Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality Assurance Procedures for Estimating Purchasing Power Parities

The International Comparison Program (ICP) is a worldwide statistical initiative designed to estimate purchasing power parities (PPPs). PPPs are conversion rates that convert to a common currency while equalizing the purchasing power of different currencies, hence allowing for accurate volume measures of economic activity as well as comparisons of standards of living across countries. Among many other uses, the Millennium Development Goals (MDGs) and Sustainable Development Goals (SDGs) rely on PPPbased indicators for their key goals on economic growth, poverty, energy and environment. To estimate PPPs for the world’s economies, the ICP conducts surveys to collect price and expenditure data for all goods and services that make up the gross domestic product (GPD). Significant resources are allocated to data collection and validation in order to ensure PPP estimates of the highest possible quality. Validation procedures are carried out first at the national level to ensure intra-country data quality, subsequently at the regional level to ensure inter-country data quality, and finally at the global level to ensure inter-country data quality across the regions. Moreover, efforts are devoted to validating the resulting regional and global PPPs from an economic point of view to ensure their soundness. The quality procedures require close cooperation and collaboration between participating countries, regional implementing agencies and the global implementing agency. Frequent meetings, training sessions and validation workshops are organized to ensure consistency of methodology, comparability of prices and soundness of resulting PPPs. The ICP Book (World Bank, 2013) and the ICP Operational Guidelines (World Bank, 2015) were also developed as reference materials to ensure a common understanding of PPPs and their underlying methodology, quality assurance and data validation procedures.
Combining Local and Document-Level Context: The LMU Munich Neural Machine Translation System at WMT19

We describe LMU Munich’s machine translation system for English→German translation which was used to participate in the WMT19 shared task on supervised news translation. We specifically participated in the document-level MT track. The system used as a primary submission is a context-aware Transformer capable of both rich modeling of limited contextual information and integration of large-scale document-level context with a less rich representation. We train this model by fine-tuning a big Transformer baseline. Our experimental results show that document-level context provides for large improvements in translation quality, and adding a rich representation of the previous sentence provides a small additional gain.
TOTAL FLAVONOIDS , TOTAL PHENOLICS AND VITAMIN C : INDICATORS OF THE ANTIOXIDANT POTENTIALS OF SELECTED FRUIT PEELS

The environment has been dumped with various solid wastes. A good part of this kind of wastes are the peels from fruits. Recent scientific researches have discovered the worth of the fruit peels in terms of substances that are good for the health. This study determined the antioxidant properties in terms of total flavonoids, total phenolics and vitamin C of the methanolic extract of the ten (10) selected fruit peels, namely, rambutan (Nephelium lappaceum), mango (Mangifera indica), marang (Artocarpus odoratissimus), santol (Sandoricum koetjape), soursop (Annona muricata), lakatan (Musa sapientum), avocado (Persia americana), lanzones (Lansium domesticum), watermelon (Citrullus vulgaris) and dragon fruit (Hylocereus undatus). Quantitative analysis showed that lanzones had the highest total flavonoids (213.45 mg quercetin/g dried material). Rambutan was high in both vitamin C (36.47 mg ascorbic acid/g dried material) and total phenolics concentration (96.69 mg GAE/g dried material). Dragon fruit came out with the lowest total flavonoids (5.70 mg quercetin/g dried material) and total phenolics (0.66 mg GAE/g dried material); no vitamin C was detected. Flavonoids, phenolics and vitamin C are recognized antioxidants. Analysis of the 10 selected fruit peels showed the total flavonoids content to have this order (highest to lowest concentration) – lanzones > santol > rambutan > marang > watermelon > mango > lakatan > avocado > soursop > dragon fruit. In terms of total phenolics, rambutan > mango > santol > marang > lanzones > soursop > lakatan > watermelon > avocado > dragon fruit. For vitamin C, rambutan > lanzones > lakatan > watermelon > soursop > marang > mango > avocado > santol > dragon fruit. Keywords— Antioxidants, Total Flavonoids, Total phenolics, Vitamin C, Fruit peels.
Implementation of the Bayesian Approach to Imputation at SORS Prepared by

1. Renewal and modernization of the data editing procedures is one of the key development tasks at the Statistical Office of the Republic of Slovenia (SORS). In the spirit of integration of new ideas and methods we tested the Bayesian approach to data editing. Specifically, we implemented the imputation method based on Bayes’ idea. The theoretical approach was firstly implemented in the editing process of the Statistics on Income and Living Conditions (EU-SILC Survey).
A Viscoplastic Model with Application to LiF-22 % CaF 2 Hypereutectic

A viscoplastic model for class M (metal-like behavior) materials is presented. One novel feature of this model is its use of internal variables to change the stress exponent of creep (where n _ 5) to that of'natural' creep (where n = 3), in accordance with experimental observations. Another feature is the introduction of a coupling in the evolution equations of the kinematic and isotropic internal variables, making thermal recovery of the kinematic variable implicit. These features enable our viscoplastic model to reduce to that of steady-state creep in closed form. In addition, the hardening parameters associated with the two internal state variables (one scalar-valued, the other tensor-valued) are considered to be functions of state, instead of being taken as constant-valued. This feature enables each internal variable to represent a much wider spectrum of internal states for the material. We apply our model to a LiF-22%CaF2 hypereutectic salt, which is being considered as a thermal energy storage material for space-based solar dynamic power systems.
ECOLOGICAL FITNESS OF TRIBENURON METHYL ( ALS-INHIBITOR HERBICIDE ) SUSCEPTIBLE AND RESISTANT BIOTYPES OF WILD MUSTARD IN COMPETITION WITH WHEAT

The occurrence of ALS-herbicide-resistant Sinapis arvensis in wheat crops causes crop yield losses, which makes it necessary to understand the factors that influence the interference of this weed to develop safer management strategies. This study was aimed to evaluate the ecological fitness of wild mustard that is susceptible (S biotypes) and resistant (R biotypes) to Tribenuron Methyl herbicide in competition with wheat in 2014-2017. The experiments were conducted in a greenhouse using a completely randomized design with four replications. The treatments were placed in pots and arranged in replacement series for three experiments: 1) wheat with the R biotype; 2) wheat with the S biotype; and 3) the R biotype with the S biotype) at the following ratios: 100:0, 75:25, 50:50, 25:75, and 0:100. The results showed that S biotype of wild mustard was more competitive than R biotype. There was no significant difference between S biotype and R biotype with accordance of the aggressivity index. The difference between the relative yield of wheat and biotypes of S. arvensis was significant, and regarding relative yield total, the S biotype was superior. Relative seed production index as the resultant index of competition at similar densities was not significant.
Germline BRCA 1 mutation reprograms breast epithelial cell metabolism towards mitochondrial-dependent biosynthesis : evidence for metformin-based “ starvation ” strategies in BRCA 1 carriers

We hypothesized that women inheriting one germline mutation of the BRCA1 gene (“one-hit”) undergo cell-type-specific metabolic reprogramming that supports the high biosynthetic requirements of breast epithelial cells to progress to a fully malignant phenotype. Targeted metabolomic analysis was performed in isogenic pairs of nontumorigenic human breast epithelial cells in which the knock-in of 185delAG mutation in a single BRCA1 allele leads to genomic instability. Mutant BRCA1 one-hit epithelial cells displayed constitutively enhanced activation of biosynthetic nodes within mitochondria. This metabolic rewiring involved the increased incorporation of glutamineand glucosedependent carbon into tricarboxylic acid (TCA) cycle metabolite pools to ultimately generate elevated levels of acetyl-CoA and malonyl-CoA, the major building blocks for lipid biosynthesis. The significant increase of branched-chain amino acids (BCAAs) including the anabolic trigger leucine, which can not only promote protein translation via mTOR but also feed into the TCA cycle via succinyl-CoA, further underscored the anabolic reprogramming of BRCA1 haploinsufficient cells. The anti-diabetic biguanide metformin “reversed” the metabolomic signature and anabolic phenotype of BRCA1 one-hit cells by shutting down mitochondria-driven generation of precursors for lipogenic pathways and reducing the BCAA pool for protein synthesis and TCA fueling. Metformin-induced restriction of mitochondrial biosynthetic capacity was sufficient to impair the tumorinitiating capacity of BRCA1 one-hit cells in mammosphere assays. Metabolic rewiring of the breast epithelium towards increased anabolism might constitute an unanticipated and inherited form of metabolic reprogramming linked to increased risk of oncogenesis in women bearing pathogenic germline BRCA1 mutations. The ability of metformin to constrain the production of mitochondrial-dependent biosynthetic intermediates might open a new avenue for “starvation” chemopreventive strategies in BRCA1 carriers. Research Paper
GRAIL: Efficient Time-Series Representation Learning

The analysis of time series is becoming increasingly prevalent across scientific disciplines and industrial applications. The effectiveness and the scalability of time-series mining techniques critically depend on design choices for three components responsible for (i) representing; (ii) comparing; and (iii) indexing time series. Unfortunately, these components have to date been investigated and developed independently, often resulting in mutually incompatible methods. The lack of a unified approach has hindered progress towards fast and accurate analytics over massive time-series collections. To address this major drawback, we present GRAIL, a generic framework to learn compact time-series representations that preserve the properties of a user-specified comparison function. Given the comparison function, GRAIL (i) extracts landmark time series using clustering; (ii) optimizes necessary parameters; and (iii) exploits approximations for kernel methods to construct representations in linear time and space by expressing each time series as a combination of the landmark time series. We extensively evaluate GRAIL for querying, classification, clustering, sampling, and visualization of time series. For these tasks, methods leveraging GRAIL's representations are significantly faster and at least as accurate as state-of-the-art methods operating over the raw time series. GRAIL shows promise as a new primitive for highly accurate, yet scalable, time-series analysis.
Hyperdimensional Computing for Text Classiﬁcation

—Hyperdimensional computing explores the emulation of cognition by computing with hypervectors as an alternative to computing with numbers. Hypervectors are high-dimensional, holographic, and (pseudo)random with i.i. d. components. These properties provide an opportunity for efﬁcient computing. We focus on an application of hyperdimensional computing for text classiﬁcation. Accordingly, we present an algorithm for classifying news articles from a stream of input letters. Using pentagrams of letters, the algorithm achieves a classiﬁcation accuracy above 94% on eight news topics, surpassing other techniques reported in the literature, including Bayes, K-NN, and SVM. We demonstrate a software framework that enables efﬁcient execution of such algorithms on contemporary hardware fabrics.
Dynamic stress monitoring system for stay cables using piezoelectric strain sensors *

This study presents a dynamic stress monitoring system for stay cables using piezoelectric strain sensors. First, a dynamic strain-based monitoring system to estimate cable stress in real-time manner is schematized. In this approach, the static stress of cable is estimated by using natural frequencies extracted from the dynamic piezoelectric voltage signal. Meanwhile, the dynamic stress component is estimated from magnitude of the signal. The signal of the piezoelectric sensor, which is straininduced voltage, is calibrated with the strain signal measured from a commercial electrical strain gauge. Next, the proposed monitoring system is evaluated by an experiment on a lab-scale steel cable.
Review on Efficacy of Garlic and Onion on Performances , Blood Profile and Health Status of Broiler Chickens By Melaku

This seminar aimed to review the use of herbal growth promoting factor in poultry production which is acceptable among chicken producers to enhance productivity and control diseases. In poultry production, many alternatives have been investigated to replace antibiotics without any loss of productivity or negative influence on health. One possible way to solve this problem is searching of different plants which have positive influences on growth performance, carcass quality and cholesterol content of the blood without any residual effect on consumers. Garlic and onion are among the most popular plants widely used on the world. In farm animal’s different research had been reported on efficacy of onion and garlic as best alternatives of antibiotics in decreasing blood cholesterol, high density lipid and triglyceride, enhancing growth performances, due to, antimicrobial properties of both plants. Garlic and onion contain active ingredients, which have an ability to alter broiler performances. Being the case, Garlic and onion can replace one of the most promising alternatives to antibiotic. However, report of many outers, on dose and efficacy of both plants were not consistent. Therefore, future work will be expected to get accurate result on appropriate dose and rate of effects on broiler.
Selection for Big Data and Analytical Applications

The term Big Data has become pervasive in recent years as smart phones, televisions, washing machines, refrigerators, smart meters, diverse sensors, eyeglasses and even clothes connect to the Internet. However, their generated data is worthless without information retrieval through data analytics. As Big Data is too big for a single person to investigate, appropriate technologies are being used. Unfortunately, there is not one solution but a large variety of different tools, each of them with other functionalities, properties and characteristics. Especially small and midsized companies have a hard time to keep track as this requires time, skills, money, and specific knowledge which result in high entrance barriers for Big Data utilization. This papers aims to reduce these barriers by explaining and structuring different classes of technologies and basic criteria for proper technology selection. It proposes a framework that guides especially small and mid-sized companies through a suitable selection process that can serve as a basis for further advances.
Maths Support provision through embedded classes at LSBU

The present report summarises the communications presented at the sigma Network event on ‘Maths Support through Embedded Classes’ held at London South Bank University (LSBU). Two keynote speakers Professor Jon Warwick, from the LSBU Business School and Dr Lesley Roberts, Head of Skills for Learning, contributed valuable presentations. They outlined how maths support went through various stages and demonstrated the experience of embedded classes at LSBU. Five other delegates communicated their experiences of Maths Support through an embedded approach in their respective institutions.
1 Contextual Effects on Prosodic Prominence

This article provides an introduction to the phenomenon of prosodic focus, as well as to the theory of Alternative Semantics (Rooth, 1992b). Alternative Semantics provides an insightful account of what prosodic focus means, and gives us a notation that can help with better characterizing focusrelated phenomena and the terminology used to describe them. We can also ‘translate’ theoretical ideas about focus and givenness into this notation to facilitate a comparison between frameworks. The discussion will partly be structured by an evaluation of the theories of Givenness (Schwarzschild, 1999), the theory of Relative Givenness (Wagner, 2005, 2006b), and Unalternative Semantics (Büring, 2015, 2016), but we will cover a range of other ideas and proposals in the process. The article concludes with a discussion of phonological issues, and of association with focus.
Author ' s personal copy

CD4 T helper (Th) cell differentiation defined by in vitro cytokine-directed culture systems leaves major gaps in our knowledge of the mechanisms driving divergent Th differentiation. This is evident from our analysis of the response of mouse ovalbumin-specific CD4 T cells to different forms of ovalbumin that induce markedly distinct responses in vivo. We show that live attenuated ovalbumin-expressing Salmonella (SalOVA) induce Th1-associated T-bet and IFN. Conversely, alum-precipitated ovalbumin (alumOVA) induces the Th2-associated GATA-3 and IL-4. The early diversity occurring within these CD4 T cells isolated 3 days after immunization was assessed using real-time RT-PCR microfluidic cards designed with 384 selected genes. The technique was validated both at the population and single cell levels at different stages of the responses, showing 2-microglobulin to be a more stably expressed reference mRNA than either -actin or 18S RNA. SalOVA was then shown selectively to induce the OVA-specific CD4 T cells to produce many chemokines and pro-inflammatory cytokines, contrasting with alumOVA-induced cells that only produced a few Th2-associated cytokines. Several cytokines and features associated with follicular helper functions were induced in the OVA-specific CD4 T cells by both antigens. Finally, IL-17RB is strongly associated with OVA-specific CD4 T cells responding to alumOVA, suggesting that alum may promote Th2 immune response through a role for the IL-25/IL-17RB pathway. © 2008 Elsevier Ltd. All rights reserved.
Zbornik 20. mednarodne multikonference

Much of current research in Artificial Intelligence and Music, and particularly in the field of Music Information Retrieval (MIR), focuses on algorithms that interpret musical signals and recognize musically relevant objects and patterns at various levels -from notes to beats and rhythm, to melodic and harmonic patterns and higher-level segment structure --, with the goal of supporting novel applications in the digital music world. This presentation will give the audience a glimpse of what musically "intelligent" systems can currently do with music, and what this is good for. However, we will also find that while some of these capabilities are quite impressive, they are still far from (and do not require) a deeper "understanding" of music. An ongoing project will be presented that aims to take AI & music research a bit closer to the "essence" of music, going beyond surface features and focusing on the expressive aspects of music, and how these are communicated in music. This raises a number of new research challenges for the field of AI and Music (discussed in much more detail in [Widmer, 2016]). As a first step, we will look at recent work on computational models of expressive music performance, and will show some examples of the state of the art (including the result of a recent musical 'Turing test'). References Widmer, G. (2016). Getting Closer to the Essence of Music: The Con Espressione Manifesto. ACM Transactions on Intelligent Systems and Technology 8(2), Article 19.
WATER-RESISTANT COSMETC FORMULATIONS COMPRISINGA HYDROPHOBCALLY MODIFIED VINYLPYRROLIDONE COPOLYMER

(57) ABSTRACT (21) Appl. No.: 13/519,897 The present invention relates to the use of copolymers com prising N-vinylpyrrolidone and a hydrophobically modified (22) PCT Filed: Jan. 12, 2011 acrylic acid derivative as agents for improving the water resistance of a cosmetic formulation, and to the use of these (86). PCT No.: PCT/EP2011/050291 copolymers in Sunscreen compositions for increasing the Sun
Word Sense Disambiguation Focusing on POS Tag Disambiguation in Persian : A Rule-based Approach

The present study deals with ambiguity at word level focusing on homographs. In different languages, homographs may cause ambiguity in text processing. In Persian, the number of homographs is high due to its orthographic structure as well as its complex derivational and inflectional morphology. In this study, a broad list of homographs was extracted from some Persian corpora first. The list indicates that the number of homographs in Persian corpora is high and homographs with high frequency are those that occur as a result of the identical orthographic representation of some inflectional and derivational morphemes. Based on the list, the most frequent homographs are nouns and adjectives ending in /i/. POS tag disambiguation of such homographs would make word sense disambiguation easier and lead to better text processing. In this study, a list of noun and adjective homographs ending in is extracted in order to decide their correct POS tag. The result was studied to extract context-sensitive rules for allocating the right POS tag to the homograph in syntactic structures. The accuracy of rules was checked, and the result showed that the accuracy of most rules is high which proves most rules are true.
FACIAL EXPRESSION CLASSIFIER BASED ON MACHINE LEARNING ALGORITHMS

Sentiment analysis is a hot topic nowadays, an algorithm extracts subjective information from users, and helps a business to monitor the social reaction toward certain product or service. Sentiment can be extracted from different sources, e.g. speech, text, images. In this document, we are going to focus on computer vision algorithms using images as input data. In recent years, convolutional neural networks (CNN) have become the state-of-art deep learning models in image recognition. They have the power of deep learning as well as optimized feature extraction capabilities. CNNs are considered the top most accurate models in last decade, and new architectures are constantly being developed. This paper proposes several convolutional neural network designs, trained with the greatest public dataset in facial expression, AffectNet, with over 420K manually labeled images. Once the model is trained and tested, the most accurate model is deployed in Affective, a photo manager application capable of classifying stored images in any android device according to 8 facial expressions.
BUILDING COMPANY COMPETITIVE ADVANTAGE BASED ON CUSTOMER VALUE DELIVERY STRATEGY AND SUSTAINABLE MARKETING SYSTEM

Different from views about competitive advantage th ories studied by former scholars, this paper probes into building company competitive adva ntage based on customer value delivery strategy and sustainable marketing system. The paper describ the logical relation of customer value delivery strategy and company competitive advantage. Then it i troduces the company sustainable marketing system and builds company competitive advantage mod el. The STV triangle can identify customer value, deliver customer value, and communicate customer va lue, and creates sustainable competitive advantage in the end.