Miracle-dz/UniFAR-FTUs huggingface dataset:
An Empirical Assessment of the Proximity-Concentration Tradeoff between Multinational Sales and Trade

This paper empirically investigates the role of transport costs, trade and investment barriers, production scale economies, and firm- specific advantages in determining the use of overseas production relative to exports. The proximity-concentration hypothesis is robust in explaining the share of total sales accounted for by affiliate sales: this share is greater the higher are transport costs and trade barriers and the lower are plant scale economies and investment barriers. Although strictly speaking, the proximity-concentration hypothesis applies to the shares of affiliate sales and exports rather than the levels, the effects of trade and investment barriers on the levels are similar to their effects on the shares, controlling for simultaneity, and so is that of freight factors in the trade estimates. The elasticity of inward and outward net affiliate sales with respect to tariffs is around 0.45, and that with respect to NTBs is an additional 0.17. The elasticity of both imports and exports with respect to freight factors is -1. However, the effect of freight factors on the level of affiliate sales is not robust, and the probability of observing any affiliate sales is increasing in proximity. The overall complementarity between trade and affiliate sales arises in part because relative income and intellectual property intensity increase both. In contrast, affiliate sales and trade move in opposite directions with increases in advertising intensity, suggesting that advertising-intensive products require a local presence.
Preparing for Success in Canada and the United States: The Determinants of Educational Attainment Among the Children of Immigrants

This paper reviews the recent research on the determinants of the educational attainment among the children of immigrants (the 2nd generation) in Canada and the United States. The focus is on the gap in educational attainment between the 2nd and 3rd-and-higher generations (the children of domestic born parents), as well as the intergenerational transmission of education between immigrants and their children. On average, the children of immigrants have educational levels significantly above their counterparts with domestic born parents in Canada. In the U.S., educational levels are roughly the same between these two groups. In both countries, conditional on the educational attainment of the parents and location of residence, the children of immigrants outperform the 3rd-and-higher generation in educational attainment. Parental education and urban location are major determinants of the gap in educational attainment between the children of immigrants and those of Canadian or American born parents. However, even after accounting for these and other demographic background variables, much of the positive gap between the 2nd and 3rd-and-higher generations remains in Canada. In Canada, parental education is less important as a determinant of educational attainment for the children in immigrant families than among those with Canadian-born parents. Less educated immigrant parents are more likely to see their children attain higher levels of education than are their Canadian-born counterparts. Outcomes vary significantly by ethnic/source region group in both countries. In the U.S., some 2nd generation ethnic/source region groups, such as those with Mexican, Puerto Rican, Central American backgrounds, have relatively low levels of education, even though conditional on background characteristics they outperform their 3rd-and-higher generation counterparts. In contrast, in Canada, children of the larger and increasingly numerically important immigrant groups (the Chinese, South Asians, Africans, etc) register superior educational attainment levels to those of the 3rd-and-higher generation. This result is partly related to the high levels of parental education and group-level â€œethnic capitalâ€ among these immigrant groups.
Enhancing Drug-Drug Interaction Classification with Corpus-level Feature and Classifier Ensemble

The study of drug-drug interaction (DDI) is important in the drug discovering. Both PubMed and DrugBank are rich resources to retrieve DDI information which is usually represented in plain text. Automatically extracting DDI pairs from text improves the quality of drug discov-ering. In this paper, we presented a study that focuses on the DDI classification. We normalized the drug names, and developed both sentence-level and corpus-level features for DDI classification. A classifier ensemble approach is used for the unbalance DDI labels problem. Our approach achieved an F-score of 65.4% on SemEval 2013 DDI test set. The experimental results also show the effects of proposed corpus-level features in the DDI task.
Complexity and Dual Institutionality: The Case of IFRS Adoption in Russia

Manuscript Type. Empirical. Research Questions/Issue. The widespread adoption of International Financial Reporting Standards (IFRS) by many transition economies is expected to contribute to greater transparency in financial reporting. However, the business environment in many of these countries is associated with institutional voids and ongoing economic and institutional change. Organizations operating in this environment face considerable institutional complexity due to influences from incongruent institutional logics of local and global institutions. This study investigates how organizations manage institutional complexity created by the incompatible institutional logics which are linked to IFRS adoption. Research Findings/Insights. In Russia, institutional change related to IFRS adoption was not revolutionary as IFRS did not replace Russian Accounting Standards (RAS) but both standards coexist. Based on a sample of 1,236 firms, organizational identity and the discretion in standard implementation were identified as factors that play a role in how organizations manage institutional complexity created by the coexistence of both standards. Theoretical/Academic Implications. With organizations in transition economies increasingly managing global and local pressures, this study highlights conditions under which practices rooted in conflicting institutional logics coexist and create dual institutionality. Dual institutionality occurs when distinct but related practices that organizations are using have legitimacy but are rooted in diverse institutional logics and coexist due to different levels of discretion associated with their implementation. This concept is distinct from previously identified institutional duality, where competing institutional logics of subsidiary and the host country influence how a particular practice is implemented by organizations. Practitioner/Policy Implications. While adoption of IFRS is expected to contribute to greater financial transparency and comparability, some countries choose to continue with the local standards while permitting or requiring IFRS. This type of parallel adoption may undermine the influence of IFRS. However, divergence between the logics and discretion in standard implementation makes it possible for both practices to exist.
Substructure Assembling Network for Graph Classification

Graphs are natural data structures adopted to represent real-world data of complex relationships. In recent years, a surge of interest has been received to build predictive models over graphs, with prominent examples in chemistry, computational biology, and social networks. The overwhelming complexity of graph space often makes it challenging to extract interpretable and discriminative structural features for classification tasks. In this work, we propose a novel neural network structure called Substructure Assembling Network (SAN) to extract graph features and improve the generalization performance of graph classification. The key innovation of our work is a unified substructure assembling unit, which is a variant of Recurrent Neural Network (RNN) designed to hierarchically assemble useful pieces of graph components so as to fabricate discriminative substructures. SAN adopts a sequential, probabilistic decision process, and therefore it can tune substructure features in a finer granularity. Meanwhile, the parameterized soft decisions can be continuously improved with supervised learning through back-propagation, leading to optimizable search trajectories. Overall, SAN embraces both the flexibility of combinatorial pattern search and the strong optimizability of deep learning, and delivers promising results as well as interpretable structural features in graph classification against state-of-the-art techniques.
Specification and Testing the Profits-Concentration Relationship: Some Experiments for the UK

This paper discusses a simple methodological point which provides the basis of one explanation of the rather surprising set of results suggesting that concentration is not a significant determinant of industry profitability in the UK (see the survey by Hart and Clarke, 1979). The methodological point is the familiar one that, in fitting a regression, one is constraining the data to a specific functional form; thus, prior to hypothesis testing, one must ensure that the imposed form is an acceptable representation of the data. We shall apply this principle to the basic profits-concentration model which is almost always unquestioningly taken to be linear. In Section I below, we shall outline the basic profits-concentration relationship, showing that linearity is not an obviously appealing assumption to make. In Section II, we shall discuss estimation and testing procedures given uncertainty concerning the appropriate functional form; Section III contains some experiments on UK data (which show that the relationship between profits and concentration is positive but not linear); and Section IV contains our principal conclusions.
The Causal Effect of Compulsory Voting Laws on Turnout: Does Skill Matter?

A very important, yet unsettled, question is whether mandatory voting affects political participation. This paper exploits a natural experiment to assess the causal impact of compulsory voting on turnout and, more importantly, to test whether the impact is different across skill groups. I find that compulsory voting increases voter turnout by 18 percentage points (28%) and the increase is twice as much in the unskilled citizens than that in the skilled citizens. This study is the first to show, with rigorous empirical evidence, that compulsory voting laws are effective in reducing the skill/socioeconomic gap in political participation. Furthermore, by shaping the electorate, these laws have relevant consequences in terms of the economic policies applied.
Innovation, Diversity and Diffusion: A Self-organisation Model

A number of features of innovation diffusion are identified: appropriability, diversity, expectations, selection, learning, and spillover externalities. A dynamic model is formul ated to embed the diffusion question into a more general framework of disequilibrium competition. The model incorporates distinct vintage structures reflecting a change in technological trajectory, learning-by-using, a nd expectations-driven investment rules of thumb. Simulation studies reveal robust quasi-logistic curves, but a complicated pattern of net market share gains and losses. Uncertainty regarding the rationality of early or late adoption, it is argued, ensures that the requisite behavioral variety is present to generate these diffusion patterns. Copyright 1988 by Royal Economic Society.
Mycobacterium avium infection in CD14‐deficient mice fails to substantiate a significant role for CD14 in antimycobacterial protection or granulomatous inflammation

CD14 is a pattern‐recognition receptor implicated in the inflammatory response to microbial components such as lipopolysaccharide, peptidoglycan and lipoarabinomannan. In this work, we made use of CD14‐deficient (CD14−/−) mice to evaluate the relative importance of CD14 in response to infection with viable, intact cells of Mycobacterium avium in vitro and in vivo. Following co‐incubation of either bone marrow‐derived macrophages (Mφ) or thioglycollate‐elicited peritoneal Mφ from CD14−/− mice with viable M. avium, tumour necrosis factor (TNF) production was significantly reduced and delayed compared to TNF secretion by infected CD14+/+ Mφ. However, following intravenous infection with a M. avium strain of either high virulence (TMC724) or intermediate virulence (SE01), there was no difference in the bacterial loads of lungs, livers or spleens at 3, 5 and 8 weeks postinfection in CD14−/− mice when compared with syngeneic CD14+/+ mice. At these time‐points, TNF and interferon‐γ (IFN‐γ) mRNA expression in the liver was similar in infected CD14+/+ and CD14−/− mice, and granuloma formation and expression of inducible nitric oxide synthase within granuloma Mφ was the same in both mouse groups. In conclusion, although the absence of CD14 results in significantly reduced and delayed TNF production in response to stimulation with M. avium in vitro, there is no evidence that CD14 plays a significant role in either the antibacterial defence or the chronic granulomatous reaction to M. avium infection in vivo.
The impact of student loans on educational attainment: the case of a program at the pontifical catholic university of Peru

During the past decades, the Pontifical Catholic University of Peru (known as PUCP) has been giving student loans to some of its students with satisfactory academic performance but who face certain economic problems which might interrupt their studies. Although this program was created more than forty years ago, its results have not been rigorously evaluated. This document attempts to assess to what extent the program has benefited students. Because the collected data come from academic and social records, the completion of this task requires using modern techniques specifically designed to work with non experimental data. After estimating by propensity score matching with multiple treatments, I find a statistically significant impact of this program on the time a student employs to complete the course of study at PUCP (measured in semesters) only when a student was awarded with a loan for 6 semesters or more. That effect is not significantly different from zero when the loan lasts less than 6 semesters. Similar results were found when I analyzed the impact on the probability of degree completion of student loans, where students with loan were more likely to meet all graduation requirements by 6 years and a half after they start studying at PUCP. Again this effect was significant only when the student participates in the program for six semesters or more. However, the impact on that probability was small.
A Unified Model for Document-Based Question Answering Based on Human-Like Reading Strategy

Document-based Question Answering (DBQA) in Natural Language Processing (NLP) is important but difficult because of the long document and the complex question. Most of previous deep learning methods mainly focus on the similarity computation between two sentences. However, DBQA stems from the reading comprehension in some degree, which is originally used to train and test people's ability of reading and logical thinking. Inspired by the strategy of doing reading comprehension tests, we propose a unified model based on the human-like reading strategy. The unified model contains three major encoding layers that are consistent to different steps of the reading strategy, including the basic encoder, combined encoder and hierarchical encoder. We conduct extensive experiments on both the English WikiQA dataset and the Chinese dataset, and the experimental results show that our unified model is effective and yields state-of-the-art results on WikiQA dataset.
Learning the Behavior of a Dynamical System Via a "20 Questions" Approach

Using a graphical discrete dynamical system to model a networked social system, the problem of inferring the behavior of the system can be formulated as the problem of learning the local functions of the dynamical system. We investigate the problem assuming an active form of interaction with the system through queries. We consider two classes of local functions (namely, symmetric and threshold functions) and two interaction modes, namely batch mode (where all the queries must be submitted together) and adaptive mode (where the set of queries submitted at a stage may rely on the answers received to previous queries). We develop complexity results and efficient heuristics that produce query sets under both query modes. We demonstrate the performance of our heuristics through experiments on over 20 well-known networks.
The efficacy and safety of adrenergic blockade after burn injury: A systematic review and meta-analysis

BACKGROUND The hypermetabolic state after severe burns is a major problem that can lead to several pathophysiologic changes and produce multiple sequelae. Adrenergic blockade has been widely used to reverse these changes and improve outcomes in burned patients but has not been rigorously evaluated. The aim of this systematic review was to investigate the efficacy and safety of the use of adrenergic blockade after burn injury. METHODS The databases MEDLINE via OVID, PubMed, EMBASE, CINAHL, Cochrane Library, and Web of Science were searched from inception to December 2014 with search terms including burns and beta-blockers with appropriate synonyms. Articles were restricted to those published in English, French, or Spanish. Randomized controlled trials, nonrandomized controlled trials, and systematic reviews were screened. After an independent screening and full-text review, 10 articles were selected, and an appraisal of risk of bias was performed. RESULTS From 182 articles screened, 9 randomized controlled trials and 1 nonrandomized controlled trial met the inclusion criteria. Pooled analyses were performed to calculate effect sizes and 95% confidence intervals (CIs). There was a positive effect favoring propranolol use that significantly decreased resting energy expenditure (g = −0.64; 95% CI, −0.8 to −0.5; p < 0.001) and trunk fat (g = −0.3; 95% CI, −0.4 to −0.1; p < 0.001) as well as improved peripheral lean mass (g = 0.45; 95% CI, 0.3–0.6; p < 0.001) and insulin resistance (g = −1.35; 95% CI, −2.0 to −0.6; p < 0.001). Occurrence of adverse events was not significantly different between the treated patients the and controls. CONCLUSION Limited evidence suggests beneficial effects of propranolol after burn injury, and its use seems safe. However, further trials on adult population with a broader range of outcome measures are warranted. LEVEL OF EVIDENCE Systematic review and meta-analysis, level III.
Real-Time Observations of Food and Fluid Timing During a 120 km Ultramarathon

The aim of the present case study was to use real-time observations to investigate ultramarathon runners' timing of food and fluid intake per 15 km and per hour, and total bodyweight loss due to dehydration. The study included 5 male ultramarathon runners observed during a 120 km race. The research team members followed on a bicycle and continuously observed their dietary intake using action cameras. Hourly carbohydrate intake ranged between 22.1 and 62.6 g/h, and fluid intake varied between 260 and 603 mL/h. These numbers remained relatively stable over the course of the ultra-endurance marathon. Runners consumed food and fluid on average 3–6 times per 15 km. Runners achieved a higher total carbohydrate consumption in the second half of the race (p = 0.043), but no higher fluid intake (p = 0.08). Energy gels contributed the most to the total average carbohydrate intake (40.2 ± 25.7%). Post-race weight was 3.6 ± 2.3% (range 0.3–5.7%) lower than pre-race weight, revealing a non-significant (p = 0.08) but practical relevant difference. In conclusion, runners were able to maintain a constant timing of food and fluid intake during competition but adjusted their food choices in the second half of the race. The large variation in fluid and carbohydrate intake indicate that recommendations need to be individualized to further optimize personal intakes.
Performance of water policy reforms under scarcity conditions: a case study in Northeast Brazil.

Increasing demand for water amid variable hydrology and climate uncertainty challenges the traditional methods of allocating scarce water resources. Water markets are an oft-promoted allocation method but their adoption is limited. This paper evaluates the performance of policy alternatives to water markets in terms of economic efficiency using analytical models of allocation. Priority systems, pricing systems and negotiation are compared for varying levels of scarcity. The analysis finds that the performance of each system depends on the level of scarcity. In general, a priority-based system is best in the worst conditions, while negotiation is better otherwise. This finding is pertinent to water policy and drought management, as negotiation is often only used in the worst conditions and priority used at other times. These results imply the reverse should be true. The paper also shows the means for evaluating non-market allocation in economic terms.
Fair Inference on Outcomes

In this paper, we consider the problem of fair statistical inference involving outcome variables. Examples include classification and regression problems, and estimating treatment effects in randomized trials or observational data. The issue of fairness arises in such problems where some covariates or treatments are "sensitive," in the sense of having potential of creating discrimination. In this paper, we argue that the presence of discrimination can be formalized in a sensible way as the presence of an effect of a sensitive covariate on the outcome along certain causal pathways, a view which generalizes (Pearl 2009). A fair outcome model can then be learned by solving a constrained optimization problem. We discuss a number of complications that arise in classical statistical inference due to this view and provide workarounds based on recent work in causal and semi-parametric inference.
Optimization of Frame Length Modulation-Based Wake-Up Control for Green WLANs

In this paper, green wireless local area networks (WLANs), where idle access points (APs) are put into sleep and activated upon the request of mobile nodes, are realized by exploiting WLAN signals to convey wake-up messages. Specifically, wake-up messages, sent by nodes, are modulated onto frame lengths (physical transmission time) of successive WLAN signals and detected by non-WLAN low-cost receivers equipped at APs. This method, however, is susceptible to serious 1) false negative events due to low signal quality or collisions with background WLAN frames and 2) false positive events where background WLAN frames happen to have the same frame lengths as those of wake-up messages. In the proposed scheme, WLAN frames forming a wake-up message are transmitted in a burst and interpreted as an equivalent message. On this basis, false probability is reduced from two aspects: 1) Modulation constellations of frame lengths are optimized to maximize the Hamming distance between equivalent messages, and 2) preamble frame and envelope smoothing are used to mitigate false events. In addition to theoretical analysis and simulation, a prototype test bed is built and experimented on. Extensive evaluations confirm that the proposed scheme helps to greatly improve the reliability of wake-up control compared with state-of-the-art methods.