Miracle-dz/UniFAR-FTUs huggingface dataset:
Dividend policy and stock price volatility: Finnish evidence

Dividend policy has been a major field of study in corporate finance for decades, mostly concentrating on the relation of dividend policy and expected stock returns. However, dividend policy has been also used to explain the volatility of stock prices. This research includes a data sample of 131 Finnish public companies, listed on Nasdaq Helsinki ́s main list during the time period of 1992-2015. The impact of dividend yield and payout ratio on stock price volatility is examined using OLS-regression analysis, while controlling for earnings volatility, leverage, market capitalization and asset growth. The results provide a “middle road” between Baskin ́s (1989) results from the US and Allen and Rachim ́s (1996) results from Australia. Baskin ́s reported dominant dividend yield coefficient is recognized as significant but not dominant, while Allen and Rachim ́s emphasis on the effect of earnings volatility and leverage is partly supported. The findings suggest that payout ratio affect price volatility the most, although dividend yield, earnings volatility and market capitalization have an almost equal influence. As expected, dividend yield and payout ratio have a significant negative relationship with price volatility, and simultaneously earnings volatility ́s coefficient is significant but positive. Interestingly, against expectations, market capitalization has a significant, but positive relationship with price volatility. This was contrary to Baskin ́s results but in line with Allen and Rachim ́s. Two possible explanations are provided: the ownership structure of Finnish small cap companies, and the higher amount of short-term liabilities large cap companies face. The effect of leverage is contradictory to both Baskin, and Allen and Rachim, as leverage have no significant effect on price volatility at all. The bank-orientated capital markets of Finland and the significant negative relationship between earnings volatility and the amount of debt might provide a valid explanation about this matter. Baskin ́s suggestion that dividend policy would affect price volatility on its own is not supported. Rather, the results suggest that multiple factors alongside dividend policy explain the volatility of stock prices.
Nutrient Composition of Foods

Guiding nutritionists toward an understanding of the scientific principles underlying what they know about nutrition, this book helps them gain effective decision-making skills about nutritional choices. Unique Science Applied boxes answer the questions about how we learn what we know about the science of nutrition and why knowledge changes. Critical Thinking exercises included in each chapter allow them to learn the basics of how to think about a problem or situation creatively and critically. A case study is also included in each chapter that builds interest in the material. Each chapter then concludes with a postscript that solidifies the nutritionists' understanding of the links between the science and application.
Sincerity in Acted Speech: Presenting the Sincere Apology Corpus and Results

The ability to discern an individual’s level of sincerity varies from person to person and across cultures. Sincerity is typically a key indication of personality traits such as trustworthiness, and portraying sincerity can be integral to an abundance of scenarios, e. g. , when apologising. Speech signals are one important factor when discerning sincerity and, with more modern interactions occurring remotely, automatic approaches for the recognition of sincerity from speech are beneficial during both interpersonal and professional scenarios. In this study we present details of the Sincere Apology Corpus (SINA-C ). Annotated by 22 individuals for their perception of sincerity, SINA-C is an English acted-speech corpus of 32 speakers, apologising in multiple ways. To provide an updated baseline for the corpus, various machine learning experiments are conducted. Finding that extracting deep data-representations (utilising the DEEP SPECTRUM toolkit) from the speech signals is best suited. Classification results on the binary (sincere / not sincere) task are at best 79.2 % Unweighted Average Recall and for regression, in regards to the degree of sincerity, a Root Mean Square Error of 0.395 from the standardised range [-1.51; 1.72] is obtained.
PolyprenolsAreSynthesizedby aPlastidial cis-Prenyltransferase and In fl uence Photosynthetic Performance

Tariq A. Akhtar,a,1 Przemysław Surowiecki,b Hanna Siekierska,b Magdalena Kania,c Kristen Van Gelder,a Kevin A. Rea,a Lilia K.A. Virta,a Maritza Vatta,a Katarzyna Gawarecka,b Jacek Wojcik,b Witold Danikiewicz,c Daniel Buszewicz,b Ewa Swiezewska,b and Liliana Surmaczb,1 a Department of Molecular and Cellular Biology, University of Guelph, Guelph, Ontario N1G 2W1, Canada b Institute of Biochemistry and Biophysics, Polish Academy of Sciences, 02-106 Warsaw, Poland c Institute of Organic Chemistry, Polish Academy of Sciences, 01-224 Warsaw, Poland
LEARNING DIRECTION MATTERS A STUDY ON L 2 RHYTHM ACQUISITION BY DUTCH LEARNERS OF SPANISH AND SPANISH LEARNERS

This study examines the acquisition process of speech rhythm in Dutch learners of Spanish (DLS) and Spanish learners of Dutch (SLD) at different proficiency levels to determine whether learning direction affects the success of rhythm acquisition in a foreign language (L2). Analyses of lengthening effects This research was made possible through grants from the Prins Bernhard Cultuurfonds (40005750/HEV/ILE), the Jo Kolk fund, the Grup de Recerca Consolidat 2017 (SGR _ 971) and Spanish Ministry of Economy and Competitiveness (FFI2015-6653). We thank Gerdientje Oggel, Johanna Sattler, Arthur Verbiest, and Astrid van Winden for their help during data collection. We gratefully acknowledge Joan Borràs-Comes, Elena Kireva, Mart Lubbers, and Paolo Mairano for their help with data analyses, and Núria Esteve-Gibert and Constantijn Kaland for coding part of the data to test coding reliability. Finally, thanks are due to three anonymous reviewers for their helpful input and feedback on the content of this manuscript. Any errors that remain are our own. Preliminary versions of the first two studies of this paper were presented at the Speech Prosody conference in May 2016 in Boston and at the New Sounds conference in June 2016 in Aarhus, Denmark, respectively. The current paper includes a more detailed theoretical background and description of the experimental methods, more extensive discussions of the results, and more advanced statistical analyses over the complete dataset. *Correspondence concerning this article should be addressed to Lieke van Maastricht, Radboud University, Postbus 9102, 6500 HC Nijmegen, Netherlands. E-mail: l.vanmaastricht@let.ru. nl Copyright © Cambridge University Press 2018 of use, available at https://www.cambridge. org/core/terms. https://doi.org/10.1017/S0272263118000062 Downloaded from https://www.cambridge. org/core. IP address: 54.70. 40.11, on 19 Sep 2019 at 02:48:37, subject to the Cambridge Core terms showed that the two learner groups followed different developmental paths in their acquisition of accentual and final lengthening: Both groups showed transfer effects from the L1, but while the DLS systematically approached their target until attainment, the SLD showed more variability in their development. In addition, syllable structure complexity affected L2 rhythm acquisition, and to a substantially larger extent for the SLD compared to the DLS. The results support a model of L2 rhythm acquisition in which learning direction is included as a factor, and that allows for the interaction of various language-specific properties that contribute to speech rhythm, like syllable structure complexity.
Papain-mediated reduction of MTT is an artifact but not an indicator of cell apoptosis in Saccharomyces cerevisiae

Papain is a proteolytic enzyme of the cysteine protease family used for tissue dissociation and cell separation. Papain’s nonspecific proteolysis of the plasma membrane enzymes plays a crucial role in the homeostasis by disrupting the intracellular pH of the affected cells which might lead to cell death. When the Saccharomyces cerevisiae cells were treated with different concentrations of papain (1.0, 5.0, 10.0, 20.0, and 30.0 μg/ml), we found no alteration in the trans-plasma membrane electron transport (TPMET) activity and the intracellular pH of the cells, while it significantly decreased the mitochondrial dehydrogenase activity when measured by 3-(4,5-Dimethylthiazol-2-yl)2,5-Diphenyltetrazolium Bromide (MTT) assay. Additional verification of cell viability by trypan blue assay showed 98%–99% cell viability, contrary to the higher cell death observed with MTT assay. To better understand the decrease in cell viability with MTT assay, we tested the cell-free system that demonstrated a significant decrease of MTT concentration but the trypan blue assay showed more number of viable cells. This study shows that papain interferes with the MTT assay.
Nano Silver-Iron-Reduced Graphene Oxide Modified Titanium Dioxide Photocatalytic Remediation System for Organic Dye

The organic water contaminant, methyl orange contaminant (M.O), has shown a hazardous increase in our water systems over the past few years due to its increasing demand in industrial processes. The photocatalytic degradation of the commercial dye was studied through the application of modified TiO2 composite catalysts in aqueous solution under artificial irradiation. The improvement of photocatalytic activity is strongly affected by the various functional groups emerging in the organic substances. In this work, the effect of both silver-iron and silver-iron-reduced graphene oxide-modified titanium dioxide towards M.O remediation as a cost-effective photocatalyst was investigated. We confirmed that the novel AgFe functionalized TiO2 catalyst (AgFe-TiO2) showed more superior remediation activity than the reduced graphene oxide (rGO)-modified TiO2 due to the decreased band gap from 3.02 eV–2.5 eV with increased photocatalysis. Based on the spectroscopic and microscopic results, the enhanced photocatalytic degradation of M.O dye was induced by its enhanced surface area, electron diffusion, and the reduction of photo-generated electron-hole pairs’ recombination.
India : private health services for the poor

Despite India's great strides since independence, fertility, mortality, and morbidity remain unacceptably high. Although poverty and low levels of education are the root causes of poor health outcomes, poor stewardship over the health system bears some responsibility. Although India's states exhibit a wide variation in health outcomes, all but the best-performing states need to focus on improving both sexual and reproductive health care and child health care, and on reducing communicable diseases for the poor. This paper examines the public and private responses to this situation detailing the reasons behind the failure of the public sector and ways in which the private sector can be encouraged to play a role in providing health care for the poor in India. The paper concludes that there are three promising areas for the private sector including; (i) contracting out the primary health centers, (ii) social franchising and (iii) demand-led financing. The study is focused on what to do to improve health care for the poor, while a series of separate background papers focus on how to do it, and state specific issues in Andhra Pradesh, Bihar, Karnataka, and Punjab.
Emotional Decision-Making Biases Prediction in Cyber-Physical Systems

This article faces the challenge of discovering the trends in decision-making based on capturing emotional data and the influence of the possible external stimuli. We conducted an experiment with a significant sample of the workforce and used machine-learning techniques to model the decision-making process. We studied the trends introduced by the emotional status and the external stimulus that makes these personnel act or report to the supervisor. The main result of this study is the production of a model capable of predicting the bias to act in a specific context. We studied the relationship between emotions and the probability of acting or correcting the system. The main area of interest of these issues is the ability to influence in advance the personnel to make their work more efficient and productive. This would be a whole new line of research for the future.
Veri fi cation of a Lagrangian particle model for short-range fi rebrand transport

Firebrands are a harbinger of damage to infrastructure; their effects cause a particularly important threat to people living within the wildland-urban-interface. Short-range firebrands travel with the wind with little or no lofting, and cause spotfires. In this work, the design of a novel firebrand generator prototype is discussed to achieve a uniform shower of firebrands. The transport of short-range firebrand is studied to verify the existing Lagrangian particle model of Fire Dynamics Simulator. Uniform, non-combusting cubiform and cylindrical firebrands are projected using the firebrand generator. The experimentally observed distribution of particles on the ground is compared with a simulated distribution using the fire dynamic simulator. The results show that the existing Lagrangian model gives a good agreement with the experimental data.
ENERGY-EFFICIENT CARRIER SDN NETWORKS

In the last years, the economic and environmental costs related to energy consumption led to efforts for enhancing the energy efficiency of networking equipment. Unfortunately, most of the proposals have not been implemented due to the limited flexibility of current networks. On the other hand, the Software-Defined Networking (SDN) paradigm introduces flexibility and programmability through the separation of control and data planes. In this thesis, we focus on minimizing the energy consumption in bundles of Energy Efficient Ethernet links leveraging SDN. We first analyze the problem from the point of view of SDN. Then, we design a complete application to minimize the energy consumption by periodically reallocating the traffic flows in the ports of the aggregate, dynamically adapting to variations in the traffic demand. We validate the proposed algorithms through simulations and also by implementing the application in a real SDN controller. The results show that our algorithms are capable of concentrating the traffic in few ports, saving up to a 50% of energy when there is a low traffic load. Nevertheless, the results show a trade-off between energy consumption and packet delay. Accordingly, we extend our solution to give support to traffic with low latency QoS requirements while keeping energy consumption minimized. Our results confirm that the latency of time-sensitive traffic can be reduced some orders of magnitude without increasing the energy consumption.
An Energy-Efficient and Fault-Tolerant Topology Control Game Algorithm for Wireless Sensor Network

Due to resource constraints and severe conditions, wireless sensor networks should be self-adaptive to maintain certain desirable properties, such as energy efficiency and fault tolerance. In this paper, we design a practical utility function that can effectively balance transmit power, residual energy, and network connectivity, and then we investigate a topology control game model based on non-cooperative game theory. The theoretical analysis shows that the topology game model is a potential game and can converge to a state of the Nash equilibrium. Based on this model, an energy-efficient and fault-tolerant topology control game algorithm, EFTCG, is proposed to adaptively constructs a network topology. In turn, we present two subalgorithms: EFTCG-1 and EFTCG-2. The former just guarantees network single connectivity, but the latter can guarantee network biconnectivity. We evaluate the energy-efficient effect of EFTCG-1. Meanwhile, we also analyze the fault-tolerant performance of EFTCG-2. The simulation results verify the validity of the utility function. EFTCG-1 can efficiently prolong the network lifetime compared with other game-based algorithms, and EFTCG-2 performs better in robustness, although does not significantly reduce the network lifetime.
How We Teach Now : The GSTA Guide to Student-Centered Teaching View project

Major advances in multimedia computer technology over the past decades have made sophisticated computer games readily available to the public. This, combined with the observation that most children, including those with autism spectrum disorders (ASD), show an affinity to computers, has led researchers to recognize the potential of computer technology as an effective and efficient tool in research and treatment. This paper reviews the use of computer-assisted technology (CAT), excluding strictly internet-based approaches, to enhance social, communicative, and language development in individuals with ASD by dividing the vast literature into four main areas: language, emotion recognition, theory of mind, and social skills. Although many studies illustrate the tremendous promise of CAT to enhance skills of individuals with ASD, most lack rigorous, scientific assessment of efficacy relative to non-CAT approaches.
VALIDATION OF THE MONTEBURNS CODE FOR CRITICALITY CALCULATIONS OF TRIGA REACTORS

Use of Monte Carlo methods in burnup calculations of nuclear fuel has become practical due to increased speed of computers. Monteburns is an automated computational tool that links the Monte Carlo code MCNP with the burnup and decay code ORIGEN2.1. This code system was used to simulate a criticality benchmark experiment with burned fuel on a TRIGA Mark II research reactor. Two core configurations were simulated and keff values calculated. The comparison between the calculated and experimental values shows good agreement, which indicates that the MCNP/Monteburns/ORIGEN2.1 system gives reliable results for neutronic simulations of TRIGA reactors.
Performance of Static Voltage Stability Analysis in MATLAB Environment with Further Applications

Nowadays, electric power systems have been often operated close to their feasible limits due to increased electric power consumptions, large installments of renewable power sources, and deliberated power market policies. These pose a serious threat to stable network operation and control. Therefore, both static and dynamic voltage stabilities are currently one of the key topics worldwide for preventing related black-out and islanding scenarios. In this paper, modelling and simulations of static voltage stability problems in MATLAB environment are performed using author-developed computational tool implementing both conventional and more advanced numerical approaches. Their performances are compared with Simulink-based library Power System Analysis Toolbox (PSAT) in terms of solution accuracy, CPU time and possible limitations. Furthermore, their use for locating critical network buses/branches/areas and most critical loading scenarios in terms of voltage stability are demonstrated. Eventually, their both real-time and off-line monitoring and assessment capabilities of system's voltage stability are also discussed.
Modelling land-use and transport at a national scale-the MARS Austria model

This paper presents the attempt to set up the dynamic land-use transport interaction (LUTI) model MARS (Metropolitan Activity Relocation Simulator) for a nation wide case study of Austria. To this end we adapted the existing urban MARS model. The purpose of the model is to capture the most important interactions and feedback mechanisms between the land-useand the transport system. The MARS model consist of a transport model, a housing development model, a household location choice model, a workplace development model, a workplace location choice model, as well as a fuel consumption and emissions model. In terms of transport and land-use policies which can be modelled, MARS was developed to investigate strategic level issues over a long time period; 30 years. It is therefore an aggregate model. The development of MARS at the Research Center of Transport Planning and Traffic Engineering started some 10 years ago, partly funded by a series of EU-research projects. To date MARS has been applied to 13 cities (10 European, two Asian and one South American). In this paper particular attention was paid to the structural changes of the model (from urban to national scale) and the estimation of the transport model parameters as well as the landuse model parameters, which are modelled with a gravity model approach. For this purpose we used the build-in optimizer of the system dynamics modelling software Vensim by minimizing the sum of squared deviations between observed and predicted data. We present the model fit and estimated parameters.
USE OF MIST NETS AS A TOOL FOR BIRD POPULATION MONITORING

Ahstract. Mist nets are an important tool for population monitoring. here defined as asse1. ,1. ,ment of '>pecics composition. relative abundance. population siLe. and demography. We re\ ie\\ the strength<. , and limitation-. of mist netting for monitoring purposes. based on papers in this volume and other literature. Ad\antages of using mi'>t nets over aural or\ isual count method include ea1. ,e of '>tandardized sampling, low observer bias. ability to detect species that arc often missed using other count rm:thods. and opportunity to examine birds in the hand (providing information on conJition, age. sex. and capture history). The primary limitation of mist netting. in common with most other survey methods. is from potential bias in '>ampling. However. there are many approaches to reducing or adJU'>ting for bias, including standardiz.ition of netting method. ,. combining mi. ,t-net '>ampling \\Ith other sune) types, and us111g mark-recapture techmque<. , . Mist netting is an essential tool for '>pecies inventory. pro\idcs useful indice1. , of relative abundance. and can be u<,ed lo track temporal trend. , in abundance It is al. o one of the most efficient methods of capture for mark recapture studie .
A Chinese Dataset for Identifying Speakers in Novels

Identifying speakers in novels aims at determining who says a quote in a given context by text analysis. This task is important for speech synthesis systems to assign appropriate voices to the quotes when producing audio books. Several English datasets have been constructed for this task. However, the difference between English and Chinese impedes processing Chinese novels using the models built on English datasets directly. Therefore, this paper presents a Chinese dataset, which contains 2,548 quotes from World of Plainness , a famous Chinese novel, with manually labelled speaker identities. Furthermore, two baseline speaker identiﬁcation methods, i.e., a rule-based one and a classiﬁer-based one, are designed and experimented using this Chinese dataset. These two methods achieve accuracies of 53.77% and 58.66% respectively on the test set.
D Distributed Machine Learning

Distributed machine learning refers to multinode machine learning algorithms and systems that are designed to improve performance, increase accuracy, and scale to larger input data sizes. Increasing the input data size for many algorithms can significantly reduce the learning error and can often be more effective than using more complex methods [8]. Distributed machine learning allows companies, researchers, and individuals to make informed decisions and draw meaningful conclusions from large amounts of data. Many systems exist for performing machine learning tasks in a distributed environment. These systems fall into three primary categories: database, general, and purpose-built systems. Each type of system has distinct advantages and disadvantages, but all are used in practice depending upon individual use cases, performance requirements, input data sizes, and the amount of implementation effort.