Miracle-dz/UniFAR-FTUs huggingface dataset:
Household Heterogeneity and the Transmission of Foreign Shocks

We study the role of heterogeneity in the transmission of foreign shocks. We build a Heterogeneous-Agent New-Keynesian Small Open Model Economy (HANKSOME) that experiences a current account reversal. Households' portfolio composition and the extent of foreign currency borrowing are key determinants of the magnitude of the contraction in consumption associated with a sudden stop in capital inflows. The contraction is more severe when households are leveraged and owe debt in foreign currency. In this setting, the revaluation of foreign debt causes a larger contraction in aggregate consumption when debt and leverage are concentrated among poorer households. Closing the output gap via an exchange-rate devaluation may therefore be detrimental to household welfare due to the heterogeneous impact of the foreign debt revaluation. Our HANKSOME framework can rationalize the observed "fear of floating" in emerging market economies, even in the absence of contractionary devaluations
Options for agricultural service cooperatives in a postsocialist economy: Evidence from Romania

Almost three decades since the collapse of the socialist regime, Romania’s farm structure is characterized by a distinct dual pattern. The far majority of farms is relatively small, while a small number manages about half of the total utilized agricultural area. Most farmers face significant constraints in creating viable farm businesses. When this is the case, it can be assumed that farmers will unite and establish agricultural service cooperatives (ASCs), as has been observed in many other parts of the world. In Romania, however, as in many other postsocialist economies, farmers tend to be reluctant to form or join formal organizations of mutual assistance. Yet there are signs of change, as first ASCs have recently been established. The objectives of this contribution are twofold: First, we discuss the major obstacles why ASCs did not develop after regime change. Second, we analyze the major reasons and influencing factors why private family farmers become more open to this type of formal organization in recent years. The analysis is based on a literature review, farm statistics, and qualitative in-depth interviews with farmers in 2018.
A Trust Region Filter Algorithm for Surrogate-based Optimization

Modern nonlinear programming solvers can efficiently handle very large scale optimization problems when accurate derivative information is available. However, black box or derivative free modeling components are often unavoidable in practice when the modeled phenomena may cross length and time scales. This work is motivated by examples in chemical process optimization where most unit operations have well-known equation oriented representations, but some portion of the model (e.g. a complex reactor model) may only be available with an external function call. The concept of a surrogate model is frequently used to solve this type of problem. A surrogate model is an equation oriented approximation of the black box that allows traditional derivative based optimization to be applied directly. However, optimization tends to exploit approximation errors in the surrogate model leading to inaccurate solutions and repeated rebuilding of the surrogate model. Even if the surrogate model is perfectly accurate at the solution, this only guarantees that the original problem is feasible. Since optimality conditions require gradient information, a higher degree of accuracy is required. In this work, we consider the general problem of hybrid glass box/black box optimization, or gray box optimization, with focus on guaranteeing that a surrogate-based optimization strategy converges to optimal points of the original detailed model. We first propose an algorithm that combines ideas from SQP filter methods and derivative free trust region methods to solve this class of problems. The black box portion of the model is replaced by a sequence of surrogate models (i.e. surrogate models) in trust region subproblems. By carefully managing surrogate model construction, the algorithm is guaranteed to converge to true optimal solutions. Then, we discuss how this algorithm can be modified for effective application to practical problems. Performance is demonstrated on a test set of benchmarks as well as a set of case studies relating to chemical process optimization. In particular, application to the oxycombustion carbon capture power generation process leads to significant efficiency improvements. Finally, extensions of surrogate-based optimization to other contexts is explored through a case study with physical properties.
Dynamic generalisation from single detailed database to support web based interaction

It is believed that Web-based visualisation of spatial information could be greatly enhanced through the use of dynamic or 'onthe-fly' map generalisation. This involves dynamically deriving scaleand theme-dependent displays from a single detailed dataset, thus eliminating the need to maintain duplicate datasets at different resolutions. Dynamic generalisation also prevents the generation of cartographically-poor maps that result from the display of spatial information at a considerably different resolution from that at which it was captured. The implementation involves combining automated generalisation and symbolisation techniques together in a simple rule-base to produce a virtual map of central Edinburgh in which both the level of detail and the symbology is dynamically tailored to a user-specified scale and map theme (tourist or topographic maps). The paper explores the inherent differences between the generalisation of a virtual map and that of a paper map, and also considers issues such as those arising from the relationship between map scale, map theme and utility. The research demonstrates that it is possible to achieve effective results using a limited number of simple mechanisms, and argues that the true potential of dynamic generalisation lies in two main areas firstly, in an ability to narrowly-define the map theme, thus enhancing map clarity and more closely matching user requirements; and secondly, in using control over the map scale as a gateway to other types of map use and other themes.
The Influence of Leadership by Public University Students to the Development of Citizenship in Malaysia

As envisioned in Vision 2020, the progress and development depending on the succeed of a leader in maintaining the unity and sovereignty of the country continuously with cohesive step upon the Federal Constitution 1948 and the Principles of Rukun. Citizenship development and democratization of education is very important in ensuring the harmony and peace of a country. This process must take place properly for the benefit of all citizens to improve the country’s progress in the future. Furthermore the undergraduates is the vanguard of countries that are expected to take on trust the leadership in the future. Students play an important role as a national leader and must have a level of understanding an appreciation of democratization and obligation as citizen of Malaysia. In particular level, this study is focusing on the influence of student leadership towards development of citizenship and democratization of education among students of public university of Malaysia. The cross-sectional survey method id applied in the process of collecting data which involve Student Leadership questionnaire which is formed by Kouzes & Posner in the year of 2007, the Development of Citizenship questionnaire formed by Musil in the year of 2003 and the Democratization Education questionnaire by Evans & Rose in 2007. 326 of students leader in the public university in Peninsula Malaysia were involved as the respondents in this research. The finding shows that there is 77.2% of the leadership practice of the Development of Citizenship and 39.6% towards the Democratization Education. The Development of Citizenship proved to act as mediator in the relationship between student leadership and democratization education. This research can be used by the nation leaders, university administration and the department of education as guidance in valuing the aspect of leadership of the nation leaders apprentice. Besides, this research can be used as a basic reference International Journal of Academic Research in Business and Social Sciences Vol. 8 , No. 11, Nov, 2018, E-ISSN: 2222-6990 © 2018 HRMARS 340 to increase various knowledge regarding leadership management based on the citizenship development and the democratization education in forming the identity of the leaders.
Implementation of Low-Cost Architecture for Control an Active Front End Rectifier

In AC-DC power conversion, active front end rectifiers offer several advantages over diode rectifiers such as bidirectional power flow capability, sinusoidal input currents and controllable power factor. A digital finite control set model predictive controller based on fixed-point computations of an active front end rectifier with unity displacement of input voltage and current to improve dynamic response has been presented in this paper. Here by using a predictive cost function and fixed-point computations, the optimal switching state to be applied in the next sampling is selected. The low-cost architecture is implemented on a FPGA platform. Designed architecture is constructed based on fixed-point arithmetic with minimal functional units. The control algorithm, which is used in this architecture, is FiniteSet Model Predictive Control (FS-MPC). Compared with other controllers, this controller provides a much better dynamic performance. Finally, in order to evaluate the accuracy of the fixed-point computations several cases for various loading conditions and word lengths are verified.
Human Rights Abused? Terrorist Labeling and Individual Reactions to Call to Action

What leads individuals to be motivated to act for human rights causes? Human rights organizations (HROs) often use personal and emotional stories of the abused in order to gain the attention of individuals reading newspapers or emails directly from the organization. McEntire, Leiby, and Krain show that personal frames are most successful at increasing knowledge about a specific human rights situation and motivating individuals to act. However, HROs are not operating in a political vacuum; repressive governments often try to spin information about abuses and the abused to their advantage. This study uses an experimental approach to address how the discursive interactions between states and HROs influence individual-level support of HRO efforts. When governments respond to HRO claims by labeling the abused as a terrorist, individuals are much less likely to be spurred into certain types of action, like signing a petition, and feel differently about the specific case. Interestingly, we do not find that trust in the information provided by an HRO is harmed by being associated with someone labeled a terrorist.
Falling in love with a place because of a song: the transportation effects of music on place attachment

ABSTRACT With the growing influence of media on tourism destination marketing, this research proposes a possible psychological process of music effect on place attachment, using the narrative transportation theory. Data were collected through an online survey in China (n = 531) and analyzed using SEM. Results indicate that (1) music transportation positively affects individuals’ attachment; (2) attitude plays a partial mediating role in the relationship between music transportation and place attachment; (3) previous visits have significant moderate effects on the attitude-attachment path rather than on the transportation-attachment path or the transportation-attitude path. Theoretical and practical implications for destination marketing are provided.
What’s Really in a Deal? Evidence from Textual Analysis of M&A Conference Calls

Using a sample of 814 transcripts from 2011 to 2018, we examine information within merger and acquisition conference calls. Textual analysis reveals significant differences between the content of M&A call transcripts and both contemporaneous corporate press releases and earnings conference calls. We find participation of target executive types in M&A calls is related to payment choice and consistent with managerial incentives. Appearances of target executives are associated with a negative market reaction which is attributed to retention of these executives. We also identify a negative relation between textual sentiment and market reaction consistent with a response to higher levels of information asymmetry. Greater quantitative information, however, is positively related to the market reaction of M&A calls. We develop an M&A motive dictionary to identify financial and strategic content within call transcripts. Consistent with prior literature on merger motivation, deals with more finance (strategy) oriented words have a higher (lower) market reaction. Overall, our results show that deal-related textual analysis explains a highly significant and economically important component of gains/losses to acquirers.
The Effect of Corporate Governance on Islamic Banking Performance: A Maqasid Shari’ah Index Approach on Indonesian Islamic Banks

This study aims to provide empirical evidence on the Maqasid al-Shari’ah performance of Islamic banks in Indonesia for the period from 2012 to 2016. The Simple Additive Weighting (TSAW) is employed to obtain the performance of IBs according to the Maqasid al-Shari’ah. This study found that the Maqasid Index for Indonesia IBs within the range between 11% and 28% with only few banks achieved above 20%. The impact of SSB characteristics and board structures are then tested on the IBs Maqasid al-Shari’ah performance. Regression result indicates that SSB characteristics (SSB size, SSB cross membership, SSB Education and SSB reputation) and board structures (Board size and Board independence) have an essential role in improving the performance of IBs. The findings denote SSB with smaller size, higher portion of SSB cross membership, lesser SSB hold doctorate degree, lesser reputable scholar, more members on board of directors, and less independence non-executive directors enhance the performance of IBs. This study offers practical implication and regulators in Indonesia should set up and impose a more robust and new tool to evaluate the Maqasid al-Shari’ah performance index in order to assess how far the role of IBs have contributed to the society. This will help all stakeholders to have informed decision which not only concentrates on performance based on financial ratios but also the entire dimensions of IBs that reflect the main purpose of IBs.
A Hierarchical multi-input and output Bi-GRU Model for Sentiment Analysis on Customer Reviews

Multi-label sentiment classification on customer reviews is a practical challenging task in Natural Language Processing. In this paper, we propose a hierarchical multi-input and output model based bi-directional recurrent neural network, which both considers the semantic and lexical information of emotional expression. Our model applies two independent Bi-GRU layer to generate part of speech and sentence representation. Then the lexical information is considered via attention over output of softmax activation on part of speech representation. In addition, we combine probability of auxiliary labels as feature with hidden layer to capturing crucial correlation between output labels. The experimental result shows that our model is computationally efficient and achieves breakthrough improvements on customer reviews dataset.
Optical beam classification using deep learning: a comparison with rule- and feature-based classification

Deep-learning methods are gaining popularity because of their state-of-the-art performance in image classification tasks. In this paper, we explore classification of laser-beam images from the National Ignition Facility (NIF) using a novel deeplearning approach. NIF is the world’s largest, most energetic laser. It has nearly 40,000 optics that precisely guide, reflect, amplify, and focus 192 laser beams onto a fusion target. NIF utilizes four petawatt lasers called the Advanced Radiographic Capability (ARC) to produce backlighting X-ray illumination to capture implosion dynamics of NIF experiments with picosecond temporal resolution. In the current operational configuration, four independent short-pulse ARC beams are created and combined in a split-beam configuration in each of two NIF apertures at the entry of the pre-amplifier. The subaperture beams then propagate through the NIF beampath up to the ARC compressor. Each ARC beamlet is separately compressed with a dedicated set of four gratings and recombined as sub-apertures for transport to the parabola vessel, where the beams are focused using parabolic mirrors and pointed to the target. Small angular errors in the compressor gratings can cause the sub-aperture beams to diverge from one another and prevent accurate alignment through the transport section between the compressor and parabolic mirrors. This is an off-normal condition that must be detected and corrected. The goal of the off-normal check is to determine whether the ARC beamlets are sufficiently overlapped into a merged single spot or diverged into two distinct spots. Thus, the objective of the current work is three-fold: developing a simple algorithm to perform off-normal classification, exploring the use of Convolutional Neural Network (CNN) for the same task, and understanding the inter-relationship of the two approaches. The CNN recognition results are compared with other machine-learning approaches, such as Deep Neural Network (DNN) and Support Vector Machine (SVM). The experimental results show around 96% classification accuracy using CNN; the CNN approach also provides comparable recognition results compared to the present feature-based off-normal detection. The feature-based solution was developed to capture the expertise of a human expert in classifying the images. The misclassified results are further studied to explain the differences and discover any discrepancies or inconsistencies in current classification.
Determinants of the Usage of Management Accounting Practices in Small and Medium Sized Enterprises Operating in Egypt-An Exploratory Study

This study aims to respond to the recent call for more research, investigating the applicability of management accounting practices (MAPs), in small and medium sized enterprises (SMEs), particularly those operating in developing economies. Accordingly, stemming from escalating importance of SMEs in the development of the Egyptian economy, this study employs a questionnaire, to collect information about the extent of usage of five MAPs (namely, cost accounting systems, budgeting systems, financial and non-financial performance evaluation tools, decision support systems, and strategic management accounting systems), by SMEs that are listed on the Nile Exchange (NILEX), and those operating in Gamasa Industrial Zone, at Dakahlia Governorate. Additionally, the study questionnaire investigates the main determinants of usage of MAPs by SMEs operating in Egypt. The study results suggest that MAPs are employed by Egyptian SMEs at varying degrees. The reliance on advanced MAPs is not as common as traditional ones. However, employing advanced MAPs by some SMEs is a good sign that there is an awareness among accountants and owners in such SMEs about the types and uses of different MAPs. On the other hand, results generated through regression analysis, indicate that the extent of usage of MAPs is significantly and positively influenced by owner/manager belief in the importance of MAPs, listing status, company size, SME industry, and employment of technology within the firm. These results lend support to the contingency theory. Accordingly, the study made a number of recommendations including increasing awareness about the advantages of using MAPs among owners of SMEs and the need to provide training to inform them about management accounting different practices and uses of each, as well as the necessity of reviewing and developing management accounting modules that are taught by Accounting professors at Egyptian universities. On the other hand, the findings of this study could be considered as a starting point for further future research, targeting a greater number of Egyptian SMEs, as well as other MENA developing economies.
Cerrado Mineiro Region D.O. Mark: Internationalization Strategy

The specialty coffee market has been increasing consistently with growth rates above the traditional markets. The number of consumers who are willing to pay higher prices for high quality coffee has increased in recent years. The high-end independent coffee shops, known as HEICS, had spread all over the big cities such as New York, Shanghai, London and Berlin. Also, it’s intense the rivalry between world producers to positioned its product as high quality coffee. Colombia coffee has been a relevant marketing case demonstrating the power of country origin image. Brazil, instead, has a powerful image as world leader coffee producer but not necessarily connected with high quality. Cerrado Mineiro Region (CMR) and its Designation of Origin (D.O.) mark could be a starting point to change this scenario. The article presents the CMR D.O. mark in the perspective of its internationalization process. CMR was the first coffee region in Brazil to obtain the Indication of Origin in 2005 and the first region in the world to issue a D.O. seal for green coffee as well for roasting coffee in 2013. In 2017, there were 57 brands using the D.O. seal in their coffee packages, including one American roaster selling at the retailer Wholefoods.
Risk Assessment of Pedestrian Accident Area Using Spatial Analysis and Deep Learning

The purpose of this study is to construct the spatial characteristics of pedestrians' accident points as learning materials and to develop a model for deep learning them and to predict the risk of similar areas. In order to construct learning materials for pedestrian accident points, the characteristics of geometric factors related to pedestrian accidents at the accident points were quantitatively analyzed through spatial analysis. As a result of the study, in the analysis of the deep learning pattern, the prediction results could be improved by changing the middle layer and adjusting the parameters. It is expected that this result will contribute to lowering the accident rate of pedestrians by preparing measures for high accident rate points by reviewing vulnerable traffic accident sites in the future.
Delicate Hybrid Gift

A myriad of digital files such as digital photos, music tracks, and illustration images are exchanged through digital devices. Some are intentionally given as a gift for a gesture of good relationship, but they often get dismissed from the receiver’s attention due to many drawbacks of digital materials including intangibility. Gifts are realized in various forms such as artefacts, food, and hospitality, which embody multiple layers of functions and meanings that frame our social interactions. In this regard, it is questionable whether the digital gifts are able to express the sense of “gift-ness” from the outset. If doubtful, can we reform the method of the gift exchange to be distinct from mere file exchange? Building on the basis of literature in the gift exchange, this paper delivers design insights in a series of interactive prototypes to depict implications of our prior study. Prototypes are purposely designed to highlight the ephemerality of the unwrapping experience to employ in digital gifting. We demonstrate the Research Through Design practice that comprises of framing the problem space, prototyping the artefacts, and probing with potential users. Moreover, we discuss how tangibly wrapped digital gifts are appropriate in retaining the wider social recognition about the gift and gifting.