Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Public Funding on the Different Types of Private Contributions

We analyze the effect of public funding on private contributions to 67 nongovernmental development organizations (NGDOs) in Spain from 2006 to 2011. Previous literature gives theoretical explanations for both the crowding‐in and the crowding‐out effects, while the empirical evidence presents different realities. In this study, we find a partial crowding‐out effect (€1.00 of public funding reduces private contributions by €0.43) by using generalized method of moments estimators. However, this overall effect does not hold when analyzing the influence that different sources of public funds have on each type of private contribution.
Pendeteksian dan Pengenalan Wajah Manusia untuk Peningkatan Kinerja Kamera Pengaman

A security camera is a camera used to help improve the security that produces a video image and is stored into a storage medium. The stored image is the recording taken at the moment of the occurrence of the recording and can only be evidence for a crime. For that needed an approach that helps improve the performance of the security camera. The approach that can be done is to detect the human object that is in front of the camera and provide information about the human object is. The methods used for this approach are Support Vector Machine and Deep Convolutional Neural Network. The image inputted from the camera will experience the process of grayscalling, then threshold will be done to separate the background and object which will then be extracted value and classified with Support Vector Machine and Deep Convolutional Neural Network which will be stored when there is human and send notification when humans are not recognized. In this study the accuracy of face recognition reached 83% and savings of storage media was 73.3%. Keyword : Deep neural network, Security Camera, Tensorflow, Deep Convolutional Neural Network, Support Vector Machine, Face Recognition, Human Detection. Universitas Sumatera Utara
Disproportionately higher exposure to urban heat in lower-income neighborhoods: a multi-city perspective

A growing literature documents the effects of heat stress on premature mortality and other adverse health outcomes. Urban heat islands (UHI) can exacerbate these adverse impacts in cities by amplifying heat exposure during the day and inhibiting the body’s ability to recover at night. Since the UHI intensity varies not only across, but also within cities, intra-city variation may lead to differential impact of urban heat stress on different demographic groups. To examine these differential impacts, we combine satellite observations with census data to evaluate the relationship between distributions of both UHI and income at the neighborhood scale for 25 cities around the world. We find that in most (72%) cases, poorer neighborhoods experience elevated heat exposure, an incidental consequence of the intra-city distribution of income in cities. This finding suggests that policymakers should consider designing city-specific UHI reduction strategies to mitigate its impacts on the most socioeconomically vulnerable populations who may be less equipped to adapt to environmental stressors. Since the strongest contributor of intra-urban UHI variability among the physical characteristics considered in this study is a neighborhood’s vegetation density, increasing green space in lower income neighborhoods is one strategy urban policymakers can adopt to ameliorate some of UHI’s inequitable burden on economically disadvantaged residents.
Cross-impact of leverage and firm performance: developed vs frontier bank-based economies

Purpose The purpose of this paper is to investigate the cross-impact of leverage and performance for firms operating in the developed and frontier bank-based economies. Design/methodology/approach This study uses annual panel data for a sample of 400 firms over a period of 27 years from 1990 to 2016. The sample sample firms consist of developed, Germany, France and Japan, and frontier including Argentina and Sri Lanka bank-based economies firms. The authors employ a simultaneous equation modeling consisting of two equations estimated using the two-stage least squares procedure to examine the cross-relationships between leverage and performance after controlling for other firm-level variables like size, growth and liquidity. Findings The empirical results are presented in two sets. First, in the case of firms in the developed bank-based sample, the authors find a negative debt-to-performance relationship and a negative performance-to-debt relationship. This inconsistent negative debt–performance relationship implies that firms operating in these economies use debt beyond a threshold limit, which, in turn, increases agency issues between the managers and debt-holders, thereby influencing firm performance adversely. Second, for frontier economies firms, the authors find a positive debt-to-performance relationship in line with the “trade-off theory. ” Furthermore, the authors find a negative performance-to-debt relationship for both sub-samples in line with the “pecking-order theory. ” Originality/value The study is distinct from earlier empirical studies and contributes largely to the existing literature. First, it emphasizes whether financial leverage influences firm performance in bank-based economies as firms operating in such systems are exposed directly to the strict regulatory environment. Second, it investigates whether any reverse relationship emanating from firm performance to capital structure holds for firms of these countries. This issue, to the best of author knowledge, is unanswered in previous research, more specifically for developed and frontier bank-based economies. Moreover, the results are relevant, as firm managers, analysts and policymakers must consider the importance of such cross-debt-performance relationships, while determining the optimal capital structure, in the bank-based economies.
Ideology and the Role of Natural Resources in Bolivia

Abstract: The growth literature has identified four channels of transmission by which the abundance of natural resources can negatively affect economic growth. In this article, I suggest ideology as a fifth transmission channel. To test this hypothesis, I exploit the geography of Bolivia whose western regions have natural resources that differ considerably from its eastern regions. I find that regions with predominantly extractive natural resources tend to choose redistributive and interventionist rather than laissez-faire policies. Additionally, I identify two effects on growth depending upon the type of natural resource that a region possesses in abundance.
Monitoring, Evaluation and Accountability Against Corruption: A South African Case Study

CITATION: Mantzaris, E. A. & Pillay, P. 2019. Monitoring, evaluation and accountability against corruption : a South African case study. Journal of Reviews on Global Economics, 8:521-531, doi:10.6000/1929-7092.2019. 08.45.
Les activités familiales de littératie atténuent les effets négatifs du temps-écrans sur le développement langagier.

Problematique : Les habiletes de langage (comprehension et production) chez les enfants d’âge prescolaire s’averent un important determinant de la reussite scolaire future. Dans cette perspective, cerner les facteurs qui peuvent les influencer est un objectif des plus pertinents. Objectif : En sachant que les activites de litteratie familiales et le temps-ecrans (television et jeux electroniques) presentent respectivement des correlations positives et negatives avec le developpement langagier, la presente recherche se pose la question suivante : les activites de litteratie familiales peuvent-elles attenuer les effets deleteres du temps-ecrans sur le developpement langagier ? Methode : L’echantillon est constitue de 240 enfants et de leur mere. Les habiletes langagieres ont ete evaluees par le WIPSSI et le questionnaire de Dube (1987) sur les habiletes socio-conversationnelles. La frequence des activites de litteratie familiales a, quant a elle, ete sondee par un questionnaire elabore par Martini et Senechal (2012) alors que le nombre d’heures par semaine du temps-ecrans a ete recueilli a l’aide d’un questionnaire sur les loisirs et les activites a la maison (Bigras, 2009). Des donnees d’ordres sociodemographiques ont egalement ete colligees. Resultats : Les activites de litteratie familiales s’averent un mediateur significatif pour expliquer la relation negative entre le temps-ecrans et le developpement langagier chez les enfants de 4 et 5 ans.
Comparison of two control programs of the VVER-1000 nuclear power unit using regression data mining models

A load-following mode of nuclear power plants (NPP) is a complicated procedure, since there are significant changes in many interrelated processes. In order to show which control program (CP) of NPP is better to use, data mining (DM) techniques can be introduced. This study proposes a DM approach in order to show a possibility of using DM regression models for NPP. The datasets for DM were obtained by simulating two static CP of VVER-1000 NPP in Simulink software of Matlab program package.
Some Recent Developments on Pareto-optimal Reinsurance

This thesis focuses on developing Pareto-optimal reinsurance policy which considers the interests of both the insurer and the reinsurer. The optimal insurance/reinsurance design has been extensively studied in actuarial science literature, while in early years most studies were concentrated on optimizing the insurer’s interests. However, as early as 1960s, Borch argued that “an agreement which is quite attractive to one party may not be acceptable to its counterparty” and he pioneered the study on “fair” risk sharing between the insurer and the reinsurer. Quite recently, the question of how to strike a balance in risk sharing between an insurer and a reinsurer has drawn considerable attention. This thesis contributes to the existing study in terms of the following aspects: first, we derive the set of Pareto-optimal reinsurance policies within risk mimization framework; second, we obtain the set of Pareto-optimal reinsurance policies within expected utility maximization framework. In addition, we uniquely identify the policy according to classical bargaining models; third, we blend risk minimization criterion and expected utility maximization criterion and study the so called Pareto-optimal reinsurance policy with maximal synergy. The thesis is structured as follows. Chapter 1 introduces the problem and reviews the most recent advances on related topics. Chapter 2 applies a geometric approach to derive the Pareto-optimal reinsurance policy under Value-at-Risk minimization criterion. The geometric approach visualize the process of seeking the solution which greatly simplifies the mathematical proof. As a natural extention, Chapter 3 studies the design of Pareto-optimal reinsurance policy by assuming that distortion risk measures are employed to measure the risks of the insurer and the reinsurer. The optimal reinsurance policy is derived through three methods: Lagrange dual method, generalized Neyman-Pearson lemma and dynamic control approach. Chapter 4 studies the problem through maximizing the weighted expected utility and applies the results from classical bargaining models to identify the “best” policy on the Pareto efficient frontier. Chapter 5 revisits the problem by considering a mixture of risk minimization and expected utility maximization criteria. Chapter 6 gives potential directions for future research.
Relationship between Sustainable Disclosure and Performance—An Extension of Ullmann’s Model

Due to the lack of consensus on the Sustainable Disclosure (SD)–Sustainable Performance (SP) relationship and the absence of a robust theoretical framework base, this research tests this relationship. Based on Ullmann’s argument that the execution of corporate responsibility regarding SD, SP and EP (economic performance) is determined by the management’s (unobservable) overall strategy, we apply Partial Least Squares, introducing EP, size and membership in sensitive sectors and subjecting them to a multiplicity of external pressures (social, environmental and legislative) as determinants of the SD–SP link. There is a moderate SD–SP relationship, with a significant effect due to EP and conditioned by size. Specifically, (1) the companies that are concerned and which act sustainably have a higher SD, (2) the greater the EP, the greater its effect on this SD, but (3) when the sample is segmented by size, the moderating effect is only positive and significant for large companies. An awareness of the added value of the sustainable business model exists, more than simply reporting (actions beyond words), but the value that its profitability yields will not be determinant for SP, though it will affect SD, despite there being no direct relationship between performance and SD.
Self-Reported Versus Digitally Recorded: Measuring Political Activity on Facebook

Facebook has been credited with expanding political activity by simultaneously lowering barriers to participation and creating new ways to engage. However, many of these findings rely on subjects’ abilities to accurately report their Facebook use and political activity on the platform. This study combines survey responses and digital trace data from 828 American adults to determine whether subjects over- or underreport a range of political activities on Facebook, including whether they like political pages or share news links. The results show that individuals underestimate their frequency of status posting and overestimate their frequency of sharing news links on Facebook. Political interest is associated with a decrease in underreporting several political activities, while increasing the likelihood of overreporting the frequency of sharing news links. Furthermore, political interest serves a moderating effect, improving self-reports for high-volume users. The findings suggest that political interest not only predicts political activity but also shapes awareness of that activity and improves self-reports among heavy users.
Primary school teachers' understanding of themselves as professionals

This research study set out to gain an insight into primary school teachers’ understanding of themselves as professionals. The knowledge to be generated in this research is subjective as it involved teachers expressing their opinions and beliefs in the context of their own experience as teachers. This places the research study in the qualitative field as it is grounded in people’s own experiences and perceptions. The data were gathered in semi-structured interviews conducted with primary school teachers; this reflects a constructivist view of knowledge as coming from experience and interaction with others. My position as the researcher conducting this study can be considered as an insider researcher as my own experience as a primary school principal provides me with a tacit understanding of the situations and context described by the interviewees; this situational knowledge is regarded as an advantage in conducting the interviews for this research. The study includes a detailed history of the education system in Ireland which provides a context for the development of primary teaching as a profession. The literature review outlines the key elements of professionalism and considers these in relation to primary teaching. The key question being asked was ‘What is primary school teachers’ understanding of themselves as professionals? ’ and this is explored in the interviews under various headings. The data generated are analysed using themes; these provide a structure for identifying the key points being made. The study concludes with a summary of how primary school teachers view themselves as professionals, what their understanding of ‘being a professional’ is, and what issues are of concern to them.
An Empirical Study on Factors Affecting Switching Intention to Cloud Enterprise Resource Planning: A Comparison Between Public and Private Clouds

With the diffusion of cloud computing, public and private enterprise resource planning (ERP) have received increasing attention. However, several prior studies have investigated the factors that affect cloud system adoption for either public or private cloud systems. This article attempts to compare public and private cloud ERP. A research model is developed based on Two-Factor Theory and empirically test our hypotheses by collecting 253 public cloud samples and 227 private cloud samples. The results show that system quality and perceived ease of use positively affect switching benefits, which in turn positively affect switching intention. Security risk, satisfaction, and breadth of use positively affect switching costs. The moderating effects of public and private clouds affect the relationships between perceived ease of use and switching benefits, between breadth of use and switching costs, and between switching costs and switching intention. The findings offer suggestions for promoting organizations to switch to cloud public and private ERP.
Blocked and Accelerated Wavelet De-noising Algorithm Based on Data Splitting and Wavelet Analysis in Large Data Environment for Aero-Engine Health Monitoring

Data de-noising is a necessary part of health management, and it is the premise and foundation of effective feature extraction, condition monitoring and fault diagnosis for aero-engine. Random noise can cause serious interference to effective signals, and even lead to signal distortion and misdiagnosis of health condition. In view of the contradiction between the limited computing power of aircraft airborne system and the large amount of data processing, an blocked wavelet de-noising algorithm for large data is proposed based on the principle of data splitting theory and the wavelet theory under the multiple constraints of large data, high de-noising precision and fast processing speed. The algorithm used data splitting principle to split large data into small data sets, reduced the computational requirements of large data, and accelerated the speed of wavelet de-noising. The processing results of the theoretical data and the actual airborne aero-engine monitoring data showed that, compared with the traditional algorithms, the algorithm can protect the effective information and maintain the same de-noising accuracy, and the data de-noising time in the aero engine health monitoring data environment was accelerated by 4 times at least. 
Theories on Tornado and Waterspout Formation in Ancient Greece and Rome

Tornadoes and waterspouts have long fascinated humankind through their presence in myths and popular beliefs and originally were believed to have supernatural causes. The first theories explaining weather phenomena as having natural causes were proposed by ancient Greek natural philosophers. Aristotle was one of the first natural philosophers to speculate about the formation of tornadoes and waterspouts in Meteorologica (circa 340 BCE). Aristotle believed that tornadoes and waterspouts were associated with the wind trapped inside the cloud and moving in a circular motion. When the wind escapes the cloud, its descending motion carries the cloud with it, leading to the formation of a typhon (i.e., tornado or waterspout). His theories were adopted and further nuanced by other Greek philosophers such as Theophrastus and Epicurus. Aristotle’s ideas also influenced Roman philosophers such as Lucretius, Seneca, and Pliny the Elder, who further developed his ideas and also added their own speculations (e.g., tornadoes do not need a parent cloud). Almost ignored, Meteorologica was translated into Latin in the twelfth century, initially from an Arabic version, leading to much greater influence over the next centuries and into the Renaissance. In the seventeenth century, the first book-length studies on tornadoes and waterspouts were published in Italy and France, marking the beginning of theoretical and observational studies on these phenomena in Europe. Even if speculations about tornadoes and waterspouts proposed by Greek and Roman authors were cited after the nineteenth century only as historical pieces, core ideas of modern theories explaining these vortices can be traced back to this early literature.
Crash Fears and Stock Market Effects: Evidence From Web Searches and Printed News Articles

Abstract The authors studied the complex relationship between information supply and demand using newspaper articles and web searches that reflect investors’ crash fears. They report that more web searches lead to more news, whereas more news does not have that effect on web search in the future. The authors show also that web searches have an immediate effect on stock market returns and the VIX implied volatility, whereas the effect of news articles lasts longer, up to 11 weeks. The results suggest collectively that the web searches related to market crashes lead both the printed news stories about market crashes.
The responsibilization of entrepreneurs in legalized local prostitution in the Netherlands

markdownabstractBy way of a case study on the regulatory role of owners and managers of brothels and rented rooms for prostitution, this study focuses on the strategies deployed by a municipality to govern these intermediaries. The analysis is based on a typology of responsibilization distinguishing between who the responsible should govern (themselves or others) and forms of power (repressive or facilitative). The regulator concomitantly renders these entrepreneurs responsible for their own possible criminal conduct (self-governing) and empowers them to keep out traffickers and pimps and to control sex-workers (others-governing). Moreover, the municipality applies both repressive and facilitative power. Although the responsibilization strategy succeeds in having entrepreneurs govern themselves, it also unintentionally undermines sex-workers’ independence and favors the largest entrepreneurs. Our study enriches the regulator intermediary target model by showing how varied and contentious the interactions between regulators and involuntary intermediaries are and by demonstrating the power game that the responsibilization strategy entails.
Deep CNN-Based Real-Time Traffic Light Detector for Self-Driving Vehicles

Due to the unavailability of Vehicle-to-Infrastructure (V2I) communication in current transportation systems, Traffic Light Detection (TLD) is still considered an important module in autonomous vehicles and Driver Assistance Systems (DAS). To overcome low flexibility and accuracy of vision-based heuristic algorithms and high power consumption of deep learning-based methods, we propose a lightweight and real-time traffic light detector for the autonomous vehicle platform. Our model consists of a heuristic candidate region selection module to identify all possible traffic lights, and a lightweight Convolution Neural Network (CNN) classifier to classify the results obtained. Offline simulations on the GPU server with the collected dataset and several public datasets show that our model achieves higher average accuracy and less time consumption. By integrating our detector module on NVidia Jetson TX1/TX2, we conduct on-road tests on two full-scale self-driving vehicle platforms (a car and a bus) in normal traffic conditions. Our model can achieve an average detection accuracy of 99.3 percent (mRttld) and 99.7 percent (Rttld) at 10Hz on TX1 and TX2, respectively. The on-road tests also show that our traffic light detection module can achieve <inline-formula><tex-math notation="LaTeX">$<\pm\; 1.5m$</tex-math><alternatives><mml:math><mml:mrow><mml:mo><</mml:mo><mml:mo>±</mml:mo><mml:mspace width="0.277778em"/><mml:mn>1</mml:mn><mml:mo>. </mml:mo><mml:mn>5</mml:mn><mml:mi>m</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href="guizani-ieq1-2892451.gif"/></alternatives></inline-formula> errors at stop lines when working with other self-driving modules.