Miracle-dz/UniFAR-FTUs huggingface dataset:
Embedding through Large-scale Heterogeneous Text Networks

Unsupervised text embedding methods, such as Skip-gram and Paragraph Vector, have been attracting increasing attention due to their simplicity, scalability, and effectiveness. However, comparing to sophisticated deep learning architectures such as convolutional neural networks, these methods usually yield inferior results when applied to particular machine learning tasks. One possible reason is that these text embedding methods learn the representation of text in a fully unsupervised way, without leveraging the labeled information available for the task. Although the low dimensional representations learned are applicable to many different tasks, they are not particularly tuned for any task. In this paper, we fill this gap by proposing a semi-supervised representation learning method for text data, which we call the predictive text embedding (PTE). Predictive text embedding utilizes both labeled and unlabeled data to learn the embedding of text. The labeled information and different levels of word co-occurrence information are first represented as a large-scale heterogeneous text network, which is then embedded into a low dimensional space through a principled and efficient algorithm. This low dimensional embedding not only preserves the semantic closeness of words and documents, but also has a strong predictive power for the particular task. Compared to recent supervised approaches based on convolutional neural networks, predictive text embedding is comparable or more effective, much more efficient, and has fewer parameters to tune.
R³ Adversarial Network for Cross Model Face Recognition

In this paper, we raise a new problem, namely cross model face recognition (CMFR), which has considerable economic and social significance. The core of this problem is to make features extracted from different models comparable. However, the diversity, mainly caused by different application scenarios, frequent version updating, and all sorts of service platforms, obstructs interaction among different models and poses a great challenge. To solve this problem, from the perspective of Bayesian modelling, we propose R3 Adversarial Network (R3AN) which consists of three paths: Reconstruction, Representation and Regression. We also introduce adversarial learning into the reconstruction path for better performance. Comprehensive experiments on public datasets demonstrate the feasibility of interaction among different models with the proposed framework. When updating the gallery, R3AN conducts the feature transformation nearly 10 times faster than ResNet-101. Meanwhile, the transformed feature distribution is very close to that of target model, and its error rate is incredibly reduced by approximately 75% compared with a naive transformation model. Furthermore, we show that face feature can be deciphered into original face image roughly by the reconstruction path, which may give valuable hints for improving the original face recognition models.
econstor Make Your Publications Visible . A Service of zbw

I provide a broad overview of the findings reported in the articles submitted for this special volume on experimental studies of social dilemma problems. I start by providing a synopsis of where current research stands on this topic. Then I go on to discuss the specific papers and how those papers extend our knowledge in this area and add value to the current state of the art.
Rumen impaction in cattle due to plastic materials

ARTICLE INFO The present study was carried out on 22 cows suffering from ruminal impaction with plastic materials as foreign bodies and ten apparently healthy cows as a control group. Clinical examination included clinical signs, temperature, pulse, respiratory rate and ruminal motility were recorded prior to treatment. Hematological parameters such as hemoglobin (Hb), packed cell volume (PCV), erythrocyte count (RBCs), total leucocytes (WBCs) count and the glutaraldehyde test were performed. Ruminal fluid was evaluated for pH and the methylene blue reduction time (MBRT). The mean pH of rumen fluid, MBRT, total leucocytes count, and PCV were increased significantly (P<0.05). Rumen motility was significantly reduced (P<0.05) preoperative in the animals suffering from rumen impaction, but the mean value of pulse rate, respiration rate, temperature, glutaraldehyde test, haemoglobin and total erythrocyte count were non-significantly changed. On the 5 postoperative day the clinical and the laboratory parameters in the study group had largely become normalized. Six months after the procedure, 18 (81.9%) cows showed complete recovery and 4 (18.9%) animals were slaughtered within 3 months following surgery. This study concluded that the clinical and laboratory findings might be of diagnostic importance. Rumen impaction with plastic materials should be differentiated from anorexia, emaciation, ruminal hypomotility, tympany and dehydration in cows. The surgical removal of foreign body demonstrated positive effects on animal health. Article history:
Gaining advantage by winning contests

We consider a principal who faces many identical competitors, and who can distribute a prize fund over two consecutive contests. The winner of contest one gains an advantage in contest two where his effort is more productive than all rivals. We identify a tipping point for the productivity parameter, below which it is optimal for an effort-maximizing principal to place the whole prize in the second contest. Above this level, a single symmetric contest is preferred. The institution chosen depends inextricably upon the number of competitors and their valuation of future gains and costs. We identify the optimal setting of the productivity parameter, showing that introducing asymmetry can increase total efforts by as much as one quarter compared to a single symmetric contest.
Real Estate Booms and Endogenous Productivity Growth ∗

This paper studies the inefficiency in capital reallocations following sectoral booms. I argue that imperfect financial market and external barriers to entry in the booming sector creates an inefficient reallocation of entrepreneurial talent and show that this argument applies to the recent Chinese real estate boom. Using matched firm-to-firm shareholding and balance sheet data from China, I document a significant pattern of capital reallocation within existing private businesses from the manufacturing sector to the real estate sector in the recent real estate boom. The capital reallocation, however, happened among the more productive private businesses. I then argue empirically that the real estate boom caused the capital reallocation, and that the particular pattern of reallocation is likely driven by more productive business owners being less financially constrained. To formalize the idea, I model the capital reallocation decision of private business owners assuming: 1) an imperfect financial market; 2) an entry barrier in the booming real estate sector; 3) a flexible comparative advantage structure. In my model, private business owners with higher absolute advantage in manufacturing accumulate more wealth through self-financing, and they are therefore less constrained by the cost of entering the real estate sector. Inefficient talent allocation arises if these business owners do not have a comparative advantage in real estate. Finally, I bring the model back data and structurally estimate the comparative advantage of private manufacturing business owners. My structural estimation confirms the existence of an inefficient reallocation of talent during the Chinese real estate boom. ∗I am extremely grateful to my advisors Daron Acemoglu, Robert Townsend, and Jonathan Parker for their invaluable guidance and support. I thank Ricardo Caballero, Emi Nakamura, Marios Angeletos, Ivan Werning, Jón Steinsson, Alp Simsek, Arnaud Costinot, David Berger, Johannes Stroebel, David Atkin, Glenn Ellison, Alberto Abadie, Anna Mikusheva, Bill Wheaton, and participants in MIT Macroeconomics Seminar, UCSD Macro Seminar, LSE Finance Seminar, Tsinghua PBC Seminar, and the IMF RESMF Seminar for helpful comments. This paper benefited from numerous discussions with Kai Yan. I also thank Greg Howard, Sebastian Fanelli, Ludwig Straub, Rachael Meager, Vivek Bhattacharya, John Firth, Otis Reid, Daniel Green, Jie Bai, Yan Ji, Chen Lian, Alex He, Rodrigo Adao, Yao Zeng, Yixin Chen, and Chen Sun for sharing their comments on this paper. I thank the MIT STL Lab and MIT Economics Department Shultz Fund for financial support. Finally, I thank Xiaowen Yang for help in working with the GIS data. Sizhu Lu provided excellent research assistance for this paper. All errors are my own. †Economics Department, Massachusetts Institute of Technology (yshi25@mit.edu)
New ways of lumped parameter analysis in an enclosed environment

When the prediction of acoustics needs to be done accurately, and fast. It is good to use a lumped parameter approach. Nowadays Sabine’s equations are leading when making lumped parameter analysis, but Eyring already proposed to skip some of the simplifications in order to analyze anechoic rooms. In this paper new equations for lumped parameter room acoustics are derived, that could be used regardless of the type of room. The mathematical simplification of Sabine turns out to lead to high inaccuracies at higher absorption values in anechoic rooms, this is consistent with experience in the field. In case of the determination of the sound reduction index, both the new, and Sabine equation work well in laboratory conditions. In a room with more sound absorption the use of the new equation proposed in this paper is a necessity. The new equation has considerable consequences throughout the field of room acoustics. For the reverberant distance, a more general equation is proposed.
PHOTO-INJECTOR OPTIMIZATION AND VALIDATION STUDY WITH THE OPAL BEAM SIMULATION CODE

A 42 keV x-ray free electron laser (XFEL) is a plausible technology alternative for the Matter Radiation Interactions in Extremes (MaRIE) experimental project, a concept developed by Los Alamos National Laboratory. An early preconceptual design for such an XFEL calls for 100 pC electron bunches with very low emittance and energy spread. High fidelity simulations that capture all beamline physics will be required to ensure a successful design. We expect to use the beam simulation code OPAL as one of the tools in this process. In this study, we validate OPAL as a photo-injector design tool by comparing its performance with published PITZ experimental data and simulations.
Practical " Modern " Bayesian Statistics in Actuarial Science

The aim of this paper is to convince actuaries that Bayesian statistics could be useful for solving practical problems. This affirmation is due to two main characteristics of Bayesian modelling not yet fully explored by practitioner actuaries: first, the possibility of absorbing subjective information and second, the wider range of models available in the Bayesian framework. In order to help in this "convincing" process this paper includes an overview of Bayesian statistics in actuarial science and cites many published papers based on this theory with insurance applications. An approach with as few formulae as possible will be used to make it easier to follow for all actuaries, independently of their involvement in statistics.
MIXING LOSSES INVESTIGATION DOWNSTREAM OF TURBINE BLADE CASCADE WITH COOLANT FLOW BLOWING

A major cause of noise and vibration characteristics of turbomachinery has caused by wakes. The characteristics of the wake, the wake decay, the path that it follows, and the mechanisms of mixing losses generated due to the mixing of blade trailing edge cold jet issued into the hot cross flow are important to find adequate solution to the problem. At the present work the wake characteristic was observed by introducing experimental work inside a cascade test rig to investigate the wake domain downstream of blade cascade with the aid of fivehole probe. The case studies were done with cold jets blowing ratios 1.58, 1.667 and 1.935 with jet stream wise angle and jet lateral injection angle 37.5 and 35 respectively. The measurement showed that there is a certain harmonization in the region of high reverse pressure loss coefficient which reflects the concentration of wake region. Also it was observed three distinct wake regions located in the centre of the passage vortex region. The wake characteristics measurements of the movement path, the growth of wake width, and the physical awareness of the wake propagating may help to explain the mechanisms of mixing losses.
Do Underwriters Misuse Discretionary Powers ? Corresponding

Using an exogenous regulatory change in the discretionary allocation powers of the Indian IPO underwriters, we investigate whether discretionary powers add value to investors, by providing higher information production, or destroys value, by inducing retail investors to overpay and increase underwriter incentives through IPO proceedings. We find that, in the discretionary regime, retail investors overpay and get influenced by active and aggressive pre-trade IPO grey market. Regulatory intervention, through restricting discretionary powers, lets retail investors participate less in the grey market due to lower reference prices and lowers underpricing. Our paper supports recent findings of Chang et al. (2017) that, as long as underwriters exercise their discretionary power and work for their private benefits, even in the transparent markets, retail investors overpay and underpricing persists.
Flow in the nose region and annular film around a Taylor bubble rising through vertical columns of stagnant and flowing Newtonian liquids

The flow in the nose region and in the annular film around individual Taylor bubbles rising through stagnant and co-current vertical columns of liquid were studied, employing particle image velocimetry (PIV) and pulsed shadowgraphy techniques (PST) at the same time. The combined techniques enabled simultaneous determination of the bubble shape and the velocity profiles in the liquid film. Experiments were performed with water and aqueous glycerol solutions in a wide range of viscosities (1 × 10−3 Pa s < < 1.5 Pa s), in an acrylic column of 32 mm ID. Values for the distance ahead of the nose in which the flow is disturbed by the presence of the bubble are presented for the conditions studied. The bubble shapes in the nose region are compared with Dumitrescu’s shape for potential flow. The velocity profiles show that after the nose region the liquid begins to accelerate downwards, and at a certain distance from the bubble nose the velocity profile and the liquid film thickness stabilise. The liquid film acquires characteristics of a free-falling film. Values of the developing length and film thickness are reported for the experimental conditions studied. Average velocity profiles in the fully developed film are also presented. A critical Reynolds number of around 80 (based on the mean absolute velocity in the liquid film and on the film thickness) is reported for the transition from laminar to turbulent regime. Shear stress profiles (in the fully developed film) are also provided. The data reported are relevant for the validation of numerical codes in slug flow. 2005 Elsevier Ltd. All rights reserved.
Crowdsourcing for Requirements Engineering : A Simplified Review

The need to deal with large scale stakeholders to ensure the correctness of software requirements make crowdsourcing technique very useful. It helps to improve the optimal level of requirements quality in terms of breath and save the development cost at the same time. This paper presents and provides evidence of the relevance of crowdsourcing for requirements engineering. A systematic literature review method is adopted here and the literature exploration is based on two specific research questions. The findings from the literature show that many efforts have been done to explore and further improve crowdsourcing for software engineering in general and requirements engineering in specific. This paper provides a foundation to pursue research in improving crowdsourcing technique for the benefit of requirements engineering.
Salicylhydroxamic Acid Effects on Relative Levels of Ascorbic Acid Oxidase and Amylases in Different Grains Growing in the Same Spikelet of Wheat

The salicylhydroxamic acid effects on relative levels of ascorbic acid oxidase, aand bamylases were studied within developing grains of wheat (Triticum aestivum L. var. PBW-343). The plants were grown in a screen covered hall under otherwise natural conditions. A concentration of 10 ppm salicylhydroxamic acid was applied at anthesis stage in five replications with the help of cotton plugs, which remained on ears of mother shoots for 48 hours. Labeled spikes were sampled five times, seven-day intervals started from seventh day after anthesis (DAA) up to 28 DAA, and at maturity. The spikelets were divided into two grain types included basal (bold) and apical (small). The salient points emerging through the use of salicylhydroxamic acid were that (i) both bold and small grains showed a decrease in relative levels of ascorbic acid oxidase, a-amylase and b-amylase from about 14 DAA stage and (ii) in spite of the aforementioned decline, they continued to exhibit the disparity between them and at maturity the smaller grains still showed higher ascorbic acid oxidase, aand bamylases than the bolder grains.
FDI AND TRADE OPENNESS : THE CASE OF EMERGING AFRICAN ECONOMIES

The primary objective of this study was to examine the effect of trade openness of foreign direct investment using a panel of nine African countries, over the period 2009 -2016. We analyzed our data using the panel data method. Building on from the new growth theories, the results from the random effects model show that trade openness positively influences inward FDI although the relationship is only significant at 10%. Other FDI determinants that emerged were real exchange rate which was positive and very significant, while the lag of FDI was positive and significant at 5%; capital openness was positive but insignificant. In light of these findings, we therefore recommend that host countries remove trade tariffs and reduce taxation rates for multinational corporations that deter foreign investment. Further to this, they should ensure that their investment and macroeconomic policies are suitable to ensure capital accumulation, which will spur productivity and increase employment.
Using improved generalizable features in domain adaptation for cross-domain sentiment classification

Sentiment classification doesn’t aim to identify the topic or factual content of a document, but aims to classify sentiments expressed in a text. The general sentiment expressed by the author towards a subject is identified by analyzing text-features within the document. Traditional machine learning techniques have been applied with reasonable success, but a severe decline in classification accuracy of such techniques has been shown when there is no proper match between the training and test-data with respect to the topic of the document (domain). Traditional approaches have favored domain-specific supervised machine learning techniques such as Naive Bayes, Maximum Entropy and Support Vector Machines. When building models to classify the sentiment of texts using machine learning techniques, extensive sets of labeled training-data from the same domain as the intended target text are often required. Gathering and labeling new datasets whenever a model is needed for a new domain is often time-consuming and difficult, especially if a dataset with labels is not available. This thesis will explore the difficulties experienced with current favored techniques (with regard to cross-domain adaptation) and propose a solution to this problem by offering a model with which high sentiment classification accuracy can be achieved without the aid of labeled datasets for the target domain. The problem of transferring domain-specific knowledge will be addressed by making use of an adapted form of the Naive Bayes classifier introduced by Tan et al. (2009). The adapted form of the Naive Bayes classifier uses generalizable features from both source and target domain. Generalizable features are features which are consistently used between domains and can thus serve as a bridge between the domains. The generalizable features are explored in three variations: using frequently co-occurring entropy measures (FCE), using a subjectivity lexicon as generalizable features and using an importance measure in combination with FCE to select improved generalizable features. Based on the selected generalizable features a domain transfer can be made between source and target domain using the EM-algorithm. EM is used to estimate the Naive Bayes probabilities in order to maximize a model with which unsupervised, cross-domain sentiment classification can be achieved.
BIOECONOMIC ANALYSIS : A CASE STUDY OF THE INDUSTRIAL PELAGIC FISHERIES IN CAPE VERDE

This paper develops a bioeconomic model to identify optimal management of the pelagic fisheries, applied to the industrial pelagic fisheries of Cape Verde. The result of the analysis of the period 2003 to 2012 show very high fluctuation in the net benefits of the fishery. The net benefits were mostly negative due to excessive fishing effort which results in high cost, while the total revenue remains weak. The current (2012) fishery reference situation indicates a slightly excessive fishing effort. Hence, the fisheries exist at a stage that requires care in terms of management with bioeconomic criteria at levels very close the biological equilibrium (BE). Despite this, it is known that adequate fishery management is necessary to achieve sustainable fishing, so this current state represents an opportunity for management. By analysing this scenario, we emphasise biological and economic outcomes. To achieve maximum sustainable profits, around 111,602 thousand CVE annually equal to 22% of the total revenue, the fishing effort must be reduced from 6,264 to 3,752 days at sea in a long-run sustainable option. However, it must only reduce from 6,264 to 5,042 days at sea to achieve the maximum sustainable profits around 32,827 thousand CVE annually, equal to 6% of the total revenue, in a short-run sustainable option. The fundamental problem of economic inefficiency in fisheries, the called common property problem, may be seen to be caused by inadequate property rights in the underlying natural resources. Due to this lack of property rights, trades in the natural resources cannot occur. As a result, markets cannot form and, consequently, there are no market forces to guide behaviour to the common good. All potential economic rents from the fishing activity are fritted away by investment in excessive fishing capital and fishing effort. Moreover, this economic waste is generally accompanied by an unjustifiable reduction in and, sometimes, even decimation of the biological capital, the fish stocks. However, the analysis shows that the main source of improvement of the fishery management in this case of study is linked to the implementation of the ITQs to the harvest sector, to correct this management failure, and reduce the fishing efforts and rebuild the fish