Miracle-dz/UniFAR-FTUs huggingface dataset:
Industry Concentration and Investment Funding: The Importance of Understanding the Market Structure

Prior studies document that firms use less debt financing relative to equity financing, and preserve more cash holding when they face competitive pressure. However, those studies are silent on the potential difference in market structure between price and non-price competition. Focusing on the industry concentration as an inverse measure of competition pressure, we find that the influences of industry concentration on external financing and cash holding are stronger for non-price competition industries than for price competition industries. Further analysis shows that the difference between price and non-price competition is more pronounced when industry is growing, firm has growth opportunity, or firm is younger. This implies that high industry concentration is more likely to indicate low competition pressure for non-price competition industries than for price competition industries.
Structural Equation Modeling of Relationship Marketing, Ethics and Performance of Soyabean Traders in Benue State, Nigeria

The objective of this study was to analyze the relationships between relationship marketing, ethics and performance of soyabean traders in Benue State, Nigeria. Multistage sampling technique was used in selecting 120 soyabean traders for the study. Primary data was used via the administration of questionnaire in the study area. Data collected was carried out with the aid of SEM. The Comparative Fit Index (CFI) of 0.846 was close to 1 which indicates a better fit for the relationship marketing, ethics and performance model. The standardized root mean square residual (SRMR) value of 0.076 is the difference between the observed correlation and the model implied correlation matrix. This value is close to 0, which indicates good model fit for the study. The three paths covariance (i.e., Cov [RMKT, ETHICS], Cov [ETHICS, PERF] and Cov [RMKT, PERF]) were significant at 1% level (p=0.000) with positive relationships. This indicates consistency in the paths movements which also entails that a unit increase in one variable leads to a corresponding increase in another. The Chi-square value of 82.45 is significant at 1% for the full model of the three paths and indicates significance for relationship marketing, ethics and performance respectively. The study concluded that, relationship marketing and ethics influence soyabean performance; this is exhibited by traders and it is pertinent for the survival of soyabean business in the various local markets in Zones A and B of Benue State, Nigeria. In order for soyabean traders to reduce costs, successful execution of relationship marketing orientation requires that soyabean traders and markets define their business, and understand how to create and manage total service offering. Relevant and timely information should be designed and made available to soyabean traders and markets as regards the current ethics codes of conduct and required market standards.
ON MEASURING MISORIENTATION OF SEISMIC SENSORS USING AMBIENT NOISE DATA

The dependence of the results of many seismic studies (e.g. seismic anisotropy, extracting Love wave from ambient noise data, measuring wave amplitude and receiver functions) to the accuracy of seismic sensor’s orientation are experienced many times. Therefore, the misorientation correction of seismic data in such studies must be taken into account seriously. Aligning the seismometer to the true geographical orientation is harder than it seems. Usually, a magnetic compass is used to estimate the geographic orientation in the sensor deployment stage. In this case, the accuracy of determining the true geographic orientation is affected by a variety of factors such as the presence of magnetic and mineral resources near the installation location and the lack of declination correction which is more important in high-latitude regions. In addition, although fiberoptic gyrocompass is very accurate to determine true geographic orientation, the cost and weight of such equipment prevents its usage widely (Wang et al., 2016). Due to such reasons, seismograms analysis has been considered as a new tools to correct misorientation of the sensors in the recent years. There are two main methods for correcting misorientation of seismometers by seismograms analysis. The first one is based on the polarization analysis of long-period Rayleigh waves (2550 s) or intermediate period P-waves (10-25 s) generated by telesismic earthquakes. The second method, which is used in this paper, is based on the analysis of empirical green functions through the cross correlation of ambient noise data. However, synthetic methods can be used for removing misorientation which is computationally expensive. In this paper, we estimated misorientation of the sensors for IIEES and IRSC seismic networks using the method developed by Zha et al. (2013) based on ambient noise analysis. First, we assumed that station A has a misorientation ψ (Figure 1).
Mathematical Formulation of Feedback Linearizing Control of Doubly Fed Induction Generator Including Magnetic Saturation Effects

This paper proposes a control methodology based on feedback linearization for a doubly fed induction generator (DFIG) incorporating the magnetic saturation. The feedback linearization algebraically converts a nonlinear system model into a linear model, allowing the use of linear control techniques. Feedback linearization control depends on the model of the system and is therefore sensitive to parameter variations. The doubly fed induction generator (DFIG) operating under the magnetic saturation conditions results in the nonlinear variation of magnetizing inductance, which affects the performance of the control algorithm. From this stand point, on the basis of the dynamic model of the doubly fed induction generator considering magnetic saturation, the feedback linearizing control technique has been formulated. The mathematical model of the doubly fed induction generator, integrating the magnetic saturation has been formulated in the stator flux-oriented reference frame with rotor current and stator magnetizing current as state variables. Simulation studies demonstrate that the inclusion of magnetic saturation in the feedback linearization control of the doubly fed induction generator model increases its accuracy and results in a more efficient and reliable synthesis of the control algorithm.
Towards Implementing Inclusive Authentication Technologies for Older Adults

Two-factor authentication (2FA) provides protection for on-line accounts through efﬁcient and highly robust access con-trol. Adoption and usability, however, remain challenging for such security tools and technologies. Most current research on 2FA focuses on convenience samples of experts in the technology sector while neglecting non-experts. As older adults increasingly use everyday digital technologies, providing convenient means for them to protect their online data has become extremely crucial. To aid with this, we investigated the user experience of 2FA security tokens with ten older adults ( > 60 years) using surveys, semi-structured interviews, and a think-aloud protocol. Their limited adoption of the 2FA security token stems from its non-inclusive design, unclear instructions, lack of tangible beneﬁts, and device dependencies. Hence, we propose design modiﬁcations and effective risk communication techniques to encourage 2FA adoption among organizations that are most invested in protecting older adults - such as retirement management funds, banking institutions, and health care organizations.
Empirical quantiﬁcation of privacy loss with examples relevant to the 2020 US Census

The 2020 US Census will use differential privacy for disclosure avoidance, employing a new algorithm called TopDown to guarantee privacy loss of at most (cid:15) . However, it is possible that there is some slack in the bound (which is proven using the sequential composition theorem), and in practice, the privacy loss will be substantially less than (cid:15) . In this paper, I develop an empirical measure of privacy loss, and apply it to three example algorithms, inspired by some aspects of TopDown, to better understand how the empirical privacy loss might compare to the theoretical guarantee. My results suggest that (1) it is possible to quantify privacy loss empirically in a reasonable amount of time, at least for counting algorithms like TopDown; and (2) it is likely that the empirical privacy loss of hierarchical counting algorithms like TopDown is substantially lower than the privacy bound derived from the serial composition theorem.
Immigrant Links, Trade Creation, and Trade Diversion

I derive a simple gravity model of trade that diffe rentiates between native agents and immigrants and allows for shifts in bilateral trade flows due to immigrant links. I calculate the share of total trade between the OECD and non-OECD countries attributabl e to immigrant links and find that immigrantdriven trade accounts for as much as 10.98 percent of aggregate OECD exports to and 9.99 percent of aggregate OECD imports from the non-OECD source cou ntries in the sample. The evidence nonetheless suggests that part of immigrants’ contribution migh t be offset by less trade with other trade partners . A onepercentage-point increase in the aggregate size of the overseas immigrant diaspora relative to the cou ntry of origin’s population would result in a decrease in t he OECD country’s total exports by roughly 1.75 per cent and its total imports by 2.28 percent.
Task mapping on a dragonfly supercomputer

—The dragonﬂy network topology has recently gained traction in the design of high performance computing (HPC) systems and has been implemented in large-scale supercomputers. The impact of task mapping, i.e., placement of MPI ranks onto compute cores, on the communication performance of applications on dragonﬂy networks has not been comprehensively investigated on real large-scale systems. This paper demonstrates that task mapping affects the communication overhead signiﬁ-cantly in dragonﬂies and the magnitude of this effect is sensitive to the application, job size, and the OpenMP settings. Among the three task mapping algorithms we study (in-order, random, and recursive coordinate bisection), selecting a suitable task mapper reduces application communication time by up to 47%.
‘Dead people don’t claim’: A psychopolitical autopsy of UK austerity suicides

One of the symptoms of post financial crisis austerity in the UK has been an increase in the numbers of suicides, especially by people who have experienced welfare reform. This article develops and utilises an analytic framework of psychopolitical autopsy to explore media coverage of ‘austerity suicide’ and to take seriously the psychic life of austerity (internalisation, shame, anxiety), embedding it in a context of social dis-ease. Drawing on three distinct yet interrelated areas of literature (the politics of affect and psychosocial dynamics of welfare, post and anti-colonial psychopolitics, and critical suicidology), the article aims to better understand how austerity ‘kills’. Key findings include understanding austerity suicides as embedded within an affective economy of the anxiety caused by punitive welfare retrenchment, the stigmatisation of being a recipient of benefits, and the internalisation of market logic that assigns value through ‘productivity’ and conceptualises welfare entitlement as economic ‘burden’. The significance of this approach lies in its ability to widen analytic framing of suicide from an individual and psychocentric focus, to illuminate culpability of government reforms while still retaining the complexity of suicide, and thus to provide relevant policy insights about welfare reform. Corresponding author: China Mills, School of Education, University of Sheffield, Sheffield, S10 2JA, England. Email: china.mills@sheffield.ac. uk 726263CSP0010.1177/0261018317726263Critical Social PolicyMills research-article2017
Muslim Consumers Style Inventory: A Case from Pakistan

The primary objective of the study is to investigate the Muslim consumers’ style inventory. An allied objective of this study is to test the reliability and validity of consumer style inventory in an economically developing country like Pakistan. For this purpose, data was collected from university graduate and under-graduate students. Factor reduction technique was used in SPSS to examine Muslim consumers’ style inventory. Findings of the study indicate that Muslim consumers are partially different from their non-Muslims counterparts. The result of principal component analysis revealed that factors like “Impulsive” and “recreational” were not confirmed by the Muslim consumers. However, other factors like price conscious, quality conscious and ‘confused by over choice’ were confirmed. Thus, study suggests that formal consumers’ education system should be enhanced and all concerned bodies like Islamic scholars, Government agencies and universities should play their role in formulating shopping orientation of Muslim consumers. Furthermore, the future direction of study provides an avenue to coming scholars on the area.
Memristor Behavior under Dark and Violet Illumination in Thin Films of ZnO/ZnO-Al Multilayers

ZnO/ZnO-Al thin films were grown aiming the development of a memristor. Electrical voltage sweeps were imposed to induce dopant migration and to achieve several resistance states. A memristor behavior was observed, presenting adaptation to external electrical stimulus. Voltage sweeps occurred under the influence of violet light and in the dark, alternately, and the influence of the photon incidence on the current intensity was noticed. Throughout the alternating cycles between light and dark, less resistance was observed under illumination, but the migration of Al and O ions caused the formation of Al 2 O 3 and ZnO oxides, resulting in a gradual increase in resistance. With constant voltage, the device presented continuous modification of resistance and sensitivity to the violet light with generation of free carriers. These results bring new opportunities for using memristors as violet light sensors as well as new insights for light-controlled memristor development.
Finland’s National Report for the Third United Nations Conference on Housing and Sustainable Urban Development (Habitat III)

In its resolution 66/207 of 14 March 2012, the General Assembly decided to convene, in line with the bi-decennial cycle (1976, 1996 and 2016), a third United Nations conference on housing and sustainable urban development (Habitat III) in 2016 to reinvigorate the global commitment to sustainable urbanization focusing on the implementation of a ―New Urban Agenda‖. This conference should build on the Habitat Agenda, various relevant declarations on sustainable development, the outcomes of the major United Nations conferences and summits, particularly the Rio+20 conference, as well as the Post-2015 Development Agenda and the Sustainable Development Goals.
Linguistic Distance, Networks and the Regional Location Decisions of Migrants to the EU∗

This paper analyzes the interaction between migrant networks and linguistic distance in the location decisions of migrants to the European Union at the regional level. We test the hypothesis that language and networks are substitutes in the location decision. Based on individual level data and a random utility maximization framework we find that networks have a positive effect on location decisions while the effect of linguistic distance is, as expected, negative. We also find a positive interaction effect between the two variables: networks are more important the larger the linguistic distance between the home and host countries, and the negative effect of linguistic distance is smaller the larger the network size. JEL Classifications: F22, J61, R23
Composites Modeling Capabilities of Abaqus

Composites occupy a noticeable place in the materials industry. Their characterization during the forming process as well as during their life cycle in different industrial fields impose an advanced knowledge of their mechanical and thermal behavior. Different industrial processes are considered in the forming of a composite sheet into a desired shape (blow molding, thermoforming etc.). Generally, the deformation during these processes is very fast, non-uniform, multiaxial and occurs at temperatures above the glass transition temperature. The modeling of this phenomenon remains delicate and creates several difficulties since it involves contact, large deformations, as well the implementation of nonlinear constitutive laws (hyperelastic, viscoelastic, etc.). The present work summarizes the capabilities of Abaqus for modeling the thermoforming of composites (short and long fibers). A presentation of the Composite Modeler Plugin shows a robust approach to define different plies, layups, and offsets associated with a long fibers composite model. It also shows the great capability of simulating real time draping and the generated shear stresses. The Micromechanics Plugin offers a great tool for subscale modeling in order to simulate the fiber-matrix interaction using an FE-RVE (Finite Element model of a Representative Volume Element) approach, and the generation of the homogenized material parameters. A presentation of material parameters calibration using Isight coupled with Abaqus illustrates how the two tools can be joined together to solve the classical identification problems associated with new materials or non-linear constative laws. Tosca structure Bead optimization capabilities are shown through the optimization based on natural frequencies. Fatigue analysis has been performed using Fe-safe and shows the fatigue life contours.
Automated text scoring, keeping it simple

In traditional automated text scoring approaches stop-words are either immediately removed or authors do not give importance to the handling of stop-words [1, 2, 3]. Recent studies have, however, found that removing stop-words may adversely affect certain models and should not be considered a standard component of the text pre-processing pipeline [4]. Given an essay, the task is to predict a numerical score or grade. To improve the accuracy of existing neural network approaches for essay scoring, recent attempts have focused on developing increasingly complex neural networks with little to no consideration of the text pre-processing pipeline [5, 6, 7]. In this work we investigated the text pre-processing pipeline for automated text scoring (ATS). We investigated how stacked LSTMs coupled with an adjustment to the text pre-processing pipeline and basic word embedding models can achieve results on par with the state-of-the-art. We used the ASAP dataset to train a basic LSTM deep learning model. For automated text scoring, which is concerned with the quality of writing, stop words contain crucial information for the system to predict accurate scores and should therefore, remain in text. We compared cases with and without stop-words removed to determine if there are any significant changes in the score prediction accuracy. We also compared twoand threelayer deep LSTMs to identify any significant differences. We found that keeping stop-words present significantly improves the prediction accuracy of the model while increasing the depth of the neural network shows no statistical significance. We showed that simple deep learning models coupled with tailored text pre-processing achieve results on-par with state-of-the-art models reducing the need for complex models and feature engineering for automated text scoring. The ASAP dataset [8], sponsored by the Hewlett Foundation for a Kaggle competition, has been used extensively for neural text scoring and contains 12,976 essays, marked by two raters. The essays range in length between 150 – 650 words and were written by students in Grades 7 – 10. For this experiment, we used this dataset with the resolved combined domain score between the two raters. We constructed twoand three-layer LSTMs. We did not lemmatize or stem the essays. We cleaned the text by removing punctuation and special characters. All the text was converted to lower-case. Importantly, in the case where we kept stop-words present, we did not identify dataset-specific stop-words and opted not to remove stopwords via the use of stop-word lists. For the removal of stop-words we used a popular word list from a python NLP library (NLTK). We tokenized the essays into word and
Power Quality Improvement Using Interleaved Boost Converter Fed Shunt Active Filter In Photo Voltaic System

Interleaved Boost Converter(ILBC) is a better converter between Photo Voltaic(PV) source and shunt active power filter. This paper deals with comparison of time domain outputs of PI and Fuzzy Logic controlled ILBC fed shunt active filter in a grid connected PV system. The aim of this work is to minimize current ripple using ILBC between PV system and filter to improve the performance of shunt active filter. Closed loop monitored PI and fuzzy systems are modeled, and the corresponding results are presented. MATLAB results of load voltage, current, converter voltage and currents with Fuzzy Logic Controller exhibits enhanced dynamic response. The proposed fuzzy logic controlled ILBC Fed Shunt Active Filter system (ILBCFSAF) has advantages like low settling time, less peak over shoot and reduced steady state error in load voltage.
Antibacterial and antioxidant activity of Justicia spicigera extracts: Activity enhancement by addition of metal salts

Justicia spicigera was screened for its phytochemicals. The results showed the presence of alkaloids, flavonoids, tannins, phenols, saponins and steroids. Extracts of J. spicigera prepared with solvents of different polarities (n-Hexane, Chloroform, Methanol, and Ethyl acetate) was used to analyze the antibacterial properties in the absence and in the presence of metal salts. The antioxidant activity was analyzed using 2, 2-diphenyl-1picrylhydrazyl reagent (DPPH). Quantitative determination of total phenolics was carried out using spectrophotometric method. The results indicate that the tested bacterial strains were most sensitive to the nHexane extract but moderately sensitive to the chloroform and methanol extracts. The chloroform, methanol, and ethyl acetate extracts showed potent radical scavenging activities. The ethyl acetate and methanol extracts showed higher total phenolic content than the other extracts. Antioxidant activity was found in the extract-Fe 3+ ion combination. The extract-Zn 2+ ion combination showed enhanced antibacterial activity against tested bacterial strains compared to the extract alone. The results scientifically establish the efficacy of using the plant extracts and its metal salt combination as antibacterial and antioxidant agents.
On the prediction of surface tension for multicomponent mixtures

A prediction method for surface tension of real mixtures was developed based on the Davis theory, and tested with the molecular dynamics simulation results of Mecke et al. (1997) for surface tension of the Lennard-Jones fluid. An effective Lennard-Jones potential was introduced for correlating surface tension for real pure liquids and binary liquid mixtures, leading to prediction of surface tension of multicomponent systems, including aqueous mixtures. The overall average absolute percentage deviations (AAPD) obtained in the correlated results for 62 pure liquids, 91 non-aqueous and 11 aqueous binaries are 0.66, 0.80, and 1.75, respectively. In the prediction of the surface tension for 9 ternary and 4 quaternary systems, using the molecular parameters of pure liquids and the adjustable binary parameters, the overall AAPDs are 1.75 and 1.03, respectively.