Miracle-dz/UniFAR-FTUs huggingface dataset:
Momentum in the European Corporate Bond Market: The Role of Bond-Specific Returns

This paper analyzes momentum patterns in the European corporate bond market. We study a broad sample of Euro-denominated investment grade and noninvestment grade bonds covering the period January 2004 to October 2016. Our empirical findings reveal that momentum is mainly concentrated among noninvestment grade bonds. Furthermore, the composition of the momentum portfolios varies over time and is related to bond characteristics. Taking this into account, we apply characteristics-based adjustments in context with performance measurement and find momentum profits to remain robust. Most importantly, bond-specific return components seem to drive momentum patterns, indicating gradual information diffusion in bond prices.
Untangling the puzzle of “Russia’s influence” in Kazakhstan

ABSTRACT The theme of “Russian influence” has been invading the think tank world. Yet the concept of influence must be deployed with care. Analysts have frequently assumed that, when states do things thought favourable to Russia, it must be because Moscow has either forced them to act in that manner, or has actively manipulated their domestic politics so that they do so. Left largely unconsidered are the various other reasons that one state might act in a manner desirable to another. In this article we look at the different vectors that might yield Russia-favorable behavior by Kazakhstan: exogenous ones that Russia actively and passively generates and endogenous ones that are passively or even actively generated within Kazakhstan itself. We discuss Russia’s economic and strategic links with Kazakhstan, the issue of the Russian minority, the status of the Russian language, Russian media presence, Russia’s governmental and non-governmental networks, and the “payoff” of the latter three vectors: Kazakhstani popular Russophilia. By distinguishing between active and passive vectors, as well as between exogenous and endogenous ones, we propose a more nuanced and better theoretically articulated picture of Russia’s “influence” in Kazakhstan.
Pathways in Bioinformatics: A Window in Computer Science

— Bioinformatics is an emerging field galvanized by intense research in computational and molecular biology. It continues to grow with vast potential for the present and future. As a result, the role of computer science in driving research and results forward remains crucial. Yet this field is barely understood. It is not in the standard domain of course curriculum in many institutions, even at post graduate level. This paper looks at Bioinformatics from the perspectives of Computer Science. In the process, provides entry point and pathways for more active and productive participation.
A A STUDY OF LISTENING COMPREHENSION PROBLEMS ENCOUNTERED BY THE THIRD SEMESTER STUDENTS AT STMIK PRABUMULIH

Even though listening is often categorized as a passive activity, it is not a simple process as it may seem. There is an active process because in it. Listeners must focus on the spoken language and actively draw what message is being delivered. There are some factors that make a listener may need a lot of work to comprehend a spoken language such as colloquialism, accent, intonation, hesitation, word or phrase clusters, and content. Preliminary data gained from pre-observation at STMIK Prabumulih showed that the third semester students found themselves hard to acquire information from spoken language, hence it is necessary to find out the causes so that make an effort to develop their listening skills. The method used is descriptive research design. The result reveals that students encounter various kinds of listening problems in learning comprehension such as unfamiliar words, the length and of the spoken text, speed rate, lack of concentration and pronunciation, and the noises around come from both the background sound of the spoken language recording and environmental sound such as sound from outside classroom. Keywords: listening; comprehension; listening comprehension problems; descriptive
A Contemporary Functional Form for NCAA Division I FBS Contributions: Internal and External Considerations

While managing the intercollegiate athletic development office is critical to contributions generation, the nearly 40 years of research modeling intercollegiate athletic fundraising emphasized limited factors external to this department. Both theoretical and statistical justification warrants a broader scope in contemporary factor identification. With a resource-based view as the theoretical foundation, a list of 43 variables both internal and external to the intercollegiate athletic development office was generated through an extensive literature review and semistructured interviews with athletic and nonathletic fundraising professionals. Based on the factors identified, random and fixed effects regression models were developed via test statistic model reduction across a 5-year panel (FY2011–FY2015). Ninety-three schools were included, representing 73% of the Football Bowl Subdivision (FBS) membership (85% of public FBS institutions). The results highlight the role of both internal and external factors in explaining intercollegiate athletic fundraising procurement.
Can Bureaucrats Really Be Paid Like Ceos? Substitution Between Incentives and Resources Among School Administrators in China

Abstract Unlike performance incentives for private sector managers, little is known about performance incentives for managers in public sector bureaucracies. Through a randomized trial in rural China, we study performance incentives rewarding school administrators for reducing student anemia—as well as complementarity between incentives and orthogonally assigned discretionary resources. Large (but not small) incentives and unrestricted grants both reduced anemia, but incentives were more cost-effective. Although unrestricted grants and small incentives do not interact, grants fully crowd-out the effect of larger incentives. Our findings suggest that performance incentives can be effective in bureaucratic environments, but they are not complementary to discretionary resources.
A FRAMEWORK TO ANALYZE AFFORDANCES WHEN USING BIG DATA AND ANALYTICS IN ORGANIZATIONS: A PROPOSAL

ABSTRACT Purpose: The article presents the development of a framework to analyze the use of big data and analytics in organizations. The framework is based on affordance theory and actor-network theory (ANT). Originality/value: Big data and analytics are a set of tools and techniques that are not new, but recently have received much attention from the media and academia. The media promotes big data and analytics while the academia addresses the fact that there are still implementation obstacles and the process of using big data analytics is not well understood. Design/methodology/approach: We used a qualitative approach, in the form of a theoretical essay. We analyzed papers that related affordance theory with IT and, in particular, with big data and analytics. Further, in order to create the resulting framework, an illustrative case study was conducted. Findings: Affordance theory, allied to the translation concept of ANT, can be useful when analyzing the process of using big data and analytics in organizations, because it contemplates individual and organizational aspects, covering the perception of utility, necessary sociotechnical transformations in processes, people and structures, actual use and organizational effects. As the main contribution, we proposed a framework that includes elements of translation to guide future research.
Does corporate governance affect dividend policy in India? Firm-level evidence from new indices

Purpose The purpose of this paper is to investigate the nexus between corporate governance and dividend policy of listed Indian firms. Design/methodology/approach Using new corporate governance stipulations, five new indices were constructed, namely, overall board governance index, board structure index, audit committee index, compensation committee index and nomination committee index. Using the newly developed indices, disclosure index and different firm-specific control variables, different panel Logit and Tobit regression models were estimated for 482 non-financial and non-utility listed firms during 2006–2017. Also, before the econometric analysis, mean difference test was conducted to examine the differences in dividend behaviour and corporate governance practices during pre- and post-Companies Act, 2013 and between payers and non-payers. Findings The overall evidence suggests that the firms having stronger corporate governance tend to pay higher dividends suggesting that the firm’s propensity to pay dividends increases with the improvement in corporate governance standards. Among the corporate governance indices board structure, audit committee and disclosure norms show a significant and positive relationship, whereas compensation committee and nomination committee show a positive but insignificant relationship with dividend policy. Control variables mostly had the expected impact on the dividends of the firms. Practical implications This study suggests that the establishment of the strong and effective corporate governance system is desirable to mitigate the agency conflicts between managers and shareholders and limit managers’ opportunistic behaviour in dividend payout policy. Originality/value This study is one of the latest studies to use several newly constructed indices on corporate governance mechanism based on new stipulations which bring new evidence on their specific impact on the dividend policy for an emerging market economy like India.
Automatic correction of C programming exercises through Unit-Testing and Aspect-Programming

We present a framework for the automatic testing of C Programming assignments that is based on Unit tests and Aspect programming. Students are required to implement a set of C functions and are given each function’s prototype. Teachers are required to write unit tests for each function, a ”reference implementation” of each function and a feedback message for each test failed. The system applies the unit tests to the code and replaces a failing function with the corresponding reference implementation to test also functions depending on the failed one. We are developing the system while testing it on the homeworks submitted for two courses: ”Programming 2” and ”Programming Laboratory”, delivered during the second term of first year of our Computer Science MS degree. We present the design of the system and the issues solved so far to test 4 homeworks (a total of 186 tests run over 28 implemented functions).
Talk to me: Exploring user interactions with the Amazon Alexa

Amazon Alexa is a voice-controlled application that is rapidly gaining popularity. We examined user interactions with this technology, and focused on the types of tasks requested of Alexa, the variables that affect user behaviors with Alexa, and Alexa’s alternatives. The data about Alexa usage were collected from 19 participants via the online questionnaire and diary methods over the course of several days. The results indicate that across all age groups, Alexa was primarily used for checking weather forecasts, playing music, and controlling other devices. Several participants reported using Apple Siri and Google Now applications in addition to Alexa for similar purposes except for controlling other devices. Alexa uses over the weekends were more frequent than on weekdays, but its overall usage tended to decrease over time. The users reported being satisfied with Alexa even when it did not produce sought information, suggesting that the interaction experience is more important to the users than the interaction output. More work is required to understand whether users treat Alexa and similar voice-controlled applications as primarily a traditional information retrieval system, a casual leisure system, a control interface for smart home devices, or, simply, a new toy.
Effectiveness of social media marketing on enhancing performance: Evidence from a casual-dining restaurant setting

Social media sites serve as lead generators for achieving marketing communication and raising brand awareness for casual-dining restaurant firms. This study attempts to measure social media engagement across different social networking sites (SNSs) and promotional activities for the casual-dining restaurant industry. This study also explores the influence of the dimensionality of social media engagement on the performance of casual-dining restaurants. The findings show that the metrics of social media engagement are different across channels and promotional activities. The results also reveal that these metrics have significant positive impacts on casual-dining restaurant performance. Pragmatically, the findings provide an assessment that enables casual-dining restaurant marketers to select the most effective SNSs and implement the most appropriate promotional activities, given the limited marketing budget of small and medium-sized casual-dining restaurants.
Experience maketh the mind? Top management teams’ experiential background and cognitive search for adaptive solutions

The adaptive strategies of firms depend on executives’ forward-looking cognitive search. We examine how cognitive search is affected by the formative experiences of the executives making up a firm’s top management team (TMT). Drawing on research on adaptive search, cognition, and the upper echelons, we examine the extent to which educational level, diversity of functional expertise, and the length of industry tenure of TMT members will be associated with whether cognitive search centers more on proximal or on distal solutions. Analysis of 10 years of panel-data from US companies shows that whereas a TMT’s educational level does not seem to affect cognitive search, diversity of functional expertise does so, as predicted, and industry tenure does so in a manner we had not fully anticipated. Additional analysis also shows that whether cognitive search is proximal or distal is associated with whether firms enter into related or unrelated new product-markets. The article discusses the implications of these findings.
Sustainable Agritourism in Thailand: Modeling Business Performance and Environmental Sustainability under Uncertainty

This study aims to identify the causal attributes of sustainable agritourism in Thailand. Agritourism is a systematic approach based on farm diversification for tourism purposes. Agritourism is usually assessed with qualitative information. However, the assessment of agritourism attributes involves considering the interrelationships among the attributes. Prior studies on sustainable agritourism do not identify and address interrelated attributes using qualitative information. This study applies the Delphi method to identify a set of valid attributes. Moreover, this study applies triangular fuzzy numbers to transform the qualitative information into comparable values and uses a decision-making trial and evaluation laboratory to identify the interrelationships among the attributes in the causal model. The results show that sustainable business performance and rural economic conditions are the key drivers of environmental sustainability. This result suggests that the attributes that may potentially stimulate sustainable agritourism are the development and implementation of an agritourism-specific plan, the development of a local business value chain, and government-led tourism promotion.
Public Sector Employees' Experiences Executing Strategic Management in a Political Environment

Public Sector Employees’ Experiences Executing Strategic Management in a Political Environment by Aarion L. Franklin MBA, University of Maryland University College, 2007 BA, University of Maryland, 1998 Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Management Walden University May 2019
Combining GF-2 and RapidEye satellite data for mapping mangrove species using ensemble machine-learning methods

ABSTRACT Mangrove forests are important constitutions for sustainable development of coastal ecosystems, and they are often mapped and monitored with remote sensing approaches. Satellite images allow detailed studies of the distribution and composition of mangrove forests, and therefore facilitate the management and conservation of the ecosystems. The combination of multiple types of satellite images with different spatial and spectral resolutions is helpful in mangrove forests extraction and mangrove species discrimination as it reduces sampling workload and increases classification accuracies. In this study, the 1.0-m-resolution Gaofen-2 (GF-2) and the 5.0-m-resolution RapidEye-4 (RE-4) satellite images, acquired in February 2017 and November 2016 respectively, were used with ensemble machine-learning and object-oriented methods for mangroves mapping at both the community and species levels of the Qi’ao Island, Zhuhai, China. First, the mangroves on the island were segmented from the GF-2 image on a large scale, and then they were extracted combining with their digital elevation model (DEM) data. Second, the GF-2 image was further processed on a fine scale, in which object-oriented features from both the GF-2 and RE-4 images were extracted for each mangrove species. Third, it is followed by the mangrove species classification process which involves three ensemble machine-learning methods: the adaptive boosting (AdaBoost), the random forest (RF) and the rotation forest (RoF). These three methods employed a classification and regression tree (CART) as the base classifier. The results show that the overall accuracy (OA) of mangrove area extraction on the Qi’ao Island with the auxiliary data, DEM, achieves 98.76% (Kappa coefficient (κ) = 0.9289). The features extracted by the GF-2 and RE-4 images were shown to be beneficial for mangrove species discrimination. A maximum improvement in the OA of approximately 8% and a κκ of approximately 0.10 were achieved when employing RoF (OA = 92.01%, κ = 0.9016). Ensemble-learning methods can significantly improve the classification accuracy of CART, and the use of a bagging scheme (RF and RoF) is shown as a better way to map mangrove species than adaptive boosting (AdaBoost). In addition, RoF performed well in mangrove species classification but it was not as robust as the RF, whose average OA and κκ were 80.59% and 0.7608, respectively, while the RoF’s were 77.45% and 0.7214, respectively, in the 10-fold cross-validation.
Removal of salt and pepper noise from images using hybrid filter (HF) and fuzzy logic noise detector (FLND)

Image restoration is the practice of removing or reducing the degradation. Degradation occurs due to image acquisition, out of focus, and image transfer over the internet. Image restoration tries to recover images that have been degraded. The restored image is not an original image; it is an approximation of the actual image. Image restoration is the preprocessing task done before other image processing tasks such as image segmentation, image compression, etc. This research implements a restoration algorithm using hybrid filter (HF) and fuzzy logic noise detector (FLND) for the removal of impulse noise from images. The proposed technique consists of two stages. In the first stage, we split the image into a number of windows, and each window applies the hybrid filter (Mean Filter and Adaptive Median Filter). The output from the first stage is given as an input to the second stage in which FLND generates the fuzzy rules, the rules used to classify the pixel as noisy and noise free. If the pixel is considered as noisy pixel, then it is restored by median filter. The noise‐free pixels were left unchanged. Increasing the (peak‐signal‐to noise ratio) PSNR of an image is the foremost objective of this research work. The proposed method is evaluated on standard lena image and the PSNR value at different noise level are presented in this research paper. The results are compared with Mean Filter (MF), Adaptive Median Filter (AMF), Weighted Median Filter (WMF), Decision‐Based Filter (DBF), Weighted Fuzzy Mean Filter (WFM), Adaptive Fuzzy Mean Filter (AFM) and Wavelet Filter (WF). The drawbacks in existing methods are rectified in our proposed method. It suppresses noise, protects image characteristics, and also increases visual quality and PSNR value.
Island Biodiversity in the Anthropocene

Biodiversity on marine islands is characterized by unique biogeographic, phylogenetic and functional characteristics. Islands hold a disproportionate amount of the world's biodiversity, and they have also experienced a disproportionate loss of it. Following human contact, island biodiversity has sustained negative human impacts increasing in rate and magnitude as islands transitioned from primary through secondary to tertiary economies. On islands, habitat transformation and invasive non-native species have historically been the major threats to biodiversity, and although these threats will continue in new forms, new impacts such as human-induced climate change and sea-level rise are emerging. Island biodiversity is changing with some species going extinct, others changing in abundance, non-native species becoming a part of many ecosystems, and humans shaping many ecological processes. Islands thus are microcosms for the emerging biodiversity and socioecological landscapes of the Anthropocene. Islands will require new strategies for the protection and restoration of their biodiversity, including maintaining biological and cultural heritage through regenerative practices, mainstreaming biodiversity in cultural and production landscapes, and engaging with the reality of novel ecosystems.
Existential Vacuum of High School Students as a Defect of Socialization in the Context of the War for Consciousness

The article analyzes the victimization rate of NSTU students as possible victims of the war for consciousness. Our investigation is based on Ammon's I-structural test. Taking into account the results of testing students, the rationale for the creation of a psychological university service and practical recommendations are given. Keywords— war for consciousness, identity, existential vacuum, competencies, I-structure test, Aggression, Anxiety / Fear, External I-delimitation, Internal I-delimitation, Narcissism and Sexuality
Multiculturality as an Antecedent to Work Well-being and Work Passion

Within the workplace, promoting positive feelings in regard to work well-being and work passion has become essential to an increase in health, motivation, and consequently to an increase in productivity. This study aims to assess cultural values, cultural intelligence and multicultural personality as predictors of work well-being and work passion. Based on a sample of 240 workers aged 20 to 64 years (M = 36.78, SD = 10.22), multiple linear regression was carried out. The results of the multiple linear regression analysis show that the dimensions of power distance and uncertainty avoidance have a negative influence on work well-being and work passion, whereas emotional stability is the dimension with the highest predictive value for both constructs. On the other hand, cultural intelligence has no significant predictor effect. As organisations must invest in enhancing work well-being and work passion, the identification of their predictors is of the utmost importance.