Miracle-dz/UniFAR-FTUs huggingface dataset:
Winter 12-6-2018 Structural Pattern Recognition of Fraudster Groups in P 2 P Transaction Websites

The advent of online platform economy has increased online fraudsters. To detect them, most research explored to recognize characteristics from behavioral data of online users. In those works, each user was regarded as an individual subject, while relationship between users was underestimated. This paper introduced methodology of social network analysis to mine characteristics of relationship among online fraudsters. Using dataset from a Bitcoin trading website, a weighted signed network is constructed. By removing normal user nodes from the network, relationships between fraudsters are clarified. Then, major structural patterns of the snipped network are uncovered by way of community partitioning method. Based on real data from the Bitcoin trading website, 3 typical structures of fraudster groups are found: star-shaped structure, double-core structure and reticular
The effect of autotrawl systems on the performance of a survey trawl

Abstract— Three aspects of a survey bottom trawl performance—1) trawl geometry (i.e., net spread, door spread, and headrope height); 2) footrope dis-tance off-bottom; and 3) bridle dis-tance off-bottom—were compared among hauls by using either of two autotrawl systems (equal tension and net symmetry) and hauls conducted with towing National Marine Fisheries Servicecables of equal length and locked winches. The Alaska Fisheries Science Center,effects of environmental conditions, vessel heave, crabbing (i.e., the difference between vessel heading and actual vessel course over ground), and bottom current on trawl performance with three trawling modes were investigated. Means and standard deviations of trawl geometry mea-sures were not significantly different between autotrawl and locked-winch systems. Bottom trawls performed better with either autotrawl system as compared to trawling with locked winches by ofreducing andthe variance and increasing the symmetry of the footrope contact with the bottom. The equal tension autotrawl system was most effective in counteracting effects of environmental conditions on footrope bottom contact. Footrope bottom contact was most influenced by environmental conditions during tows with locked winches. Both of the autotrawl systems also reduced the thevariance and increased the state,symmetry of bridle bottom contact. Autotrawl systems proved to be effective in decreasing the effects of environmental factors on some aspects of trawl performance and, as a result, have the potential to reduce among-haul variance in catchability of survey trawls. Therefore, by incorporating an autotrawl system into standard survey procedures, precision of survey estimates of relative abundance may be improved. Manuscript submitted 27 October 2004 to the Scientiﬁc Editor’s Ofﬁce. Manuscript approved for publication 6 June 2005 by the Scientiﬁc Editor. Fish. Bull. 104:35–45 (2006).
Children’s Awareness of Peer Rejection and Teacher Reports of Aggressive Behavior

Lack of awareness of one’s negative social reputation is linked to aggressive behavior among older school-age children. The present study extends this research to the first year of elementary school. The first goal was to compare generalized and dyadic perspectives in studying discrepancies between children’s actual and perceived rejection. The second goal was to determine whether discrepancies between actual and perceived rejection are related to sociometric status. The third goal was to examine whether discrepancies between actual and perceived rejection are related to aggressive behaviors at school. Actual peer rejection was measured with peer negative nominations, perceived peer rejection with students’ self-ratings and meta-perceptions, and aggressive behavior with teacher ratings. The discrepancies between actual and self-perceived rejection were substantial in the total sample. Furthermore, non-rejected children had higher scores than rejected children in dyadic overestimation (identifying peers who they believed disliked them but did not), while it was the reverse for dyadic underestimation (not identifying peers who in fact disliked them). High levels of dyadic underestimation were negatively associated with the concurrent aggressive behavior. Rejected children’s underestimation of their peer rejection appeared to have protective effects on antisocial and aggressive problems. Findings are discussed in terms of theories of symbolic interactionism and social information processing.
Organizational Learning and Multiteam Systems

Multiteam systems consist of two or more teams, each of which pursues subordinate team goals, while working interdependently with at least one other team toward a superordinate goal. Many teams work in these larger organizational systems, where oft-cited challenges involve learning processes within and between teams. This chapter brings a learning perspective to multiteam systems and a multiteam system perspective to organizational learning. Several classic illustrations of organizational learning—for example, the Challenger and Columbia disasters—actually point to failures in organizational learning processes within and between teams. We offer the focus on intrateam knowledge creation and retention and interteam knowledge transfer as a useful starting point for thinking about how to conceptually and operationally define learning in multiteam systems. Furthermore, we think leadership structures and multiteam emergent states are particularly valuable drivers of learning.
Functional characterization of cotton genes responsive to Verticillium dahliae through bioinformatics and reverse genetics strategies

Verticillium wilt causes dramatic cotton yield loss in China. Although some genes or biological processes involved in the interaction between cotton and Verticillium dahliae have been identified, the molecular mechanism of cotton resistance to this disease is still poorly understood. The basic innate immune response for defence is somewhat conserved among plant species to defend themselves in complex environments, which makes it possible to characterize genes involved in cotton immunity based on information from model plants. With the availability of Arabidopsis databases, a data-mining strategy accompanied by virus-induced gene silencing (VIGS) and heterologous expression were adopted in cotton and tobacco, respectively, for global screening and gene function characterization. A total of 232 Arabidopsis genes putatively involved in basic innate immunity were screened as candidate genes, and bioinformatic analysis suggested a role of these genes in the immune response. In total, 38 homologous genes from cotton were singled out to characterize their response to V. dahliae and methyl jasmonate treatment through quantitative real-time PCR. The results revealed that 24 genes were differentially regulated by pathogen inoculation, and most of these genes responded to both Verticillium infection and jasmonic acid stimuli. Furthermore, the efficiency of the strategy was illustrated by the functional identification of six candidate genes via heterologous expression in tobacco or a knockdown approach using VIGS in cotton. Functional categorization of these 24 differentially expressed genes as well as functional analysis suggest that reactive oxygen species, salicylic acidand jasmonic acid-signalling pathways are involved in the cotton disease resistance response to V. dahliae. Our data demonstrate how information from model plants can allow the rapid translation of information into non-model species without complete genome sequencing, via high-throughput screening and functional identification of target genes based on data-mining and VIGS.
A one-step process employing various amphiphiles for an electrically insulating silica coating on graphite

Ceramic coatings endow carbon materials with electrically insulating properties. For graphite, it is unclear whether ceramic coatings applied via a one-step process under mild conditions can lead to superior coverage. This paper reports that a modified Stober method with an appropriate choice of amphiphiles could yield an electrically insulating coating layer on graphite (d50 3–300 μm, d90 6–550 μm) within 24 h with high reproducibility. A silica coating mechanism involving functional groups on the edge of the graphite, Oswald ripening agents, and a bridgemer was investigated. The mechanism was based on the silica coating morphology, which depends on the amphiphile, and the correlation between coverage and surface resistivity was assessed. Amphiphile-assisted silica@graphite with a surface resistivity of 1012 ohm sq−1 was produced. The thermal conductivity of the silica-coated graphite (amphiphile-assisted silica@graphite)/TPEE composite reached values over 75% higher than that of the raw graphite/TPEE composite with electrically insulating properties.
Aalborg Universitet Generation of Land Cover Maps Using High-Resolution Multispectral Aerial Cameras Höhle

─The generation of land cover maps has new advanced tools at its disposal. Besides new aerial cameras also new advanced processing tools are available. Elevations can be derived from images with high density and high positional accuracy. The combination of multispectral high-resolution imagery and high-density elevations for the automatic generation of land cover maps is discussed by means of a practical example. Imagery of a new aerial camera is used together with advanced software for generation of digital elevation models and for derivation of vegetation maps. These two products are the input for classification of land cover. A high degree of automation can be achieved. The obtained results of a practical example are checked with reference values derived from ortho-images in natural colour and from colour images using stereo-vision. An error matrix is applied in the evaluation of the results. The classification had an overall accuracy of 79%. Suggestions for the improvements in the applied methodology are made. The potential of land cover maps lies in updating of topographic databases, quality control of maps, studies of town development, and other geo-spatial domain applications. The automatic generation of land cover maps is also a trend in future mapping. Keywords-land cover map; classification; assessment; multispectral camera; map revision.
SOME CONSIDERATIONS FOR CPUE STANDARDIZATION ; VARIANCE ESTIMATION AND DISTRIBUTIONAL CONSIDERATIONS

Two stage statistical models, such as the delta lognormal, that explicitly model the distribution of the proportion positive and the non-zero observations are widely used for CPUE standardization. Estimation of the variance of the index is obtained as the variance of the product of two random variables. Many current treatments assume or explicitly test for the independence of the two components and use a covariance term to estimate the index variance. Subsequent work indicates that this is incorrect, that much of the code used to estimate the covariance should be replaced and the two components are, under most situations, independent such that the covariance is zero. This allows for an exact variance estimate based on Goodman (1960). Existing code should be revised to reflect this development. Most CPUE treatments also assume a delta-lognormal model when other distributions may be more appropriate and may obviate the need for a two-stage model. We present alternatives to two-stage models that implicitly assume a lognormal distribution for the positive observations, for cases when other distributions may be more appropriate. We also present a set of decision rules for selecting the appropriate discrete distribution with examples of simulated data that demonstrate the various distributional forms, along with statistical codes, with the goal of improving CPUE modeling.
A Multi-Level Naïve Bayes Classifier for Sentiment Classification

A great demand of sentiment classification comes with the rapid development of the internet. At present, the methods about sentiment classification based on machine learning have been widely used. The sentiment classification is a more difficult task, which needs more in-depth study than the traditional topic-based classification method [1]. Naïve Bayesian classifier is widely used in text classification. However, it requires two basic assumptions as its prerequisite and the performance would have been poor if these two were dissatisfied. We propose a multi-level naïve Bayes classifier to make up the deficiency of the traditional naïve Bayes classifier. The research below shows that the multi-level naïve Bayes classifier gets better performance than the traditional naïve Bayes classifier on the sentiment classification of movie reviews.
MULTIPLE STELLAR POPULATIONS IN 47 Tucanae

We use Hubble Space Telescope (HST) and ground-based imaging to study the multiple populations of 47 Tucanae (47 Tuc), combining high-precision photometry with calculations of synthetic spectra. Using filters covering a wide range of wavelengths, our HST photometry splits the main sequence into two branches, and we find that this duality is repeated in the subgiant and red giant regions, and on the horizontal branch. We calculate theoretical stellar atmospheres for main-sequence stars, assuming different chemical composition mixtures, and we compare their predicted colors through the HST filters with our observed colors. We find that we can match the complex of observed colors with a pair of populations, one with primeval abundance and another with enhanced nitrogen and a small helium enhancement, but with depleted C and O. We confirm that models of red giant and red horizontal branch stars with that pair of compositions also give colors that fit our observations. We suggest that the different strengths of molecular bands of OH, CN, CH, and NH, falling in different photometric bands, are responsible for the color splits of the two populations. Near the cluster center, in each portion of the color–magnitude diagram the population with primeval abundances makes up only ∼20% of the stars, a fraction that increases outward, approaching equality in the outskirts of the cluster, with a fraction ∼30% averaged over the whole cluster. Thus the second, He/N-enriched population is more concentrated and contributes the majority of the present-day stellar content of the cluster. We present evidence that the color–magnitude diagram of 47 Tuc consists of intertwined sequences of the two populations, whose separate identities can be followed continuously from the main sequence up to the red giant branch, and thence to the horizontal branch. A third population is visible only in the subgiant branch, where it includes ∼8% of the stars.
Whole Genome Sequencing of the Dzo: Genetic Implications for High Altitude Adaptation, Sterility, and Milk and Meat Production

The Dzo, a hybrid between the domestic Yak and cattle found on the Qinghai-Tibetan plateau are commercially important owing to increased meat and milk production, as well as their adaptation to extremely high-altitude environments. To better understand the genomic architecture and adaptive capabilities of this unique domesticated hybrid, we performed whole genome resequencing and compared the genomic architecture and variation of the Dzo to its progenitors: the cattle and Yak. In total, 33.17 M single nucleotide variations (SNVs) were detected between the Dzo and cattle reference genomes. Even though the Dzo is known to be sterile, no genetic signatures associated with sterility were found on the Dzo Y chromosome. On the contrary, our results suggest that the autosomal DMC1 locus (Chromosome 5. 110729098. C>CT) plays a role in the sterility of Dzo, which warrants further exploration of its functions. We integrated the whole genome resequencing data of cattle and Yak to obtain candidate genes with a high degree of variation that might be associated with altitudinal adaptation. We found that the EPAS1 gene, which encodes hypoxia-inducible factor 2α, exhibited significant variation (Chromosome 11.28664187 C>T) between Yak and cattle, and may play a key role in the genetic basis of altitudinal adaptation. In addition, in analyzing differences between the Dzo, Yak, and cattle genomes, we uncovered several additional genomic signatures relevant to high altitude adaptation and meat and milk production. These findings underscore the need for further studies to improve ruminant stock for sustainable agriculture on the Qinghai-Tibet plateau.
Output Value Risk for Commodity Producers: The Uncertain Benefits of Diversification

Significant changes in commodity price dynamics have occurred since 2004, including a strong increase in commodity return correlations. What has been the impact on the uncertainty faced by commodity producers? We answer this question through an empirical analysis of the market value of commodity producers' output, using a sample of 54 countries engaged in the production of 22 commodities. We find that between 1986 and 2012 commodity output value correlated strongly with exports and that its volatility was strongly increasing in the degree of specialization. Between 1986 and 2003, producers specialized in the production of two or fewer commodities experienced an average output value volatility of 25.1%, and producers diversified in three or more commodities faced an average volatility of 14.1%. Average pairwise commodity correlation during this period was 9%. In the 2004-2012 period average commodity correlation was 29%, leading to output volatilities of 25.3% and 18.7% for specialized and diversified producers respectively. We explain this reduction in the benefits of diversification through an approximate decomposition of national output variance in terms of the Herfindahl index associated to diversification in production, average commodity volatility and average commodity correlations.
Aalborg Universitet Transient Response Analysis of Inverter-based Microgrids under Unbalanced Conditions using Dynamic Phasor Model

Microgrids (MGs) are often unbalanced due to the integration of single-phase generators, unbalanced loads and asymmetrical faults. To better analyze such a MG, this paper presents an approach to analyze the transient response for an inverter-based MG under unbalanced condition. The dynamic phasor (DP) concept is used for the MG modeling under stationary abc reference frame. First, the DP model of the inverter-based DG is developed. The influence of unbalanced conditions on the inverter including oscillations on dc side are considered in this paper. Then, the model of the network and loads is developed. Finally, all the sub-modules are combined on a time-variable system frequency to obtain the complete DP model of unbalanced MG. To validate the proposed approach, the DP method is applied to a MG test system with three-phase and single-phase DGs. Small signal analysis is carried out to derive the dominant modes and their influence on the system response. Simulation results from the DP model are compared against the detailed model built in MATLAB/SimPowerSystem. The results from load disturbances and asymmetrical faults are used to verify the DP model.
EFFICIENT KNN CLASSIFICATION ALGORITHM FOR BIG DATA

K Nearest Neighbors (kNN) is an efficient lazy learning algorithm and has successfully been developed in real applications. It is natural to scale the kNN method to the large scale datasets. In this paper, we propose to first conduct a k-means clustering to separate the whole dataset into several parts, each of which is then conducted kNN classification. We conduct sets of experiments on big data and medical imaging data. In this paper we study how to efficiently perform set-similarity joins in parallel using the popular MapReduce framework. We propose a 3-stage approach for end-to-end setsimilarity joins. We take as input a set of records and output a set of joined records based on a set-similarity condition. We efficiently partition the data across nodes in order tobalance the workload and minimize the need for replication. We study both self-join and R-S join cases, and show how to carefully control the amount of data kept in main memory on each node. We also propose solutions for the case where, even if we use the most fine-grained partitioning, the data still does not fit in the main memory of a node. We report results from extensive experiments on real datasets, synthetically increased in size, to evaluate the speedup and scaleup properties of the proposed algorithms using Hadoop. Keyword: Classification, kNN, Big data, MapReduce, Performance Evaluation
Financial Inclusion, Shocks, and Poverty

We estimate the effect of mobile money adoption on consumption smoothing, poverty, and human capital investments in Tanzania. We exploit the rapid expansion of the mobile money agent network between 2010 and 2012 and use this together with idiosyncratic shocks from variation in rainfall over time and across space in a difference-in-difference framework. We find that adopter households are able to smooth consumption during periods of shocks and maintain their investments in human capital. Results on time use of children and labor force participation complement the findings on the important role of mobile money for the intergenerational transmission of poverty.
Prediction of Solar Energetic Particle Event Peak Proton Intensity Using a Simple Algorithm Based on CME Speed and Direction and Observations of Associated Solar Phenomena

We assess whether a formula obtained by Richardson et al. (2014, https://doi.org/10.1007/s11207‐014‐0524‐8) relating the peak intensity of 14‐ to 24‐MeV protons in a solar energetic particle (SEP) event at 1 AU to the solar event location and the speed of the associated coronal mass ejection (CME) may be used in a scheme to predict the intensity of an SEP event at any location at this heliocentric distance. Starting with all 334 CMEs in the CCMC/SWRC DONKI database in October 2011 to July 2012, we use the CME speed and direction to predict the proton intensity at Earth and the two Solar Terrestrial Relations Observatory spacecraft using this formula. Since most (∼85%) of these CMEs were not in fact associated with SEP events, many SEP events are predicted that are not actually observed. Such cases may be reduced by considering whether type II or type III radio emissions accompany the CMEs, or by selecting faster, wider CMEs. This method is also applied to predict the SEP intensities associated with ∼1,100 CMEs observed by the Solar and Heliospheric Observatory Large Angle and Spectrometric Coronagraph during 1997–2006 in solar cycle 23. Various skill scores are calculated, which assess different aspects of the skill of the SEP predictions. We conclude that the Richardson et al. (2014) formula has potential as a simple empirical SEP intensity prediction tool.
Comparative Study of Urban Area Growth: Determining the Key Criteria of Inner Urban Development

Urban population is steadily growing worldwide, while the number of people in Eastern Europe is decreasing. These two contradictory trends have outlined the proposal for sustainable solutions to solve civil engineering issues that are aimed at implementing the principles of sustainable development and ensuring a better quality of urban life. When considering the problem that is encountered in Eastern European countries, a multi-criteria model for sustainable urban development has been designed and focused on planning and simulating an inner urban living environment. The suggested model has disclosed the social, economic, environmental, and sustainable components of the infrastructure that are necessary for developing inner urban areas. The components have been adapted and presented in three different size territories covering Lithuanian cities and towns. The applied expert evaluation method has assisted in determining the key criteria that should be considered in order to identify the most important inner areas of urban development. It is expected that this study will extend activities that are performed in the field of improvement of sustainability engineering processes and offer guidelines for other researchers investigating the areas of inner urban development.