Miracle-dz/UniFAR-FTUs huggingface dataset:
Utilization of Learning Media by the English Teachers in Teaching English at MAN Kemantan

Yafrizal. 2019. "Utilization of Learning Media by the English Teachers in Teaching English at MAN Kemantan". English Education Section. The Graduate Program. Faculty of language and art. Universitas Negeri Padang. The aims of this research was to find out how the utilization of learning media in English language teaching. Approach on this research was conducted as qualitative by using ethnography method. The informant of this research was three English teachers of MAN Kemantan. The research problems are: (1) what kinds of learning media are used by the teachers in teaching English? (2) How do the teachers utilize the learning media in teaching English? (3) What are the teachers’ problems in utilizing of learning media? The data were collected by using instruments, namely: observation checklist sheets, interview guidelines, and documentations. Then they are analyzed qualitatively. Based on the data analysis, it was found that (1) the English teachers at MAN Kemantan used (a) recorder, smart phone, and cassette as audio media (b) visual printed media such as book, magazine, newspaper, and mail (c) visual display such as picture, slide, realia/mock up, and graphic (d) audio visual media such as computer and video (e) teacher herself as model (2) the utilization of learning media by the teachers includes 3 main activities namely preparation before using the media, activities during using the media, and follow-up activities (3) The problems faced by the teachers in utilizing learning media are the standard guideline in using the learning media is not available, the teachers have difficulty in designing syllabus of learning by using media, the time allocation is not enough to utilize the learning media in English teaching process. From the explanation above, it can be concluded that the English teacher at MAN Kemantan need to improve their knowledge of the utilization of the learning media in language teaching. The researcher hopes this research could be a useful input for the English teachers in teaching by using the learning media.
New Ciders Made by an Exhaustion Method: An Option to Val-Orise Subproducts from the Making of Ice Ciders

Cryo-extraction (pressing of frozen apples), is one of the two freeze-enrichment systems allowed for the making of ice juices. Its ciders are often described as more complex and aromatic, however, the production yield is quite low. The Exhaustion method associated with the previous one proposes the valorisation of the discarded apple juice fractions for the making of new ciders. Three types of apple juices and three species of yeasts (S. bayanus, C6; S. cerevisiae, Levuline-CHP, and T. delbrueckii, Biodiva-TD291) have been used to evaluate the Exhaustion method. The ciders obtained were analysed for chemical and volatile composition as well as sensory characteristics. The yield (%) of the Exhaustion process ranged between 24 and 37%. The yeasts promoted the fermentation at different rates, providing ciders with alcoholic degrees between 9 and 12 (%v/v), and low volatile acidities. The yeast strain significantly influenced most of the parameters analysed, whereas the raw apple juice influenced the perception of the attributes fruity, apple and butter. Although the ciders produced by Exhaustion presented significantly lower concentrations of all the volatile compounds analysed than the corresponding ice ciders obtained by Cryo-extraction, the S. bayanus C6 and T. delbrueckii TD291 gave highly valued ciders from the sensory point of view.
A Novel Machine Learning Based Approach for Post-OCR Error Detection

Post processing is the most conventional approach for correcting errors that are caused by Optical Character Recognition(OCR) systems. Two steps are usually taken to correct OCR errors: detection and corrections. For the first task, supervised machine learning methods have shown state-of-the-art performances. Previously proposed approaches have focused most prominently on combining lexical, contextual and statistical features for detecting errors. In this study, we report a novel system to error detection which is based merely on the n-gram counts of a candidate token. In addition to being simple and computationally less expensive, our proposed system beats previous systems reported in the ICDAR2019 competition on OCR-error detection with notable margins. We achieved state-of-the-art F1-scores for eight out of the ten involved European languages. The maximum improvement is for Spanish which improved from 0.69 to 0.90, and the minimum for Polish from 0.82 to 0.84.
EPR CHARACTERIZATION OF NEW CADMIUM , ZINC AND RARE-EARTH TUNGSTATES AND MOLYBDATES

Some well known double molybdates and tungstates single crystals, as e.g. CsDy(MoO4)2, KDy(WO4)2, KLa0.25Pr0.75(WO4)2, KLa0.25Pr0.75(MoO4)2, as well as new cadmium and rare-earths tungstates or molybdates with the formulas CdRE2W2O10, Cd0.25RE0. 50MoO4, and, rare-earth double molybdato-tungstates Cd0.25RE0. 50(MoO4)0.25(WO4)0.75 (RE=Pr, Nd, Sm-Dy) as well as zinc and rare-earth molybdato-tungstates ZnRE2MoWO10 (RE=Pr, Sm-Dy) and II-Pr2W2O9 and II-Pr2WO6 were analyzed using EPR method. The obtained compounds crystallize in the scheelite type structure and some of them show solubility in e.g. CdMoO4 forming solid solutions.
Word Count : 4 , 264 Tables : 1 Figures : 1 High Resolution Brain SPECT Imaging and EMDR in Police Officers with PTSD

Objective: Eye Movement Desensitization and Reprocessing (EMDR) has been shown to be an effective treatment for posttraumatic stress disorder (PTSD). In this study we evaluated the effectiveness and physiological effects of EMDR in police officers involved with on-duty shootings who had PTSD. Method: Six police officers involved with on-duty shootings and subsequent delayed-onset PTSD were evaluated with standard measures, the Posttraumatic Stress Diagnostic Scale, and high-resolution brain SPECT imaging, be fore and after treatment. Results: All police officers showed clinical improvement and marked reductions in the PDS (mean reduction from scores of 43.2 to 5.2). In addition, there were decreases in the left and right occipital lobe, left parietal lobe and right precentral frontal lobe, as well as significant increased perfusion (>0.001) in the left inferior frontal gyrus. Conclusions: In our study EMDR was an effective treatment for PTSD in this police officer group, showing both clinical and brain imaging changes.
Purchasing Green Products as a Means of Expressing Consumers’ Uniqueness: Empirical Evidence from Peru and Bangladesh

Does consumers’ consumption of green products represent a method of satisfying their need for uniqueness? Does it enhance their self-image? In order to answer these questions, the present study attempts to understand how personal-level factors (such as the need for uniqueness) and product-level factors (such as self-expressive benefits) drive customers to go green. Survey-based data were collected from 247 customers in Bangladesh and 132 customers in Peru during 2017–2018. A hierarchical linear regression analysis was employed to test the proposed hypotheses. The results of this study highlight the important role played by the need for uniqueness as a major driver of green behavior among customers in both countries. Furthermore, self-expressive benefits were found to represent another reason on the part of customers in both Peru and Bangladesh for buying green products. This study hence contributes to the current literature by strengthening existing knowledge of the drivers of pro-environmental purchasing behavior in developing countries.
Nanoscale Sub-Compartmentalization of the Dendritic Spine Compartment

Compartmentalization of the membrane is essential for cells to perform highly specific tasks and spatially constrained biochemical functions in topographically defined areas. These membrane lateral heterogeneities range from nanoscopic dimensions, often involving only a few molecular constituents, to micron-sized mesoscopic domains resulting from the coalescence of nanodomains. Short-lived domains lasting for a few milliseconds coexist with more stable platforms lasting from minutes to days. This panoply of lateral domains subserves the great variety of demands of cell physiology, particularly high for those implicated in signaling. The dendritic spine, a subcellular structure of neurons at the receiving (postsynaptic) end of central nervous system excitatory synapses, exploits this compartmentalization principle. In its most frequent adult morphology, the mushroom-shaped spine harbors neurotransmitter receptors, enzymes, and scaffolding proteins tightly packed in a volume of a few femtoliters. In addition to constituting a mesoscopic lateral heterogeneity of the dendritic arborization, the dendritic spine postsynaptic membrane is further compartmentalized into spatially delimited nanodomains that execute separate functions in the synapse. This review discusses the functional relevance of compartmentalization and nanodomain organization in synaptic transmission and plasticity and exemplifies the importance of this parcelization in various neurotransmitter signaling systems operating at dendritic spines, using two fast ligand-gated ionotropic receptors, the nicotinic acetylcholine receptor and the glutamatergic receptor, and a second-messenger G-protein coupled receptor, the cannabinoid receptor, as paradigmatic examples.
Data Reconstruction Method for CD Basis Weight Analysis of Paper by using Compressed Sensing Technology

The control of the cross-directional (CD) basis weight of paper is very challenging. The actuator of the system needs to control the properties of the entire sheet according to a set of restricted data measured by a scanning sensor. The scanning sensor measures the sheet in the cross direction of the paper. For the moving sheet, CD variations were those along an axis perpendicular to the motion of the sheet, while MD (machine direction) variations were those along the axis of motion. One of the problems that make the CD control difficult is data sampling, which is obtained by continuously measuring the CD basis weight of paper through multiple scanning sensors. As the paper moves vertically, the scanning sensor can only measure the “Z” shape area on the paper. When the scanning frequency was not at least twice the maximum frequency of the paper variation, it was difficult to estimate the sheet profile. According to the sparse characteristics of paper signal, a novel approach to accurately reconstruct the sheet properties by a random sampling protocol was proposed by using compressed sensing technology. Compared with the simple bandwidth based uniform sampling theory, it could accurately reconstruct the real process variations from less measurement data. Based on the reconstructed data and actual industrial process data, the CD response model was identified and the reconstruction effect was verified. The CD and MD basis weight data were separated by the predictive separation algorithm, which ensured the basis for CD control. The approach of the compressed sensing technology was found to be effective.
Using machine learning analysis to interpret the relationship between music emotion and lyric features

Melody and lyrics, reflecting two unique human cognitive abilities, are usually combined in music to convey emotions. Although psychologists and computer scientists have made considerable progress in revealing the association between musical structure and the perceived emotions of music, the features of lyrics are relatively less discussed. Using linguistic inquiry and word count (LIWC) technology to extract lyric features in 2,372 Chinese songs, this study investigated the effects of LIWC-based lyric features on the perceived arousal and valence of music. First, correlation analysis shows that, for example, the perceived arousal of music was positively correlated with the total number of lyric words and the mean number of words per sentence and was negatively correlated with the proportion of words related to the past and insight. The perceived valence of music was negatively correlated with the proportion of negative emotion words. Second, we used audio and lyric features as inputs to construct music emotion recognition (MER) models. The performance of random forest regressions reveals that, for the recognition models of perceived valence, adding lyric features can significantly improve the prediction effect of the model using audio features only; for the recognition models of perceived arousal, lyric features are almost useless. Finally, by calculating the feature importance to interpret the MER models, we observed that the audio features played a decisive role in the recognition models of both perceived arousal and perceived valence. Unlike the uselessness of the lyric features in the arousal recognition model, several lyric features, such as the usage frequency of words related to sadness, positive emotions, and tentativeness, played important roles in the valence recognition model.
Phase IB study of the EpCAM antibody adecatumumab combined with docetaxel in patients with EpCAM-positive relapsed or refractory advanced-stage breast cancer

M. Schmidt1, D. Rüttinger2,3, M. Sebastian4, C. A. Hanusch5, N. Marschner6, P. A. Baeuerle2,3, A. Wolf2,3, G. Göppel2,3, D. Oruzio7, G. Schlimok7, G. G. Steger8, C. Wolf9, W. Eiermann5, A. Lang10 & M. Schuler11* Department of Obstetrics and Gynecology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany; Micromet, Inc., Bethesda, USA; Micromet AG, Munich; Department of Internal Medicine III, University Medical Center of the Johannes Gutenberg University Mainz, Mainz; Gynecological Hospital Red Cross, Munich; Practice for Oncology and Hematology, Freiburg; Hospital Augsburg, II. Medical Center, Augsburg, Germany; Medical University Vienna, Department of Oncology, Vienna, Austria; Cooperative Breast Center, Ulm, Germany; State Hospital Feldkirch at State Hospital Rankweil, Rankweil, Austria; Department of Medical Oncology, West German Cancer Center, University Duisburg-Essen, Essen, Germany
Adapting creative workflows

The aim of this study is to find a means to profitably manage companies that have a focus on aesthetical and creative values. To achieve this, a business model tool is applied in a case study at one company. The results and conclusions are then presented with reflections on how a company can develop and adjust a business model with aesthetical and creative values. Preface and Acknowledgements It all started a relatively long time ago. I come from a Swedish background that is heavily saturated by influences from natural sciences. However, two years of studying aesthetical subjects on Gotland made me change. Then, at Luleå University of Technology, I enrolled in the Industrial Management and Engineering program and the changes deepened. My exploration of the concepts of creativity and aesthetics continued. Eventually, thinking about implementing aesthetics in general business workflows took over. Adapting the values examined in this study so that everyone can understand has been a challenge. Many days and nights have been spent honing the thought process. Refining the vocabulary was essential in order to present an article worth reading. The final result leaves me feeling a bit of pride. Hopefully my readers will be inspired and after thinking about it will look at companies from a different angle. I would like to thank Arctic Trend CEO Annkathrin Lundqvist for her help in creating this article. My tutors TorBjörn Nilsson and Diana Chronéer also deserve thanks for their help. Hanna Pääjärvi has also helped me on numerous occasions. Last but not least, I offer my gratitude to my family for their constant support. I hope you will find this study to your liking and thought provoking. ______________________________ Niclas Wennström 2013Z04Z19 Table of
Spiking Neural Networks for Computational Intelligence: An Overview

Deep neural networks with rate-based neurons have exhibited tremendous progress in the last decade. However, the same level of progress has not been observed in research on spiking neural networks (SNN), despite their capability to handle temporal data, energy-efficiency and low latency. This could be because the benchmarking techniques for SNNs are based on the methods used for evaluating deep neural networks, which do not provide a clear evaluation of the capabilities of SNNs. Particularly, the benchmarking of SNN approaches with regards to energy efficiency and latency requires realization in suitable hardware, which imposes additional temporal and resource constraints upon ongoing projects. This review aims to provide an overview of the current real-world applications of SNNs and identifies steps to accelerate research involving SNNs in the future.
Re‐evaluation of the Roseau Tuff eruptive sequence and other ignimbrites in Dominica, Lesser Antilles

The island of Dominica hosts several ignimbrites, including the Roseau Tuff, thought to represent the largest eruption in the Caribbean in the past 200 000 years. The volcanic stratigraphy of the island is poorly understood due to limited outcrops and a paucity of geochemical and geochronological data. The discovery of a new fully accessible exposure of three ignimbrites intercalated with paleosols provides an opportunity to re‐evaluate the current stratigraphic framework of ignimbrite‐forming eruptions on the island. Whole‐rock analyses of pumice clasts from Dominica ignimbrites are andesitic (61–66% SiO2) and in most cases are geochemically indistinguishable. Ignimbrites in the north of the island have less evolved glass compositions (73–75% SiO2) and more mafic orthopyroxene compositions (En > 56) than their southern counterparts (75–78% SiO2; En < 56). Pumice clasts from ignimbrites in southern Dominica have indistinguishable groundmass glass and mineral chemistry, making correlation of these deposits difficult. New (U–Th)/He eruption ages for the southern ignimbrites indicate that at least six separate explosive eruptions occurred between 24 and 61 ka. The non‐unique geochemistry of these deposits, together with the new (U−Th)/He ages, suggests that the large volume inferred for the Roseau Tuff eruption may actually be a composite of six smaller, geochemically homogeneous eruptions.
Ensemble Learning-based Fake News and Disinformation Detection System

In the age of the Internet, access to information is no longer a concern, the credibility, however, is the new era challenge. Information reaches people in an unfiltered format and therefore raises questions about the authenticity, validity, and credibility. This paper focuses on increasing the reliability of the news, concentrating on static analysis of written text intending to detect possible disingenuous information. To achieve this goal, intelligent solutions were engaged, designed to detect patterns of fake articles that can hint at the lack of knowledge or outright maliciously. The architecture, of the proposed fake news detection system is a composite solution of different classification algorithms, with a final network output obtained through the use of the ensemble learning methods, respectively the comparison of three voting systems. The baseline model allowed a satisfactory accuracy of 99% for the given dataset.
Has the ECB’s monetary policy prompted companies to invest, or pay dividends?

ABSTRACT This paper focuses on the influence of the European Central Bank’s (ECB) monetary policies on non-financial firms. It sheds light on non-financial firms’ decisions regarding leverage, and on how the ECB’s conventional and unconventional policies may have affected them. The paper also examines how these policies influenced non-financial firms’ decisions on capital allocation – primarily capital spending and shareholder distribution (for example, dividends and share repurchases). We use an exhaustive and unique dataset comprised of income statements and balance sheets of leading non-financial firms operating in the European Economic and Monetary Union (EMU). The main results suggest that ECB’s monetary policies have encouraged firms to raise their debt burden, especially after the global recession of 2008. Finally, the ECB’s policies, especially after 2011, also seem to have led non-financial firms to allocate more resources not just to capital spending but to shareholder distribution as well.
Ju n 20 10 Scalar Field Theory on Non-commutative Snyder Space-Time

We construct a scalar field theory on the Snyder non-commutative space-time. The symmetry underlying the Snyder geometry is deformed at the co-algebraic level only, while its Poincaré algebra is undeformed. The Lorentz sector is undeformed at both algebraic and co-algebraic level, but the co-product for momenta (defining the star-product) is non-co-associative. The Snyder-deformed Poincaré group is described by a non-co-associative Hopf algebra. The definition of the interacting theory in terms of a non-associative star-product is thus questionable. We avoid the non-associativity by the use of a space-time picture based on the concept of realization of a non-commutative geometry. The two main results we obtain are: (i) the generic (namely for any realization) construction of the co-algebraic sector underlying the Snyder geometry and (ii) the definition of a non-ambiguous self interacting scalar field theory on this space-time. The first order correction terms of the corresponding Lagrangian are explicitly computed. The possibility to derive Noether charges for the Snyder space-time is also discussed.
Topic Modelling of Croatian News During COVID-19 Pandemic

This paper addresses topic modelling in Croatian news articles related to COVID-19 pandemics and corresponding comments. We identify and analyze Croatian online news media's main topics for the first nine months of pandemics shedding some light on the leading themes covered in news articles and corresponding comments. Topics are derived automatically by training the model and calculating topics' coherence values. We report the results by listing the top 15 detected words in top 10 detected topics from the content of articles and corresponding comments. Our findings include the analysis of intersected topics and discussion of dissents. Obtained results are the first step toward better information monitoring and hopefully mitigating the infodemics effect in Croatia.
Schatten ideal behavior of a generalized Hardy operator

We show the SP-criteria and the cut-off result for an operator closely related to the classical Hardy inequality. INTRODUCTION For a function g defined on (0, oo) we consider the operator Ag acting on L2(O, oo), which is given by the formula Agh(y)= g(y) h(x)dx. We prove the SP-criteria for Ag , 1 < p < oo, and the cut-off result at p = 1 which states that Ag cannot be trace class. This cut-off for Ag is related to the result of Rochberg in [R2]. In a more general sense it resembles the critical index behavior of commutators of singular integral operators found by Janson and Wolff in [JW] and the behavior of Hankel operators on Bergman spaces studied by Arazy, Fisher, and Peetre in [AFP]. The case p = oo is also contained in the paper [BK] by Bloom and Kerman. After this work was done the author was informed that closely related results had been obtained earlier by Birman and Solomyak in [BS]. The boundedness of Ag on L2(0, oo) for g -1 becomes the classical Hardy inequality. The operator Ag is essentially a square root of a Calder6n-Toeplitz operator T,, defined in the context of the Haar wavelet, i.e., AgAg = PT#P, where P: L2(R) -+ L2(0, oc) is the orthogonal projection, and also T77 may be expressed in terms of AgAg. The symbol of 77# is the measure ,u defined on the upper half plane by the formula 00 00 00s) )g()2ds F(u, s)du(u, s) F(O, s)lg()l2. -oo O S Received by the editors September 26, 1991. 1991 Mathematics Subject Classification. Primary 47B10, 47B35.