Miracle-dz/UniFAR-FTUs huggingface dataset:
THE CONTRIBUTION OF ICT TO ECONOMIC ACTIVITY : A GROWTH ACCOUNTING EXERCISE WITH SPANISH FIRM-LEVEL DATA Preliminary version October 2001

This paper uses a well-established growth accounting framework to measure the contribution of ICT goods (considered as capital inputs) to output and labour productivity growth in the Spanish economy. We apply this framework to a sample of around 1300 Spanish firms per year over the 1991-1999 period. The use of micro-level data is especially useful for the purpose at hand. Firstly, our database provides detailed breakdowns of capital. This helps mitigate the usual mismeasurement problems in obtaining capital stocks. Secondly, by avoiding the usual availability lags associated with the use of aggregate data, we can focus on a more recent period. The main findings may be summarised as follows. 1) The use of ICT as a capital input has made a positive and, relative to its cost share, significant contribution to output and productivity growth. 2) This contribution has been higher in the second half of the 1990s. For this period, we estimate that the use of ICT inputs accounted for about one-fifth of labour productivity growth. 3) At a sectoral level, we find that there is a generalised rise in the share of ICT in total capital and a generalised reduction in ICT cost shares, driven by the sharp downward trend in the prices of ICT products. However, the contribution of ICT inputs displays a degree of heterogeneity across sectors, owing to the disparity of sectoral accumulation rates of ICT inputs. Finally, results at the firm level exhibit a notable heterogeneity, although a majority of firms have seen their ICT capital growth rate and contribution to growth, increase.
SOME COMBINATORIAL PROBLEMS IN THE PLANE

The subsets of a d-element set under set inclusion form a poset whose Hasse diagram consists of the edges of a d-dimensional cube. The projection of such a cube into three-dimensional space produces a zonohedron-see [S] for the definition of a zonohedron. Since there is a one-to-one correspondence between arrangements of lines in the plane and zonohedra (see [7]), it seems reasonable to look for a partial ordering on the regions generated by an arrangement of lines, since these correspond to the vertices of the zonohedron. In this paper we define a partial ordering on the regions and discuss the size of its largest antichain under the assumption that not too many lines of the arrangement are parallel or concurrent (pass through the same point). Edelman has also discussed this poset in the plane and higher dimensions [3] and the complicated relationship between the zonotopes and Hasse diagrams in some special cases.
Discovering and Exploiting Statistical Properties for Query Optimization in Relational Databases: A Survey

Discovering and exploiting statistical features in relational datasets is key to query optimization in a relational database management system (RDBMS ), and is also needed for database design, cleaning, and integration. This paper surveys a variety of methods for automatically discovering important statistical features such as correlations, functional dependencies, keys, and algebraic constraints. We discuss proactive approaches in which the data is scanned or sampled (periodically, at optimization time or at query time), or in which exploratory queries are executed. Also discussed are reactive approaches that monitor the results of the query processing. Finally, we discuss methods for dealing with the practical challenges of maintaining statistical information in the face of heavy system utilization, and of dealing with inconsistencies that arise from incomplete cardinality models, use of multiple discovery methods, or changes in the underlying data over time. © 2009 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 1: 000‐000, 2008
A Review Study on Ozone Phytotoxicity Metrics for Setting Critical Levels in Asia

Ground-level ozone (O3) can be a menace for vegetation, especially in Asia where O3 levels have been dramatically increased over the past decades. To ensure food security and maintain forest ecosystem services, such as nutrient cycling, carbon sequestration and functional diversity of soil biota, in the over-populated Asia, environmental standards are needed. To set proper standards, dose-response relationships should be established from which critical levels are derived. The predictor of the response in the dose-response relationship is an O3 metric that indicates the dose level to which the plant has been exposed. This study aimed to review the relevant scientific literature and summarize the O3 metrics used worldwide to provide insights for Asia. A variety of O3 metrics have been used, for which we discuss their strengths and weaknesses. The most widely used metrics are based only on O3 levels. Such metrics have been adopted by several regulatory agencies in the global. However, they are biologically irrelevant because they ignore the plant physiological capacity. Adopting AOT40 (O3 mixing ratios Accumulated Over the Threshold of 40 nmol mol−1) as the default index for setting critical levels in Asia would be a poor policy with severe consequences at national and Pan-Asian level. Asian studies should focus on flux-based O3 metrics to provide relevant bases for developing proper standards. However, given the technical requirements in calculating flux-based O3 metrics, which can be an important limitation in developing countries, no-threshold cumulative exposure indices like AOT0 should always accompany flux-based indices.
CER-ETH-Center of Economic Research at ETH Zurich Economics Working Paper Series

This paper formalizes international status seeking in a two-country model of endogenous growth: utility of agents in developing countries is a¤ected by consumption gaps with advanced economies. By distorting intertemporal choices, envy tends to revert growth di¤erentials in favor of the developing country when traded goods are substitutes. Notably, asymmetric preferences with endogenous status desire generate (i) convergence in growth rates in the presence of structural gaps, and (ii) convergence in income levels, if productivity di¤erences are absorbed by technology di¤usion. This process is driven by declining terms of trade and faster capital accumulation of the status seeker. A calibration exercise shows that the model predictions are consistent with the stylized facts that characterized the growth performance of East Asian economies. JEL Codes O33, F12, D91.
Magnetosphere‐Ionosphere Connection of Storm‐Time Region‐2 Field‐Aligned Current and Ring Current: Arase and AMPERE Observations

Storm‐time region‐2 field‐aligned currents (R2 FACs) are believed to be connected between the ring current region and the ionosphere, but this connection has not been clarified by simultaneous in situ observations. We confirmed the connection of upward R2 FACs during 16 July and 18 June 2017 storm events using coordinated magnetic observations by the Arase satellite in medium‐Earth orbit and the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). The upward FACs were determined by drastic changes in the azimuthal magnetic field at Arase in the off‐equatorial (3‐ to 4‐RE radial distance and 1–2 RE above the magnetic equator) postmidnight inner magnetosphere. The magnetic latitude of the FAC observed by Arase projected onto the ionosphere was consistent with that of the ionospheric FAC observed by the AMPERE. Using the conservation of the ratio between the current density and the total magnetic field along the field line, we showed that the current between Arase and AMPERE was almost conserved, meaning that a large portion of the R2 FAC was generated in the low‐latitude inner magnetosphere. We also calculated the plasma pressures of H+ and O+ ions and pressure‐driven currents to examine their relationship for the first event. The O+ pressure contributed significantly to the inner part of the total azimuthal current. The peaks of combined pressure of H+ and O+, and pressure‐driven currents were located inside and outside the FAC, respectively. A simple model calculation indicated that this spatial relationship is controlled by the day‐night asymmetry of magnetic field.
DISTRIBUTION OF THE GENUS CEDRELA IN ECUADOR

The genus Cedrela in Ecuador has four species: C. odorata, C. montana, C. fissilis and C. nebulosa. Cedrela was one of the economically most important timber in the past, due to its wood properties. The genus has a long history of overharvesting and selective logging; as a consequence a substantial genetic degradation have occurred in Ecuador. Currently, three species of Cedrela are included in the IUCN Red List. C. odorata and C. nebulosa are listed as vulnerable species and C. fissilis as endangered species. In spite of their conservation status and priority, few studies related to geographical distribution have been done. Then, the geographic distribution at local level had been carried out to provide a valuable tool to the conservation and management of these species. Field sampling and herbarium compilation showed C. montana is restricted to the Ecuadorian highlands in the western and eastern Andean montane region between 805 to 3200 masl (meters above sea level). Cedrela nebulosa is located in Andean region about 1400 to 2300 masl. C. odorata is the most widely distributed, occupying areas in the Amazon (200-1300 masl), Pacific (330-825 masl) and insular regions (350 masl). While, Cedrela fissilis is only found in the Amazon Region about 200 to 510 masl. This basic information about current distribution and abundance of cedar species is primordial to generate sufficient tools to formulate the strategies of management and conservation of these species in the country. The widespread distribution of C. odorata have been found in the Amazonian and Pacific regions, indicating that it is adapted to tropical rainforest and tropical monsoon climates. To prove if there are adaptations to both habitats morphological, ecological and phylogenetic studies must be carried out.
Eye in the Sky: Investigating Spatial Performance Following Perspective Change

Unmanned Aerial Systems (UASs) are becoming more prevalent in civilian use, such as emergency response and public safety. As a result, UASs pose issues of remote perception for human users (Eyerman, 2013). The purpose of this experiment was to test the effects of combining aerial and ground perspectives on spatial judgments of object positions in an urban environment. Participants were shown randomly ordered image pairs of aerial and ground views of objects in a virtual city and were asked to make judgments about where a missing object was in the second image of the pair. Response times and error were collected with error being calculated using the Euclidean distance formula. The results were consistent with previous research and showed that congruent trials (aerial-aerial and ground-ground) resulted in less error and response time. It was also shown that there was a significant four-way interaction between stimulus image, response image, object density, and stimulus duration. The results of this study are intended to provide the basis for future work in understanding the underlying reasons behind spatial errors that might occur during use of UASs and lead to design implementations for interfaces to reduce these errors.
Influence of labyrinth seals in cavities on the flow of an axial compressor

The vortex structure inside the upstream cavity-trench depends on the cavity outlet angle. Independently of the cavity outlet angle, the interaction of the upstream rotor wake and the leakage flow induces a wake-leakage vortex. The proximity of the cavity outlet with the rotor modifies the number of induced wake-leakage vortices. This investigation reveals that in the downstream cavity-trench a windage effect occurs similar to the upstream cavity-trench but with minor intensity. The leakage flow cannot recirculate to the upstream cavity-trench and be reheated. All investigated configurations modify the recovery factor near the hub, namely below 10% span with the inclusion of the cavity. The Kerrebrock and Mikolajczak’s effect remains on the stator suction-side at the hub due to the leakage flow transported by wake-leakage vortices while at mid-span the effect appears on the stator pressure-side. The overall performance of the third compressor’s stage shows that the effect of the cavity outlet angle is more influential at lower leakage rates. As the leakage rate progressively increases, the cavity outlet angle loses its influence. Independently of the cavity outlet angle, the inclusion of the cavity in the third stage reduces the total pressure level and increases the total temperature level of the stage as a consequence of the transport within the wake-leakage vortices. This combination results in a more pronounced deterioration of the isentropic stage efficiency. For every 1% of labyrinth seal clearance increase, the stage total pressure ratio decreases between 0.114 to 0.132%, and total temperature ratio increases between 0.039 to 0.051% resulting in an isentropic efficiency reduction by 0.828 to 0.944%.
Developing Children’s Oral Health Assessment Toolkits Using Machine Learning Algorithm

Objectives: Evaluating children’s oral health status and treatment needs is challenging. We aim to build oral health assessment toolkits to predict Children’s Oral Health Status Index (COHSI) score and referral for treatment needs (RFTN) of oral health. Parent and Child toolkits consist of short-form survey items (12 for children and 8 for parents) with and without children’s demographic information (7 questions) to predict the child’s oral health status and need for treatment. Methods: Data were collected from 12 dental practices in Los Angeles County from 2015 to 2016. We predicted COHSI score and RFTN using random Bootstrap samples with manually introduced Gaussian noise together with machine learning algorithms, such as Extreme Gradient Boosting and Naive Bayesian algorithms (using R). The toolkits predicted the probability of treatment needs and the COHSI score with percentile (ranking). The performance of the toolkits was evaluated internally and externally by residual mean square error (RMSE), correlation, sensitivity and specificity. Results: The toolkits were developed based on survey responses from 545 families with children aged 2 to 17 y. The sensitivity and specificity for predicting RFTN were 93% and 49% respectively with the external data. The correlation(s) between predicted and clinically determined COHSI was 0.88 (and 0.91 for its percentile). The RMSEs of the COHSI toolkit were 4.2 for COHSI (and 1.3 for its percentile). Conclusions: Survey responses from children and their parents/guardians are predictive for clinical outcomes. The toolkits can be used by oral health programs at baseline among school populations. The toolkits can also be used to quantify differences between pre- and post-dental care program implementation. The toolkits’ predicted oral health scores can be used to stratify samples in oral health research. Knowledge Transfer Statement: This study creates the oral health toolkits that combine self- and proxy- reported short forms with children’s demographic characteristics to predict children’s oral health and treatment needs using Machine Learning algorithms. The toolkits can be used by oral health programs at baseline among school populations to quantify differences between pre and post dental care program implementation. The toolkits can also be used to stratify samples according to the treatment needs and oral health status.
SIGNAL PROCESSING Independent component analysis , A new concept ? *

The independent component analysis (ICA) of a random vector consists of searching for a linear transformation that minimizes the statistical dependence between its components. In order to define suitable search criteria, the expansion of mutual information is utilized as a function of cumulants of increasing orders. An efficient algorithm is proposed, which allows the computation of the ICA of a data matrix within a polynomial time. The concept of lCA may actually be seen as an extension of the principal component analysis (PCA), which can only impose independence up to the second order and, consequently, defines directions that are orthogonal. Potential applications of ICA include data analysis and compression, Bayesian detection, localization of sources, and blind identification and deconvolution. Zusammenfassung Die Analyse unabhfingiger Komponenten (ICA) eines Vektors beruht auf der Suche nach einer linearen Transformation, die die statistische Abh~ingigkeit zwischen den Komponenten minimiert. Zur Definition geeigneter Such-Kriterien wird die Entwicklung gemeinsamer Information als Funktion von Kumulanten steigender Ordnung genutzt. Es wird ein effizienter Algorithmus vorgeschlagen, der die Berechnung der ICA ffir Datenmatrizen innerhalb einer polynomischen Zeit erlaubt. Das Konzept der ICA kann eigentlich als Erweiterung der 'Principal Component Analysis' (PCA) betrachtet werden, die nur die Unabh~ingigkeit bis zur zweiten Ordnung erzwingen kann und deshalb Richtungen definiert, die orthogonal sind. Potentielle Anwendungen der ICA beinhalten Daten-Analyse und Kompression, Bayes-Detektion, Quellenlokalisierung und blinde Identifikation und Entfaltung. R~sum~ L'Analyse en Composantes Ind6pendantes (ICA) d'un vecteur al6atoire consiste en la recherche d'une transformation lin6aire qui minimise la d6pendance statistique entre ses composantes. Afin de d6finir des crit6res d'optimisation appropribs, on utilise un d6veloppement en s6rie de l'information mutuelle en fonction de cumulants d'ordre croissant. On propose ensuite un algorithme pratique permettant le calcul de I'ICA d'une matrice de donn6es en un temps polynomial. Le concept d'ICA peut 6tre vu en r~alitb comme une extension de l'Analyse en Composantes Principales (PCA) qui, elle, ne peut imposer l'ind6pendance qu'au second ordre et d6finit par cons6quent des directions orthogonales. Les applications potentielles de I'ICA incluent l'analyse et la compression de donn6es, la d&ection bayesienne, la localisation de sources, et l'identification et la d6convolution aveugles. + This work was supported in part by the DRET. 0165-1684/94/$7.00 © 1994 Elsevier Science B.V. All rights reserved SSDI 0165-1684(93)E0093-Z 288 P. Comon / Signal Processing 36 (1994) 28~314
Understanding the Determinants of Information Technology Adoption . Evidence from Italian Manufacturing Firms

Our empirical study aims at identifying the determinants of Information Technology adoption by small and medium sized Italian manufacturing firms (<100 employees). An ordered probit analysis is conducted on a sample of about 17,000 firms surveyed by the Italian Statistical Institute (ISTAT), using as a dependent variable an index of IT adoption called ITA. Our results show that firm size, geographical location, functional composition of the workforce, R&D activity, subcontracting, exports and collaboration between firms are all highly significant determinants of IT adoption. Such results are consistent with most of the predictions advanced in the few studies existing on this topic.
A new effective method for estimating missing values in the sequence data prior to phylogenetic analysis

In this article we address the problem of phylogenetic inference from nucleic acid data containing missing bases. We introduce a new effective approach, called “Probabilistic estimation of missing values” (PEMV), allowing one to estimate unknown nucleotides prior to computing the evolutionary distances between them. We show that the new method improves the accuracy of phylogenetic inference compared to the existing methods “Ignoring Missing Sites” (IMS), “Proportional Distribution of Missing and Ambiguous Bases” (PDMAB) included in the PAUP software [26]. The proposed strategy for estimating missing nucleotides is based on probabilistic formulae developed in the framework of the Jukes-Cantor [10] and Kimura 2-parameter [11] models. The relative performances of the new method were assessed through simulations carried out with the SeqGen program [20], for data generation, and the BioNJ method [7], for inferring phylogenies. We also compared the new method to the DNAML program [5] and “Matrix Representation using Parsimony” (MRP) [13], [19] considering an example of 66 eutherian mammals originally analyzed in [17].
Proceedings of the First Landscape State-and-Transition Simulation Modeling Conference, June 14–16, 2011, Portland, Oregon

Kerns, Becky K. ; Shlisky, Ayn J.; Daniel, Colin J., tech. eds. 2012. Proceedings of the First Landscape State-and-Transition Simulation Modeling Conference, June 14–16, 2011, Portland, Oregon. Gen. Tech. Rep. PNW-GTR-869. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 215 p. The first ever Landscape State-and-Transition Simulation Modeling Conference was held from June 14–16, 2011, in Portland Oregon. The conference brought together over 70 users of state-and-transition simulation modeling tools—the Vegetation Dynamics Development Tool (VDDT), the Tool for Exploratory Landscape Analysis (TELSA) and the Path Landscape Model. The goal of the conference was to (1) provide opportunities for sharing experiences with different applications of the tools, (2) identify major existing conceptual or technological gaps, and develop goals for future state-and-transition simulation model (STSM) development, and (3) start building an international network of STSM users. Eighteen oral presentations and thirteen posters were presented. This proceeding includes thirteen papers that build on some key STSM concepts, applications, and innovations from that conference, and shares them with a wider audience. The goal of these proceedings is to provide a state-of-the-science reference for STSM modelers and users. All papers were peer-reviewed by two blind reviewers and one editor. The presentation of these papers reveals that the STSM approach has been applied to a wide range of management and land-use questions and ecosystems, with an equally wide variation in the amounts of scientific data and expert knowledge available for model parameterization.
Quantifying uncertainties in the global mass balance of mercury

We quantify uncertainties in the global mass balance of mercury and identify research priorities to reduce these uncertainties. This is accomplished by developing a new spatially resolved global multimedia model (WorM3) that quantitatively describes the fate of mercury at a process level, and conducting an uncertainty analysis on its unit‐world variant which computes similar global estimates. In our modeling approach, all mass transfer processes and reactions in ocean water, soil and vegetation, are represented as pseudo‐first order; reactions in air are represented using the ratios of observed concentrations of mercury species. We use Monte Carlo analysis to estimate uncertainties in the unit‐world modeled global mass balance of mercury and quantitatively identify the input parameters which contribute most to these uncertainties. A key finding is that uncertainties in input parameters that describe the rates of reduction and oxidation reactions in surface ocean contribute more than uncertainties in anthropogenic emissions to the total uncertainties in atmospheric concentration and depositional fluxes of mercury. More research should therefore be targeted toward understanding of these oceanic processes.