 Jülich, Germany 4School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore 5ITP, Universität Bremen, Otto-Hahn-Allee 1, 28359 Bremen, Germany 6BCCMS, Universität Bremen, Am Fallturm 1, 28359 Bremen, Germany 7Department of Physics and Astronomy, University of Southern California, Los Angeles, California 90089-0484, USA 8PNDetector GmbH, Otto-Hahn-Ring 6, 81739 München, Germany
LitSens : An Improved Architecture for Adaptive Music Using Text Input and Sentiment Analysis

LitSens aims to be a sound system which takes into account the contingencies of real-time decision making in video games. Through this article, we present several improvements for an earlier version of our system architecture, which consisted of an emotion manager attached to predesigned, interactive texts. The main additions to said system are the possibility for users to input custom text to a dialogue manager and the automatic tagging of that text by using real time sentiment analysis, thus improving the knowledge base. We conclude that, though lacking validation due to its early development stage, LitSens can constitute an efficient method for generating adaptive music in real time, suitable for interactive experiences like video games.
The interplay of informative assessment criteria and continuous feedback with mathematics students' learning orientations

Many researches have suggested that making assessment criteria visible supports learning. On the other hand, others have claimed that too much clarity in assessment criteria and feedback could lead to instrumentalism: superficial observance of criteria without deeper thinking. Due to this ambiguous body of knowledge, we wanted to investigate what type of mathematics learning occurs during a course which provides clear assessment criteria and continuous feedback, combined with a technology enhanced learning environment based on self-assessment and reflection of learning.
Non-Newtonian Two-Phase Flow Characteristics across Sudden Expansion in Horizontal Rectangular Minichannel

In the present paper, in order to clarity the effects of non-Newtonian liquid properties on the flow, similar experiments have been conducted for that of 0.4 wt% polyacrylamide (PAM) aqueous solutions as the working liquid, and air as the working gas. Liquid single-phase and air-liquid two-phase flow experiments were conducted at room temperature using the horizontal rectangular mini-channel with a sudden expansion. The cross-sectional dimensions of the narrow channel upstream from the sudden expansion were 2.79 mm, 3.09 mm and 2.94 mm in the height (H), the width (W) and the hydraulic diameter (DH), while those for the wide channel were 2.95 mm, 5.98 mm and 3.95 mm. The pressure distributions in the channels upstream and downstream from the expansion were measured with calibrated pressure transducer to determine the pressure change due to the expansion. The flow pattern, the bubble velocity, the bubble length, and the void fraction were measured with a high-speed video camera. The flow pattern map is drawn from the observed flow pattern, i.e., bubble flow, slug flow and annular flow in both the wide and the narrow channels. The bubble length data were compared with the calculation by the scaling law proposed by Kanezaki et al. and Kawahara et al. The pressure change data at the expansion were compared with our previous data together with several correlations in literature. Results of such experiment and comparisons are reported in the present paper.
6 Mean-Variance Analysis of Supply Chain Contracts

According to the Council of Supply Chain Management Professionals (September 2007), we have the following description for supply chain management: “supply chain management encompasses the planning and management of all activities involved in sourcing and procurement, conversion, and all logistics management activities. Importantly, it also includes coordination and collaboration with channel partners, which can be suppliers, intermediaries, third-party service providers, and customers. In essence, supply chain management integrates supply and demand management within and across companies. ” From this description, it is obviously true that a supply chain in general has multiple channel members (usually called stages) and the coordination and collaboration among these members is a crucial task in supply chain management. In the literature, various policies for supply chain optimization and channel coordination have been proposed. Among them, setting a supply chain contract between individual parties has received much attention in recent years (Tsay et al. 1999, Cachon 2003). Contracts such as buy-back contract, revenue sharing contract, quantity flexibility contract and rebates contract are all known forms of contract which can help to achieve channel coordination in a supply chain. However, in the majority of the literature works, the channels' and supply chain’s objectives are either maximizing the expected profit or minimizing the expected cost. There is no discussion on the level of risk associated with these contracts. As a result, the contract parameters under which coordination is achieved may be viewed as unrealistic by decision makers. In light of this, we conduct in this paper a mean-variance analysis on some popular forms of supply chain contracts such as buy-back contract. By including a constraint on profit uncertainty, we illustrate how decision makers can make a scientifically sound and tailored decision with respect to their degrees of risk aversion. Managerial implications are discussed. The organization of the rest of this chapter is as follows: We briefly review some related literature in Section 2, the discussion of the supply chain’s structure is presented in Section 3. The mean-variance analyses on the buy-back contract and wholesale pricing profit sharing contract are conducted in Sections 4 and 5, respectively. We conclude with some discussions on managerial implications in Section 6. For a notational purpose, we use the following notation in many places throughout this chapter: P = profit, EP = expected profit, SP = standard deviation of profit, MV = mean-
Interpolating the isotopic composition of modern meteoric precipitation

An accurate representation of the spatial distribution of stable hydrogen and oxygen isotopes in modern precipitation is required for many hydrological, paleoclimate, and ecological applications. No standardized method for achieving such a representation exists, and potential errors associated with previously employed methods are not understood. Using resampling, we test the accuracy of interpolated δD and δ18O estimates made using four methods. Prediction error for all methods is strongly related to number of data and will likely decline with the addition of new data. The best method lowers estimation error by 10–15% relative to others tested and gives an average error, using all available data, ≈2.5% of the global range. We present and interpret global maps of interpolated δD, δ18O, and deuterium excess in precipitation and the 95% confidence intervals for these values created using the optimal method. These depict global and regional patterns, make evident the robustness of interpolated isotopic patterns, and highlight target areas for future precipitation sampling.
Multi-population analysis of Puget Sound steelhead survival and migration behavior

Until recently, research on mortality of anadromous fishes in the marine environment was largely limited to estimates of total mortality and association with group characteristics or the environment. Advances in sonic transmitter technology now allow estimates of survival in discrete marine habitats, yielding important information on species of conservation concern. Previous telemetry studies of steelhead Oncorhynchus mykiss smolts in Puget Sound, Washington, USA indicated that approx. 80% of fish entering marine waters did not survive to the Pacific Ocean. The present study re-examined data from previous research and incorporated data from additional Puget Sound populations (n = 7 wild and 6 hatchery populations) tagged during the same period (2006−2009) for a comprehensive analysis of steelhead early marine survival. We used mark-recapture models to examine the effects of several factors on smolt survival and to identify areas of Puget Sound where mortality rates were highest. Wild smolts had higher survival probabilities in general than hatchery smolts, with exceptions, and wild smolts released in early April and late May had a higher probability of survival than those released in early and mid-May. Steelhead smolts suffered greater instantaneous mortality rates in the central region of Puget Sound and from the north end of Hood Canal through Admiralty Inlet than in other monitored migration segments. Early marine survival rates were low (16.0 and 11.4% for wild and hatchery populations, respectively) and consistent among wild populations, indicating a common rather than watershed-specific mortality source. With segment-specific survival information we can begin to identify locations associated with high rates of mortality, and identify the mechanisms responsible.
Generating Captions for News Domain using Randomization Technique

Many of the search engines deployed on the web retrieve images without analyzing their content, simply by matching their user queries against their collocated textual information. This limits the applicability of search engines, a great deal of work has focused on the development of generating descriptive words for an image automatically. Images are automatically captioned in two stages: Content selection and surface realization. Content selection suggests keywords for the image using image annotation model. Whereas, surface realization technique uses extractive and abstractive methods to generate caption. The approach is to analyze the performance of captioned images using phrases rather than words.
Evaluating Different Visualization Designs for Personal Health Data

With the massive development of sensing technology and the availability of self-tracking devices and apps; the interest in personal data collection has widely increased. However, the data representation methods on these tracking devices and apps have many limitations. Our research concentrates on evaluating different data visualization alternatives that could be used to represents the tracked physical activity data (e.g. step count and heart rate) with regards to users' performance when solving visual tasks and their preferences in the proposed visualizations.
An Analysis on Academic Performance of Students using a Hybrid Model for Higher Education

— Education has been viewed as a key aspect in contributing to the welfare of the country. In modern era, Educational Institutions strive hard to improve the quality of education they render to the student community. Though many factors determine a good institution, the academic performance of the students pay a vital role in it. Data mining is a technique used to bring out such hidden knowledge which exists in the form of raw data in the repository. Many socio economic, Non-academic and academic factors influence the performance of the students. There are many well - known data mining classiﬁcation algorithms such as ID3, SimpleCART, J48, NB Tree, MLP, Bayesnet etc which are used to predict the student performance. The model proposed here is mainly focused on finding the prediction accuracy of academic performance of students using a hybrid model which is a combination of two classification algorithms ID3 and MLP. The experimental model also prove that the accuracy can be improved by intelligently generating the training dataset for the hybrid model.
Frequency and Characterization of the Infratemporal Spine in a Sample of Chilean Human Skulls

The infratemporal spine, or sphenoidal tubercle, is a bony structure described in both classical anatomical literature and contemporary literature. However, the available literature does not mention the specific anatomical characteristics or the distribution of this bony element in the population. The aim of this study was to define this structure, identify its presence, and identify its morphology in a sample of Chilean human skulls. Fifty-seven dry skulls, obtained from the morphology unit at Universidad de los Andes, wer e used. The great wings of the sphenoid bone on both sides of the skull were evaluated in search of the infratemporal spine. These spin es wer classified according to their morphological characteristics of either laminar, pyramidal, or truncated pyramidal, as they relat ed to the infratemporal crest and as they related to the pterygoid process. The presence of the infratemporal spine was found in 100 % of the studied skulls, unilaterally or bilaterally. The most common morphology was found to be laminar (40 %), followed by pyramidal ( 35 %), and, finally, truncated pyramidal (24 %). The majority (73 %) of these infratemporal spines was closely associated with the pte r goyd process with a complete or partial relation, with fewer (34 %) being associated with the infratemporal crest.
Two modal Biometrics System for Efficient Human Recognition

: This paper proposes the two different modal biometrics system for identity verification using two traits i.e., face and fingerprint. The proposed system is designed for applications where the training database contains a face and two fingerprint images. The final decision is made by fusion at “matching score level architecture” in which feature vectors are created independently for query images and are then compared to the enrollment templates which are stored during database preparation for each biometric trait. Based on the proximity of feature vector and template, each subsystem computes its own matching score. These individual scores are finally combined into a total score, which is passed to the decision module. Modal system is developed through fusion of face and fingerprint recognition.
ASSESSING THE SIGNIFICANCE OF HYPERION SPECTRAL BANDS IN FOREST CLASSIFICATION

Abstract. The classification of vegetation in hyperspectral image scenes presents some challenges due to high band autocorrelations and problems dealing with many predictor variables. The Random Forests classification method is based on an ensemble of decision trees and attempts to address these issues by dealing with only a subset of image bands in each node of each decision tree. Random Forests has previously been used for classification of vegetation using hyperspectral data. However, the variable importance measure that is a by-product of the technique has largely been ignored. In this study we investigate the spectral qualities of variable importance in the classification of forest and non-forest in a single Hyperion scene. The spectral importance curve showed broad bands of importance over wavelength regions known to be significant in biochemical absorption.
Exponentially slow transitions on a Markov chain: the frequency of Calcium Sparks

Calcium sparks in cardiac muscle cells occur when a cluster of Ca2+ channels open and release Ca2+ from an internal store. A simplified model of Ca2+ sparks has been developed to describe the dynamics of a cluster of channels, which is of the form of a continuous time Markov chain with nearest neighbour transitions and slowly varying jump functions. The chain displays metastability, whereby the probability distribution of the state of the system evolves exponentially slowly, with one of the metastable states occurring at the boundary. An asymptotic technique for analysing the Master equation (a differential-difference equation) associated with these Markov chains is developed using the WKB and projection methods. The method is used to re-derive a known result for a standard class of Markov chains displaying metastability, before being applied to the new class of Markov chains associated with the spark model. The mean first passage time between metastable states is calculated and an expression for the frequency of calcium sparks is derived. All asymptotic results are compared with Monte Carlo simulations.
Biological data on two Hector's beaked whales, Mesoplodon hectori , stranded in Buenos Aires province, Argentina

Beaked whales or ziphiids are the least known cetaceans, and are among the least studied of all mammalian groups. In August and September of 2002, a male and a female beaked whale stranded alive on the Argentine coast, 110km away from each other. The specimens died shortly after the stranding and their bodies were collected for dissection and analysis. The specimens were identified as belonging to the genus Mesoplodon . Further measurements of the skulls, shape and location of teeth as well as molecular analyses of the mtDNA control region and cytochrome b, allowed unambiguous identification of both specimens as Hector's beaked whale, Mesoplodon hectori . The color pattern was different between male and female. Standard length was 3.94 meters for the male and 3.84 meters for the female. The female's vertebral formula was C7 + T10 + L11 + Ca21 = 49. Histo-pathological analysis of the female revealed the presence of Sarcocystis sp. in the skeletal muscle, and lung lesions related to parasitic damage and pneumonia or chronic infection. The stomach of both individuals was empty. The digestive tract of both specimens was infected by larval stages L4 of Anisakis sp. The female was also infected by Tetrabothrius sp. and Bolbosoma sp. while Braunina cordiformis was only found in the male. Different composition of parasitic fauna suggests possible sex-related differences in the diet or individual variability. Total length, teeth eruption (in the male) and the degree of vertebral epiphyses fusion suggest that both individuals were mature.
DEVELOPMENT OF PROBIOTIC GRAPE JUICE AND LACTOBACILLUS PARACASEI VIABILITY UNDER COLD STORAGE

The aim of this study is to develop a probiotic grape juice with Lactobacillus paracasei and to evaluate microorganism viability and the effect of adding inulin to the formulation. Two formulations were developed, being one with 10 % (w / v) inulin added. The beverage was kept at 4oC for 28 days and cell viability, pH and Brix were monitored. In this period, the pH remained around 3.3 not statistically differing from the initial product. The soluble solids did not change with the juice containing inulin remaining at a higher level. Cell viability reduced about 3 logarithmic cycles in 14 days and remained about 6 log CFU/mL until the end of storage. It is concluded that grape juice is a promising matrix for the production of a beverage with probiotic L. paracasei but inulin did not improve cell viability in used concentrations. RESUMO – O objetivo desse trabalho foi desenvolver um suco de uva probiótico com Lactobacillus paracasei e avaliar a viabilidade do microrganismo e o efeito da adição de inulina à formulação. Foram desenvolvidas duas formulações com L. paracasei, sendo uma adicionada de 10 % (m/v) de inulina. A bebida foi mantida à 4oC por 28 dias, sendo monitorados a viabilidade celular, o pH e o oBrix. Neste período, o pH permaneceu em torno de 3,3 não diferindo estatisticamente do produto recém-produzido. Os teores de sólidos solúveis também não sofreram alteração, porém o suco contendo inulina permaneceu num patamar mais elevado. A viabilidade celular caiu 3 ciclos logaritmos em 14 dias, mantendo aproximadamente em 6 log UFC/mL até o final da estocagem. Conclui-se que o suco de uva é uma base promissora para a produção de uma bebida probiótica com L. paracasei, porém a inulina, nas concentrações utilizadas, não melhorou viabilidade celular.
50,000 Tiny Videos: A Large Dataset for Non-parametric Content-based Retrieval and Recognition

50,000 Tiny Videos: A Large Dataset for Non-Parametric Content-Based Retrieval and Recognition Alexandre Karpenko Master of Applied Science Graduate Department of Electrical and Computer Engineering University of Toronto 2009 This work extends the tiny image data-mining techniques developed by Torralba et al. [29] to videos. A large dataset of over 50,000 videos was collected from YouTube. This is the largest user-labeled research database of videos available to date. We demonstrate that a large dataset of tiny videos achieves high classification precision in a variety of content-based retrieval and recognition tasks using very simple similarity metrics. Content-based copy detection (CBCD) is evaluated on a standardized dataset, and the results are applied to related video retrieval within tiny videos. We use our similarity metrics to improve text-only video retrieval results. Finally, we apply our large labeled video dataset to various classification tasks. We show that tiny videos are better suited for classifying activities than tiny images. Furthermore, we demonstrate that classification can be improved by combining the tiny images and tiny videos datasets.
An empirical biometric-based study for user identification from different roles in the online game League of Legends

© 2017 CEUR-WS. All rights reserved. The popularity of computer games has grown exponentially in the last few years. In some games, players can choose to play with different characters from a pre-defined list, exercising distinct roles in each match. Although such games were created to promote competition and promote self-improvement, there are several recurrent issues. One that has received the least amount of attention is the problem of "account sharing" so far is when a player pays more experienced players to progressing in the game. The companies running those games tend to punish this behaviour, but this specific case is hard to identify. The aim of this study is to use a database of mouse and keystroke dynamics biometric data of League of Legends players as a case study to understand the specific characteristics a player will keep (or not) when playing different roles and distinct characters.