Miracle-dz/UniFAR-FTUs huggingface dataset:
The Quantitative Effects of Trade Policy on Industrial and Labor Location ∗ ( First draft , preliminary )

One justification for trade protectionism is the benefits of terms-of-trade manipulation. Another reason, more central in trade policy negotiations, is the idea that trade protectionism brings industries back home. The new economic geography theory has provided intuitive insights on how the location effect of trade policy shapes welfare in the protecting country. Previous work, however, has been able to say much less about the quantitative effects of trade policy on the location of firms across space and over time, and its welfare implications. We develop a multi-country dynamic general-equilibrium trade and spatial model with forward-looking decisions of firms on where to locate production, forward-looking decisions of workers on where to supply labor, and endogenous capital structure accumulation. We take the model to the data using trade and production data for many locations and industries, as well as using data on firms’ demographics from several data sources. We use the model to study how trade protectionism impacts the location of production across space and over time, as well as its welfare consequences. We find quantitative evidence that protection relocates production to the protected country but that this comes at the cost of higher prices and lower welfare. ∗Correspondence by e-mail: lorenzo.caliendo@yale.edu, fparro@princeton.edu. Fernando Parro thanks the International Economics Section at Princeton University. 1
Securing Message Transactions through Modified Playfair Cipher Technique

Secured message transactions are the procedures to transfer the messages among the communicating parties with message confidentiality, message authentication, and message integrity. One of the several approaches used to implement the mentioned security services is Cryptography. In this paper we modified the 5 × 5 matrix Playfair cipher to 17 × 17 matrix Playfair cipher. The modified cipher was implemented using java programming language. The result obtained revealed that, the modified 17 × 17 matrix Playfair cipher is more secure than the existing ones. This is because the modified system has a maximum key length of 289 characters and this range of key size yields 83521 possible keys that are strong enough to withstand attacks and this makes it very difficult for the eavesdropper to attack the message. As a result, this system is recommended to be used by banks for their online transaction and other institutions that deal with sensitive data and information. General Terms: Encryption, Decryption, Plaintext, Ciphertext.
SIMULATION OF DEPENDENT SPARRE ANDERSEN MODEL FOR A NONLIFE INSURANCE PORTFOLIO

This paper considers an application of simulation technology in insurance risk analysis under a dependent setting. Here we consider an insurance portfolio where the claim inter-arrival time, which is Erlang (2) distributed, depends upon the size of previous claim. The probability of ruin, the crucial parameter of insurance companies, is calculated by the method of simulation technology using R software.
Cranial disparity versus diversity in sabertoothed felids: a case of late morphospace saturation

In this contribution I present the first diversity (number of taxa) versus disparity (explored morphospace) comparison of sabertoothed felids performed on craniomandibular and dental characters. The graphs obtained demostrate how the morphospace exploration gradually increases in the group through time, reaching a maximum in the late Pliocene and during the Pleistocene. The latter time bins coincide with the appearance of all Eumachairodontia (with the exception of Amphimachairodus), i.e. true “saberteeth”. This is linked to major cranial modifications connected to the evolution of the characteristic hypertrophied and flattened upper canines. The continuous increase in occupied morphospace indicates that in machairodont felids real morphospace stabilization is never achieved until the Pleistocene, with the total representation of the Eumachairodontia. On the evolutionary level, the general group history seems to show a true Plio-Pleistocene radiation, identified by hyper-specialization, which led to a positive peak in disparity. The evolution of cranial disparity in machairodont felids can be included in the category of ‘top-heavy clade’, i.e. those groups who show a real radiation relatively late in their history.
Chronic exposure to environmental levels of cis-bifenthrin : Enantioselectivity and reproductive effects on zebra fi sh ( Danio rerio ) z . star ;

Synthetic pyrethroids (SPs) are broadly used to control pests and have been widely detected in aquatic environments, prompting concern over its risk to the health of non-target organisms. The present study evaluated whether long-term (60 d) exposure to low doses (0, 20, 100, and 500 ng/L) of cis-BF enantiomers (1S-cis-BF and 1R-cis-BF) could cause reproductive endocrine disturbance to zebrafish. Exposure to 1S-cis-BF has stronger reproductive impairment effect than 1R-enantiomer, indicating that the enantioselectivity of cis-BF on fish reproduction. Significant decrease of cumulative spawning of zebrafish was observed as a result of cis-BF exposure. And the retardations of testis and ovaries development found in histopathological section were suggested to be important cause for the decreased fecundity. CisBF decreased the total motility of sperm but did not affect sperm density. Relatively high levels of cis-BF detected in the gonads of males and females may directly impair gametogenesis. In addition, alterations in the expression of key genes (cyp17, cyp19a and 17b-hsd) associated with reproductive endocrine pathways were correlated well with the significant changes in sex hormone contents (E2 and T) and these results may relate to gonadal development and maturation of germ cells in females or/and males which were suspected to be a likely underlying mechanism. Furthermore, the reduction of quality of F1 embryo derived from the unexposed females and exposed males (UE\ E_) demonstrated that male exposure had greater adverse effects on offspring. Our results indicate that long term, low dose exposure to cis-BF can enantioselectively impair the reproduction system of fish, and induce toxicity related abnormalities in non-exposed offspring. This study has important implications for environmental risk assessment of chiral pesticides that are concurrently present in aquatic systems. © 2019 Elsevier Ltd. All rights reserved.
Running head: THE SEMANTICS OF NON-WORDS 1 On the semantics of non-words and their lexical category

Using computational simulations, this work demonstrates that it is possible to learn a systematic relation between words’ sound and their meanings. The sound-meaning relation was learned from a corpus of phonologically transcribed child-directed speech by using the Linear Discriminative Learning (LDL) framework (Baayen, Chuang, Shafaei-Bajestan, & Blevins, 2019), which implements linear mappings between words’ form vectors and semantic vectors. Presented with the form vectors of 16 non-words, taken from a study on word learning (Fitneva, Christiansen, & Monaghan, 2009), the network generated the estimated semantic vectors of the non-words. As half of these non-words were created to phonologically resemble English nouns and the other half were phonologically similar to English verbs, we assessed whether the estimated semantic vectors for these non-words reflect this word category difference. In seven different simulations, Linear Discriminant Analysis (LDA) successfully discriminated between noun-like non-words and verb-like non-words, based on their semantic relation to the words in the lexicon. Furthermore, how well LDA categorized a non-word correlated well with a phonological typicality measure (i.e., the degree of its form being noun-like or verb-like) and with children’s performance in an entity/action discrimination task. On the one hand, the results suggest that children can infer the implicit meaning of a word directly from its sound. On the other hand, this study shows that non-words do land in semantic space, such that children can capitalize on their semantic relations with other elements in the lexicon to decide whether a non-word is more likely to denote an entity or an action.
Electrical Treeing in Power Cable Insulation under Harmonics Superimposed on Unfiltered HVDC Voltages

Insulation degradation is an irreversible phenomenon that can potentially lead to failure of power cable systems. This paper describes the results of an experimental investigation into the influence of direct current (DC) superimposed with harmonic voltages on both partial discharge (PD) activity and electrical tree (ET) phenomena within polymeric insulations. The test samples were prepared from a high voltage direct current (HVDC) cross linked polyethylene (XLPE) power cable. A double electrode arrangement was employed to produce divergent electric fields within the test samples that could possibly result in formation of electrical trees. The developed ETs were observed via an optical method and, at the same time, the emanating PD pulses were measured using conventional techniques. The results show a tenable relation between ETs, PD activities, and the level of harmonic voltages. An increase in harmonic levels has a marked effect on development of electrical trees as the firing angle increases, which also leads to higher activity of partial discharges. This study of the influencing operational parameters of HVDC converters on power cable insulation is predicted to contribute to enhancements in cable design and progressive advancement in condition monitoring and insulation diagnostic techniques that can lead to more effective asset management in HVDC systems.
Stiefel-Whitney classes and Chern classes Part I : Introduction and Motivation

We come back to the problem of classification of vector bundles over a given basis space. In any branches of mathematics, there is always a guiding problem. Interestingly, classification is always a guiding problem in geometry. An easy way to solve such a problem is to find a very good invariant that can distinguish everything up to some condition. Examples are cardinality in set theory. However, other invariants, like homology, cohomology, homotopy group in topology, Gromov-Witten invariants, Donaldson-Thomas invariants in algebraic geometry, can only partially solve the problem. As we are working on algebraic topology, a natural idea comes out of head is using homology/cohomology. One step further, we would like to consider some particular cohomological classes associated to the vector bundle. Historically, the first characteristic classes was proposed by Hopf, Stiefel and Whitney (and if you are born early enough, you might meet the first two professors somewhere in ETH.), but the idea of characteristic class can date back to Schubert Calculus and Italian School of Algebraic Geometry. Loosely speaking, characteristic class is just to measure how a vector bundle is twisted. To classify a vector bundle, let’s first recall theorem 1.16 in [2].
The Risk-Return Tradeoff in China: Does the Market Stability Objective of Government Intervention Matter?

This study shows that the risk-return tradeoff in China varies with market instability features in the direction indicated by the market stability objective of government intervention. Using stocks traded in China between 1997 and 2016, we find that the market's mean-variance relation is significantly positive in the months of low crash-like market features, but not in high-crash months. Meanwhile, such two-regime pattern helps to account for the serial correlation of market returns and becomes more pronounced on the CSRC announcement days. We also find that bubble-like market features are useful for detecting a positive mean-variance relation of individual stocks, but not useful at the market level. Overall, the evidence is consistent with the notion that government's attempts to maintain market stability attract investor speculation in bad times and neutralize sentiment-related speculation in boom times, and an idiosyncratic shock is not sufficient to trigger such responses.
A Brief Study on MOOCs

: This paper presents a brief report on the MOOCs.Some of the famous MOOCs are discussed with their key features and revenue models. The current research gap was identified.Based on the research work already done, various factors were identified which affect the adoption of MOOCs, these were classified based on two perspectives – user point of view and the university which is offering the MOOC. At the end of the paper, we highlight some of the primary research which is to be done in this field.
Impact of Word of Mouth (WOM) on Customers

Word of mouth and consumer interaction has been the centre focussed approach in marketing now a days to overcome the barriers in marketing and retail sector. It leads to interaction between the buyers and it increases the image of the product consumed by the buyers. The main belief is that the word of mouth is the underlyning thought of the consumer which is basically influencer’s buying decision. It contributes towards buying decision and the marketing information enhancement. Thus it can affect the business positively and negatively. Word of mouth (WOM) has impact on several factors on customer such as or consumer-to-consumer interaction customer choice, service and brand switching, purchase decision, choice and alternatives analysis, perception about a product and facilitation of customer. Thus, it is more effective than traditional tools of marketing such as personal selling advertising and sales promotion. Customers pay more attention to thers now a days through various modes of marketing. The word of mouth is of two types mainly i.e negative WOM and positive WOM. Thus, in this paper main focus is to summarise the impact of positive and negative impact of word of mouth on the customer buying and perceptions. Positive WOM, leads to building loyalty and emotion and positive image of product in minds of buyers whereas, negative WOM refers to creation of gaps in minds of buyers, dissatisfaction among the wants and poor image building of the products.
TEACHERS' ATTITUDES ON THE IMPLEMENTATION OF INFORMATION AND COMMUNICATION TECHNOLOGIES IN BIOLOGY TEACHING

During the exponential scientific and technological development, and the development of the society of knowledge in which intellectual capital has become a major factor of progress, the quality of education is a priority strategic objective of many countries. Education Development Strategy in Serbia until 2020 has recognized the importance and the role of the didactic paradigm. The mission of the education system in Serbia in the 21st century is to ensure the basic foundation of life and development of every individual, society and state based on knowledge. According to education research in the world, the quality of teachers is a key factor in the quality of education. These findings are a standpoint for the definition of a specific strategy of teacher education in Serbia. It is directed to flexibility of teachers in terms of successful adaptation to new trends in education and advanced training aimed at developing competencies that are required in future. One of the tendencies in improving education is the application of information and communication technologies in teaching (ICT). Consequently, the number of training seminars for teachers, which aim is to train teachers to properly use the benefits of ICT in teaching, has increased in the Republic of Serbia in the last ten years. The effects of the application of new technologies in teaching depend on several parameters. One of these parameters is the teachers’ perception on their application in the teaching process. Therefore, the focus of this paper is aimed at examining the level of ICT application by biology teachers and their attitudes towards the ICT application in teaching. The paper also analyzes the influence of the level of skills and levels of ICT application on attitudes of biology teachers concerning their application in teaching. The research items were considered on a sample of 101 biology teachers who work in elementary schools in the Republic of Serbia. The main findings of the research show that biology teachers have a positive attitude towards the ICT application in the teaching process, that they have a high level of skills concerning the use computers and computer tools, and that they often apply them the teaching process. Pearson's coefficient has shown that there is a medium positive correlation among the level of skills and ICT application, and the teachers' attitudes.
Real-Time Hardware-inthe-Loop Platform for Hybrid AC / DC Power System Studies

Conventional power system studies are normally performed using offline analytical tools and computer-based simulations. Hardware-in-the-loop (HiL) configurations are very helpful to carry out experimental tests in a safe environment without affecting the operation of a practical power system. Following this line, a real-time HiL (RT-HiL) platform suitable for a wide range of power system studies is presented in this paper. Emphasis is placed on the individual components of the platform. To demonstrate the capabilities of the RT-HiL configuration, two case studies are presented: subsynchronous resonance damping and fast frequency support provision. The ac grids are modeled in the RT simulator, while dc networks are implemented in a physical test-bed. The ability of the RT-HiL platform to emulate ac/dc interactions and grid support services is shown. For completeness, experimental results are compared against PSCAD simulation results—showing a good agreement. It should be emphasized that the presented experimental platform goes beyond conventional HiL set-ups—instead representing a hybrid hardware-based emulator with RT-HiL simulation.
A hybrid convolutional and recurrent network approach for conversational AI in spoken language understanding

The deep learning revolution has an impact on almost all parts of our life, it brought us improved momental machine translators, modern human-like conversation voice assistant like Siri, Alexa, Alisa. This revolution had become truth because of deep learning methods which improved multiple processing layers to learn a hierarchical representation of data, and have achieved the state-of-the-art results in many lives domains. In this paper, we are focusing on one of the most famous NLP (Natural language processing) problems which is slot filling to approach the state-of-the-art results on the ticketing problem to make the Spoken Dialogue systems work more efficiently. We propose a hybrid architecture, as a combination of a Recurrent Neural Network and a Convolutional Neural Network models, for Slot Filling in Spoken Language Understanding. In particular, our network model is built from stacked units of 1-dimensional CNN (Convolutional Neural Network) across the temporal domain, which are used to train an RNN (Recurrent neural network) layer to model dependencies in the temporal domain. Experimental tests show extensive comparisons between different models for NER (Named Entities Recognition). Results demonstrate the effectiveness of hybrid models that combine benefits from both RNN and CNN architecture compared over distinct RNN and CNN models and also compared with other traditional models. Experimental results show that our model achieves F1-score of 95.11 on benchmark ATIS dataset.
Endogenous Growth and Persistence of Output Fluctuations

Fatás (2000a) shows that a stylized endogenous growth model, that is, AK model, with exogenous shocks can account for a strong positive correlation between long-term growth rates and the persistence of output fluctuations across countries. And he argues in a Schumpeterian model of growth, there will be a positive correlation between growth and persistence. We show that this relationship does not apply to all the endogenous growth models, but apply only to some special cases of the endogenous growth model in addition to AK model. The crucial factor is in whether the R&D sector uses final goods as inputs or not. In addition, we present more developed model which explains the correlation in the context of combination of RBC and endogenous model. JEL Classification: E32, O30 Key Word: R&D investment, technical innovation, economic growth, persistence, country-specific parameter
Rhodanese : One of Natures “ Sulphur ” Biotransformation Machinery

Rhodanase (EC2.8.1.1) is a sulphur transferase enzyme. It is widely distributed across all levels of living organism; microbes, fungi, plants and animals. Sulphur is a basic requirement for existence and sustenance of life, as notable in the myriad of chemical substances in which it is incorporated such as; proteins containing cysteine and/or methionine amino acid, proteins containing ironsulphur center prosthetic groups, glutathione, sulphated carbohydrates, hydrogen sulphide, and thiosulphate. Rhodanese plays an important role in the metabolism of sulphur in cells of organism. It helps to maintain homeostatic balance of sulphur pool in cell. The functional roles of sulphur also include cyanide detoxification, hydrogen sulphide detoxification, neuro-modulation, repair of iron sulphur centres, and maintenance of respiratory rates. Further study of this enzyme is desired for more insight into its role cellular metabolism and possible medical application.
A Novel Approch On Matching Algorithms

Prototype-based classifiers are usually clustering-based methods. Therefore, theyrequire a dissimilarity criterion to cluster the drill data and also to assign class labelsto test data. Euclidean distance is a commonly used dissimilarity criterion. However, theEuclidean distance may not be able towards give accurate shape-based comparisons of veryhigh-dimensional signals. This can be problematic for some classification applicationswhere high-dimensional signals are grouped into classes based on shape similarities.Therefore, a reliable shape-based dissimilarity measure is desirable. The Hungarian method proved tobe an effective method for solving assignment problems. Any new primal-dual algorithm must be effective on some class of problems to be of interest. In particular, itmust be associated to the Hungarian method for the assignment problem. With thisin mind, we have tried to determine how the nonnegative least squares primal-dualprocedure relates to the Hungarian method for the assignment problem. We haveestablished several connections between the two algorithms, and more generally, between the nonnegative least squares algorithm and the weighted matching problemon general graphs. In [6], the authors showed that the nonnegative least squaresalgorithm is a steepest ascent method for solving the dual of a linear programmingproblem. This means that this method should require fewer ladders, on average, thanthe Hungarian method. Results were shown effectively in MATLAB
IT ] 22 J an 2 01 3 Fast Marginalized Block SBL Algorithm

The performance of sparse signal recovery can be improved if both sparsity and correlation structure of signals can be exploited. One typical correlation structure is intra-block correlation in block sparse signals. To exploit this structure, a framework, called block sparse Bayesian learning (BSBL) framework, has been proposed recently. Algorithms derived from this framework showed superior performance but they are not very fast, which limits their applications. This work derives an efficient algorithm from this framework, using a marginalized likelihood maximization method. Compared to existing BSBL algorithms, it has close recovery performance but is much faster. Therefore, it is more suitable for large scale datasets and applications requiring real-time implementation.