Miracle-dz/UniFAR-FTUs huggingface dataset:
The dialectics of Japanese overseas tourists: transformation in holiday making

This research examines transformational process of tourist experience in the context of fast changing Japanese outbound tourism. The Western perspective of this market is predominantly that of organized mass tourists. However, as the market matures, a diverse style of overseas holiday making among the Japanese becomes increasingly evident: more independent and versatile tourists have recently emerged. A qualitative approach based on the constructivist perspective was chosen because a standardized survey research was recognized as being neither able to reveal the complex and interwoven processes and mechanisms of such transformation nor an evolutionary scenario of the Japanese outbound market. Semistructured interviews were conducted with 17 Japanese citizens who had holidayed to Britain. Thematic coding and narrative analysis were applied to the interview data to identify essential thematic domains for understanding critical factors that have affected their transformation of holiday making. It was recognized that the Japanese tourist lives through a dialectical-optimizing transformational process of holiday making in order to seek an optimal holiday experience. Collective changes and recent trends in Japanese outbound tourism may reflect an aggregation of such an individual�s transformational process.
Privatising the forests

Does privatisation have a role in world forestry sustainable management? Is privatisation policy valid for the forestry sector? This paper is aimed to the identification of opportunities and risks of forests privatisation in developing countries. Given the above background, privatisation may be defined as the problem of delimiting the extent of what is privately and what is publicly owned by creating social institutions to regulate the distribution of contingent rights and responsibilities. These social institutions include specific arrangements to transfer property rights (such as explicit or implicit auction mechanisms), as well as rules and regulations concerning the extent and the mode in which the rights may be exercised (the "governance" of the privatisation process). The evidence shows that, if done right, the privatisation (of resources and productive processes) produces benefits of economic efficiency and innovation. Because of its world-wide importance and prominent place among natural resources, privatisation of forests appears a research issue of great potential significance.
Tuberous Sclerosis Complex and Epilepsy: Recent Developments and Future Challenges

Summary: Tuberous sclerosis complex (TSC) is a congenital syndrome characterized by the widespread development of benign tumors in multiple organs, caused by mutations in one of the tumor suppressor genes, TSC1 or TSC2. About 80% of affected patients have a new mutation, and the remaining 20% have inherited a TSC gene mutation from a parent. The disorder affects approximately 1 in 6000 individuals. Cortical tubers are the neuropathological hallmark of TSC. The most common neurological manifestations of TSC are epilepsy, mental retardation, and autistic behavior. Epilepsy occurs in up to 80–90% of patients and is often intractable, with a poor response to anticonvulsant medications.
Data distribution platform for multimedia mobile applications

The new mobile access solutions are more valuable especially due to multimedia applications available anytime and anywhere. A problem is that the user needs to manage not only his own data but also the terminal limited memory and the available networks in conditions of a high terminal and network diversity, offering different quality for different prices. In this paper, we propose a platform that helps the user to optimize data management by data balancing between a mobile client and a fixed server. The goals are: increase the data availability, reduce the transport costs and duration and avoid filling the entire terminal memory. The decisions are made by a neural-fuzzy expert system.
A Simple Controlled All-Optical on/off Switch Using Gain Modulation in Single Mode FP-LD

A novel and simple controlled all-optical on/off switch using the gain modulation in a single-mode Fabry-Pérot laser diode (SMFP-LD) is demonstrated. The working principle of the proposed on/off switch is explained and the experimental results with 10 Gb/s data signal are presented. The 10 Gb/s data signal is switched on and off with a 350 MHz control signal. The extinction ratio of 15.6 dB is observed at the output port with a 2 dB power difference between the control signal and input signal. We measured the rising and falling time of the switch output as 48 and 59 ps, respectively.
Weighted Abstract Dialectical Frameworks

Abstract Dialectical Frameworks (ADFs) generalize Dung's argumentation frameworks allowing various relationships among arguments to be expressed in a systematic way. We further generalize ADFs so as to accommodate arbitrary acceptance degrees for the arguments. This makes ADFs applicable in domains where both the initial status of arguments and their relationship are only insufficiently specified by Boolean functions. We define all standard ADF semantics for the weighted case, including grounded, preferred and stable semantics. We illustrate our approach using acceptance degrees from the unit interval and show how other valuation structures can be integrated. In each case it is sufficient to specify how the generalized acceptance conditions are represented by formulas, and to specify the information ordering underlying the characteristic ADF operator. We also present complexity results for problems related to weighted ADFs.
Endogenous MHC Class II Processing of a Viral Nuclear Antigen After Autophagy

CD4+ T cells classically recognize antigens that are endocytosed and processed in lysosomes for presentation on major histocompatibility complex (MHC) class II molecules. Here, endogenous Epstein-Barr virus nuclear antigen 1 (EBNA1) was found to gain access to this pathway by autophagy. On inhibition of lysosomal acidification, EBNA1, the dominant CD4+ T cell antigen of latent Epstein-Barr virus infection, slowly accumulated in cytosolic autophagosomes. In addition, inhibition of autophagy decreased recognition by EBNA1-specific CD4+ T cell clones. Thus, lysosomal processing after autophagy may contribute to MHC class II–restricted surveillance of long-lived endogenous antigens including nuclear proteins relevant to disease.
Mitochondrial dysfunction disrupts trafficking of Kir4.1 in spiral ganglion satellite cells

The inward‐rectifier K+ channel Kir4.1 is responsible for maintaining cochlear homeostasis and restoring neural excitability. The large‐conductance calcium‐activated K+ channel (BKCa) plays a key role in phase locking signals in the mammalian inner ear. To evaluate the influence of mitochondrial dysfunction on the expression and subcellular localization of these channels, 3‐nitropropionic acid (3‐NP) was administered to rat round window membranes for 30 min. Auditory brainstem response was measured both before and 2 hr after 3‐NP administration. Immunofluorescent confocal microscopy was used to measure the expression and subcellular localization of Kir4.1 and BKCa. Alexa Fluor 568‐labeled bovine serum albumin (BSA) was applied to round window membranes as a tracer to explore the cochlear distribution of drug delivery and was detected in the lateral wall, spiral ganglion, cochlear nerve, and organ of Corti. Hearing loss of 23 (±4.4 SE) and 58 (±6.7 SE) dB developed in rats treated with 0.3 and 0.5 mol/liter of 3‐NP, respectively. BKCa was visualized in the cellular membrane and cytoplasm in the upper and middle region of inner hair cells, and it was not affected by 3‐NP. Kir4.1 was detected in intermediate cells of the stria, Deiter's cells, and spiral ganglion satellite cells. Kir4.1 failed to reach the perineural cytoplasm of the satellite cells after 3‐NP treatment. The results of this study suggest that mitochondrial dysfunction disrupts trafficking of Kir4.1 in spiral ganglion satellite cells. © 2008 Wiley‐Liss, Inc.
Monetary Policy and the Term Spread in a Macro Model of a Small Open Economy

Using a simple single-equation approach, many studies have shown that the term structure of interest rates or its approximation - the term spread - is a useful indicator of future inflation and/or future real economic activity. However, this paper argues that shortcomings of the single-equation approach may produce results that are biased, and that the predictive ability must be analyzed from within a model framework. We have elected to use a simple macroeconomic model of a small open economy and examine the predictive properties of the term spread from within its framework. The main contribution of this paper to the literature is threefold. First, we show that the predictive ability of the term spread is not structural but monetary-policy dependent. Second, we argue that the term spread's predictive ability with regard to future inflation (real economic activity) increases as more emphasis is placed on inflation (real economic activity) stabilization in the central bank's reaction function. Third, we show that understanding the way expectations are formed is an important prerequisite for using the term spread as an indicator. Apart from these general findings, the predictive power of the term spread is examined in the context of the Czech economy. It is shown that the term spread between one-year and three-month PRIBOR interest rates of one percentage-point indicates that agents expect inflation to be almost one percentage-point above the inflation target six quarters in the future.
Three-Dimensional Analysis of High-Resolution X-Ray Computed Tomography Data with Morpho+

Abstract Three-dimensional (3D) analysis is an essential tool to obtain quantitative results from 3D datasets. Considerable progress has been made in 3D imaging techniques, resulting in a growing need for more flexible, complete analysis packages containing advanced algorithms. At the Centre for X-ray Tomography of the Ghent University (UGCT), research is being done on the improvement of both hardware and software for high-resolution X-ray computed tomography (CT). UGCT collaborates with research groups from different disciplines, each having specific needs. To meet these requirements the analysis software package, Morpho+, was developed in-house. Morpho+ contains an extensive set of high-performance 3D operations to obtain object segmentation, separation, and parameterization (orientation, maximum opening, equivalent diameter, sphericity, connectivity, etc.), or to extract a 3D geometrical representation (surface mesh or skeleton) for further modeling. These algorithms have a relatively short processing time when analyzing large datasets. Additionally, Morpho+ is equipped with an interactive and intuitive user interface in which the results are visualized. The package allows scientists from various fields to obtain the necessary quantitative results when applying high-resolution X-ray CT as a research tool to the nondestructive investigation of the microstructure of materials.
Partial Multi-Label Learning

It is expensive and difficult to precisely annotate objects with multiple labels. Instead, in many real tasks, annotators may roughly assign each object with a set of candidate labels. The candidate set contains at least one but unknown number of ground-truth labels, and is usually adulterated with some irrelevant labels. In this paper, we formalize such problems as a new learning framework called partial multi-label learning (PML). To solve the PML problem, a confidence value is maintained for each candidate label to estimate how likely it is a ground-truth label of the instance. On one hand, the relevance ordering of labels on each instance is optimized by minimizing a rank loss weighted by the confidences; on the other hand, the confidence values are optimized by further exploiting structure information in feature and label spaces.Experimental results on various datasets show that the proposed approach is effective for solving PML problems.
Payment System Disruptions and the Federal Reserve following September 11, 2001

The monetary and payment system consequences of the September 11, 2001, terrorist attacks are reviewed and compared to selected U.S. banking crises. Interbank payment disruptions appear to be the central feature of all the crises reviewed. For some the initial trigger is a credit shock, while for others the initial shock is technological and operational, as in September 11, but for both types the payments system effects are similar. For various reasons, interbank payment disruptions appear likely to recur. Federal Reserve credit extension following September 11 succeeded in massively increasing the supply of banks’ balances to satisfy the disruption-induced increase in demand and thereby ameliorate the effects of the shock. Relatively benign banking conditions helped make Fed credit policy manageable. An interbank payment disruption that coincided with less favorable banking conditions could be more difficult to manage, given current daylight credit policies.
Why Does Fixation Persist? Experimental Evidence on the Judgment Performance Effects of Expensing Intangibles

This study shows experimentally that when individuals use information on intangibles expenditures to predict future profits, expensing (vs. capitalizing) the expenditures significantly reduces the accuracy, consistency, consensus, and self‐insight of individuals' subjective profit predictions. The experimental design allows us to eliminate several competing explanations for this apparent fixation on accounting. Subjects do not base their judgments on a nai¨ve prior belief that expensing precludes effects on future profits; a preexperiment question shows that subjects expect intangibles expenditures will affect future profits even when expensed. Moreover, subjects do not lack, or fail to use, data that would allow them to learn the exact expenditure‐profit relation. They receive data on intangibles expenditures and profits as a basis for learning, and in some respects the learning is quite successful even when intangibles are expensed; subjects' profit predictions accurately reflect the mean and standard d.
Ranks of Random Matrices and Graphs by Kevin Costello

OF THE DISSERTATION Ranks of Random Matrices and Graphs by Kevin Costello Dissertation Director: Van Vu Let Qn be a random symmetric matrix whose entries on and above the main diagonal are independent random variables (e.g. the adjacency matrix of an Erdős-Rényi random graph). In this thesis we study the behavior of the rank of the matrix in terms of the probability distribution of the entries. One main result is that if the entries of the matrix are not too concentrated on any particular value, then the matrix will with high probability (probability tending to 1 as the size of the matrix tends to infinity) have full rank. Other results concern the case where Qn is sparse (each entry is 0 with high probability), and in particular on the adjacency matrix of sparse random graphs. In this case, we show that if the matrix is not too sparse than with high probability any dependency among the rows of Qn will come from a dependency involving very few rows.
Molecular cloning of the Haemophilus influenzae gmhA (lpcA) gene encoding a phosphoheptose isomerase required for lipooligosaccharide biosynthesis

We have determined that gene HI#1181 of Haemophilus influenzae is a homolog of Escherichia coli gmhA (previously designated lpcA) (J. S. Brooke and M. A. Valvano, J. Biol. Chem. 271:3608-3614, 1996), which encodes a phosphoheptose isomerase catalyzing the first step of the biosynthesis of ADP-L-glycero-D-manno heptose. Mutations in this gene are associated with a heptoseless core lipopolysaccharide which determines an increased outer membrane permeability to hydrophobic compounds. The cloned H. influenzae gmhA restored the synthesis of a complete core in the gmhA-deleted E. coli strain chi711. Amino acid sequence comparisons of the GmhA proteins of E. coli and H. influenzae with other proteins in the databases revealed the existence of a novel family of phosphosugar a1do-keto isomerases.
Appraising shipping service quality: case of Vinalines

In shipping service realm, service quality of a carrier has been increasingly discerned as a crucial factor behind the attainment of its competitive edge and market superiority, not merely since its high service quality will increase its customers’ satisfaction, but also since its high service quality can create new values for its customers. As a result, there emerges a need for a service quality instrument with which a carrier can gaze at themselves. A question is whether the SERVQUAL instrument developed for other services’ industries can be utilised to gauge service quality perceptions and expectations in shipping. Predicated on a survey of 152 respondents from Vinalines’s customer companies, the study reveals that customers’ expectations of Vinalines’s shipping services were impacted by three factors: ‘reliability’, ‘empathy and responsiveness’, and ‘assurance’.
3D human behavior recognition based on spatiotemporal texture features

Nowadays, more and more activity recognition algorithms begin to improve recognition performance by combining the RGB and depth information. Although, the space-time volumes (STV) algorithm and the space-time local features algorithm can combine the RGB and depth information effectively, they also have their own defects. Such as they need expensive computational cost and they are not suitable for modeling nonperiodic activity. In this paper, we propose a novel algorithm for three dimensional human activity recognition that combines spatial-domain local texture features and spatio-temporal local texture features. On the one hand, in order to extract spatial local texture features, we mix the RGB and depth image sequence which have been applied with ViBe (Visual Background extractor) and binarization operator. Then we obtain the RGB-MOHBBI and depth-MOBHBI respectively and perform intersect operation on them. Afterwards, we extract LBP feature from the mixed MOHBBI to describe spatial domain feature. On the other hand, we follow the same background subtraction and binarization method to process the RGB and depth image sequences and get the spatial-temporal local texture features. And then, we project the three dimensional image volume on plane X-T and plane Y-T to get the spatio-temporal behavior volume change image to which we apply LBP operator to extract features that can represent human activity feature in spatio-temporal domain. At last, we combine the two local features that are extracted by LBP algorithm as one integrated feature of our model final output. Extensive experiments are conducted on the BUPT Arm Activity Dataset and the BUPT Arm And Finger Activity Dataset. The experimental results demonstrate the algorithm we proposed in this paper can make up for the deficiency of traditional activity recognition algorithms effectively and provide excellent experiment results on different databases of various complexities.
Understanding and measuring Social Capital

The importance of social capital for sustainable development, is by now well recognized. Anthropologists, sociologists, political scientists, and economists have in their own ways, demonstrated the critical role of institutions, networks, and their supporting norms and values, for the success of development interventions. This success often hinges on accurate assessments of social capital in target communities. But the nature, and impact of social capital - the institutions, relationships, attitudes, and values that govern interactions among people - are not easily quantified. "Understanding and Measuring Social Capital" provides a conceptual review, and measurement tools, in a form readily available for development practitioners. The book discusses the respective value of quantitative, and qualitative approaches to the analysis of social capital, illustrating the discussion with examples, and case studies from many countries. It also presents the Social Capital Assessment Tool, which combines quantitative, and qualitative instruments to measure social capital at the level of household, community, and organization, drawing on multidisciplinary, empirical experiences, an application which can provide project managers with valuable baseline, and monitoring information about social capital in its different dimensions.
Mission Impossible or Paradise Regained

Gives a preliminary exploration into mission statements and their impact on nurses′ attitudes towards them. Mission statements are given much credence by top level management, as part of the thrust towards corporate identity. Only 15 per cent of nurses (from an opportunistic sample of 87) acknowledged that mission statements were directly resonant with their own practice; 75 per cent did not know the originators of their mission statements; others were vague about their organization possessing one. Mission statements are best considered here as an organization rhetoric, a facet of managerial ideology. More research is needed to evaluate critically, by case studies, the impact of mission statements, as an organizational variable on, for example, health treatment and budgeting. Semiotics and communication theories offer this opportunity.
Information Directed Sampling for Stochastic Bandits with Graph Feedback

We consider stochastic multi-armed bandit problems with graph feedback, where the decision maker is allowed to observe the neighboring actions of the chosen action. We allow the graph structure to vary with time and consider both deterministic and Erdos-Renyi random graph models. For such a graph feedback model, we first present a novel analysis of Thompson sampling that leads to tighter performance bound than existing work. Next, we propose new Information Directed Sampling based policies that are graph-aware in their decision making. Under the deterministic graph case, we establish a Bayesian regret bound for the proposed policies that scales with the clique cover number of the graph instead of the number of actions. Under the random graph case, we provide a Bayesian regret bound for the proposed policies that scales with the ratio of the number of actions over the expected number of observations per iteration. To the best of our knowledge, this is the first analytical result for stochastic bandits with random graph feedback. Finally, using numerical evaluations, we demonstrate that our proposed IDS policies outperform existing approaches, including adaptions of upper confidence bound, epsilon-greedy and Exp3 algorithms.
Product Development and the Timing of Information Disclosure Under U.S.And Japanese Patent Systems

This paper examines the consequences of the differences in the timing of information disclosure between the U.S. and Japanese patent systems. Under the Japanese system it is possible for a firm to apply for a patent knowing the exact specifications of a rival's patent application. In contrast, in the U.S. the only way a firm learns about a rival's innovation is upon the actual granting of the rival's patent. We argue that this difference enables Japanese firms to coordinate their R&D efforts better than their U.S. counterparts and that this, in turn, leads to smaller quality improvements under the Japanese system. We show that the creation/diffusion tradeoff of patents can be influenced not only by the scope and length of patent protection but also by other features of the patenting process.