Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive comment on “ Vertical Wind Velocity Measurements using a 5-hole Probe with Remotely Piloted Aircraft to Study Aerosol-Cloud Interactions ”

The importance of vertical wind velocities (in particular positive vertical wind velocities or updrafts) in atmospheric science has motivated the need to deploy multi-hole probes developed for manned aircraft in small Remotely Piloted Aircraft (RPA). In atmospheric research, lightweight RPAs (< 2.5 kg) are now able to accurately measure atmospheric wind vectors, 5 even in a cloud, which provides essential observing tools for understanding aerosol-cloud interactions. The European project BACCHUS (impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) focuses on these specific interactions. In particular, vertical wind velocity at cloud base is a key parameter for studying aerosolcloud interactions. To measure the three components of wind, a RPA is equipped with a 5-hole probe, pressure sensors, and an Inertial Navigation System (INS). The 5-hole probe is calibrated on a multi-axis platform, and the probe/INS system is 10 validated in a wind tunnel. Once mounted on a RPA, power spectral density (PSD) functions and turbulent kinetic energy (TKE) derived from the 5-hole probe are compared with sonic anemometers on a meteorological mast. During a BACCHUS field campaign at Mace Head Atmospheric Research Station (Ireland), a fleet of RPAs was deployed to profile the atmosphere and complement ground-based and satellite observations of physical and chemical properties of aerosols, clouds and meteorological state parameters. The 5-hole probe was flown on straight-and-level legs to measure vertical wind velocities within clouds. The 15 vertical velocity measurements from the RPA are validated with vertical velocities derived from a ground-based cloud radar by showing that both measurements yield model-simulated cloud droplet number concentrations within 10 %. The updraft velocity distributions illustrate distinct relationships between vertical cloud fields in different meteorological conditions.
FREE Policy Brief Series Tajikistan Joining the Customs Union of Russia , Belarus and Kazakhstan : Pros and Cons

In this brief we summarize the results obtained in a CEFIR research project on the economic impact of Tajikistan joining the Customs Union of Russia, Belarus and Kazakhstan conducted for the Eurasian Development Bank in 2013 (EBD, 2013). We argue that integration has to be comprehensive to be mutually beneficial: indeed, trade effects are marginal, and the highest stakes are at migration regulation in the CU member-countries and the investment opportunities in Tajikistan.
Regional-Level Analysis of Oligopsony Power in the Ukrainian Milk Processing Industry : Evidence from Transition Countries

Most of the New Empirical Industrial Organization (NEIO) studies use the industry data to estimate a degree of market power at a national level; however, there are some studies that find evidence of market power exertion at the regional level. Though there is a widespread evidence suggesting for the existence of oligopsony power in the Ukrainian milk processing industry, the estimation results of the market structure model at the national level prove otherwise. While the estimation of the market structure model at the regional level suggests for the existence of oligopsony power in four out of twenty two regions of Ukraine, there is a potential deviation of raw milk prices, ranging from 3.6 % to 46.7 % of the marginal product value of raw milk.
Extrachloroplastic PP 7 L Functions in Chloroplast Development and Abiotic Stress Tolerance 1 [ OPEN ]

Duorong Xu,a Giada Marino,a Andreas Klingl,b Beatrix Enderle,c Elena Monte,d Joachim Kurth,b Andreas Hiltbrunner,c,e Dario Leister,a and Tatjana Kleinea,2,3 Plant Molecular Biology (Botany), Department Biology I, Ludwig-Maximilians-Universität München, 82152 Planegg-Martinsried, Germany Plant Development, Department Biology I, Ludwig-Maximilians-Universität München, 82152 Planegg-Martinsried, Germany Institute of Biology II, Faculty of Biology, University of Freiburg, 79104, Freiburg, Germany Plant Development and Signal Transduction Program, Center for Research in Agricultural Genomics Consejo Superior de Investigaciones Científicas-Institute of Agrifood Research and Technology-Universidad Autonoma de Barcelona-Universidad de Barcelona, 08193 Barcelona, Spain Centre for Biological Signalling Studies (BIOSS), University of Freiburg, 79104 Freiburg, Germany
Contract Report to the European Space Agency Operational Assimilation of Space-borne Radar and Lidar Cloud Profile Observations for Numerical Weather Prediction WP-1000 report : Preliminary analysis and planning

This report provides an overview of the Numerical Weather Prediction (NWP) system components that are crucial for assimilating radar and lidar observations of clouds in pre-operational set-up at ECMWF. The existing data assimilation system is outlined together with a more detailed plan for its extension towards the target configuration to be accomplished at the end of the project. The project plan accounts for the initial technical and scientific stages to be followed by testing that will allow conclusions to be drawn from the technical and scientific performance of the system. The work described in this report was done under ESA Contract. Responsibility for the contents resides in the authors or organizations that prepared it. NAMES OF AUTHORS: Marta Janisková and Mark Fielding Responsible for the study: Marta Janisková NAME OF ESA STUDY MANAGER: Tobias Wehr DEPARTMENT: Science and Applications (EOP-S) DIRECTORATE: Earth Observation Programmes ESA BUDGET HEADING .
Development and Applications of Deep Learning Structures for Point Cloud Data

This thesis makes three main contributions on a generalized method by using a surface common feature based Deep Learning struture, that amis to acheve object recognition task and emotional facial expression recognition task. Because the popularity of DL has grown rapidly in the past few years, it leads many research fields to have a qualitative leap, specially in the computer vision field. However, most of the computer vision tasks based on the DL are focused on the 2D image data, and a 2D image is very vulnerable to the changing of environment. On the other hand, the 3D point cloud data(PCD) is the collection of descriptive points of an object in 3D space. It is very activated in distance-based segmentation, object recognition, and also self-driving system. The advantages of PCD are, it able to describe full geometrical information about the objects, and it is not affected by the lighting. But it also has some disadvantaged attributes, such as its high dependency on reference coordinates, thus, its feature appears totally different in the different coordinate system. And, compare to the 2D images, the useful information in 3D PCD is not directly observable. Most of the previous researches on PCD-based methods are only considered the information from the point itself, which is the distance between the point and the observer, or using local feature extraction methods. But eventually some of these research fell into 2D image processing, which causing the information loss, and some other local feature based methods are limited in few objects, which makes these methods are not widely applicable. As a generalization methods to many problems, DL attempts to model high level abstractions in a complex data source. By changing the structure of network connection, and some techniques such as convolution, pooling, dropout and recurrence, it becomes a very powerful machine learning algorithm. A well-designed DL can avoid the amount of problems, which the deep neural network faced in previously, such as the vanishing of gradient and over-fitting problems. The most important advantage of DL is that the manual design features are not required anymore. So that, DL able to solve a complex problems freely in very high dimension weight space. However, by the same reason, it is very difficult to understand the principles of a DL.
N A ] 1 3 A ug 2 01 9 THINC-scaling scheme that unifies VOF and level set methods

We present a novel interface-capturing scheme, THINC-scaling, to unify the VOF (volume of fluid) and the level set methods, which have been developed as two completely different approaches widely used in various applications. The THINC-scaling scheme preserves at the samectime the advantages of both VOF and level set methods, i.e. the mass/volume conservation of the VOF method and the geometrical faithfulness of the level set method. THINCscaling scheme allows to represent interface with high-order polynomials, and has algorithmic simplicity which eases its implementation in unstructured grids.
Validation Of The Social Identity Group Need Satisfaction And Frustration Scale

In this paper, we argue for the need to assess social identity group need satisfaction and frustration in addition to individual level needs. We argue that political science and psychology require a measure of social identity group needs to provide empirical insights into how state treatment of groups influences their citizens' wellbeing. In this paper, we create and validate a short measure of group needs on a sample of Australian (n = 2081) and American (n = 1493) adults. We show the measure fit the data well, is invariant across gender, nation, and social identity group, and is related to validation variables in expected directions. We also contrast group needs with individual needs. We show that group needs are distinct from individual needs. Group and individual needs are associated in similar directions and strengths with wellbeing and primary goods. Individual need satisfaction is positively related to identity centrality and need frustration negatively related. Group needs are almost always positively related to identity centrality. We argue that our measure can make a meaningful contribution to empirical research in the social sciences.
The relation between firm growth and accounting quality : A test of the life cycle hypothesis

Using a range of commonly used proxies for ‘account ing quality’, this study attempts to disentangle the effects of accounting measurement u nder Generally Accepted Accounting Principles (GAAP) from the firms’ economic characte ristics, in the decision context of the firms’ future growth. Our study is motivated by the importance of quality accounting for decision making, an understanding of which is not w ell served by the conflation of the fundamental earnings process with the measurement o f the process in commonly used proxies for accounting quality. We employ firm life cycle s tages as proxies for the firms’ economic characteristics and find the firms’ economic charac teristics are key sources of ‘accounting quality’. Second, we examine the consequences for f irm growth of higher accounting quality. We find the economics of the firms explains growth, and there is little relation between the firm growth measures and ‘accounting quality’ proxi es unless the association is conditioned on the firm life cycle stages. Our results caution against simple claims about the benefits of ‘accounting quality’ without explicitly considering the multiple determinants of the commonly used proxies. The authors are grateful for helpful comments from Peter Best, Reza Monem, Majella Percy, Jenny Stewar , and Julie Walker, and workshop participants at the Univ ersity of Queensland and Griffith University.
CHAPTER 5 Particle and Gas Measurements

2) To determine specific causes of health effects. (What is the problem? ) Initial emphasis focuses on testing related to the eleven hypotheses listed in Textbox 2.5. The wide array of measurements that are needed to determine the connection between health effects and specific PM properties are enumerated in Appendix B, Table B.1. Measurements of novel PM properties are needed to test hypotheses regarding causal agents for human health effects.
PHYSICAL REVIEW APPLIED 10 , 064029 ( 2018 ) Correlating Electronic Transport and 1 / f Noise in MoSe 2 Field-Effect Transistors

Two-Dimensional Transition Metal Dichalcogenides (2D TMDCs) such as MoS2, MoSe2, WS2, and WSe2 with van der Waal’s type interlayer coupling are being widely explored as channel materials in a Schottky Barrier Field Effect Transistor (SB FET) configuration. While their excellent electrostatic control and high on/off ratios have been identified, a clear correlation between electronic transport and the lowfrequency noise with different atomic-layer thickness is missing. For multilayer channels in MoS2 FETs, the effects of interlayer-coupling resistance on device conductance and mobility have been studied, but no systematic study has included interlayer effects in consideration of the intrinsic (channel) and extrinsic (total device) noise behavior. Here, we report the 1/f noise properties in MoSe2 FETs with varying channel thicknesses (3–40 atomic layers). Contributions of channel vs access/contact regions are extracted from current-voltage (transport) and 1/f noise measurements. The measured noise amplitude shows a direct crossover from channelto contact-dominated noise as the gate voltage is increased. The results can be interpreted in terms of a Hooge relationship associated with the channel noise, a transition region, and a saturated high-gate-voltage regime whose characteristics are determined by a voltage-independent conductance and noise source associated with the metallurgical contact and the interlayer resistance. Both the channel Hooge coefficient and the channel/access noise amplitude decrease with increasing channel thickness over the range of 3–15 atomic layers, with the former remaining approximately constant and the latter increasing over a range of 20–40 atomic layers. The analysis can be extended to devices based on other TMDCs.
A new method for estimating value added tax compliance *

We develop a simple structural model of the effects of international trade on value added tax (VAT) compliance. We show how the model may be estimated with widely available national accounts data to learn about the extent of VAT evasion. The key to our approach is that international border controls improve VAT compliance, generating a correlation between imports and VAT revenues that is informative about the extent of domestic tax evasion. Using data on a large panel of countries, we estimate VAT evasion. We compare our estimates to others in the literature, and we use our methods to analyze the institutional and economic determinants of tax evasion.
STRUCTURAL ADJUSTMENT PROGRAMS AND THE LABOUR MARKET IN MALAWI

This paper examines the impact of structural adjustment programs and minimum wages on average wages and employment in Malawi. Since 1981, the Malawi government has been implementing a series of structural adjustment programs in response to an economic crisis that burst in 1979 and 1980. Several policy reforms, in a phased approach, have been introduced in the economy to induce production in all sectors of the economy. Using data on wages and employment in the formal sector, we examine the impact of minimum wages and structural reforms on average wages and employment in the economy. The test between means shows that employment and real wages significantly declined during the adjustment period. Regression results show support for a cointegrating relationship between average wages, minimum wages, inflation and openness. Minimum wages are positively associated with average wages, while we find no significant association between minimum wages and employment.
The Biomonitoring project – monitoring of forest ecosystems in non-intervention areas of the Šumava National Park

The Šumava National Park is the largest national park in the Czech Republic. It belongs to one of the most valuable terrestrial Natura 2000 sites in central Europe, where large areas are covered by mountain spruce forests. These forest ecosystems are areas of special conservation value. Nowadays, 23% of the Šumava NP area is left without human interventions and this area offers a unique opportunity to study natural forest structure and dynamics. Data about stand structure (live and dead trees, snags, stumps, lying dead wood, and tree regeneration) and plot characteristics (slope, soil, microsite cover, vegetation) are collected within the Biomonitoring project, which has been started already in 2008. Results of the project show successful regeneration of mountain forests after natural disturbances. More than 90 % of inventory plots showed the regeneration densities >100 seedlings.ha−1. We found, that there are enough young trees to guarantee the next generation of forests. The project also confirmed that the lying dead wood is an important microsite for natural regeneration of trees, especially for the Norway spruce (Picea abies), a dominant species of the spruce mountain forest.
Automatic Word-level Identification of Language in Assamese – English – Hindi Code-mixed Data

In this paper, we discuss the automatic identification of language in Assamese – English Hindi code-mixed data at the word-level. The data for this study was collected from public Facebook Pages and was annotated using a minimal tagset for code-mixed data. Support Vector Machine was trained using the total tagged dataset of approximately 20k tokens. The best performing classifier achieved a state-of-the-art accuracy of over 96%.
The design problem for single-line demand-adaptive transit systems

When demand for transportation is low or sparse, traditional transit cannot provide efficient and good-quality level service, due to their fixed structure. For this reason, mass transit is evolving towards some degree of flexibility. Although the extension of Dial-a-Ride systems to general public meets such need of adaptability, it presents several drawbacks mostly related to the extreme flexibility. Consequently, new transportation alternatives, such as Demand Adaptive Systems (DAS), combining characteristics from both the traditional transit and Dial-a-Ride, have been introduced. For their twofold nature, DAS require careful planning. We focus on tactical aspects of the planning process by formalizing the Single-line DAS Design Problem (SDDP) and proposing two alternative hierarchical decomposition approaches for its solution. The main motivation behind this work is to provide with a general methodology based on realistic assumptions and suitable to be used as a tool to build the tactical DAS plan in real-life conditions. We provide an experimental study where the two proposed decomposition methods are compared and the general behavior of the systems is analyzed when altering some design parameters.
Evaluation of the infection of cassava and Nicotiana benthamiana with cassava mosaic geminiviruses and their combinations for potential synergism

Five test plants each of cassava and Nicotiana benthamiana were inoculated in vitro with 50 ng cassava mosaic geminivirus (CMG) deoxyribonucleic acid (DNA) of components A and B and their random combinations for strains African cassava mosaic-Cameroon virus (ACMV-CM), East African cassava mosaic Cameroon virus (EACMV-CM), East African cassava mosaic Uganda virus (EACMV-UG), Indian cassava mosaic virus (ICMV) and Sri Lankan cassava mosaic virus (SLCMV) were investigated for synergistic interactions by bombardment with gold particle-coated viral DNA using the biolistic particle delivery system giving a total of 80 plants. The plants were maintained in an insect-proof greenhouse and scored for infection one week post inoculation (wpi) for 8 weeks on a scale of 1-5. The experiment was replicated twice. Incidence of infection was higher on N. benthamiana than cassava plants. The highest infection was with ACMCV/ICMV (100 %) on N. benthamiana and this was not significant over ACMV-CM (98.8 %) and the positive control ACMV-CM/EACMV-CM (96.3 %). Thus the combination ACMV-CM/ICMV probably had a synergistic effect on N. benthamiana. On cassava, however, the highest infection was ACMV-CM/EACMV-CM (50 %) which was not significant over ACMV-CM/SLCMV (46.3 %). Similarly, viral effect was more severe on N. benthamiana than on cassava plants. The most severe effects were by SLCMV (2.81), SLCMV/EACMV-CM (2.42) and ACMV-CM (2.32). ACMV-CM/EACMV-CM had earlier been demonstrated on cassava to have a synergistic effect. This study demonstrated that the ACMV-CM/ICMV combination had a synergistic effect on N. benthamiana and thus a potential threat of significance in plant virus disease epidemiology and therefore subject to further investigation.
Analysis of Open Education Service Quality with the Descriptive-Quantitative Approach.

The concept of Open Education (OE) is based on the philosophy of e-Learning which aims to provide learning environment anywhere, anytime, and for anyone. One of the main issue in the development of OE services is the availability of the quality assurance mechanism. This study proposes a metric for measuring the quality of OE service. Based on extensive literature review about e-Learning service quality guidelines, as well as the observation of existing Open Education services, we formulated Open Education Metric (OEM). OEM consists of 37 indicators which are divided into six criteria: (1) Openness, (2) Benefit, (3) Delivery, (4) Learning, (5) Evaluation, and (6) Support. Evaluation scheme is designed to give a clear guideline in assessing the quality of OE service quantitatively. The evaluation results including score and category indicate the overall quality relative to a set of indicators. Trial of evaluation was conducted using the evaluation system based on OEM to test its performance in evaluating OE service quality in institutions. Three of OE services were evaluated with their scores.
, Fatemeh 2015 Semi-extractive multi-document summarization

In this thesis, I design a Maximum Coverage problem with KnaPsack constraint (MCKP) based model for extractive multi-document summarization. The model integrates three measures to detect important sentences including Coverage, rewards sentences in regards to their representative level of the whole document, Relevance, focuses to select sentences that related to the given query, and Compression, rewards concise sentences. To generate a summary, I apply an efficient and scalable greedy algorithm. The algorithm has a near optimal solution when its scoring functions are monotone non-decreasing and submodular. I use DUC 2007 dataset to evaluate our proposed method. Investigating the results using ROUGE package shows improvement over two closely related works. The experimental results illustrates that integrating compression in the MCKP-based model, applying semantic similarity measures to detect Relevance measure and also defining all scoring functions as a monotone submodular function result in having a better performance in generating a summary.
Text Classification Using ES Based L1-LS-SVM

With the advent of big-data age, it is essential to organize, analyze, retrieve and protect the useful data or sensitive information in a fast and efficient way for customers from different industries and fields. In this paper, evolution strategies based a least squares support vector machine with L1 penalty (ES based L1-LS-SVM) is proposed to deal with LS-SVM shortcomings. A minimum of 1-norm based object function is chosen to get the sparse and robust solution based on the idea of basis pursuit (BP) in the whole feasibility region. A real Chinese corpus from Fudan University is used to demonstrate the effectiveness of this model. The experimental results show that ES based L1-LS-SVM can obtain a small number of support vectors and improve the generalization ability of ES based LS-SVM.