Miracle-dz/UniFAR-FTUs huggingface dataset:
When the party’s over: political blame attribution under an electoral authoritarian regime

ABSTRACT Which reaction takes the upper hand: a “rally around the flag,” born of geopolitical success, or grievance over economic misfortune? By means of a survey experiment, we aim to explore the mechanisms of blame and credit when a rally around the flag coincides with a major economic downturn, and we estimate the effects of the Crimean events and the economic crisis on how Russians assess the performance of federal political institutions. Our findings suggest that economic hardships are attributed exclusively to the government and the State Duma, while it is only the president who benefits from the rally around the flag. Moreover, the president receives an additional benefit when the “patriotic unity” priming meets the “economic hardship” priming, thereby resulting in a double rally around the flag effect. This suggests that the president stands apart from state institutions when responsibility is assigned, and he is the only one to enjoy national consolidation around him, which is further reinforced by poor economic conditions. Spotlighting the president increases his popularity and consequently increases the costs of political divides, while the legislature and the government can be exploited as scapegoats for policy failures.
The Impacts of Minimum Trading Units and Tick Size Changes on Bid-ask Spread, Depth, and Trading Volume: Evidence from the Indonesia Stock Exchange

Purpose – This research aims to analyze the differences in the bid-ask spread, depth, and trading volume after a new tick size and minimum trading unit policy were imposed by the Indonesian Stock Exchange (IDX) on January the 6th, 2014. <br><br>Design/Methodology/Approach – This research is exercised on the three variables of liquidity, i.e. the bid-ask spread, the depth, and the trading volume. This research used a paired difference test to measure the impact before and after the policy was imposed. <br><br>Findings – The results showed that the smaller the tick size, the greater the average decrease of the bid-ask spread, ask depth, and bid depth, but the trading volume did not show a significant average difference. <br><br>Research Implications – The tick size reduction was consistent and supported the previous research from different countries. The bid-ask spread, ask depth, and bid depth significantly decreased, and the trading volume had a tendency to increase as well, although it was not significant. <br><br>Results are aimed at the IDX and Bapepam as additional information related to the changes that occurred as a result of the implementation of the new policy in stock trading. Investors can use the information from this study to make investment decisions.
Hierarchical Attribute Based Revocable Data Access Control For Multi Authority Cloud Storage

: Distributed computing is rising colossally because of its points of interest and the adaptable stockpiling administrations given by it. Because of this the quantity of clients has come to at the top. Clearly the clients will be sharing the touchy information through the cloud. Also, the client can't trust the untrusted cloud server. Subsequently the information get to control has turned out to be exceptionally testing in distributed storage framework. In existing work revocable information get to control plan is proposed for multi-expert distributed storage frameworks which bolsters the get to control in light of the specialist control. The approved clients who have qualified traits given by different specialists can get to the information. However, it couldn't control the assaults which can happen by the approved client who are not having qualified characteristics. In this work we propose another calculation Improved Security Data Access Control which Overcomes the issue exists in the current work. And furthermore incorporate the effective characteristic renouncement technique for multi specialist distributed storage.
The impact of supply chain risks on supply chain performance: Empirical evidence from the manufacturing of Malaysia

Nowadays, competition has shifted from organization to industry level so any disruption can not only disturb organization but also affect the whole industry. Although Malaysia is known from palm oil and rubber manufacturing sector has the highest growth rate (7.1%) and the second contributor to GDP and employer. After extensive literature view, it has found that various disruptions have been reported that not only disrupt Malaysian manufacturing but also a global business but there is no study available the empirically assess these risks. This is an empirical investigation and data was collected through a questionnaire distributed by systemic probability sampling to listed Manufacturing organizations listed in the Federation of Manufacturing Malaysia by emails. Final and purified data was analyzed through Structural Equational Modeling through Smart PLS. Total three types of risks were assessed namely logistic side risks, collaboration side risks, and finance side risks. It has been found that although all three types have a negative impact on supply chain performance only logistic side risks is effecting significantly. This study will help managers to understand how supply chain risks are affecting and what type of risks they should be more aware. Furthermore, various approaches can be proposed for mitigation but there is also a need to verify these approaches for Malaysia.
Free Convection in a Caterpillar Shaped Triangular Enclosure Filled with Different Nanofluids

Received: 7 January 2018 Accepted: 17 July 2018 A numerical work is conducted for the free convection in a right triangular cavity filled with water-based nanofluids. The bottom wall is in a caterpillar wavy shape which is assumed as a hot wall whereas the rest walls of the enclosure are considered as a cold wall. Governing equations of the problem are discretized through the finite volume method. The present study is undertaken to appraise the effect of the constrained parameters i.e. various types of nanofluids (TiO2, CuO, and Al2O3), volume fractions of thenanoparticles and Rayleigh number (Ra=10-10). The higher augmentation in the rate of heat transfer is observed for the Al2O3-water-based nanofluid for each Rayleigh number.
Data Analytics for Better Informed Technology & Engineering Management

Many fields are managing better by incorporating advanced data analytics—e.g., even sports such as baseball. We illustrate with a novel set of indicators that distinguish cutting edge R&D activity to provide competitive technical intelligence on “who's doing what, where, and when. ” Our aim is to stimulate your thinking about what data analytics could help you achieve your technology management goals more effectively.
Food tourism value: Investigating the factors that influence tourists to revisit

Food consumption is an important notion in the hospitality literature. Although its role in gaining visitors’ satisfactory travel experience and in affecting tourists’ experiences of a destination is acknowledged, the impact of travelers’ local food consumption value on tourist behavior remains an underdeveloped topic. This study investigated the effect of tourists’ local food consumption value on their future behaviors by focusing on their destination food image and their attitudes toward local food. The data were collected from 891 tourists in Shiraz, Iran, through a survey-based method using structured questionnaires. Partial least square structural equation modeling was used to test the model proposed. Results indicated that taste/quality value, health value, price value, emotional value, and prestige value left a positive effect on tourist’ attitude toward local food. While destination food image did not influence the intention to visit the destination for food tourism, it positively affected the intention to recommend local food. The observations revealed marketing strategies substantially explored in the study.
Agile practices adoption with Lean in growing entrepreneur companies

There are three popular terms in the software development industry recently, they are Agile, Lean and Entrepreneurs. Agile is an approach in which requirements and solutions for the products evolve through short cycles. Entrepreneur can be defined as the process of designing, launching and running a new business based on potential opportunities and often is a small business. In recent years, entrepreneurs firms follow Lean concepts in Information Technology industry are trying to adopt Agile methodologies because they believe it helps them to avoid failures and grow faster. However, when growing they often face problems to maintain the agility which they have when they were smaller. The aim of this study is to find out approaches and lessons which can be used to adopt Agile practices in young expanding firms. In addition, those methods were compared to those from large-scale Agile frameworks to give conclusions on adoption approaches. Three interviews were conducted with the high-level managers of target case companies and two of them based in Oulu, Finland and one located in Hanoi, Vietnam. All of the companies which joined the research are working software development area but each of them has a different pathway and side services. They also share are similar numbers of employees above 9 and smaller than 30, which is the reason that they were chosen. Another reason for this selection is that all of them called themselves a Lean start-up or following core concepts of it. On another hand, large-scale Agile frameworks were introduced as an approach for big organizations to adopt Agile practices. In this research, lessons from those frameworks were proposed as suggestions and a new point of view for maintaining agility. The results of the research can be concluded that focusing on customer requirements, forming small Agile teams and giving more freedom to members are three practices that companies in the interview are using. Furthermore, from designed frameworks, it showed that having dynamic teams, enhancing the value of each iteration and improving the training process are ways to improve the adoption process in large firms.
You’ll Never Walk Alone: Why We Need a Supply Chain Practice View on Digital Procurement

Abstract This paper conceptualizes digital procurement readiness as a dyadic construct and introduces the supply chain practice view (SCPV) as a theoretical lens that can help guide future research on digital procurement. We build on a literature review and on dyadic, explanatory case studies to provide a nuanced understanding of how the digital readiness of supply chain partners—on both sides of the dyad—needs to co-evolve for the implementation of digital procurement practices. Specifically, we outline how the SCPV can serve as both a holistic and a supply chain-specific framework for future research on the following: 1) the antecedents that help explain why supply chain partners adopt inter-organizational digital procurement practices, and 2) the relational performance outcomes derived from their use. For managers, this study implies the need to explicitly consider interactions with and influences of supply chain partners in their quest to rapidly and effectively digitalize procurement.
The Effect of Mortgage Debt on Consumer Spending: Evidence from Household-level Data

We explore the relationship between owner-occupier mortgage debt and spending using detailed panel data on Australian households. We find evidence consistent with a 'debt overhang effect' – households cut back on their spending when they have higher levels of outstanding mortgage debt. This overhang effect holds even when households' net housing wealth remains constant, implying that households reduce their spending when the gross value of both their debt and assets increases. This suggests that changes in the composition of household balance sheets affect spending, which runs counter to macroeconomic models that combine assets and liabilities into a single measure of net wealth. We find the overhang effect to be pervasive across owner-occupier households and not exclusively driven by households that are financially constrained or that have strong precautionary saving motives. We find evidence that indebted households reduce their spending by more than other households during adverse macroeconomic shocks, such as the global financial crisis, but the negative effect of debt is also pervasive at other times.
The effect of game-based learning on vocabulary acquisition for middle school English language learners

English language learners (ELLs) in America face huge challenges in middle school. Although many ELLs quickly assimilate into the American culture and develop their social language rapidly, they continue to struggle academically. One reason ELLs find themselves behind their native English-speaking peers is their lack of academic vocabulary knowledge. Vocabulary can be learned both implicitly with extensive reading and explicitly with direct and focused instruction. Research has shown that implicit vocabulary learning is not as effective with ELLs and the need for effective explicit learning strategies is apparent. This study revealed no statistically significant difference in academic vocabulary scores when a game-based curriculum was introduced compared to traditional workbook lessons. Because games are popular with adolescents in today’s society, teachers should consider bringing this affinity for gaming into the classroom to increase academic learning and success.
A review on management accounting change. What's next?

The interest of researchers on the issue of changes in management accounting practices has increased over the years. Many works have been published that widely vary according to the nature of the business context in which change is implemented, the theoretical approach used, research focus and research methods adopted. The general picture which emerges from these contributions is that Management Accounting Change (MAC) is a complex topic. This is why it still lacks a clear and agreed definition and there’s no consensus on which is the most appropriate paradigm to study it. Based on this evidence, the aim of this study is to provide a deep understanding of MAC phenomenon, conducting a scoping study based on papers published in both Italian and International Accounting Journals. Typologies, causes, as well as the organizational and managerial implication of change are analyzed. Finally, some suggestions for further studies are presented.
From Employment to Engagement? Stable Jobs, Temporary Jobs, and Cohabiting Relationships

Family formation has been substantially delayed in recent decades, and birth rates have fallen below the replacement rates in many OECD countries. Research suggests that these trends are tightly linked to recent changes in the labor market; however, little is know about the role played by increases in job insecurity. In this paper, we investigate to what extent the decline in the share of permanent jobs among young workers explains observed delays in age at first cohabitation and age at first child. Using French data on the work and family history of large samples of young adults, we provide evidence that access to permanent jobs has a much stronger effect than access to temporary jobs on the probability of entering a first cohabiting relationship as well as on the probability of having a first child. We find that about half of the increases in age at first cohabitation and at first child can be explained by the rise in unemployment and in the share of temporary jobs among young workers.
Global production networks: mapping recent conceptual developments

In this framing paper for the special issue, we map significant research on global production networks during the past decade in economic geography and adjacent fields. In line with the core aim of the special issue to push for new conceptual advances, the paper focuses on the central elements of GPN theory to showcase recent rethinking related to the delimiting of global production networks, underlying political-economic drivers, actor-specific strategies and regional/national development outcomes. We suggest that the analytical purchase of this recent work is greater in research that has continued to keep a tight focus on the causal links between the organizational configurations of global production networks and uneven development. Concomitantly, considerable effort in the literature has gone into expanding the remit of GPN research in different directions, and we thus engage with five domains or ‘constituent outsides’ that relate to the state, finance, labour, environment and development. We believe such cross-domain fertilisation can help realize GPN 2.0’s potential for explaining uneven development in an interconnected world economy.
Parallel FDTD simulation using Task Parallel Library (TPL)

The ﬁnite-di ﬀ erence time-domain (FDTD) is a numerical analysis technique used for solving computational electrodynamic problems. The nature of the FDTD method is that simulation of big and complicated electromagnetic ﬁeld problems requires a vast amount of computer operational memory and runtime. Parallel-processing techniques have been broadly applied to FDTD to accelerate the simulations. The parallelism of the FDTD algorithm is based on a fact that the computational domain can be divided into parts (sub-domains), and each processor in a parallel system deals with one or several sub-domains. The FDTD algo-rithm belongs to data parallelism model and can be e ﬀ ectively implemented on shared memory system architecture. The parallel FDTD method was implemented using TPL library. The Task Parallel Library (TPL) is a library for . NET that makes easy to parallelize the program using the advantages of . NET Framework. The speedup metrics of parallel FDTD algorithm were calculated and compared with Amdahl’s estimated speedup.
IMPACT OF CONSUMER SENTIMENT ON DEFENSIVE AND AGGRESSIVE STOCK RETURNS: INDIAN EVIDENCE

This paper aims to study predictive ability of consumer sentiment of individual stocks. We consider two proxies for sentiment. One is explicit (Index of Consumer Sentiment, ICS), second is implicit (Broad Market Indicator, SP contrarily no such relation exists between explicit sentiment indicator and stocks. We find causation from ICS to S&PBSE500. Both the sentiment indicators have causal relation with aggressive stocks but not with defensive stocks. Result show that only ICS has short-term predictive power of aggressive stocks. We find significant negative relation between consumer sentiment and aggressive stock returns in the following month. This implies high consumer optimism in current month results in price shrink of aggressive stocks in following month. We conclude that implicit sentiment indicator has no predictive ability of stocks and explicit sentiment indicator is able to predict only small number of aggressive stocks. We suggest investors not to follow sentiment indicators blindly because these indicators predictive ability is very limited that too with select aggressive stocks. We find aggressive stocks have high volatility and gain investor attention during optimistic and pessimistic market conditions.
Towards a Secured Authentication Based on an Online Double Serial Adaptive Mechanism of Users' Keystroke Dynamics

Password based applications are commonly used in our daily lives such as the social networks, e-mails, e-commerce, and e-banking. Given the increasing number of hacker attacks, the only use of passwords is not enough to protect personal data and does not meet usability requirements. Keystroke dynamics is a promising solution that decreases the vulnerability of passwords to guessing attacks by analyzing the typing manner of the user. Despite its efficiency in the discrimination between users, it remains non-industrialized essentially due to the tedious learning phase and the intra-class variation of the users' characteristics. In this paper, we propose a double serial mechanism to adapt the user's model over time. An important property of the proposed solution relies in its usability as we only use a single sample as user's reference during the account creation. We demonstrate that the proposed method offers competitive performances while keeping a high usability.
Spectrum allocation algorithm based on user requirements under the circumstance of advanced user existence

Since wireless spectrum is a non-renewable resource, how to improve the spectrum utilization is always the problem to be resolved by wireless communication technology. With the development of wireless communication technology, the contradiction between supply and demand for spectrum resource has been more and more intense. In this case, cognitive radio technology emerged. The traditional list-colouring algorithm aims at maximizing the number of allocated bandwidth; CSGC algorithm (Colour Sensitive Graph Colouring algorithm) is to achieve the maximum benefits of bandwidth for the cognitive users; local bargaining algorithm is an improved algorithm on time complexity based on CSGC. However, the three algorithms do not take the bandwidth demand of cognitive users into consideration. Even with the proportion allocation of CSGC algorithm, the problem of ill-considered for the bandwidth demands of cognitive users also exists, which results in irrational allocation of spectrum resources. To solve this problem, this article proposes a priority order with the consideration of cognitive users in spectrum allocation based on advanced users.
Twitter Versus the Traditional Media

In the 2016 U.S. presidential campaign, both the traditional media and social media platforms, like Twitter, were critical in attempts to influence voters. Prior to the 2016 presidential election, the assumption was that campaign messages sent through the traditional media are perceived as more effectual by the public than those sent via Twitter. But after the election of Donald Trump, there is now a sense that things may have changed. In this new era of American politics and campaign discourse, do campaign messages sent via Twitter resonate equally with messages sent through the traditional media? This study attempts to address this question by utilizing a survey experiment to test whether campaign messages sent using USA Today headlines were perceived as more believable and persuasive by potential voters than messages sent via Twitter. The results suggest that campaign messages about candidates sent via Twitter—regardless of the candidate of focus—resonate just as strongly with potential voters as those sent via the traditional media. This provides a potential partial explanation for the shocking rise of Donald Trump’s political fortunes.
VPPP Algorithms of Baseline Vector Estimation among Multiple Antennas

In this paper, we study the VPPP (Very Precise Point Positions) algorithm based on GR (GNSS Regression) models by using multiple antennas for estimating baseline vectors. The multiple antennas are disposed with solid geometrical distances which provide the constraints of the estimated parameters, but both antennas’ positions are unknown. By using the baseline-vector length constraints, we show the VPPP algorithms based on the double-difference (DD) observables by each pair of two antennas, and apply the algorithm for estimating baseline vectors and GNSS Gyro. Finally we show the experimental results of the estimation algorithms for the baseline vectors and Euler angles.