Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study into Methodological Issues in Cross-Cultural Pragmatic Research

: The methodological issues are one of the areas of pragmatics which have gained considerable attention recently. The foundation of basic instruments in speech act research can be placed in a two-polar continuum. At one end, there are the perception/comprehension methods and at the other end production methods are placed. Each level then has its own specific instruments. As for the perception/comprehension methods, instruments such as rating, multiple choice, and interview tasks can be utilized. In production methods, instruments such as discourse completion, closed role play, open role play, and observation of authentic discourse are placed (Kasper & Dahl, 1991). Furthermore, methods can be categorized according to an elicited/observational continuum. In the elicited end, methods such as rating, multiple choice, interview tasks, discourse completion, closed role play, and open role play are placed. In the observational end, observation of authentic discourse is used. This study is useful for those novice researchers who are interested in conducting pragmatic studies and may not be familiar which instrument they should use in particular situation.
Geometric asymptotics and beyond

The analysis of Einstein's field equations in the context of Penrose's notion of asymptotic simplicity, which was originally intro- duced to provide a geometric setting for the investigation of gravitational radiation, reveals the existence of conformal representations of the field equations which imply evolution equations that are hyperbolic up to and beyond conformal infinity. This peculiar feature of the equations al- lows us to formulate various well-posed initial and initial-boundary value problems for the conformal field equations which lead to general large scale existence and strong stability results as well as to sharp results on the asymptotic behaviour and the conformal extensibility of solutions to Einstein's field equations. We discuss the physical relevance of these results and various open questions. Enormous progress has been made in the last hundred years in the investigation of Einstein's field equations, their solutions, their solution manifold, and thus the content of the theory. Research on the equations has been largely guided by physical ideas but unforeseen mathematical results repeatedly asked for revisions, a process that may not have come to an end yet (56). Mathematical analysis including approximations and formal expansions led Einstein to an approximate notion of gravitational radiation and prepared the way to the invariant concept available today. Explicit solutions, mainly dealing with highly symmetric and idealized situations, revealed physical phenomena on global scales (horizons, black holes, singularities) which had not been anticipated and which sometimes took years to be absorbed into a coherent world view. The abstract analysis of the field equations, dealing with the existence of solutions and their parametrization in terms of boundary data, evolved rather slowly, even after the breakthrough marked by the work of Choquet-Bruhat (21). More
Evaluating Two Array Autocalibration Methods with Multifrequency HF Radar Current Measurements

AbstractOne pivotal factor affecting the accuracy of HF radar current measurements is the direction of arrival (DOA) estimation performance of the current signal. The beamforming technology or superresolution algorithm cannot always perform best in practical applications because of the phase errors existing in array channels. These phase errors, which cause uncertain estimation of DOA, lead to confused values in radial current maps. To solve this problem, this paper is focused on discussing the performances of two autocalibration methods using sea echoes for multifrequency high-frequency (MHF) radar current measurements. These two array calibration methods, based on maximum likelihood (ML) and multiple signal classification (MU), first seek single-DOA sea echoes and then gather them for array calibration using different cost functions. The ML and MU methods provide approximate mean phases, while the standard phase errors of the MU method are smaller. After array calibration using these two methods, the re.
Electric-field effects on thickness dependent magnetic anisotropy of sputtered MgO/Co40Fe40B20/Ta structures

We have investigated the effect of applied electric field EG on thickness dependent magnetic anisotropy of sputtered Co40Fe40B20 sandwiched with MgO and Ta. The range of CoFeB thickness explored is 2 nm and below. As the thickness is reduced, the easy axis of magnetization becomes perpendicular from in-plane. We show that perpendicular magnetic anisotropy of in-plane samples and coercivity of perpendicular samples can be modified by applying EG at room temperature. Furthermore, superparamagnetic behavior is observed for CoFeB layers with further reduced thickness below ≈0.9 nm, where electric-field effect is also observed below their blocking temperature.
Supermassive Black Holes in Deep Multiwavelength Surveys

In recent years deep X-ray and infrared surveys have provided an efficient way to find accreting supermassive black holes, otherwise known as active galactic nuclei (AGN), in the young universe. Such surveys can, unlike optical surveys, find AGN obscured by high column densities of gas and dust. In those cases, deep optical data show only the host galaxy, which can then be studied in greater detail than in unobscured AGN. Some years ago the hard spectrum of the X-ray "background" suggested that most AGN were obscured. Now GOODS, MUSYC, COSMOS and other surveys have confirmed this picture and given important quantitative constraints on AGN demographics. Specifically, we show that most AGN are obscured at all redshifts and the amount of obscuration depends on both luminosity and redshift, at least out to redshift z~2, the epoch of substantial black holes and galaxy growth. Larger-area deep infrared and hard X-ray surveys will be needed to reach higher redshifts and to probe fully the co-evolution of galaxies and black holes.
Proteolytic and N -Glycan Processing of Human Alpha-1 Antitrypsin Expressed in Nicotiana benthamiana

SUMMARY Extensive glycoengineering or deficiency of apoplast-located beta-hexosaminidase 3 prevents the formation of paucimannosidic N-glycans on recombinant Alpha-1 Antitrypsin processed by serine proteases. ABSTRACT Plants are increasingly being used as an expression system for complex recombinant proteins. However, our limited knowledge of the intrinsic factors that act along the secretory pathway, which may compromise product integrity, renders process design difficult in some cases. Here, we pursued the recombinant expression of the human protease inhibitor alpha-1 antitrypsin (A1AT) in Nicotiana benthamiana . This serum protein undergoes intensive posttranslational modifications. Unusually high levels of recombinant A1AT were expressed in leaves (up to 6 mg/g leaf material) in two forms: (i) full-length A1AT located in the endoplasmic reticulum (ER) displaying inhibitory activity; and (ii) secreted A1AT processed in the reactive centre loop, thus rendering it unable to interact with target proteinases. We found that the terminal protein processing is most likely a consequence of the intrinsic function of A1AT, i.e. its interaction with proteases (most likely serine proteases) along the secretory pathway. Secreted A1AT carried vacuolar-type paucimannosidic N -glycans, generated by the activity of hexosaminidases located in the apoplast/plasma membrane. Notwithstanding, an intensive glycoengineering approach led to secreted A1AT carrying sialylated N -glycan structures largely resembling its serum-derived counterpart. In summary we elucidate novel insights in plant glycosylation processes and show important aspects of post ER protein processing in plants.
The Multidimensional Heston Stochastic Volatility Model based on Wishart Processes

In this thesis we study the one-dimensional Heston stochastic volatility model and its multivariate extension, the so-called multidimensional Heston stochastic volatility model. While the variance process equals the well-known Cox-Ingersoll-Ross process in the onedimensional setup, the covariance process of the multidimensional Heston stochastic volatility model follows the Wishart process introduced by M. -F. Bru. Both stochastic volatility models belong to the class of affine models whose characterizing property is the exponential affine form of the conditional characteristic function. A detailed study of the multidimensional Heston stochastic volatility model is given, and interesting relations between the marginals of the multidimensional Heston stochastic volatility model and the one-dimensional Heston stochastic volatility model are derived. Moreover, small time asymptotics for the implied volatility of a call written on one asset in the multidimensional Heston stochastic volatility model are considered. We show that an expansion of the asymptotic implied volatility proved by M. Forde and A. Jacquier for the one-dimensional Heston stochastic volatility model can be extended to the multidimensional one.
Consistency preservation methods for multi-scale design of subway infrastructure facilities

This thesis presents novel consistency preservation methods for the multi-scale design of infrastructure facilities. A comprehensive multi-scale product model for shield tunnels is presented, where space and physical objects are associated with five Levels-of-Detail (LoD). In order to guarantee the geometric consistency across the different LoDs, this thesis introduces a novel geometric modeling method which allows automated cross-LoD consistency preservation based on parametric techniques.
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Dose, Infection, and Disease Outcomes for Coronavirus Disease 2019 (COVID-19): A Review

Abstract The relationship between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) dose, infection, and coronavirus disease 2019 (COVID-19) outcomes remains poorly understood. This review summarizes the existing literature regarding this issue, identifies gaps in current knowledge, and suggests opportunities for future research. In humans, host characteristics, including age, sex, comorbidities, smoking, and pregnancy, are associated with severe COVID-19. Similarly, in animals, host factors are strong determinants of disease severity, although most animal infection models manifest clinically with mild to moderate respiratory disease. The influence of variants of concern as it relates to infectious dose, consequence of overall pathogenicity, and disease outcome in dose–response remains unknown. Epidemiologic data suggest a dose–response relationship for infection contrasting with limited and inconsistent surrogate-based evidence between dose and disease severity. Recommendations include the design of future infection studies in animal models to investigate inoculating dose on outcomes and the use of better proxies for dose in human epidemiology studies.
Smart services – characteristics, challenges, opportunities and business models

Abstract “Industry 4.0”, “Digitalization”, “Internet of Things” and “Smart Services” are the today’s buzzwords when tracking economic news. It is to ask about the meaning of those phrases. The world has changed over the last decade from a mainly physical to software controlled economy and the information technology has become an integral part of our industry and society in its entirety. Nowadays it is no longer the product that matters it is the data that are generated by using the product or service. Those usage data collected and analyzed commence new business models and services. The economic future of a company will much more rely on the ability to collect and use the data to generate Smart Services for their customers and to transform from a simple product supplier to an entertainment provider. However there are not only opportunities there are also challenges on the way to that new services which needs to be known and considered. For instance the development cycles need to be faster, the business models need to be adjusted and the positive financial results will not come into the picture on the first day. Based on those thoughts and while there only a handful of researches about that new services exists, the main purpose of the present study is at first, to gain a common understanding about the meaning and the characteristics of Smart Services and their adjacencies. Secondly, the study summarizes the identified challenges and opportunities in relation to them. Thirdly, the author introduce and explain the main business models usable for those Smart Services and the requirements for starting the transformation towards those services. The aim of this paper is to set a basis for this exciting and relatively unsought topic and to produce an interest in further empirical and practical researches in this area. The methodologies used for this research are a systematic literature review and an evaluation of existing studies with the subjects “Industrie 4.0”, “Digitization”, “Internet of Things” and “Smart Services”. Additional national initiated programs and best-practice of transformations where analyzed and interpreted. The outcome of the study is always focused on service providers.
Modelling, detection and mitigation of impulsive noise and narrowband interference for indoor broadband power line communication

Broadband power line communication (PLC) is a promising technology for the convergence of Internet, data and video for indoor networking. Impulsive noise (IN) and narrowband interference (NBI) are crucial affecting factors of the PLC system performance and cause harmful pollution to the PLC spectrum. In this thesis, a thorough study of IN and NBI is presented ranging from measurement, modelling, detection and mitigation techniques, and performance analysis. In the first contribution, the modelling of aperiodic IN for PLC is investigated. To the best of our knowledge, this is the first work to model the correlation between consecutive impulses for PLC, using a hybrid model which includes the weighted contributions of deterministic and random patterns of individual impulses in a burst. The occurrence dependence between bursts and between impulses in a burst is described by a two-level Markov Chain (MC) based model. An intensive performance analysis of the proposed models is provided. The effectiveness of the models is verified by measured results. In the second contribution, the modelling of radio NBI for PLC is investigated. A novel three-dimensional (3D) MC based statistical model is developed, to model the occurrence of NBI which is associated with the behaviours of certain radio users. An intensive performance analysis on the impact of the NBI on PLC is provided. The effectiveness of the proposed model is verified by measured results. The 3D MC model can be used for optimising cognitive PLC networks. In the third contribution, detection and mitigation of aperiodic IN over uncoded orthogonal frequency division multiplexing (OFDM) PLC systems is inves-
Riemannian Foliations and the Topology of Lorentzian Manifolds

A parallel lightlike vector field on a Lorentzian manifold $X$ naturally defines a foliation $\mathcal{F}$ of codimension one. If either all leaves of $\mathcal{F}$ are compact or $X$ itself is compact admitting a compact leaf and the (transverse) Ricci curvature is non-negative then a Bochner type argument implies that the first Betti number of $X$ is bounded by $1 \leq b_{1} \leq \dim X$ if $X$ is compact and $0 \leq b_{1} \leq \dim X -1$ otherwise. We show that these bounds are optimal and depending on the holonomy of $X$ we obtain further results. Finally, we classify the holonomy representations for those $X$ admitting a compact leaf with finite fundamental group.
Nonlinear Autoregressive Neural Network Models for Prediction of Transformer Oil-Dissolved Gas Concentrations

Transformers are one of the most important part in a power system and, especially in key-facilities, they should be closely and continuously monitored. In this context, methods based on the dissolved gas ratios allow to associate values of gas concentrations with the occurrence of some faults, such as partial discharges and thermal faults. So, an accurate prediction of oil-dissolved gas concentrations is a valuable tool to monitor the transformer condition and to develop a fault diagnosis system. This study proposes a nonlinear autoregressive neural network model coupled with the discrete wavelet transform for predicting transformer oil-dissolved gas concentrations. The data fitting and accurate prediction ability of the proposed model is evaluated in a real world example, showing better results in relation to current prediction models and common time series techniques.
Extracellular Vesicles in Trypanosoma cruzi Infection: Immunomodulatory Effects and Future Perspectives as Potential Control Tools against Chagas Disease

Chagas disease, caused by the protozoa parasite Trypanosoma cruzi, is a neglected tropical disease and a major public health problem affecting more than 6 million people worldwide. Many challenges remain in the quest to control Chagas disease: the diagnosis presents several limitations and the two available treatments cause several side effects, presenting limited efficacy during the chronic phase of the disease. In addition, there are no preventive vaccines or biomarkers of therapeutic response or disease outcome. Trypomastigote form and T. cruzi-infected cells release extracellular vesicles (EVs), which are involved in cell-to-cell communication and can modulate the host immune response. Importantly, EVs have been described as promising tools for the development of new therapeutic strategies, such as vaccines, and for the discovery of new biomarkers. Here, we review and discuss the role of EVs secreted during T. cruzi infection and their immunomodulatory properties. Finally, we briefly describe their potential for biomarker discovery and future perspectives as vaccine development tools for Chagas Disease.
A WEAKLY TURBULENT PLASMA IN A MAGNETIC FIELD

Equations describing the behavior of a weakly turbulent plasma in a magnetic field are derived by taking into account interaction between the waves. In such a plasma the interaction between various oscillations is sufficiently small and can be taken into account by expanding in powers of the square of the oscillation amplitude. The problem of anomalous diffusion of a plasma in a magnetic field in the presence of osciliations is discussed. (auth)
The Space of Actions, Partition Metric and Combinatorial Rigidity

We introduce a natural pseudometric on the space of actions of $d$-generated groups, such that the zero classes are exactly the weak equivalence classes and the metric identification with respect to this pseudometric is compact. We analyze convergence in this space and prove that every class contains an action that properly satisfies every combinatorial type condition that it satisfies with arbitrarily small error. We also show that the class of every free non-amenable action contains an action that satisfies the measurable von Neumann problem. The results have analogues in the realm of unitary representations as well.
Joint data analysis in nutritional epidemiology

Background: Joint data analysis from multiple nutrition studies may improve the ability to answer complex questions regarding the role of nutritional status and diet in health and disease. Objective: The objective was to identify nutritional observational studies from partners participating in the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) Consortium, as well as minimal requirements for joint data analysis. Methods: A predefined template containing information on study design, exposure measurements (dietary intake, alcohol and tobacco consumption, physical activity, sedentary behavior, anthropometric measures, and sociodemographic and health status), main health-related outcomes, and laboratory measurements (traditional and omics biomarkers) was developed and circulated to those European research groups participating in the ENPADASI under the strategic research area of “diet-related chronic diseases. ” Information about raw data disposition and metadata sharing was requested. A set of minimal requirements was abstracted from the gathered information. Results: Studies (12 cohort, 12 cross-sectional, and 2 case-control) were identified. Two studies recruited children only and the rest recruited adults. All studies included dietary intake data. Twenty studies collected blood samples. Data on traditional biomarkers were available for 20 studies, of which 17 measured lipoproteins, glucose, and insulin and 13 measured inflammatory biomarkers. Metabolomics, proteomics, and genomics or transcriptomics data were available in 5, 3, and 12 studies, respectively. Although the study authors were willing to share metadata, most refused, were hesitant, or had legal or ethical issues related to sharing raw data. Forty-one descriptors of minimal requirements for the study data were identified to facilitate data integration. Conclusions: Combining study data sets will enable sufficiently powered, refined investigations to increase the knowledge and understanding of the relation between food, nutrition, and human health. Furthermore, the minimal requirements for study data may encourage more efficient secondary usage of existing data and provide sufficient information for researchers to draft future multicenter research proposals in nutrition. J Nutr 2018;148:285–297.
The Iron Kα Line Profile in NGC 4151

We present the first measurements of the Fe Kα line profile in NGC 4151 from ASCA observations performed in 1993 May, November, and December. The apparent line profile is asymmetric, consisting of a peak at ~6.3-6.4 keV, a sharp drop on the blue side below ~7 keV, and a broad red wing extending to ~4-5 keV. This first clear indication of complex structure confirms earlier tentative measurements of the Fe-K region with the Broad Band X-Ray Telescope (BBXRT). The line intensity, equivalent width, and detailed shape are model dependent. Interpretation of the profile in terms of emission from a disk rotating around a central black hole strongly constrains the putative disk to be face on, but this contradicts the current body of knowledge of the geometry of this source. If the apparent red wing is not in fact part of a peculiar continuum, then a face-on disk may be allowed only if the collimated structure observed at the parsec scale is misaligned with respect to the disk normal by at least 20° and iron is overabundant by a factor of ~2, with some additional caveats. Alternatively, a different geometry of line-emitting material may be required. In contrast to clear variability in the soft X-ray line emission below ~1 keV between the observations, these data show no significant variability of the Fe Kα overall line shape, intensity, or equivalent width.
Spin liquid phase of the S = 1 2 J 1 − J 2 Heisenberg model on the triangular lattice

Author(s): Zhu, Z; White, SR | Abstract: © 2015 American Physical Society. We study the S=1/2 Heisenberg model on the triangular lattice with nearest- and next-nearest-neighbor interactions J1 and J2 with the density matrix renormalization group, on long open cylinders with widths up to nine lattice spacings. In an intermediate J2 region 0. 06â‰J2/J1â‰0.17, we find evidence for a spin liquid (SL) state with short range spin-spin, bond-bond, and chiral correlation lengths, bordered by a classical 120° Neel ordered state at small J2 and by a two sublattice collinear magnetically ordered state at larger J2. Focusing on J2/J1=0.1, we find a number of signatures of a gapped SL phase.