Miracle-dz/UniFAR-FTUs huggingface dataset:
UTILIZATION OF WASTE ROCK FROM OIL SHALE MINING

The paper deals with utilization of oil shale mining waste rock in Estonia. Crushed waste rock is utilized as an aggregate in civil engineering in frostfree environmental conditions and in road building in unbound mixtures where required resistance to fragmentation LA ≤ 35%. This study determines areas of utilization of waste rock and shows that waste rock aggregate produced using selective mining or selective crushing technology is usable in civil engineering in partially saturated conditions and in unbound mixtures where aggregates require resistance to fragmentation LA ≤ 30%. Waste rock is usable for backfilling the already mined areas.
The glacial geomorphology of the Antarctic ice sheet bed

Abstract In 1976, David Sugden and Brian John developed a classification for Antarctic landscapes of glacial erosion based upon exposed and eroded coastal topography, providing insight into the past glacial dynamics of the Antarctic ice sheets. We extend this classification to cover the continental interior of Antarctica by analysing the hypsometry of the subglacial landscape using a recently released dataset of bed topography (BEDMAP2). We used the existing classification as a basis for first developing a low-resolution description of landscape evolution under the ice sheet before building a more detailed classification of patterns of glacial erosion. Our key finding is that a more widespread distribution of ancient, preserved alpine landscapes may survive beneath the Antarctic ice sheets than has been previously recognized. Furthermore, the findings suggest that landscapes of selective erosion exist further inland than might be expected, and may reflect the presence of thinner, less extensive ice in the past. Much of the selective nature of erosion may be controlled by pre-glacial topography, and especially by the large-scale tectonic structure and fluvial valley network. The hypotheses of landscape evolution presented here can be tested by future surveys of the Antarctic ice sheet bed.
The influence of brand-product congruence on consumer evaluations : the role of processing fluency and product type

In order to investigate the influences of consumer responses recent research has focused on congruence among different factors across and within the marketing mix. According to this notion a product which incorporates, for instance, a typeface that is congruent with its shape is preferred over a product with incongruent elements. The results have shown that congruence plays a significant role in enhancing consumer evaluations. Furthermore, positive effects of congruence have been attributed to processing fluency. High processing fluency has been found to be hedonically marked and the experienced pleasant feeling is misattributed to the stimulus at hand. In this regard, processing fluency mediates the influence of congruence on consumer evaluations. However, products differ from each other and can be distinguished based on their type. Utilitarian products are mainly purchased for functional reasons and to solve a problem. In contrast, hedonic products serve experiential purposes and are purchased for their entertainment value. Based on this, it can be expected that high processing, thus quick and easy identification, is more important to utilitarian products than hedonic products. An experimental study addressing congruence among a brand and a corresponding product was conducted to validate the proposed hypotheses
Data Mining Model for Quality Control of Primary Aluminum Production Process

Received: 29 October 2012 Abstract Accepted: 28 November 2012 Traditional statistical process control approaches are less effective in dealing with multivariate and autocorrelated processes. With the continual increase in process complexity, this inefficiency is becoming more apparent. A special type of multivariate and autocorrelated process is a process occurring within a heterogeneous production environment (a variety of types of machines, pots, etc. used for the same task). This makes the quality control of such processes more difficult. The approach presented in the paper utilizes time series fitting, cluster analysis and association mining in relation to a single data mining model for the analysis of complex multivariate autocorrelated processes. The aim is to divide the production cells (machines, pots, etc.) into groups exhibiting similar behaviors. This can then be used for more effective quality control of the entire process and afterwards to analyze the reasons for this behavior. This paper includes someof the results obtained from applying the model to an actual multivariate high autocorrelated process, the production of primary aluminum using the Hall-Heroult electrolysis process. The Hall-Heroult electrolysis process is a continual process that is ongoing in several pots simultaneously. The average plant operates 300 pots. Therefore, the quality control of such a complex process faces many issues concerning monitoring and problem diagnosis. The paper describes a method for dividing the pots into control groups exhibiting similar behaviors, which can then be used in the planning phase of the quality control analysis and to make improvements within these groups and thereby within the whole process.
SYSTEM FOR OPERATIONAL FLOOD FORECASTING ON KOLUBARA RIVER

Marija Ivković 1 Predrag Živadinović 2 Samir Ćatović 3 UDK: 556.06 DOI:10.14415/konferencijaGFS2017.074 Summary: Frequent flooding on Kolubara river catchment imposed the necessity to create an automated system for the operational flood forecasting. The system relies on hydrological and meteorological data in real-time that are forwarded to the distributed hydrological model HBV via WISKI information system. Multi-day forecasted values of precipitation and temperature on the basin, provided by the model for weather forecasting, are used for the calculation of future discharge at twenty profile on Kolubara River. As an example of this joint work, the catastrophic flooding from May 2014 was used.
Exploring teaching practices of science and technology in Malawi primary schools

Research about primary school teachers’ understanding of the meaning and implications of science and technology as a learning area has revealed considerable confusion about these terms, both in their professional sense and concerning their roles in education and economic development. Many countries established science and technology in their school curriculum to help pupils develop scientific and technological literacy but programme structures and emphasis have tended to differ. Malawi also attempted to achieve the goals for a scientifically and technologically literate citizenry through the introduction of an integrated science and technology as a single learning area in schools. While the need for scientifically and technologically literate citizens is governments’ strategic goal, teachers’ understanding of science and technology has implications on their teaching practices and ultimately on student learning. This paper reports on a study that aimed at identifying the teachers’ conceptualisation of science and technology and their teaching practices. The study was implemented using a qualitative paradigm in order to develop a holistic understanding of the situation in the schools and it was undertaken in two primary schools in Blantyre. Schools participating in the study were identified through convenient sampling and involved 8 science and technology teachers for standards 5-8 from each of the two schools. Data generation for the study involved classroom observations, group discussions and teachers completing an open ended questionnaire. The data generated were analysed using thematic analysis. Findings revealed the teachers’ gaps in content knowledge about scientific and technological concepts arising from their lack of understanding of the differences between science and technology. The teachers’ perceptions and practices were also compounded by the nature of the science and technology curriculum and the teachers’ lack of induction when the subject was being introduced. The study recommends redefining the assumptions of the science and technology curriculum. It also suggests providing interventions to help teachers’ develop appropriate conceptualisation of science and technology as this has implications on their choices of what to teach and how to teach it. Key words: Science and technology, scientific literacy, technological literacy, teaching practices, curriculum change.
Targeted MRM Proteomics is a Better Protein Quantification Method Over Western-Blotting

Volume 5 • Issue 1 • 1000e117 J Anal Bioanal Tech ISSN:2155-9872 JABT, an open access journal Sensitivity and selectivity of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) for quantification of small molecules encouraged biologists to utilize this platform for protein quantification using peptide as a surrogate. MS based protein quantification, commonly referred as multiple or selective reaction monitoring (MRM or SRM) proteomics, relies on selective quantification of surrogate peptide(s) in a digested protein sample. The selectivity is achieved by the MRM characteristic of triple quandrupole MS instrument in which unique daughter ion generated from fragmentation of a parent ion (i.e, ionized analyte peptide) is monitored. This application of MS based targeted proteomics become wider with the availability of protein databases and in silico methods for surrogate peptide selection in the last five years. For instance, successful completion of human genome project and the ongoing human proteome project enabled us to select surrogate peptides for MRM quantification of nearly every human protein [1,2]. Because of its increasing popularity, Nature Methods declared targeted proteomics by mass spectrometry (MS) as Method of the Year for 2012 [3].
Application of Dual-Energy K-Edge Subtraction Imaging to Assessment of Heat Treatments in Al-Cu Alloys

Dual-energy K-edge subtraction imaging technique has been employed to analyze the spatial distribution of copper and its change in three-dimensions quantitatively during a solution treatment. In order to realize it, some preliminary investigations on the verification and assurance of accuracy and repeatability have been performed. Inhomogeneous Cu concentration distribution is revealed even after the solution treatment for a sufficiently long period of time at a high temperature in an Al-Cu alloy. The present technique has a unique potential to realize four-dimensional chemical-concentration mapping.
Films from Glyoxal-Crosslinked Spruce Galactoglucomannans Plasticized with Sorbitol

Films were prepared from a renewable and biodegradable forest biorefinery product, spruce O-acetyl-galactoglucomannans (GGMs), crosslinked with glyoxal. For the first time, cohesive and self-standing films were obtained from GGM without the addition of polyol plasticizer. In addition, glyoxal-crosslinked films were prepared using sorbitol at 10, 20, 30, and 40% (wt.-% of GGM). Glyoxal clearly strengthened the GGM matrix, as detected by tensile testing and dynamic mechanical analysis. The elongation at break of films slightly increased, and Young's modulus decreased with increasing sorbitol content. Interestingly, the tensile strength of films was constant with the increased plasticizer content. The effect of sorbitol on water sorption and water vapor permeability (WVP) depended on relative humidity (RH). At low RH, the addition of sorbitol significantly decreased the WVP of films. The glyoxal-crosslinked GGM films containing 20% sorbitol exhibited the lowest oxygen permeability (OP) and WVP of the studied films and showed satisfactory mechanical performance.
Water Use and Risk Perception: mapping estimable epidemiological risk onto heuristic failure

Traditional epidemiological analyses predict preventive behavior when individuals perceive hazards as risky and out of personal control. Recent evidence has found that both controllability perception and heuristic failure may induce risky behavior, increasing potential for disease and injury outbreaks. Based on a representative sample of 352 respondents along the Rio Doce, in Brazil, we make use of Simultaneous Equation Modeling coupled with Thematic Net Analysis to understand how failure to interpret contamination mechanisms may underestimate the epidemiological risk in contexts of high level of river water pollution. Because affect heuristic is also important to prevent risky behavior by modifying personal risk perception, we include a measure of family members ever infected by waterborne diseases in our empirical models. Our descriptive results point to an apparent paradox of high prevalence of river water use and high scores of risk perception. Our regression results suggest a significant underestimation of perceived risk of contamination from water use among those who make use of the river for consumption and leisure, even after taking endogeneity into account in the models. Although many psychological studies suggest that controllability is the main underlying mechanism in this situation, our qualitative analysis reveals that risky behavior regarding use of polluted water relies on failure to understand the mechanisms for transmission of waterborne diseases. These results suggest that population-based epidemiological campaigns aimed to promote preventive behavior must focus on educational campaigns using simple and objective examples of the how waterborne diseases are transmitted. Key-words: Water use, risk perception, waterborne diseases, simultaneous equation modeling, qualitative research  Trabalho apresentado no XIX Encontro Nacional de Estudos Populacionais, realizado em São Pedro, SP, de 24 a 28 de novembro de 2014. Este estudo contou com apoio financeiro da FAPEMIG (Edital 01/2011 Demanda Universal Processo no. SHA APQ-01807-11, Edital 01/2012 – Demanda Universal – Processo n o. CSA APQ-00244-12) e do CNPq (Edital Universal 14/2012 Processo: 483714/2012-7).  Departamento de Demografia – Universidade Federal de Minas Gerais. Email: grguedes@cedeplar.ufmg. br.  Departamento de Economia – Universidade Federal de Minas Gerais. Email: smoro@cedeplar.ufmg. br.  Escola de Serviço Social – PUC/MG. Email: deia@cedeplar.ufmg. br.  Departamento de Psicologia – Universidade Vale do Rio Doce. Email: carlosdiaspsicologo@gmail.com.  Departamento de Estatística – Universidade Federal de Minas Gerais. Email: gabrielhenryoliver@hotmail.com.  Departamento de Estatística – Universidade Federal de Minas Gerais. Email: karol.fdias@hotmail.com.
Large Eddy Simulation of Wind Turbine Wakes in Prescribed Neutral and Non-Neutral Atmospheric Boundary Layers

Large eddy simulation (LES) of an infinitely long wind farm in a fully developed flow is carried out based on solution of the incompressible Navier-Stokes equations. The wind turbines are modeled as equivalent rotating actuator disks by applying aerodynamic loads on the flow field using tabulated aerodynamic lift and drag coefficients to save computational time. As a substitute to standard wall modeling LES, a ''prescribed mean shear" profile (hereafter called PMS) approach has been implemented and analysed for generating the desired turbulent shear flow. It is applied on Neutral, Stable and Convective atmospheric boundary layers in presence of the -actuator disc represented- wind turbines and qualitatively meaningful results of mean and fluctuating velocity field is obtained. The effect of four different sub-grid scale (SGS) models on the flow structure is investigated and it is seen that subgrid scale modeling (in particular, the Mix-O and Smagorinsky models) improves the accuracy of the simulations. An optimal grid resolution is also proposed for this kind of simulation.
A Possibilistic Linear Programming Method forAsset Allocation

The mean-variance method has been one of the popular methods used by most financial institutions in making the decision of asset allocation since the 1950s. This paper presents an alternative method for asset allocation. Instead of minimizing risk for a given expected return or maximizing expected return for a fixed level of risk, our approach considers simultaneously maximizing the rate of return of portfolio, minimizing the risk of obtaining lower return, and maximizing the possibility of reaching higher return. By using a triangular possibilistic distribution to describe the uncertainty of the return, we introduce a possibilistic linear programming model which we solve by a multiple objective linear programming technique with two control constraints. We present a solution algorithm that provides maximal flexibility for decision makers to effectively balance the portfolio's return and risk. Numerical examples show the efficiency of the algorithm.
Security and Audit Trail Capabilities of a Facilitated Interface Used to Populate a Database System with Text and Graphical Data Using Widely Available Software

In prior work we described techniques used to capture, store, and retrieve narrative data forms from a database using widely available off the shelf software. This concept makes use of the security and versioning features of database architecture together with those of image-supported electronic document information capture. We present herein the security and audit trail features of our construct. Unique usernames and passwords are used at the operating system level to enforce client validation and control access to the database system via an electronic signature using a Boolean logic algorithm. We used the database domain to capture original data and any changes to the data, developing an audit trail displaying identification information. Version controlled and change tracked electronic documents can be retrieved through the client side web interface to enable direct search operations, thus uncoupling the client from database query languages.
The Roles of Implicit Causality and Discourse Context in Pronoun Resolution

Some interpersonal verbs show a bias in the proportion of times their subject and object arguments are rementioned in a sample of explanations for the eventuality the verb describes. This bias is known as the implicit causality bias. Several studies have shown that readers and listeners rapidly use the implicit causality bias during pronoun resolution. Whether listeners also rapidly incorporate relevant contextual information during pronoun resolution, is an open question. In the current paper, we report two visual world eye-tracking studies intended to answer this question. Participants listened to stories that included implicit causality verbs followed by a “because” clause with an ambiguous pronoun in its subject position. During the story, the participants looked at a screen on which potential referents of the ambiguous pronoun were displayed. In Experiment 1, a simple main effect of implicit causality bias on looks toward the character that was congruent with the bias was found among items in one of the two discourse conditions. Discourse context, however, only affected looks for a subset of verbs and in the opposite direction of what was hypothesized. In Experiment 2, no main effects of IC Bias or discourse context were found, but there was a marginally significant interaction which was not hypothesized. In both experiments, discourse context influenced looks only for a subset of verbs and never in the predicted direction. The results favor an account in which the influence of lexical semantics is, at least initially, stronger than the influence of world knowledge and discourse context. Additional exploratory analyses suggested that eye movements already reveal remention biases at an early point in the sentence, whereas the causal potency of the subject argument is predicted by looks starting from the onset of the causal connective.
Machine Learning for User Traffic Classification in Wireless Systems

The ability to answer all important questions about the radio-frequency (RF) scene is essential for cognitive radios (CRs) to be effective. In this paper, we propose a RF -based automatic traffic recognizer that, observing the radio spectrum emitted by a communication link and exploiting machine learning (ML) techniques, is able to distinguish between two types of data streams. Numerical results based on real waveforms collected by a RF sensor, demonstrate that over-the-air user traffic classification is possible with an accuracy of 97% at high signal-to-noise ratios (SNRs). Moreover, we show that using a neural network (NN) very good classification performance can be achieved also at low SNRs (around 2 dB). Finally, the impact of the observed RF bandwidth and the acquisition time window on the classification accuracy are analyzed in detail.
Approaches to the phonological analysis of loanword adaptation

In the present paper I am making an attempt to classify some of the factors that have so far motivated the investigations of loanword phonology. I will raise some problematic points that characterize this branch of phonology and will try to show the different approaches adopted when one is examining the borrowing of words into different languages. This "list" of approaches is not at all exhaustive: in fact, I will concentrate on two viewpoints through which I can show what sorts of problems arise when examining assimilation processes. First, I am going to summarize the different theoretical frameworks that assume the existence of phonological subsystems in the lexicon of a particular language. In the second part, I will collect some considerations on the role of perception in loanword adaptation. In the remainder of the paper, I will introduce some miscellaneous questions that I have encountered so far. 1 Phonological subsystems in the grammar 1.1 Mazateco and Spanish The first group of investigations is aimed at describing phonological subsystems within the grammar of certain languages. Many of these studies are concerned with the description of the subsystems of one language and do not intend to make general or universal statements. The first investigations claiming that the phonological system of a language is not homogeneous were carried out in the 1940's and 1950's by structuralist linguists, and were, in fact used to test certain hypotheses about phonemehood. According to the research carried out by Fries and Pike (1949), the pronunciation of Spanish loanwords in Mazateco 1 suggests that there might be conflicting phonological systems within a language. The point they make is that loanwords help us find out more about the native phonology, thus they
Effect of Training and Test Datasets on Image Restoration and Super-Resolution by Deep Learning

Many papers have recently been published on image restoration and single-image super-resolution (SISR) using different deep neural network architectures, training methodology, and datasets. The standard approach for performance evaluation in these papers is to provide a single “average” mean-square error (MSE) and/or structural similarity index (SSIM) value over a test dataset. Since deep learning is data-driven, performance of the proposed methods depends on the size of the training and test sets as well as the variety and complexity of images in them. Furthermore, the performance varies across different images within the same test set. Hence, comparison of different architectures and training methods using a single average performance measure is difficult, especially when they are not using the same training and test sets. We propose new measures to characterize the variety and complexity of images in the training and test sets, and show that our proposed dataset complexity measures correlate well with the mean PSNR and SSIM values obtained on different test data sets. Hence, better characterization of performance of different methods is possible if the mean and variance of the MSE or SSIM over the test set as well as the size, resolution and complexity measures of the training and test sets are specified.