Miracle-dz/UniFAR-FTUs huggingface dataset:
Credit Scoring Modeling

It is generally easier to predict defaults accurately if a large data set (including defaults) is available for estimating the prediction model. This puts not only small banks, which tend to have smaller data sets, at disadvantage. It can also pose a problem for large banks that began to collect their own historical data only recently, or banks that recently introduced a new rating system. We used a Bayesian methodology that enables banks with small data sets to improve their default probability. Another advantage of the Bayesian method is that it provides a natural way for dealing with structural differences between a bank’s internal data and additional, external data. In practice, the true scoring function may differ across the data sets, the small internal data set may contain information that is missing in the larger external data set, or the variables in the two data sets are not exactly the same but related. Bayesian method can handle such kind of problem.
Chemical study of intermediate-mass (IM) Class 0 protostars - CO depletion and N2H+ deuteration

Aims. We are carrying out a physical and chemical study of the protostellar envelopes in a representative sample of IM Class 0 protostars. In our first paper we determined the physical structure (density-temperature radial profiles) of the protostellar envelopes. Here, we study the CO depletion and N2H + deuteration. Methods. We observed the millimeter lines of C 18 O, C 17 O, N2H + and N2D + towards the protostars using the IRAM 30m telescope. Based on these observations, we derived the C 18 O, N2H + and N2D + radial abundance profiles across their envelopes using a radiative
Quantum error correction in crossbar architectures

A central challenge for the scaling of quantum computing systems is the need to control all qubits in the system without a large overhead. A solution for this problem in classical computing comes in the form of so-called crossbar architectures. Recently we made a proposal for a large-scale quantum processor (Li et al arXiv:1711.03807 (2017)) to be implemented in silicon quantum dots. This system features a crossbar control architecture which limits parallel single-qubit control, but allows the scheme to overcome control scaling issues that form a major hurdle to large-scale quantum computing systems. In this work, we develop a language that makes it possible to easily map quantum circuits to crossbar systems, taking into account their architecture and control limitations. Using this language we show how to map well known quantum error correction codes such as the planar surface and color codes in this limited control setting with only a small overhead in time. We analyze the logical error behavior of this surface code mapping for estimated experimental parameters of the crossbar system and conclude that logical error suppression to a level useful for real quantum computation is feasible.
Mapping gas-phase organic reactivity and concomitant secondary organic aerosol formation: chemometric dimension reduction techniques for the deconvolution of complex atmospheric data sets

Abstract. Highly non-linear dynamical systems, such as those found in atmospheric chemistry, necessitate hierarchical approaches to both experiment and modelling in order to ultimately identify and achieve fundamental process-understanding in the full open system. Atmospheric simulation chambers comprise an intermediate in complexity, between a classical laboratory experiment and the full, ambient system. As such, they can generate large volumes of difficult-to-interpret data. Here we describe and implement a chemometric dimension reduction methodology for the deconvolution and interpretation of complex gas- and particle-phase composition spectra. The methodology comprises principal component analysis (PCA), hierarchical cluster analysis (HCA) and positive least-squares discriminant analysis (PLS-DA). These methods are, for the first time, applied to simultaneous gas- and particle-phase composition data obtained from a comprehensive series of environmental simulation chamber experiments focused on biogenic volatile organic compound (BVOC) photooxidation and associated secondary organic aerosol (SOA) formation. We primarily investigated the biogenic SOA precursors isoprene, α-pinene, limonene, myrcene, linalool and β-caryophyllene. The chemometric analysis is used to classify the oxidation systems and resultant SOA according to the controlling chemistry and the products formed. Results show that "model" biogenic oxidative systems can be successfully separated and classified according to their oxidation products. Furthermore, a holistic view of results obtained across both the gas- and particle-phases shows the different SOA formation chemistry, initiating in the gas-phase, proceeding to govern the differences between the various BVOC SOA compositions. The results obtained are used to describe the particle composition in the context of the oxidised gas-phase matrix. An extension of the technique, which incorporates into the statistical models data from anthropogenic (i.e. toluene) oxidation and "more realistic" plant mesocosm systems, demonstrates that such an ensemble of chemometric mapping has the potential to be used for the classification of more complex spectra of unknown origin. More specifically, the addition of mesocosm data from fig and birch tree experiments shows that isoprene and monoterpene emitting sources, respectively, can be mapped onto the statistical model structure and their positional vectors can provide insight into their biological sources and controlling oxidative chemistry. The potential to extend the methodology to the analysis of ambient air is discussed using results obtained from a zero-dimensional box model incorporating mechanistic data obtained from the Master Chemical Mechanism (MCMv3.2). Such an extension to analysing ambient air would prove a powerful asset in assisting with the identification of SOA sources and the elucidation of the underlying chemical mechanisms involved.
Brazilian Robotics Olympiad

This article introduces the successful methodology adopted for the realization of the Brazilian Robotics Olympiad. Organizational and scientific issues are presented and discussed as well as results of statistical surveys performed with participants that verify the benefits brought by this robotics Olympiad. The Brazilian Robotics Olympiad is a nine-year-old nation-wide initiative created with the mission of promoting robotics among Brazilian students with or without previous knowledge of robotics, fostering their interest to engage in science, technology and engineering studies and careers. The Olympiad is fully free for participants, being annually organized by hundreds of volunteers from several Brazilian universities. It is divided into practical and theoretical components with several levels, each one designed for a certain student age. More than 300,000 students have already participated in the Brazilian Robotics Olympiad and, according to 58% of these students, the Brazilian Robotics Olympiad helped them to decide which university course to pursue.
Nexus between Tourism demand and output per capita with relative importance of trade and financial development: A study of Malaysia

This paper revisits the tourism-growth nexus in Malaysia using time series quarter frequency data over the period of 1975-2013. We examine the impact of tourism using two separate indicators – tourism receipts per capita and visitor arrival per capita. Using the augmented Solow (1956) production function and the ARDL bounds procedure, we also incorporate trade openness and financial development, and account for structural break in series. Our results show the evidence of cointegration between the variables. Assessing the long-run results using both indicators of tourism demand, it is noted that the elasticity coefficient of tourism is 0.13 and 0.10 when considering visitor arrival and tourism receipts (in per capita terms) respectively. Notably, the impact of tourism demand is marginally higher with visitor arrival. The elasticity for trade openness is 0.19, financial development is 0.09, and capital share is 0.15. In the short-run, the coefficient of tourism is marginally negative, and for financial development and trade openness, it is 0.01 and 0.18, respectively. The Granger causality tests show bi-directional causation between tourism and output per capita; financial development and tourism; and trade openness and tourism demand, duly indicating the feedback or mutually reinforcing impact between the variables, and the evidence that tourism is central to enhancing the key sectors and the overall income level.
Prospective validation of virtual design and construction methods

As new virtual design and construction (VDC) methods are developed, researchers and practitioners alike must understand the power of these methods before dedicating effort and resources towards further development or implementation on real projects. One particular aspect of power – external validation – is a challenge in VDC research because of the unique nature of projects and long waiting times for actual data on project performance. With the increased use of VDC in practice, however, prospective validation is an emerging validation method where researchers can test new VDC methods on real projects within a reasonable time frame. This paper examines how researchers can use prospective validation. It presents a framework for understanding the purpose of prospective validation, an application of prospective validation, and implementation guidelines for researchers utilizing prospective validation. The results show that prospective validation should be used when researchers want to test a new method against an existing method used by practitioners on a real project. Researchers should also want to test whether the new method can be performed within a reasonable time frame and if so, whether the results could influence future project decisions. The implementation guidelines describe the necessary steps in the planning, execution, and analysis of a prospective validation test. More broadly, prospective validation represents a new way in which researchers and practitioners can collaborate that benefits the advancement of science as well as the management of real projects.
Exact Traveling Wave Solutions of the Space Fractional (2+1)-Dimensional Breaking Soliton Equations

The fractional order differential equation is used to describe the phenomenons of physical, engineering and biological fields. In this paper, the exp (-Φ(ξ))-expansion method along with the Jumarie's modified Riemann-Liouville derivatives is proposed to solve the space fractional (2+1)-dimensional breaking soliton equations. The traveling wave solutions of the equations are useful to understand the mechanisms of the complicated nonlinear physical phenomena and fractional differential equations. In this work, it has been shown that the proposed method is very effectual and easily to find the exact traveling wave solutions to the fractional nonlinear evolution equations.
A Novel Fifth-Degree Cubature Kalman Filter for Real-Time Orbit Determination by Radar

A novel fifth-degree cubature Kalman filter is proposed to improve the accuracy of real-time orbit determination by ground-based radar. A fully symmetric cubature rule, approaching the Gaussian weighted integral of a nonlinear function in general form, is introduced, and the specific points and weights are calculated by matching the monomials of degree not greater than five with the exact values. On the basis of the above rule, a novel fifth-degree cubature Kalman filter, which can achieve a higher accuracy than UKF and CKF, is derived under the Bayesian filtering framework. Then, to describe the nonlinear system more accurately, the orbital dynamics equation with J2 perturbation is used as the state equation, and the nonlinear relationship between the radar measurement elements and orbital states is built as the measurement equation. The simulation results show that, compared with the traditional third-degree algorithm, the proposed fifth-degree algorithm has a higher accuracy of orbit determination.
CHiME 2018 Workshop: Enhancing beamformed audio using time delay neural network denoising autoencoder

In the submitted system to CHiME-5 challenge, we propose front-end enhancement of the beamformed array utterances to mitigate mismatch conditions between close-talking utterances and array utterances. Our initial experiments showed that an Acoustic Model trained by using only close-talking microphone utterances gave a superior performance than the baseline acoustic model when tested using close-talking utterances of the development set. Taking this cue, we explored the hypothesis that if array utterances are mapped to corresponding close-talking utterances, the system trained using only worn utterances will perform better. Towards this end, we trained a Time Delay Neural Network De-noising autoencoder (TDNN-DAE) using non-overlapping speech close-talking microphone utterances (targets) and their corresponding beamform utterances. However, the proposed system could not outperform the baseline.
A Cultural Comparison of the Facial Inference Process

The purpose of this study was to compare emotion and personality trait attributions to facial expression between American and Indian samples. Data were collected using Amazon.com’s Mechanical Turk (MTurk). Participants in this study were asked to correctly identify the emotion and make inferences from pictures of three different facial expressions (scowling, frowning, and smiling) of young white females and males in six photographs. Each picture was randomly presented for 10 seconds followed by four randomized questions about the individual in the picture. The first question asked participants to identify the emotion shown from a list of six emotions (anger, disgust, fear, happiness, sadness, surprise). The next three questions consisted of a) condensed sets of the Big Five personality traits, b) the three SelfAssessment Manikin dimensions (SAM), ands) various social perceptions. Smiling facial expressions were hypothesized to be inferred as happy and to have the following positive inferences in both cultures: attractive, not threatening, agreeable, extroverted, and pleasing to look at, positive, conscientious, and open-minded a “Halo Effect. ” Scowling facial expressions were hypothesized to have the following attributions: anger, unattractive, threatening, excitable, close-minded, not pleasing to look at, bad, negative, dominant, disagreeable, and unconscientiously a “Horns Effect. ” Frowning facial expressions were hypothesized to be perceived as: sad, unattractive, good, submissive, not threatening, not pleasing to look at, positive, and calm anin-between effect. Generally, results showed that both cultures attributed the hypothesized emotional and trait attributions to the six facial expressions for all four questions, except for the Indians on the scowling female facial expression across each of the four questions.
Finding of People in Economic Field based on Personal Profile

There are a lot of personal profile information on the Internet. If we can automatically collect these information on the Internet, classify them and extracting personnel information from them, it can provide some help for the finding of people in specific field. In the research, we focus on study of Finding of People in Economic Field based on Personal Profile from the Internet. We proposed a field dictionary building method base on the paper database, and make an improvement to the text segmentation technology used in people classification. We designed a hybrid segmentation method based on Field Trie Tree and HMMViterbi model. On the basis of Bayesian classifier, we build a model to find people in Economic field based on Personal Profile. Experiments shows that the method has a high rate of the recognition of people in economic field.
Genomic Diversity of Arcobacter spp. Isolated from Surface Waters

A total of 45 non-clonal Arcobacter isolates recovered from wastewater and river water samples collected around Vitoria-Gasteiz, North of Spain, were investigated. Our findings confirmed A. butzleri as the most predominant species, although A. cryaerophilus and A. lanthieri were identified also. Eight isolates showed discordant results with the identification m-PCRs. Based on the rpoB gene sequence, two of these eight isolates turned to be A. lanthieri. However, the six remaining seemed to be possible new species needing additional analysis. The occurrence of virulence-associated genes was significantly (P<0.05) higher in A. butzleri. Seven of the ten virulence-associated genes investigated (ciaB, mviN, tlyA, cadF, pldA, cj1349 and hecA) were present in a high number of isolates. Among them, hecA gene was significantly (P<0.05) related to isolates from wastewater. MLST showed a high rate of genetic diversity for A. butzleri isolates. However, there were no signs of relationships between STs and the presence of virulence related genes. In conclusion, Arcobacter population in surface waters may be more varied in species than detected because most of the enrichment media and molecular techniques are designed based on A. butzleri and this may be biasing the information in favour of this species. Additionally, we found a possible relationship between the content of virulence-associated genes and the origin of the isolates.
Role of Circadian Rhythms in the Development of Depression -like Behavior in Mice

Author(s): Long, Jaimie Elizabeth | Abstract: Mood disorders, like Major Depressive Disorder (MDD) and Bipolar Disorder (BD), are associated with circadian rhythm disruptions, but the causal relationship between the two is not well understood. Previous data from our lab show an association between depression-like helpless behavior in mice and loss of circadian rhythms in mood- regulating brain areas, including the nucleus accumbens (NAc) and the periaqueductal grey (PAG). These results led to the hypothesis that reduced circadian rhythm amplitude in mood-regulating brain areas contributes to the development of depression-like behaviors in mice, as tested by knockdown of an essential clock gene and several behavioral tests, including sucrose preference, open field test, tail suspension test, and learned helplessness. In addition, it is known that the PAG serotonin receptors (5HTR) play a critical role in developing helpless behavior. Hence, we hypothesized that circadian rhythms regulate 5HTR expression in the PAG and are involved in mood regulation. Our results indicate that losing rhythms in single mood-regulating brain regions is not sufficient for development of depression-like behavior in mice. However, disturbing rhythms throughout the entire brain by disrupting the central circadian pacemaker in the suprachiasmatic nucleus (SCN) leads to depression-like behavior in learned helplessness and significant differences in the open field test. These results suggest that disturbed circadian clocks may lead to the development of mood disorders and represent a starting point for other research to explain how circadian rhythm disruptions relate to mood disorders in psychiatric patients
Counterfactual worlds

We study a generalization of the treatment effect model in which an observed discrete classifier indicates in which one of a set of counterfactual processes a decision maker is observed. The other observed outcomes are delivered by the particular counterfactual process in which the decision maker is found. Models of the counterfactual processes can be incomplete in the sense that even with knowledge of the values of observed exogenous and unobserved variables they may not deliver a unique value of the endogenous outcomes. We study the identifying power of models of this sort that incorporate (i) conditional independence restrictions under which unobserved variables and the classifier variable are stochastically independent conditional on some of the observed exogenous variables and (ii) marginal independence restrictions under which unobservable variables and a subset of the exogenous variables are independently distributed. Building on results in Chesher and Rosen (2014a), we characterize the identifying power of these models for fundamental structural relationships and probability distributions and for interesting functionals of these objects, some of which may be point identified. In one example of an application, we observe the entry decisions of firms that can choose which of a number of markets to enter and we observe various endogenous outcomes delivered in the markets they choose to enter.
A High-precision Time Handling Library

An appropriate assessment of end-to-end network performance presumes highly efficient time tracking and measurement with precise time control of the stopping and resuming of program operation. In this paper, a novel approach to solving the problems of highly efficient and precise time measurements on PC-platforms and on ARM- architectures is proposed. A new unified High Performance Timer and a corresponding software library offer a unified interface to the known time counters and automatically identify the fastest and most reliable time source, available in the user space of a computing system. The research is focused on developing an approach of unified time acquisition from the PC hardware and accordingly substituting the common way of getting the time value through Linux system calls. The presented approach provides a much faster means of obtaining the time values with a nanosecond precision than by using conventional means. Moreover, it is capable of handling the sequential time value, precise sleep functions and process resuming. This ability means the reduction of wasting computer resources during the execution of a sleeping process from 100% (busy-wait) to 1-1.5%, whereas the benefits of very accurate process resuming times on long waits are maintained. Keywords-high-performance computing; network measurement; timestamp precision; time-keeping; wall clock. I. INTRODUCTION
Hide and Seek: Exploiting and Hardening Leakage-Resilient Code Randomization

Abstract : Information leakage vulnerabilities can allow adversaries to bypass mitigations based on code randomization. This discovery motivates numerous techniques that diminish direct and indirect information leakage: (i) execute-only permissions on memory accesses, (ii) code pointer hiding(e.g., indirection or encryption), and (iii) decoys (e.g., booby traps). Among the proposed leakage-resilient defenses, Read actor is the most comprehensive solution that combines all these techniques. In this paper, we conduct a systematic analysis of recently proposed execute only randomization solutions including Read actor, and demonstrate a new class of attacks that bypasses them generically, highlighting their limitations. We analyze the prevalence of opportunities for such attacks in popular code bases and build three real-world exploits to demonstrate their practicality. We then implement and evaluate a new defense against our attacks. Our evaluation shows that our new technique is practical and adds little additional performance overhead (9.7% vs. 6.4%).