Miracle-dz/UniFAR-FTUs huggingface dataset:
Global Value Chains and Trade Policy∗

How do global value chain (GVC) linkages modify countries’ incentives to impose import protection? Are these linkages empirically important determinants of trade policy in practice? To address these questions, we develop a new approach to modeling tariff setting with GVCs, in which optimal policy depends on the nationality of value-added content embedded in home and foreign final goods. Theory predicts that discretionary tariffs will be decreasing in the domestic content of foreign-produced final goods and the foreign content of domestically-produced final goods. Using theory as a guide, we estimate the influence of GVC linkages on trade policy with data on bilateral applied tariffs, temporary trade barriers, and value-added contents for 14 major economies between 1995 and 2015. Our empirical findings indicate that GVCs already play an important role in shaping trade policy. Governments set lower tariffs and curb their use of temporary trade protection (particularly against China) where GVC linkages are strongest. JEL Codes: F1, F13, F68 ∗We thank Adam Szeidl and three anonymous referees, whose insights and suggestions greatly improved the paper. We are also grateful to Thibault Fally, Nuno Limão, Ralph Ossa, Fernando Parro, Nina Pavcnik, Raymond Robertson, and Robert Staiger for detailed feedback on early drafts. Bown acknowledges financial support from the World Bank’s Multi-Donor Trust Fund for Trade and Development. Carys Golesworthy provided outstanding research assistance. †Tuck School of Business at Dartmouth College and CEPR; emily.blanchard@tuck.dartmouth. edu ‡Peterson Institute for International Economics and CEPR; cbown@piie.com §University of Notre Dame and NBER; rjohns24@nd.edu
Mixing Enhancement in Serpentine Micromixers with a Non-Rectangular Cross-Section

In this numerical study, a new type of serpentine micromixer involving mixing units with a non-rectangular cross-section is investigated. Similar to other serpentine/spiral shaped micromixers, the design exploits the formation of transversal vortices (Dean flows) in pressure-driven systems, associated with the centrifugal forces experienced by the fluid as it is confined to move along curved geometries. In contrast with other previous designs, though, the use of non-rectangular cross-sections that change orientation between mixing units is exploited to control the center of rotation of the transversal flows formed. The associated extensional flows that thus develop between the mixing segments complement the existent rotational flows, leading to a more complex fluid motion. The fluid flow characteristics and associated mixing are determined numerically from computational solutions to Navier–Stokes equations and the concentration-diffusion equation. It is found that the performance of the investigated mixers exceeds that of simple serpentine channels with a more consistent behavior at low and high Reynolds numbers. An analysis of the mixing quality using an entropic mixing index indicates that maximum mixing can be achieved at Reynolds numbers as small as 20 in less than four serpentine mixing units.
Survey on LCA results analysis, interpretation and reporting in the construction sector

Life Cycle Assessment (LCA) is widely recognized as the most relevant tool to evaluate building environmental impacts. Previous works have proposed different building LCA tools to spread LCA in the building sector practices. However, as initial questions are different depending on the user profiles, answers should be different from a building LCA tool developer's perspective. Indeed, one single LCA tool embedding a single methodology and a single way to analyse and express the results will not fulfil the needs of all stakeholders. In this study, a national survey was conducted in order to better understand the needs of these building stakeholders to feed back LCA tool developers. Focus was put on the interpretation and reporting steps of the LCA method as defined in ISO 14040. Results showed different practices, expertises, and scope of studies. Stakeholders not familiar with LCA prefer easy-to-go interpretation while experts still prefers keeping detailed results. Outcomes of this survey can now be used by building LCA tool developers to better ajust the analysis and interpretation tools in their software to match the user needs.
Modélisation multi-corps de roulements à billes non planaires

This work presents the dynamic modeling of ball bearing which uses multibody dynamic formalism. Such formalism allows immediate integration of the model in dynamic simulations of helicopter main gear boxes. Ball bearing is considered non-lubricated in order to predict its behavior in case of lubrication system failure. Rolling contacts are treated with the method proposed by Kalker. This approach is based on polynomial approximation of relative displacement on the contact ellipse. For low computational cost and without any spatial discretization, it gives a good estimation of tangential traction and creep. Also, a regularization of the Kalker linear creep theory is proposed. It is used here to facilitate the global convergence of the Newton iterative process. It is well suited for multibody dynamic simulations which do not need a very fine treatment of rolling contact. A numerical example of a ball bearing under thrust load is presented.
The Role of the Cloud Radiative Effect in the Sensitivity of the Intertropical Convergence Zone to Convective Mixing

Studies have shown that the location and structure of the simulated intertropical convergence zone (ITCZ) is sensitive to the treatment of sub-gridscale convection and cloud–radiation interactions. This sensitivity remains in idealized aquaplanet experiments with fixed surface temperatures. However, studies have not considered the role of cloud-radiative effects (CRE; atmospheric heating due to cloud–radiation interactions) in the sensitivity of the ITCZ to the treatment of convection. We use an atmospheric energy input (AEI) framework to explore how the CRE modulates the sensitivity of the ITCZ to convective mixing in aquaplanet simulations. Simulations show a sensitivity of the ITCZ to convective mixing, with stronger convective mixing favoring a single ITCZ. For simulations with a single ITCZ, the CRE maintains the positive equatorial AEI. To explore the role of the CRE further, we prescribe the CRE as either zero or a meridionally and diurnally varying climatology. Removing the CRE is associated with a reduced equatorial AEI and an increase in the range of convective mixing rates that produce a double ITCZ. Prescribing the CRE reduces the sensitivity of the ITCZ to convective mixing by 50%. In prescribed-CRE simulations, other AEI components, in particular the surface latent heat flux, modulate the sensitivity of the AEI to convective mixing. Analysis of the meridional moist static energy transport shows that a shallower Hadley circulation can produce an equatorward energy transport at low latitudes even with equatorial ascent.
Predictive Analytics for News Articles Using Wikipedia

Our news are saturated with various statements pertaining to future actions, employment, stock market, economic growth projections, global financial crisis, policies, globalization, climate changes, technologies, etc. Such future trends could have potential impact on our lives, business, etc. In this work, we consider a set of articles or reports by journalists or others, wherein they predict or promise something about future. The problem we address is to determine the credibility of the authors based on the predictions coming out to be true. The two specific problems we address in this thesis are automatically extracting the predictions from the articles and annotating with various prediction attributes. And then, we determine the truth of these predictions, using Wikipedia as a credible source to retrieve relevant facts which can ascertain the validity of the predictions. We estimate that large number of news articles contain references to future. The reference is detected through the notion of predictive statements (phrases). Distinguishing such predictive statements from factual statements in news articles is important for most applications such as fact checking, opinion mining, future trend analysis, etc. In this thesis, we present our approach to the problem of automatically extracting future-related information by solving two sub-problems. The first sub-problem is labeling a sentence as predictive or factual. In addition to extracting the predictions, we address the tasks of clausal scope resolution and dis-embedding linguistic peripheral clauses with respect to the predictive clause in a sentence. To solve these problems, we extract all the clauses of a given sentence and classify each of the clauses as predictive or factual. We then use a machine learning based approach to disambiguate the clause labels by using the clausal dependency relations and label the sentence. ’. We present the results obtained by our predictions extraction methods on two datasets collected and annotated from economics, politics and sports domain. Our system attained an accuracy of (0.85-0.89) on both the datasets. In addition to extracting predictive statements, we further attempted to validate the truth of these predictions. We proposed an architecture to integrate various unscaled Natural Language Processing resources to incorporate background knowledge into our modules, and built an end to end system for automated predictions validation(APV) by extracting future speculations and predictions from news articles and social media. We proposed heuristics to identify core prediction triplets and a retrieval model to extract facts relevant to the prediction. We demonstrated relation alignment based entailment methods for validating the truth of predictions against relevant facts obtained from credible sources(Wikipedia).
Modeling of Transport Properties Using the SAFT-VR Mie Equation of State

Carbon capture and storage (CCS) has been presented as one of the most promising methods to counterbalance the CO2 emissions from the combustion of fossil fuels. Density, viscosity and interfacial tension (IFT) are, among others properties, crucial for the safe and optimum transport and storage of CO2-rich steams and they play a key role in enhanced oil recovery (EOR) operations. Therefore, in the present work the capability of a new molecular based equation of state (EoS) to describe these properties was evaluated by comparing the model predictions against literature experimental data. The EoS considered herein is based on an accurate statistical associating fluid theory with variable range interaction through Mie potentials (SAFT-VR Mie EoS). The EoS was used to describe the vapor-liquid equilibria (VLE) and the densities of selected mixtures. Phase equilibrium calculations are then used to estimate viscosity and interfacial tension values. The viscosity model considered is the TRAPP method using the single phase densities, calculated from the EoS. The IFT was evaluated by coupling this EoS with the density gradient theory of fluids interfaces (DGT). The DGT uses bulk phase properties from the mixture to readily estimate the density distribution of each component across the interface and predict interfacial tension values. To assess the adequacy of the selected models, the modeling results were compared against experimental data of several CCVrich systems in a wide range of conditions from the literature. The evaluated systems include five binaries (CO2/O2, CO2/N2, CO2/Ar, CO2/n-C4 and CO2/n-C10) and two multicomponent mixtures (90%CO2 / 5%O2 / 2%Ar / 3%N2 and 90%CO2 / 6%n-C4 / 4%n-C10). The modeling results showed low absolute average deviations to the experimental viscosity and IFT data from the literature, supporting the capabilities of the adopted models for describing thermophysical properties of CO2-rich systems
Automatic Mapping of Lineaments Using Shaded Relief Images Derived from Digital Elevation Model ( DEM ) in Kirkuk Northeast Iraq

The area of this study is one of the important places in Iraq, which contains many important oil fields. Shaded relief images created from digital elevation models (DEMs) are helpful in identifying lineaments in different distinct relief and topography. Combining four shaded relief images into a final image leads to enhancing lineaments within the four sun azimuth directions(Anwar Abdullah, 2010) the method can enhance lineaments at different orientations by simulating topographic illumination under varied light directions. Combining four shaded relief images into a final image leads to enhancing lineaments within the four sun azimuth directions. Two shaded relief images with multi-directional light were created, the first image with the four azimuth angles of the light sources that are 0°, 45°, 90° and 135°, and the second image with the four azimuth angles of the light sources that are 180°, 225°, 270°,and 315°. Both images have been used for automatic lineament extraction using PCI Geomatica2013 software. The extracted lineaments of the first image show that the most automatic lineaments represent positive lineaments; and the automatic lineaments of second image represent negative lineaments of the study area. The term “lineament” is one of the most commonly used terms in geology. A lineament is any extensive linear surface on a planet, as a fault line or fracture line. Hobbs (1904) first used the term lineament to define a significant line of landscape of Basement rocks. O’Leary et al. (1976) described the term lineament as a mappable, simple or composite linear feature of a surface whose parts are aligned in a rectilinear or slightly curvilinear relationship and which differs from the pattern of adjacent features and presumably reflects some sub-surface phenomenon
Cataract influence on iris recognition performance

This paper presents the experimental study revealing weaker performance of the automatic iris recognition methods for cataract-affected eyes when compared to healthy eyes. There is little research on the topic, mostly incorporating scarce databases that are often deficient in images representing more than one illness. We built our own database, acquiring 1288 eye images of 37 patients of the Medical University of Warsaw. Those images represent several common ocular diseases, such as cataract, along with less ordinary conditions, such as iris pattern alterations derived from illness or eye trauma. Images were captured in near-infrared light (used in biometrics) and for selected cases also in visible light (used in ophthalmological diagnosis). Since cataract is a disorder that is most populated by samples in the database, in this paper we focus solely on this illness. To assess the extent of the performance deterioration we use three iris recognition methodologies (commercial and academic solutions) to calculate genuine match scores for healthy eyes and those influenced by cataract. Results show a significant degradation in iris recognition reliability manifesting by worsening the genuine scores in all three matchers used in this study (12% of genuine score increase for an academic matcher, up to 175% of genuine score increase obtained for an example commercial matcher). This increase in genuine scores affected the final false non-match rate in two matchers. To our best knowledge this is the only study of such kind that employs more than one iris matcher, and analyzes the iris image segmentation as a potential source of decreased reliability
IRIS RECOGNITIONWITH MATCH-ON-CARD

The paper presents a biometric smart card that supports on-card matching. The card supports twoor three-factor verification of the card holder (biometrics, smart card and optionally password or PIN). We use a novel iris coding based on Zak-Gabor transform, which may adapt to image quality. Basic properties of the proposed coding are presented in the paper. The biometric smart card is an element of Iris Recognition System, which also includes eye aliveness detection. The system, evaluated with a proprietary database of iris images, shows very favorable results.
Combining Class Taxonomies and Multi Task Learning To Regularize Fine-grained Recognition

Fine-grained classification is an extremely challenging problem in computer vision, impaired by subtle differences in shape, pose, illumination and appearance, and further compounded by subtle intraclass differences and striking inter-class similarities. While convolutional neural networks have become versatile jack-of-all-trades tool in modern computer vision, approaches for fine-grained recognition still rely on localization of keypoints and parts to learn discriminative features for recognition. In order to achieve this, most approaches necessitate copious amounts of expensive manual annotations for bounding boxes and keypoints. As a result, most of the current methods inevitably end up becoming complex, multi-stage pipelines, with a deluge of tunable knobs, which makes it infeasible to reproduce them or deploy them for any practical scenario. Since image level annotation is prohibitively expensive for most fine-grained problems, we look at the problem from a rather different perspective, and try to reason about what might be the minimum amount of additional annotation that might be required to obtain an improvement in performance on the challenging task of fine-grained recognition. In order to tackle this problem, we aim to leverage the (taxonomic and/or semantic) relationships present among fine-grained classes. The crux of our proposed approach lies in the notion that fine-grained recognition effectively deals with subordinate-level classification, and as such, subordinated classes imply the presence of inter-class and intra-class relationships. These relationships may be taxonomical, such as super-classes, and/or semantic, such as attributes or factors, and are easily obtainable in the sense that domain expertise is needed for each fine-grained label, not for each image separately. We propose to exploit the rich latent knowledge embedded in these inter-class relationships for visual recognition. We posit the problem as a multi-task learning problem where each different label obtained from inter-class relationships can be treated as a related yet different task for a comprehensive multi-task model. Additional tasks/labels, which might be super-classes or attributes, or factor-classes can act as regularizers, and increase the generalization capabilities of the network. Class relationships are almost always a free source of labels that can be used as auxiliary tasks to train a multi-task loss which is usually a weighted sum of the different individual losses. Multiple tasks will try to take the network in diverging directions, and the network must reach a common minimum by adapting and learning features common to all tasks in its shared layers. Our main contribution is to utilize the taxonomic/semantic hierarchies among classes, where each level in the hierarchy is posed as a classification problem, and solved jointly using multi-task learning. We employ a cascaded multi-task network architecture, where the output of one task feeds into the next, thus
QuadriFlow: A Scalable and Robust Method for Quadrangulation

QuadriFlow is a scalable algorithm for generating quadrilateral surface meshes based on the Instant Field‐Aligned Meshes of Jakob et al. (ACM Trans. Graph. 34(6):189, 2015). We modify the original algorithm such that it efficiently produces meshes with many fewer singularities. Singularities in quadrilateral meshes cause problems for many applications, including parametrization and rendering with Catmull‐Clark subdivision surfaces. Singularities can rarely be entirely eliminated, but it is possible to keep their number small. Local optimization algorithms usually produce meshes with many singularities, whereas the best algorithms tend to require non‐local optimization, and therefore are slow. We propose an efficient method to minimize singularities by combining the Instant Meshes objective with a system of linear and quadratic constraints. These constraints are enforced by solving a global minimum‐cost network flow problem and local boolean satisfiability problems. We have verified the robustness and efficiency of our method on a subset of ShapeNet comprising 17,791 3D objects in the wild. Our evaluation shows that the quality of the quadrangulations generated by our method is as good as, if not better than, those from other methods, achieving about four times fewer singularities than Instant Meshes. Other algorithms that produce similarly few singularities are much slower; we take less than ten seconds to process each model. Our source code is publicly available.
Predictive physiological anticipatory activity preceding seemingly unpredictable stimuli: An update of Mossbridge et al’s meta-analysis

Background: This is an update of the Mossbridge et al’s meta-analysis related to the physiological anticipation preceding seemingly unpredictable stimuli which overall effect size was 0.21; 95% Confidence Intervals: 0.13 - 0.29 Methods: Nineteen new peer and non-peer reviewed studies completed from January 2008 to June 2018 were retrieved describing a total of 27 experiments and 36 associated effect sizes. Results: The overall weighted effect size, estimated with a frequentist multilevel random model, was: 0.28; 95% Confidence Intervals: 0.18-0.38; the overall weighted effect size, estimated with a multilevel Bayesian model, was: 0.28; 95% Credible Intervals: 0.18-0.38. The weighted mean estimate of the effect size of peer reviewed studies was higher than that of non-peer reviewed studies, but with overlapped confidence intervals: Peer reviewed: 0.36; 95% Confidence Intervals: 0.26-0.47; Non-Peer reviewed: 0.22; 95% Confidence Intervals: 0.05-0.39. Similarly, the weighted mean estimate of the effect size of Preregistered studies was higher than that of Non-Preregistered studies: Preregistered: 0.31; 95% Confidence Intervals: 0.18-0.45; No-Preregistered: 0.24; 95% Confidence Intervals: 0.08-0.41. The statistical estimation of the publication bias by using the Copas selection model suggest that the main findings are not contaminated by publication bias. Conclusions: In summary, with this update, the main findings reported in Mossbridge et al’s meta-analysis, are confirmed.