Miracle-dz/UniFAR-FTUs huggingface dataset:
Reference String Extraction Using Line-Based Conditional Random Fields

The extraction of individual reference strings from the reference section of scientific publications is an important step in the citation extraction pipeline. Current approaches divide this task into two steps by first detecting the reference section areas and then grouping the text lines in such areas into reference strings. We propose a classification model that considers every line in a publication as a potential part of a reference string. By applying line-based conditional random fields rather than constructing the graphical model based on the individual words, dependencies and patterns that are typical in reference sections provide strong features while the overall complexity of the model is reduced.
Detection of Metabolites Using High‐Performance Liquid Chromatography and Mass Spectrometry

This unit provides a discussion of high‐pressure liquid chromatography‐atmospheric pressure ionization mass spectrometry (LC‐API‐MS) for separation, detection, and identification of products from xenobiotic metabolism. It includes an introduction and important technical information for electrospray and atmospheric pressure chemical ionization methods as well as scan modes. Emphasis has been placed on each method as related to phase I and phase II metabolite identification and there are listings of specific applications (and references) to reduce method development time.
A Prior Neurophysiologic Knowledge Free Tensor-Based Scheme for Single Trial EEG Classification

Single trial electroencephalogram (EEG) classification is essential in developing brain-computer interfaces (BCIs). However, popular classification algorithms, e.g., common spatial patterns (CSP), usually highly depend on the prior neurophysiologic knowledge for noise removing, although this knowledge is not always known in practical applications. In this paper, a novel tensor-based scheme is proposed for single trial EEG classification, which performs well without the prior neurophysiologic knowledge. In this scheme, EEG signals are represented in the spatial-spectral-temporal domain by the wavelet transform, the multilinear discriminative subspace is reserved by the general tensor discriminant analysis (GTDA), redundant indiscriminative patterns are removed by Fisher score, and the classification is conducted by the support vector machine (SVM). Applications to three datasets confirm the effectiveness and the robustness of the proposed tensor scheme in analyzing EEG signals, especially in the case of lacking prior neurophysiologic knowledge.
The Evolvability of iTasks using Normalized Systems

The problem of evolvability of information systems is playing a bigger and bigger role in the world of IT. Projects have great overhead expenses when a change in a large system is necessary. In the struggle to define evolvability, we experience difficulties finding stable solutions. Normalized Systems theory is a novel approach that makes a promising step towards finding this solution. In this thesis, we follow its path and put the method in a functional programming context in order to analyze the evolvability of the iTask framework. We have found that the two domains share similarities and the iTask approach shows promising qualities.
Simple Assessment of Nitrogen Nutrition Index in Summer Maize by Using Chlorophyll Meter Readings

Rapid and non-destructive diagnostic tools to accurately assess crop nitrogen nutrition index (NNI) are imperative for improving crop nitrogen (N) diagnosis and sustaining crop production. This study was aimed to develop the relationships among NNI, leaf N gradient, chlorophyll meter (CM) readings gradient, and positional differences chlorophyll meter index [PDCMI, the ratio of CM readings between different leaf layers (LLs) of crop canopy] and to validate the accuracy and stability of these relationships across the different LLs, years, sites, and cultivars. Six multi-N rates (0–320 kg ha−1) field experiments were conducted with four summer maize cultivars (Zhengdan958, Denghai605, Xundan20, and Denghai661) at two different sites located in China. Six summer maize plants per plot were harvested at each sampling stage to assess NNI, leaf N concentration and CM readings of different LLs during the vegetative growth period. The results showed that the leaf N gradient, CM readings gradient and PDCMI of different LLs decreased, while the NNI values increased with increasing N supply. The leaf N gradient and CM readings gradient increased gradually from top to bottom of the canopy and CM readings of the bottom LL were more sensitive to changes in plant N concentration. The significantly positive relationship between NNI and CM readings of different LLs (LL1 to LL3) was observed, yet these relationships varied across the years. In contrast, the relationships between NNI and PDCMI of different LLs (LL1 to LL3) were significantly negative. The strongest relationship between PDCMI and NNI which was stable across the cultivars and years was observed for PDCMI1−3 (NNI = −5.74 × PDCMI1−3+1.5, R2 = 0.76**). Additionally, the models developed in this study were validated with the data acquired from two independent experiments to assess their accuracy of prediction. The root mean square error value of 0.1 indicated that the most accurate and robust relationship was observed between PDCMI1–3 and NNI. The projected results would help to develop a simple, non-destructive and reliable approach to accurately assess the crop N status for precisely managing N application during the growth period of summer maize crop.
Cold start of a 240 MVA generator step-up transformer filled with natural ester fluid

A 240 MVA, 165 GRDY/20 kV generator step-up transformer was insulated with EnvirotempTM FR3TM fluid. The transformer was energized during a cold temperature period in mid-December 2010. This is believed to be the largest generator step-up transformer filled with a natural ester fluid that was energized at low temperatures. The lack of cold start experience of natural ester filled power transformers created questions and at least some uncertainty as to outcome. This paper describes the instrumentation used and data collected during the cold startup procedure. In addition, a computational fluid dynamics analysis of this transformer design was performed that provided calculated temperatures and elapsed times until steady state temperatures were achieved. Comparisons are made between the actual and calculated values. The results indicate that the cold start up procedures for a power transformer are the same whether filled with mineral oil or natural ester fluid of similar characteristics as used for this work.
A cross-layer adaptive algorithm for multimedia QoS fairness in WLAN environments using neural networks

The authors address the problem of providing fair multimedia quality-of-service (QoS) in IEEE 802.11 distributed co-ordination function-based wireless local area networks in the infrastructure mode where mobile hosts experience heterogeneous channel conditions due to mobility and fading effects. It was observed that unequal link qualities can pose significant unfairness of channel sharing, which may thereby lead to the degradation of multimedia QoS performed in adverse conditions. A cross-layer adaptation scheme that provides fair QoS by online adjusting the multidimensional medium access control layer backoff parameters in accordance with the application-layer QoS requirements as well as the physical-layer channel conditions was proposed. The solution is based on an optimisation approach, which utilises neural networks to learn the cross-layer function. Simulation results demonstrate that the proposed adaptation scheme can tackle heterogeneous channel conditions and random joining (or leaving) of hosts to achieve fair QoS in terms of throughput and packet delay.
Immunogenicity by Electroporation In Vivo Increased DNA Vaccine Delivery and

DNA vaccines have been demonstrated to be potent in small animals but are less effective in primates. One limiting factor may be inefﬁcient uptake of DNA by cells in situ. In this study, we evaluated whether cellular uptake of DNA was a signiﬁcant barrier to efﬁcient transfection in vivo and subsequent induction of immune responses. For this purpose, we used the technique of electroporation to facilitate DNA delivery in vivo. This technology was shown to substantially increase delivery of DNA to cells, resulting in increased expression and elevated immune responses. The potency of a weakly immunogenic hepatitis B surface Ag DNA vaccine was increased in mice, as seen by a more rapid onset and higher magnitude of anti-hepatitis B Abs. In addition, the immunogenicity of a potent HIV gag DNA vaccine was increased in mice, as seen by higher Ab titers, a substantial reduction in the dose of DNA required to induce an Ab response, and an increase in CD8 1 T cell responses. Finally, Ab responses were enhanced by electroporation against both components of a combination HIV gag and env DNA vaccine in guinea pigs and rabbits. Therefore, cellular uptake of DNA is a signiﬁcant barrier to transfection in vivo, and electroporation appears able to overcome this barrier. The Journal of Immunology, 2000, 164: 4635–4640.
An Inductively Active Filtering Method for Power-Quality Improvement of Distribution Networks With Nonlinear Loads

This paper proposes an inductively active filtering (IAF) method to comprehensively improve the power quality (PQ) for not only the distribution network (public grid) but also the power-supply system (nonlinear load) connected to the network. At first, a new main-circuit topology for implementing the IAF method is presented, which consists of an inductively filtered transformer and a fully tuned branch controlled by an inverter. Its operating principle and technical features are introduced by comparing with the traditional active filtering method. Based on this, the equivalent circuit is established and by means of mathematical modeling, the unique filtering mechanism of the IAF method is revealed in theory. Further, the control strategy of the FT branch and the impedance coordination for the inductively filtered transformer are designed based on theoretical analysis. A case study is investigated in detail to illustrate the operating characteristics of the IAF method. Both the theoretical and the case studies show that the IAF method can effectively prevent harmonic components from flowing into the primary (grid) winding of the transformer. Since the harmonic components are suppressed near the harmonic source, it is good for the power-supply system and especially good for the converter transformer. Besides, since the harmonic flow is limited to near the harmonic source, the PQ of the public network can be guaranteed completely.
Light hadron and diquark spectroscopy in quenched QCD with overlap quarks on a large lattice

A simulation of quenched QCD with the overlap Dirac operator has been completed using 100 Wilson gauge configurations at β = 6 on an 183 × 64 lattice and at β = 5.85 on a 143 × 48 lattice, both in Landau gauge. We present results for light meson and baryon masses, meson final state ``wave functions,'' and other observables, as well as some details on the numerical techniques that were used. Our results indicate that scaling violations, if any, are small. We also present an analysis of diquark correlations using the quark propagators generated in our simulation.
An Ensemble-based Approach to Click-Through Rate Prediction for Promoted Listings at Etsy

Etsy1 is a global marketplace where people across the world connect to make, buy and sell unique goods. Sellers at Etsy can promote their product listings via advertising campaigns similar to traditional sponsored search ads. Click-Through Rate (CTR) prediction is an integral part of online search advertising systems where it is utilized as an input to auctions which determine the final ranking of promoted listings to a particular user for each query. In this paper, we provide a holistic view of Etsy's promoted listings' CTR prediction system and propose an ensemble learning approach which is based on historical or behavioral signals for older listings as well as content-based features for new listings. We obtain representations from texts and images by utilizing state-of-the-art deep learning techniques and employ multimodal learning to combine these different signals. We compare the system to non-trivial baselines on a large-scale real world dataset from Etsy, demonstrating the effectiveness of the model and strong correlations between offline experiments and online performance. The paper is also the first technical overview to this kind of product in e-commerce context.
Maternal obesity: pregnancy complications, gestational weight gain and nutrition

The obesity epidemic affects all, including women of reproductive age. One in five women attending prenatal care in the UK is obese. Prepregnancy obesity is associated with serious short‐ and long‐term complications for mother and child. Furthermore, gestational weight gain (GWG) of obese pregnant women generally exceeds the Institute of Medicine recommended ranges. This observation can partially be explained by an unbalanced diet and lack of daily physical activity. Despite this, few lifestyle intervention trials in obese pregnant women are available. Two out of seven intervention trials focusing on GWG, nutrition and physical activity, reached a significant decrease in GWG. Developing guidelines to promote appropriated weight gain and healthy lifestyle in overweight and obese pregnant women remains a challenge.
The Shared Antibiotic Resistome of Soil Bacteria and Human Pathogens

(07/08/2019) The Shared Antibiotic Resistome of Soil Bacteria and Human Pathogens From Farm to Clinic? Soil organisms have long been assumed to be an important source of antibiotic resistance genes, in part because of antibiotic-treated livestock and in part because of the natural ecology of antibiotic production in the soil. Forsberg et al. (p. 1107) developed a metagenomic protocol to assemble short-read sequence data after antibiotic selection experiments, using 12 different drugs in all antibiotic classes, and compared antibiotic resistance gene sequences between soil bacteria and clinically occurring pathogens. Sixteen sequences, representing seven gene products, were discovered in farmland soil bacteria within long stretches of perfect nucleotide identity with pathogenic proteobacteria.
Microwave microlitre lab-on-substrate liquid characterisation based on SIW slot antenna

A microwave microlitre binary liquid mixture concentration detection sensor with potential biological analysis is presented. The microwave lab-on-substrate sensor is fabricated using a substrate integrated waveguide (SIW) slot antenna. The microfluidic channel encapsulating liquid under investigation is located on top of the antenna slot at a quarter wavelength from the short-circuited end of the SIW. The radiated electric near-field interaction with the liquid mixture exhibits different relationships between the complex permittivity of the liquid mixtures versus the resonant frequency and return loss, discriminating types and percentages of mixed liquid. The sensor was initially demonstrated with three types of samples: deionised water, methanol and air. A resonant frequency shift of 110MHz was measured to discriminate between air and deionised water while we obtained a 20MHz resonant frequency shift between air and methanol. Furthermore, the sensor was used to assess deionised water-methanol mixtures with methanol fractional volumes of 0 to 1 in 0.2 steps. The microwave-microfluidic sensor is contactless, uses readily available materials, cost effective and offers fast and accurate liquid characterisation.
Methods to Generate Chimeric Mice from Embryonic Stem Cells

A chimera is an animal that has two or more populations of genetically distinct cells that originated in different embryos, fetuses, or individuals of the same or different species. During recent decades, embryos, the inner cell mass (ICM), teratocarcinoma stem cells, embryonal carcinoma stem cells, embryonic stem (ES) cells (ESCs), primordial germ cells, spermatogonial stem cells, extraembryonic endoderm (XEN) cells (Kunath et al., 2005), induced pluripotent stem cells (iPSCs) (Boland et al., 2009; Kang et al., 2009; Takahashi & Yamanaka, 2006; Zhao et al., 2009), epiblast stem cells (EpiSCs) (Brons et al., 2007; Tesar et al., 2007), and other cells have been used to generate chimeric embryos that can develop into chimeras once transferred to a foster mother. To date, three methods can be applied to produce ESC-derived chimeric embryos: (1) aggregation, (2) microinjection, and (3) coculture. This review uses mouse ES cells as an example to describe and compare existing methods for generating chimeric embryos.
An investigation into value co-creation in service supply chains

In service supply chains, customers select a service provider with whom value would be maximized through the interaction between the service provider and the customer. This study investigates the link between value co-creation and customers' (re)purchasing intentions in the financial and professional services industry. This research was conducted via a case study of PricewaterhouseCoopers (PwC) and one of its clients, Jaguar Land Rover (JLR) and included in-depth interviews with senior managers. The findings underline that the financial and professional services industry is dominated by end of service results and that the only viable option in gaining competitive advantage is to stand out in today's dynamic marketplace. It also reveals that there is a huge demand for outsourcing services and that most clients will choose to purchase one which offers the desired value at the right time. Lastly, it proposes a value co-creation framework derived from the study.
Integration and Fluctuations : The Case of MENA

This paper analyzes the impact of global integration on the dynamics of economic growth and business cycles in the emerging economies of Middle East and North Africa (MENA) and Asia. In particular, the paper examines the evolution of structural characteristics, growth dynamics, and business cycle properties of these countries during the 1960-2000 period. Although both groups of countries became more open and were able to diversify their industrial structures and export bases over time, the MENA countries lagged behind the Asian economies in both trade integration and the extent of diversification of exports during the globalization period (1986-2000). Although economic growth slowed in both groups during the period of globalization, the extent of the slowdown was much sharper in the MENA countries. Moreover, business cycle fluctuations in the MENA countries were much more volatile than in the Asian economies. In addition, although both groups of countries witnessed a moderation in the amplitude of macroeconomic fluctuations during the globalization period, the decline in the volatility of cyclical fluctuations in the MENA countries was relatively small, partially because of the inability of these countries to utilize the benefits of global integration.
Deterrence in Competition Law

This paper provides a comprehensive discussion of the deterrence properties of a competition policy regime. On the basis of the economic theory of law enforcement we identify several factors that are likely to affect its degree of deterrence: 1) sanctions and damages; 2) financial and human resources; 3) powers during the investigation; 4) quality of the law; 5) independence; and 6) separation of power. We then discuss how to measure deterrence. We review the literature that use surveys to solicit direct information on changes in the behavior of firms due to the threats posed by the enforcement of antitrust rules, and the literature based on the analysis of hard data. We finally argue that the most challenging task, both theoretically and empirically, is how to distinguish between â€œgoodâ€ deterrence and â€œbadâ€ deterrence.
A novel approach to reduce interconnect complexity in ANN hardware implementation

Hardware implementation of large digital artificial neural networks is limited by several constraints, such as the complexity of neural interconnections. This paper presents a novel approach to solve the interconnection problem for artificial neural networks, using reconfigurable computing and dynamically reconfigured FPGAs in a new computational way: the execution patterns (EPs). The EPs allow reducing the influence of interconnections through the removal of data transport via busses. Thus, data transport is not necessary to perform the computation and interconnection complexity between neurons is reduced.
Molecular identification of mycorrhizal fungi in Dactylorhiza sambucina (Orchidaceae)

We amplified and sequenced internal transcribed spacer (ITS) region of the nuclear ribosomal repeat from fungi in roots of Dactylorhiza sambucina (Orchidaceae) and used the extended database to identify the mycorrhizal fungi. We molecularly identified three ITS recovered from D. sambucina roots, one belonging to Rhizoctonia group, and two to ascomycetes, for the first time in Orchidoidae. In many cases, two sequence types were found from the same orchid root, providing that two taxa may be involved in mycorrhizal formation (multiple mycobiont colonization). Moreover, we demonstrated that D. sambucina plants, irrespective of their colour polymorphism, possess roots containing several fungi belonging to both asco- and basidiomycetes.
Place Marketing of Georgian Hypermarket Retailers: Carrefour and Goodwill and Their Market Share Prediction by Drive Time Analyzes and the Expectancy Value Model

Marketing plays a great role in retailing business. There are some marketing approaches and methods according which the proper place for a hypermarket retailer can be found in Tbilisi, capital of Georgia. There are retailer marketing approaches, place marketing strategies and methods on the one side, and the knowledge of attitude building process and expectancy value models on the other side. The task of this article was to show how these different models work in the example of Georgia, where two hypermarket retailers compete with each other for one interesting place, in a single road from Tbilisi to the West Georgia, crowded by cars of family moms and housewives, by citizens, many tour operators, tourist buses, and single travelers. This research shows the opinion of customers and their point of views about the retailers in such a strategic area. These opinions work in comprehensive ways rationally and emotionally which are related to price, primary characteristics, secondary features, product reliability of the rational side and quality, credibility and feelings about the emotional way in the Georgian market of hypermarket retailing. This research was conducted to study the market share prediction of retailers by retailing place marketing and expectancy value models. Quantitative and qualitative survey was used as the research method to gather primary data by designing questionnaires for 196 samplemembers. Microsoft excel was used to analyze the data gathered from this study. The aim of this research is to further help hypermarket retailers to improve their marketing strategy to increase their market share and also to utilize the consumer expectations, attitudes and behaviors as well.
The New Public Management

CONTENTS List of Figures and Boxes Preface Acknowledgments 1.Studying the New Public Management 2.Case Studies on Public Management Policy-Making 3.Comparative Analysis of Public Management Policy-Making 4.How to Argue about the New Public Management 5.Controversy and Cumulation in NPM Argumentation 6.Conclusion Notes References Subject Index Name Index