Miracle-dz/UniFAR-FTUs huggingface dataset:
Title: European multicentre study validates ELF test as biomarker of fibrosis in systemic sclerosis 

Objectives: To validate in a international multicentre cohort the role of Enhanced Liver Fibrosis (ELF) test and its components amino-terminal pro-peptide of procollagen type III (PIIINP), tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) and hyaluronic acid (HA)are biomarkers of overall fibrosis in systemic sclerosis (SSc). Methods: Two hundred fifty-four SSc patients from six European Rheumatology Centres were included in this study. Clinical data were collected at time of sampling. Serum samples were collected and stored according to EUSTAR biobanking recommendations. Sera were analysed employing a high-throughput in vitro diagnostic (Siemens AlphaCentaur). Statistical analysis was performed with SPSS software for Mac V.24. 0. Results: Two hundred forty-seven SSc patients were analysed. Patients had a mean age 55.7 ± 13.9 years, and included 202 females and 80 patients with diffuse cutaneous SSc (dcSSc). ELF score, TIMP-1, PIIINP levels were higher in males and in dcSSc. ELF score and the single markers significantly correlated with the degree of skin involvement and inversely correlated with FVC%, TLC % and DLCO%. Concordantly, all markers significantly correlated with skin, lung and total Medsger’s disease severity score. Multivariate analysis indicated that age, mRSS and DLCO% were independently associated with ELF score. Conclusions: This study confirms in a second independent multicentre cohort the value of ELF score as independent marker of skin and lung involvement in SSc. A longitudinal study paired with analysis of large cohort of healthy controls is currently on going to identify a SSc specific test with the highest predictive value for skin and lung progression independently of age and gender.
A MEASUREMENT MODEL OF RISK PERCEPTION IN INTERNET BANKING BASED ON MALAYSIAN CONTEXT

Internet banking risks continue to intensify as accessibility to banking transactions around the world expands. Banks in Malaysia are faced with among the largest number of cyber-threats in the world. Considering these factors, the understanding of internet banking risks is important to enable banks to develop appropriate counter-measures. However, studies on internet banking in Malaysia have not examined risk factors in a comprehensive manner. Therefore, the purpose of this study was to test a measurement model for perceived risk in Internet banking using structural equation modeling analysis. This study extends the Technology Acceptance Model by incorporating seven risk constructs into the model to understand the impact of risks on intention to use internet banking in Malaysia. The survey method was used in the study and the data collection instruments were questionnaires, which were distributed through the drop-off and pick-up (DOPU) technique, to bank branch managers. The purposive sampling technique was employed to determine the respondents, individuals using Internet banking services in Peninsular Malaysia. A total of 413 questionnaires were analyzed using Structural Equation Modeling (SEM) with the Analysis of Moment Structures (AMOS) software. The results clearly indicate that perceived risk dimensions are strong determinants of intention to use internet banking. Furthermore, the seven dimensional measure of perceived risk is supported by acceptable fit indices. All dimensions showed modest but not high intercorrelations, as such, a second order measure of risk was ruled out. The distinctiveness of different risk measures were confirmed by the satisfactory discriminant validity assessment. This research draws together the key risk factors that need to be addressed by internet banking providers in Malaysia to ensure effective adoption and highlights the need to use risk as a multi-dimensional measure in future internet banking studies.
OP-ICBJ190075 1..11

Synopsis Coral reefs are faced with almost complete destruction by the end of the century due to global warming unless humanity can cap global temperature rise. There is now a race to develop a diverse set of solutions to save coral reefs. In this perspective, a case is made for understanding the cell biology of coral–dinoflagellate symbiosis to help inform development of solutions for saving reefs. Laboratory model systems for the study of coral symbiosis, including the sea anemone Exaiptasia pallida, are featured as valuable tools in the fight to save corals. The roles of host innate immunity and inter-partner nutrient dynamics in the onset, ongoing maintenance, and dysregulation of symbiosis are reviewed and discussed. Key innate immune genes and pathways, such as glycan–lectin interactions, the sphingosine rheostat, and the cytokine transforming growth factor beta are shown to modulate a host immune response in the symbiotic state. An upset in the homeostatic inorganic nutrient balance during heat stress and high exogenous nutrient availability is credited with driving the partnership toward dysregulation and coral bleaching. Specific examples are given where knowledge of the cell biology of symbiosis is informing the development of solutions, including studies showing clear limitations in the value of partner switching and acclimatization protocols. Finally, emphasis is placed on rapid advancement of knowledge to try to meet the urgent need for solutions. This includes real-time open communication with colleagues on successes and failures, sharing of resources and information, and working together in the spirit of a collective mission to save coral reefs.
Risk Premium Shocks Can Create Inefficient Recessions

We develop a simple flexible-price model of business cycles driven by spikes in risk premiums. Aggregate shocks increase firms’ uninsurable idiosyncratic risk and raise risk premiums. We show that risk shocks can create quantitatively plausible recessions, with contractions in employment, consumption, and investment. Business cycles are inefficient—output, employment, and consumption fall too much during recessions, compared to the constrained-efficient allocation. Optimal policy involves stimulating employment and consumption during recessions.
Ingestive Behavior and Nutritional and Physiological Parameters of Sheep Fed Diets Based on Cashew Byproduct

Clésio dos Santos Costa Tallita da Ponte Ribeiro Roberto Cláudio Fernandes Franco Pompeu Fernando Lisboa Guedes Marco Aurélio Delmondes Bomfim Arnaud Azevedo Alves Luciana Freitas Guedes Delano de Sousa Oliveira Marcos Cláudio Pinheiro Rogério 1. Department of Animal Science, Federal University of Ceará, Fortaleza, Ceará, Brazil 2. Department of Animal Science, State University Vale do Acaraú,, Sobral, Ceará, Brazil 3. Brazilian Agricultural Research Corporation, Embrapa Goats & Sheep, Estrada Sobral-Groaíras, Km 04, 62.011-970, Sobral, Ceará, Brazil 4. Department of Animal Science, Federal University of Piauí, Teresina, Piauí, Brazil
COMPARISON OF THE PERFORMANCE OF THE METOFFICE UK-WATERS WAVE MODEL WITH A NETWORK OF SHALLOW WATER MOORED BUOY DATA

The design and management of most coastal engineeringand operational shoreline management schemes, within the UK, has relied historically upon hindcast synthetic wave data and numerical models of wave transformations, to provide wave climate design conditions and operational management data. Such data sets are occasionally supplemented with short time series of localized wave data but hitherto there has been no systematic shallow water wave measurement programme off the UK coast. Some long-term buoy measurements are available for sites on the UK shelf, but these are all in deep-water conditions.
Prognostic significance of renal arterial resistance index in living related kidney transplant recipients from elderly donors

The aim of this study was to evaluate the clinical correlation of the renal arterial resistive index (RRI) in living related kidney transplantation (LRKT) recipients from elderly donors as well as its role in predicting outcome of patients and grafts. 136 LRKT recipients from elderly donor with blood pressure monitoring and renal color doppler ultrasonography as well as laboratory tests. We analyzed the association between RRI value and its baseline characteristics. Next, univariate survival analysis was performed using Kaplan-Meier method and the Log-rank test. Finally, a Cox multivariate analysis model was performed to investigate the predictor role of RRI in recipient’s survival. We found that RRI was related to recipient age, serum creatinine and eGFR measured at day 7 after LRKT. However, there was no difference observed in gender, BMI, immunosuppressive regimen, blood pressure and proteinuria. Kaplan-Meier analysis with the log-rank test revealed that high RRI (>0.7) had a significant impact on recipient overall survival. Finally, in a multivariate Cox model, we found that high RRI value was an independent poor prognostic factor for overall survival rate. Our results indicated that RRI was an important indicator in LRKT recipients from elderly donor.
Associative Memory and Belief Formation

Information is often embedded in memorable contexts, which may cue the asymmetric recall of similar past news through associative memory. We design a theory-driven experiment, in which participants observe signals about hypothetical companies. Here, identical signal realizations are communicated with identical contexts: stories and images. Because participants asymmetrically remember those past signals that get cued by the current context, beliefs systematically overreact. This overreaction depends in predictable ways on the signal history; the correlation between signals and contexts; and the scope for forgetting and associative memory. We quantify these results by structurally estimating a model of associative recall.
A Model of Synaptic Formation Neurons in a Network

In our days, there is a need of designing a more realistic model of a dynamic complex neural system. The inspiration arise from the biological hypothesis about the functionality of certain subsystems of the nervous system. An idea, that began in some previous papers, was materialized in the construction of the so called prion neural system. The present article focuses on the way the synapses between neurons of a network can be modeled by designing the binding affinities between them. Of biological inspiration is also the original idea that governs this article: in a network of neurons any neuron should not be able to bind with any other neuron. This is the reason we present a model of synaptic formation between different kinds of neurons in a network. A detailed case of study is presented in the end of
Moving Forward with Learning Analytics: Expert Views

Learning analytics involve the measurement, collection, analysis, and reporting of data about learners and their contexts, in order to understand and optimise learning and the environments in which it occurs. Since emerging as a distinct field in 2011, learning analytics has grown rapidly, and early adopters around the world are already developing and deploying these new tools. This paper reports on a study that investigated how the field is likely to develop by 2025, in order to make recommendations for action to those concerned with the implementation of learning analytics. The study used a Policy Delphi approach, presenting a range of future scenarios to international experts in the field and asking for responses related to the desirability and feasibility of these scenarios, as well as actions that would be required. Responses were received from 103 people from 21 countries. Responses were coded thematically, inter-rater reliability was checked using Cohen’s kappa coefficient, and data were recoded if kappa was below 0.6. The seven major themes that were identified within the data were power, pedagogy, validity, regulation, complexity, ethics, and affect. The paper considers in detail each of these themes and its implications for the implementation of learning analytics.
Analysis of illness uncertainty and the related factors in patients undergoing heart valve surgeries during the perioperative period

Objective: This study was designed to explore the uncertainty in illness during the perioperative period for patients undergoing heart valve surgeries and analyze the related factors. Methods: A total of 162 patients who have received heart valve surgeries were selected as subjects. General information investigation scale, self-efficacy evaluation scale, medical coping modes questionnaire and Connor-Davidson resilience scale were used to gather relevant information before operation, while Mishel uncertainty in illness scale (MUIS) was used one day before operation and one day before hospital discharge to assess the level of illness uncertainty in patients and analyze relevant influential factors. Results: The scores of ambiguity, complexity, deficit information and unpredictability and total MUIS score for patients one day before hospital discharge were significantly lower than those for patients one day before operation (P<0.001). Age, years of education, average monthly family income, marital status, number of heart valve surgeries, complications and self-efficacy had significant effects on patients’ perception of uncertainty in illness before operation (P<0.05). Pearson correlation analysis showed that there was a significant negative correlation between the total MUIS score one day before operation and resilience, self-reliance, optimism, confrontation, resignation, utilization of support, objective support and total social support (P<0.05), and there was a significant positive correlation between the total MUIS score and avoidance (P<0.05). Multivariate logistic regression analysis showed that age, years of education, number of heart valve surgeries, monthly family income, self-reliance, optimism, confrontation and resignation were important risk factors for illness uncertainty in patients before operation (P<0.05). Conclusion: The illness uncertainty felt by patients undergoing heart valve surgeries is at a medium level. Age, education background, number of heart valve surgeries, monthly family income, psychological resilience and coping modes are main factors affecting illness uncertainty in patients.
Hyperarticulation in Lombard speech: A preliminary study

Over the last century researchers collected a considerable amount of data reﬂecting the properties of Lombard speech, i.e., speech in a loud environment. The documented phenomena include effects on intensity, fundamental frequency, spectral tilt, speech rate and articulation. Relatively little attention has been paid to the effects on relative extent of movement of individual articulators. In an attempt to ﬁll in this gap we present a preliminary analysis of EMA data collected in increasing levels of babble noise. We introduce HH-index as a measure of overall relative activity of articulators. Our results indicate a non-linearity of the effect of noise on articulatory movement and quantitatively different effects on the movement extent for different groups of articulators. The effects of noise are compared with those brought out by other techniques for eliciting articulatory variation. We also discuss possible application of Lombard speech as an elicitation paradigm for studies of hyperarticulation.
Arabic Tweeps Traits Prediction AT2P

Author profiling is the process of extracting author traits, which constitute the profile of an author, by analyzing his/her writings. Detecting these traits is useful and important process in the domain of social media analysis. In this notebook, we present our approach for author profiling task that is one of the tasks required in “Author Profiling and Deception Detection in Arabic (APDA)” workshop 2019. The focus of this task is to identify the age, gender, and language variety of Arabic Twitter users (tweeps). For this purpose, several feature vectors and classifiers were evaluated to find out the best prediction models for the three traits. SMO classifier with the feature vector that consisted of UniGram and Stem was the best model for each three traits: gender, age and variety 1 .
A Durational Study of German Speech Rhythm by Chinese Learners

This study focuses on the temporal and metrical features of the German speech produced by Chinese speakers. German is described to be a stress-timed language, while standard Chinese is regarded as a syllable-timed language. It has been suggested that the rhythm of the target language can be inﬂuenced by the learners’ native language. In this study we conducted an investigation of ten sentences with 18 Chinese students in the low in-termediate proﬁciency level in comparison with six native German speakers. We compared the duration values in terms of pairwise variability indices, and found that most of these Chinese speakers have a lower nPVI-V and a higher rPVI-C than the German speakers. We illustrate that the conventional duration measures of nPVI-V can be inﬂuenced by the syllable structures of the utterance and the classiﬁcation approach of vocalic intervals, and a comparable nPVI-V can hardly be expected from different investigations. Furthermore, we argue that duration values alone cannot fully capture the rhythmic patterns of speech because other prosodic parameters such as pitch and energy also join to contribute to rhythmic characteristics of the speech.
Probabilistic Aquatic Exposure Assessment for Pesticides I: Foundations

Models that capture underlying mechanisms and processes are necessary for reliable extrapolation of laboratory chemical data to field conditions. For validation, these models require a major revision of the conventional model testing paradigm to better recognize the conflict between model user’s and model developer’s risk (as Type I and Type II errors) in statistical testing of model predictions. The predictive reliability of the models must be hypothesized and tested by methods that lead to conclusions of the form “the model predictions are within a factor-of-two of reality at least 95% of the time. ” Once predictive reliability is established, it can be treated as a “method error” within a probabilistic risk assessment framework. This report, developed under APM 131 (“Develop a Probability-Based M ethodology for Conducting Regional Aquatic Ecosystem Exposure and V ulnerability Assessments for Pesticides”), describes a step-by-step process for establishing the predictive reliability of exposure models. Monte Carlo simulation is the preferred method for capturing variability in environmental driving forces and uncertainty in chemical measurements. Latin Hypercube Sampling (LHS) software is under development to promote efficient computer simulation studies and production of tabular and graphical outputs. Desirable outputs include exposure metrics tailored to available toxicological data expressed as distribution functions (pdf, cdf) and, if needed, empirical distribution functions suitable for use in M onte Carlo risk assessments combining exposure and effects distributions. ORD numerical models for pesticide exposure supported under this research program include a model of spray drift (AgDisp), a cropland pesticide persistence model (PRZM ), a surface water exposure model (E XA M S), and a model of fish bioaccumulation (BASS). A unified climatological database for these models is being assembled by combining two National Weather Service (N W S) products: the Solar and Meteorological Surface Observation Network (SAMSON) data for 1961-1990, and the Hourly United States Weather Observations (H U SW O) data for 1990-1995. Together these N W S products provide coordinated access to solar radiation, sky cover, temperature, relative humidity, station atmospheric pressure, wind direction and speed, and precipitation. By using observational data for the models, “trace-matching” M onte Carlo simulation studies can transmit the effects of environmental variability directly to exposure metrics, by-passing issues of correlation (covariance) among external driving forces. Additional datasets in preparation include soils and land-use (planted crops) data summarized for the State divisions of Major Land Resource Areas (MLRA), derived from National Resource Inventory (NRI) studies. This report covers a period from May 2, 2001 to September 30, 2001 and work was completed as of September 30, 2001.
ALUMINA COATINGS BY ELECTRON BEAM EVAPORATION

In this chapter we have discussed the characterization results of alumina coatings deposited by electron beam evaporation technique. Alumina coatings were characterized by Grazing incidence X-ray diffraction (GIXRD), UV-visible absorption spectroscopy, Atomic Force Microscopy (AFM), Nanoindentation, Field Emission Scanning Electron Microscopy (FESEM) and 27 Al MAS NMR spectroscopy. The details of thin film deposition and the characterization results are discussed below:
Using Math to Explore Social Issues

This study examines high school students’ views of mathematics as a tool for social inquiry in light of their classroom experiences using mathematics to explore social issues. A critical theoretical perspective on mathematics literacy is used to ascertain the ways in which their views challenge or affirm the dominant image of mathematics in society. The study concludes that mathematics applications addressing social justice issues are promising vehicles for developing students’ appreciation of mathematics as a social problemsolving tool, an awareness of its limitations, and a healthy skepticism toward its uses. Introduction U.S. schools are under considerable pressure to get students to learn more mathematics. A mathematically literate populace is deemed essential for enhancing our country’s economic competitiveness. Less frequently heard in discourse on education reform is the importance of mathematics literacy for informed and active democratic citizenship in technologically advanced countries such as our own where mathematics is increasingly used to characterize societal problems and formulate solutions to them. Without some mathematical competence, ordinary citizens are unlikely to comprehend, let alone influence, many of the decisions and actions of those in power in political, social, and economic institutions. This lack of agency by ordinary citizens undermines democracy (Apple, 1992; Bohl, 1998; Christiansen, 1996; Davis, 1993; Ernest, 1991; Frankenstein, 1983; Gellert, Jablonka, & Keitel, 2001; Skovsmose, 1994a; Tate, 1996). Progressive educators have long viewed schooling as essential for developing the competencies and dispositions that are needed to create a more democratic and just society. Dewey envisioned classrooms as places where citizenship could be meaningfully practiced as students freely engaged in social inqury, grappling with the unresolved social issues of their time. In bringing disciplinary knowledge and democratic values to bear on deliberations of these issues, youth develop, in part, the capacities and dispositions needed for present and future participation in political life. The insights that mathematics can contribute to an understanding of societal problems are lost on many U.S. high school students, however. “What good is this stuff? ” is a question they too often ask their teachers about the mathematics they are learning (Research Advisory Committee [RAC], 2000). This is not surprising given that school mathematics is a subject that traditionally has been divorced from the problems of society (Frankenstein, 1989; Gutstein, 2003). Two important documents for mathematics education address this issue— the National Council of Teachers of Mathematics’ (NCTM) (2000) Principles and Standards for School Mathematics Anastasia Brelias is an associate professor at Northeastern Illinois University in Chicago, Illinois. This article is based on the author’s doctoral dissertation. Submit a response to this article Submit online at democracyeducationjournal.org/home Read responses to this article online http://democracyeducationjournal.org/home/vol23/iss1/4