Miracle-dz/UniFAR-FTUs huggingface dataset:
Properties of inductively coupled rf Ar/H2 plasmas: Experiment and global model

Experiments with a Langmuir probe and optical emission spectroscopy combined with actinometry are carried out in inductively coupled rf (13.56 MHz) Ar/H2 discharges at total pressures of 20 m, 40 m, and 60 mTorr in hydrogen fractions ranging from 0% to 50%. The measured electron energy probability functions (EEPFs), which deviate from the Maxwellian distributions owing to the depletion of high-energy electrons, can be approximated using two temperatures. The electron temperatures, which can be deduced from the slopes of low-energy and high-energy parts of the EEPFs, relatively abruptly increase with increasing the hydrogen fraction in the hydrogen fractions below 10%, whereas the measured electron density markedly decreases with increasing the hydrogen fraction in the hydrogen fractions below 20%. The effective ion mass, which can be estimated from the ion current collected into the probe, markedly decreases with increasing the hydrogen fraction. The density of hydrogen atoms estimated by actinometry mark.
Phenotypic and molecular characterization of resistance to stem rust in wheat cultivars and advanced breeding lines from Iran and Syria

Patpour, M. , Nazari, K. , Ogbonnaya, F. , Alavi, S. M. , and Mousavi, A. 2014. Phenotypic and molecular characterization of resistance to stem rust in wheat cultivars and advanced breeding lines from Iran and Syria. Crop Breeding Journal 4(1):1-14. Seedling and adult-plant response to stem rust of 103 Iranian and Syrian bread and durum wheat genotypes was investigated using stem rust races TKTTC and TTKSK in seedling tests and TKTTC and TTKST at the adult-plant stage. The same genotypes were characterized with simple sequence repeat (SSR), sequence tagged site (STS) and cleaved amplified polymorphic sequence (CAPS) markers linked to Sr2, Sr22, Sr24, Sr25, Sr26, Sr31, Sr36, Sr39, and Sr46. In seedling tests, three phenotypic groups were identified: those lacking effective resistance genes, those postulated to carry Sr31, and those that were resistant to TKTTC and TTKSK. Adult-plant assessment indicated the presence of adult-plant resistance (APR) to TKTTC and TTKST mainly due to Sr2 and uncharacterized resistance gene(s). Using molecular markers, Sr2 was confirmed as the most common resistance gene detected in Iranian genotypes. It was detected alone in 38 genotypes, in combination with Sr31 in 11 genotypes, and combined with Sr31+Sr25 in one genotype. In total, Sr31 was postulated in 19 genotypes. Among Syrian genotypes, Sr2 was detected alone in one and in combination with Sr31 in two bread wheat cultivars. No diagnostic DNA fragment associated with the markers was present in the durum wheat genotypes. Haplotype analysis of 103 genotypes using Sr2-linked markers csSr2 and STS#Sr2 indicated that csSr2 was a better predictor of the presence of Sr2 gene in wheat.
Social media advertising: An investigation of consumer perceptions, attitudes, and preferences for engagement

The rapid rise of social media has captured the attention of marketers and consumers on a global scale, and together with a rapidly changing communications environment marketers now confront new challenges in terms of our understanding of consumer behaviour and consumption patterns in the new millennium. Social media brings with it powerful opportunities for brands to engage with consumers, one method being through interactive advertising. To broaden our understanding and assist in managing marketing communications effectively, this exploratory research investigates the role of social media within the broader advertising and communications mix. Qualitative focus groups were conducted with consumers to assess perceptions and attitudes towards social media advertising, and preferences for brand engagement through this channel. Findings suggest that use of social media advertising in a multichannel communications approach could have powerful impact on brand loyalty and engagement. ANZMAC 2010 Page 2 of 9 2 Social Media Advertising: An Investigation of Consumer Perceptions, Attitudes, and Preferences for Engagement
HIGH REPRESENTATIVE OF THE UNION FOR FOREIGN AFFAIRS AND SECURITY POLICY - ANALYSIS OF THE LISBON TREATY PROVISION

The introduction of the Treaty of Lisbon has brought important changes to the architecture of the European Union and its institutions. The institutional balance of the new structure, which abolished the pillars of the EU, and the external representation of the Union have undergone especially deep changes, focused mainly on the High Representative of the Union for Foreign Affairs and Security Policy. Through literal, systemic and functional interpretation this article provides an analysis of the evolution and content of the provisions concerning the High Representative in order to ascertain the value and effect of the changes introduced. The research indicates that the new legal solutions encompassed by the function of the High Representative, although incomplete, offer many interesting possibilities for consolidating the Union’s institutional structure. Regrettably however, they leave too much to negotiations and political manoeuvring and too little to concrete legal solutions, leaving the Union with an incomplete and unclear external relations institutional structure.
Ground Truth Locations Using Synergy Between Remote Sensing and Seismic Methods

Abstract : In this study, we have relocated a set of 50 ground truth (GT) earthquakes as determined from regional modeling, to estimate the performance of the station correction methodology. We constructed station-specific source correction or 'station correction' surface from 760 station correction (global distribution) based on a small set of five well and closely located earthquakes in the central Tibetan Plateau. The station corrections were interpolated to develop a global surface for P-wave travel time corrections. As a test, we relocated a set of 50 GT earthquakes, with some seismic events located about 800 km from the center of the PASSCAL array across the Tibetan Plateau and surrounding regions. When the corrections were applied to the iasp91 velocity model, the mislocations decreased by an average by 37% for 37 out of the 50 GT events. This indicates significant improvement in seismic event locations relative to using the iasp91 model without P-wave travel-time corrections. Surprisingly, the distribution of mislocations did not vary or correlate with distance and some of the farthest events from the center of the Tibetan Plateau were improved more than the locations in the center where the travel time corrections are more relevant. Myers and Schultz (2000) noted that correction surfaces for nearby stations are similar, suggesting coherent assessment of the results, corrections could be developed from a small cluster of earthquakes and transported for use with seismic events outside of the area out to a radius of 800 km. Additional tests should be performed to further validate these claims especially when crossing tectonic boundaries.
Effect of β Glucan on Haematology of Common Carp (Cyprinus Carpio) Infected by Ectoparasites

In this study, the effects of beta-glucan on haematological parameters of common carp, Cyprinus carpio, which were naturally infested with ecto-parasites were determined. In the experimental group, infested fish were fed with 0.3% beta-glucan containing pellets during thirty days. In control, infested fish were fed with fish pellets without beta-glucan. Blood samples were collected from each group after feeding. Mortality rates, haemoglobin (Hb) (g/dl), haematocrite (hct) (%), erythrocyte (RBC) (x10 6 /mm 3 ), leukocyte (WBC) (x10 3 /mm 3 ) amounts and leukocyte cell types (%) were determined. In comparison with the control group, Hct and WBC amounts were increased in the fish fed with beta glucan (P 0.05) for Hb and RBC amounts. Lymphocytes were decreased, while monocytes and neutrophils were increasing among the leukocyte cell types. Survival rate values were 91.12 and 77.78% for fish fed with β-1,3/1,6 glucan and the control group, respectively.
Building a Survey Tool to Assess Consumers Perception and Behavior Towards Green Consumption

Studies on green consumption behavior in Vietnam are neither popular nor conducted carefully, especially empirical studies. With the aim of contributing to this research field, this paper adopts a new approach to find out consumers’ perception and behaviors towards green consumption by constructing a survey tool. Based upon the conceptual framework developed as a combination of determinants affecting green consumption found in previous studies and Ajzen’s Theory of planned behavior, a sample questionnaire for survey has been designed and pre-tested. The paper also provides guidelines for question design, trials and adjustments.
Firm productivity growth and skill

ABSTRACT This paper examines firm multifactor productivity (mfp) growth and changing skill levels of labour in New Zealand, using NZ microdata for 2001–2012. Strong employment growth for lower skilled workers lowered average skill by 1.8% over the period, with declining unobserved skill (−3.6%) outweighing increasing observed skill (1.8%). Consequently, skill-adjusted mfp growth (0.24% pa) was higher than unadjusted growth (0.14% pa). The impact of skill adjustment was almost entirely due to changing skill composition within continuing firms. Skill dilution was strongest pre-global financial crisis (GFC), and was reversed when employment contracted in 2009 and 2010. Adjusting for skill dilution reveals stronger procyclical variation in mfp.
Synthesis and review: delivering on conservation promises: the challenges of managing and measuring conservation outcomes

Growing threats and limited resources have always been the financial realities of biodiversity conservation. As the conservation sector has matured, however, the accountability of conservation investments has become an increasingly debated topic, with two key topics being driven to the forefront of the discourse: understanding how to manage the risks associated with our conservation investments and demonstrating that our investments are making a difference through evidence-based analyses. A better understanding of the uncertainties associated with conservation decisions is a central component of managing risks to investments that is often neglected. This focus issue presents both theoretical and applied approaches to quantifying and managing risks. Furthermore, transparent and replicable approaches to measuring impacts of conservation investments are noticeably absent in many conservation programs globally. This focus issue contains state of the art conservation program impact evaluations that both demonstrate how these methods can be used to measure outcomes as well as directing future investments. This focus issue thus brings together current thinking and case studies that can provide a valuable resource for directing future conservation investments.
Strong-Motion Observations of the M 7.8 Gorkha, Nepal, Earthquake Sequence and Development of the N-SHAKE Strong-Motion Network

We present and describe strong-motion data observations from the 2015 M 7.8 Gorkha, Nepal, earthquake sequence collected using existing and new Quake-Catcher Network (QCN) and U.S. Geological Survey NetQuakes sensors located in the Kathmandu Valley. A comparison of QCN data with waveforms recorded by a conventional strong-motion (NetQuakes) instrument validates the QCN data. We present preliminary analysis of spectral accelerations, and peak ground acceleration and velocity for earthquakes up to M 7.3 from the QCN stations, as well as preliminary analysis of the mainshock recording from the NetQuakes station. We show that mainshock peak accelerations were lower than expected and conclude the Kathmandu Valley experienced a pervasively nonlinear response during the mainshock. Phase picks from the QCN and NetQuakes data are also used to improve aftershock locations. This study confirms the utility of QCN instruments to contribute to ground-motion investigations and aftershock response in regions where conventional instrumentation and open-access seismic data are limited. Initial pilot installations of QCN instruments in 2014 are now being expanded to create the Nepal–Shaking Hazard Assessment for Kathmandu and its Environment (N-SHAKE) network. Online Material: Figures of Pg arrivals, earthquake locations, epicenter change vectors, and travel-time misfit vector residuals, and tables of QCN and NetQuake stations and relocated hypocenter timing, location, and magnitude.
Comparing the Rainfall Patterns Produced by Hurricanes Frances (2004) and Jeanne (2004) over Florida

During 2004, Hurricanes Frances and Jeanne produced heavy rainfall across Florida. Although making landfall at the same location and moving along similar tracks, these storms produced different rainfall patterns. We employ a GIS to analyze rain gauge and radar-estimated rainfall data spatially, and we determine which physical mechanisms caused the asymmetrical rain swaths produced by each storm. We find that due to a moist environment and weakening vertical wind shear, the rain fields of Frances covered a large area. Strong convection in several outer rainbands and slow forward velocity yielded high rainfall totals. Although Jeanne contained more convective rainfall than Frances, vertical wind shear, a faster forward velocity, and existence within a relatively dry environment caused rainfall totals to be lower. The techniques employed in this study could be applied to a larger number of landfalling tropical cyclones to better understand where high rain totals occur under different combinations of environmental conditions.
Frimpong, Kwabena and Al-Shuridah, Obaid and Wilson, Alan and Asafo-

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Margin Based Learning Framework with Geometric Margin Minimum Classification Error for Robust Speech Recognition

Statistical learning theorycombines empirical risk and generalization functionin single optimized objective function of margin based learning for optimization. Margin concept incorporating in Hidden Markov Model (HMM)for speech recognition, Margin based learning frame work based on minimum classification error (MCE) training criteria show higher capability over any other conventional DT methods in improvingclassification robustness (generalization capability) of the acoustic model by increasing the functional margin of the acoustic model. This paper introduces Geometric Margin based separation measure in the loss function definition of margin based learning frame work instead of functional margin separation measure to develop a mathematical framework of new optimize objective function of soft margin estimation (SME) for ASR. Derived SME objective function based on Geometric Margin based separation (misclassification) measure would be capable for representing the strength of margin based learning framework in term of classification robustness by minimizing the classification error probability as well asmaximizing the geometric margin.
WELFARE MEASURES FROM DISCRETE CHOICE MODELS IN THE PRESENCE OF INCOME EFFECT

Welfare evaluation is central to the appraisal of transportation projects and many countries rely on a formal calculation procedure to obtain consumer surplus change, often as an input to a more general Cost Benefit Analysis. In transport planning practice, it is commonplace to derive consumer surplus change by means of a twostage procedure, as follows. First, data on the discrete choices of individuals are analysed by means of a Random Utility Model (RUM), producing forecasts of choice probability under a ‘do something’ scenario (e.g. a price change). Second, these forecasted probabilities are aggregated to the market-level (e.g. reflecting demand over a period of time, for a population of travellers); then referencing against current market demand (or demand in a ‘do nothing’ scenario), one can derive a linear approximation to the change in consumer surplus arising from the price change. Following this procedure, the latter metric is referred to as the ‘rule-of-a-half’, and is rationalised as an approximation to the change in Marshallian consumer surplus.
Short-term forecasting and composite indicators construction with help of dynamic factor models handling mixed frequencies data with ragged edges

This paper aims at presenting practical applications of latent variable extraction method based on second generation dynamic factor models, which use modified Kalman Filter combined with Maximum Likehood Method and can be applied for time series with mixed frequencies (mainly monthly and quarterly) and unbalanced beginning and the end of the data sample (ragged edges). These applications embrace short-term forecasting of Polish GDP and construction of composite coincident indicator of economic activity in Poland. Presented approach adopts the idea of short-term forecasting used by Camacho and Perez-Quirioz in Banco de Espana and concept of Arouba, Diebold and Scotti index compiled in the FRB of Philadelphia. According to the author’s knowledge, it is the first such adaptation for Central and Eastern Europe country. Quality of the forecast obtained with these models is compared with standard methods used for short-term forecasting with series of statistical tests in the pseudo real-time forecasting exercise. Moreover described method is applied for construction of composite coincident indicator of economic activity in Polish economy. This newly-created coincident indicator is compared with first generation coincident indicator, based on standard dynamic factor model (Stock and Watson) approach, which has been computed by the author for Polish economy since 2006.
Goal sketching from a concise business case

This paper describes how the business case can be characterized and used to quickly make an initial and structurally complete goal-responsibility model. This eases the task of bringing disciplined support to key decision makers in a development project in such a way that it can be instantiated quickly and thereafter support all key decisions. This process also greatly improves the understanding shared by the key decision makers and helps to identify and manage load- bearing assumptions. Recent research has revealed two interesting issues, which are highlighted in this paper.
Fast and reliable inference algorithm for hierarchical stochastic block models

Network clustering reveals the organization of a network or corresponding complex system with elements represented as vertices and interactions as edges in a (directed, weighted) graph. Although the notion of clustering can be somewhat loose, network clusters or groups are generally considered as nodes with enriched interactions and edges sharing common patterns. Statistical inference often treats groups as latent variables, with observed networks generated from latent group structure, termed a stochastic block model. Regardless of the definitions, statistical inference can be either translated to modularity maximization, which is provably an NP-complete problem. Here we present scalable and reliable algorithms that recover hierarchical stochastic block models fast and accurately. Our algorithm scales almost linearly in number of edges, and inferred models were more accurate that other scalable methods.
Analysis and Application of Hydraulic Jump

Analytical-statistical solutions of the characteristics in hydraulic jump, including submerged situation with the sluice gate effects, of 2DV flows, such as primary velocity profile for fixed bed, turbulent shear stress profiles and profiles of turbulent kinetic energy and kinetic energy dissipation rate of fixed bed are derived respectively. Then, the comparisons of the analytical results are made with the experimental results and numerical model solutions. Good trends and agreements are obtained, while the applicability of the analytical results are also presented and discussed.
High Performance Numerical Computing for High Energy Physics: A New Challenge for Big Data Science

Modern physics is based on both theoretical analysis and experimental validation. Complex scenarios like subatomic dimensions, high energy, and lower absolute temperature are frontiers for many theoretical models. Simulation with stable numerical methods represents an excellent instrument for high accuracy analysis, experimental validation, and visualization. High performance computing support offers possibility to make simulations at large scale, in parallel, but the volume of data generated by these experiments creates a new challenge for Big Data Science. This paper presents existing computational methods for high energy physics (HEP) analyzed from two perspectives: numerical methods and high performance computing. The computational methods presented are Monte Carlo methods and simulations of HEP processes, Markovian Monte Carlo, unfolding methods in particle physics, kernel estimation in HEP, and Random Matrix Theory used in analysis of particles spectrum. All of these methods produce data-intensive applications, which introduce new challenges and requirements for ICT systems architecture, programming paradigms, and storage capabilities.
Towards a consistant safety format of steel beam-columns: application of the new interaction formulae for ambient temperature to elevated temperatures

Two new formulae for the design of beam-columns at room temperature have been proposed into Eurocode 3, prEN 1993-1-1 (2002), and are the result of great efforts made by two working groups that followed different approaches, a French-Belgian team and an Austrian-German one. Under fire conditions the prEN 1993-1-2 (structural fire design) presents formulae, for the design of beam-columns based on the prENV 1993-1-1 (1992). In order to study the possibility of having, in part 1-1 and part 1-2 of the Eurocode 3, the same approach, a numerical research was made using the finite element program SAFIR, developed at the University of Liege for the study of structures subjected to fire.