Miracle-dz/UniFAR-FTUs huggingface dataset:
The Tourism Planning Process in the Context of Organised Interests, Industry Structure, State Capacity, Accumulation and Sustainability

This paper presents a framework for the analysis and ongoing comparative study of the tourism planning process. This framework holds tourism planning to be a complex and contingent process occurring within and between three locations: the individual tourism organisation; the industry; and within the state. After sketching the central factors shaping the planning process within the various locations, the paper presents five ideal typical configurations of the planning process, representing specific forms of the relationship between the three locations. Each of these configurations reflects a distribution of organisational and power resources in the planning process.
In situ preparation of cubic Cu2O-RGO nanocomposites for enhanced visible-light degradation of methyl orange

There has been a growing interest in gathering together photocatalysis of semiconductors, like cuprous oxide (Cu2O), and the excellent electron transmittability of graphene to produce a graphene-based semiconductor for photocatalytic degradation. In this paper, a mild one-pot in situ synthesis of cubic cuprous oxide-reduced graphene oxide (Cu2O-RGO) nanocomposites has been proposed for the removal of methyl orange. In contrast to pure cubic Cu2O particles under similar preparation conditions, the cubic Cu2O-RGO nanocomposites demonstrate enhanced visible-light-driven photocatalytic activity for methyl orange dye with a 100% degradation rate in 100 min. The enhanced photocatalytic performance is mainly attributed to the increased charge transportation, effective separation of photoelectrons from vacancies, and the improved contact area.
Can the VIX Signal Market's Direction? An Asymmetric Dynamic Strategy

The article shows statistically that the VIX Implied Volatility Index is an important driver of the S&P 500 future returns. The statistical analysis is performed by means of a regression based on dummy variables in order to circumvent the difficulties posed by the lack of linearity between the variables. The results obtained are then used to construct an automated procedure that signals daily whether it is convenient to invest in the S&P 500 or to stay put. Finally, we test the quality of the signal by implementing an asymmetrical buy-and-hold strategy with 3-months horizon on the S&P 500. Our results show that the strategy outperforms the long-only strategy on the same index, thus confirming a widespread belief among traders.
RP-Ring: A Heterogeneous Multi-FPGA Accelerator

To reduce the cost of designing new specialized FPGA boards as direct-summation MOND (Modified Newtonian Dynamics) simulator, we propose a new heterogeneous architecture with existing FPGA boards, which is called RP-ring (reconfigurable processor ring). This design can be expanded conveniently with any available FPGA board and only requires quite low communication bandwidth between FPGA boards. The communication protocol is simple and can be implemented with limited hardware/software resources. In order to avoid overall performance loss caused by the slowest board, we build a mathematical model to decompose workload among FPGAs. The dividing of workload is based on the logic resource, memory access bandwidth, and communication bandwidth of each FPGA chip. Our accelerator can achieve two orders of magnitude speedup compared with CPU implementation.
The "Socialness" of Virtual Worlds

The intent of this paper is to explore the implications of the social aspects enabled by virtual world technology on an individual’s intention to use the technology. We identify variables such as social awareness, social interaction, and social quality that may play an important role. We test our research model by means of a controlled laboratory experiment conducted in a virtual world, Second Life. The results show that perceived social interactions and social awareness positively influence the cognitive absorption that an individual feels when using virtual worlds. These are influenced by an individual’s social skills, and his/her perception of the social quality of the technology. Cognitive absorption in turn significantly predicts outcomes such as the satisfaction with, and the intention to return to the virtual world.
Fabrication of malleable three-dimensional-printed customized bolus using three-dimensional scanner

A three-dimensional (3D)-printed customized bolus (3D bolus) can be used for radiotherapy application to irregular surfaces. However, bolus fabrication based on computed tomography (CT) scans is complicated and also delivers unwanted irradiation. Consequently, we fabricated a bolus using a 3D scanner and evaluated its efficacy. The head of an Alderson Rando phantom was scanned with a 3D scanner. The 3D surface data were exported and reconstructed with Geomagic Design X software. A 3D bolus of 5-mm thickness designed to fit onto the nose was printed with the use of rubber-like printing material, and a radiotherapy plan was developed. We successfully fabricated the customized 3D bolus, and further, a CT simulation indicated an acceptable fit of the 3D bolus to the nose. There was no air gap between the bolus and the phantom surface. The percent depth dose (PDD) curve of the phantom with the 3D bolus showed an enhanced surface dose when compared with that of the phantom without the bolus. The PDD of the 3D bolus was comparable with that of a commercial superflab bolus. The radiotherapy plan considering the 3D bolus showed improved target coverage when compared with that without the bolus. Thus, we successfully fabricated a customized 3D bolus for an irregular surface using a 3D scanner instead of a CT scanner.
Modeling Dynamic Adaptive Streaming Over Information-Centric Networking

The dynamic adaptive streaming technique flexibly adapts the video bit-rate to link fluctuations, which can improve the quality of experience (QoE). In this paper, we present a systematic framework of video streaming in the context of information-centric networking, in order to facilitate the large-scale deployment of the dynamic adaptive streaming technique. Specifically, we design the network as a two-layer coordinating structure, namely, the control layer and the transmission layer. The control layer employs the statistical data recorders to record the variations of the video popularity, link states, and user demands. On the other side, the network forwards user requests and caches data packets in the transmission layer, based on the statistical data which is obtained in the control layer. In addition, the network executes the real-time monitoring of link conditions in the transmission layer, and adjusts the video bit-rate accordingly. Under the above feedback circumstance, we first develop a distributed algorithm of joint dynamic forwarding and caching to theoretically maximize the total user demand rates within the network stability region. Then, we modify the distributed algorithm with a practical caching strategy to make the system applicable to real scenarios. Simulation results show the superior performance of the modified distributed algorithm in terms of low user delay and high QoE performance.
Joint Learning of Set Cardinality and State Distribution

We present a novel approach for learning to predict sets using deep learning. In recent years, deep neural networks have shown remarkable results in computer vision, natural language processing and other related problems. Despite their success,traditional architectures suffer from a serious limitation in that they are built to deal with structured input and output data,i.e. vectors or matrices. Many real-world problems, however, are naturally described as sets, rather than vectors. Existing techniques that allow for sequential data, such as recurrent neural networks, typically heavily depend on the input and output order and do not guarantee a valid solution. Here, we derive in a principled way, a mathematical formulation for set prediction where the output is permutation invariant. In particular, our approach jointly learns both the cardinality and the state distribution of the target set. We demonstrate the validity of our method on the task of multi-label image classification and achieve a new state of the art on the PASCAL VOC and MS COCO datasets.
EMPIRICAL INVESTIGATION OF THE RICE PRODUCTION STRUCTURE IN TAIWAN, 1976-93

N the early period of Taiwan’s economic development, in particular during the 1950s and 1960s, rice production increased rapidly, not only meeting the needs of domestic food consumption but also providing a surplus for export. However, since around the mid-1970s, Taiwan’s agriculture has witnessed a general decrease in the production of rice which fell from a peak of 2.71 million metric tons (in terms of brown rice) in 1976 to 1.82 million metric tons in 1993, corresponding to a 33 per cent reduction during the seventeen-year period. Needless to say, the total production is a product of the total planted area and the yield per unit of land. How did these two factors change in the course of rice production in Taiwan? To begin with, the total planted area for rice production has shown a strong downward trend. It decreased drastically from 790,248 hectares in 1975 to 391,457 hectares in 1993, corresponding to a 50 per cent reduction during the eighteen-year period. There are two main reasons for such a decrease in the rice production: (1) a switch in 1977 from a policy of unlimited purchases to one that limited purchases by the government; and (2) the paddy field diversion program launched in 1984. On the other hand, however, there has been a significant increase in the yield per hectare from 3,450 kilograms in 1976 to 4,655 kilograms in 1993 (in terms of brown rice), corresponding to almost a 35 per cent increase during the seventeenyear period, and implying a compound annual growth rate of 1.8 per cent which is fairly high on an international standard (see Hayami 1995, p. 101). The higher
RiFCN: Recurrent Network in Fully Convolutional Network for Semantic Segmentation of High Resolution Remote Sensing Images

Semantic segmentation in high resolution remote sensing images is a fundamental and challenging task. Convolutional neural networks (CNNs), such as fully convolutional network (FCN) and SegNet, have shown outstanding performance in many segmentation tasks. One key pillar of these successes is mining useful information from features in convolutional layers for producing high resolution segmentation maps. For example, FCN nonlinearly combines high-level features extracted from last convolutional layers; whereas SegNet utilizes a deconvolutional network which takes as input only coarse, high-level feature maps of the last convolutional layer. However, how to better fuse multi-level convolutional feature maps for semantic segmentation of remote sensing images is underexplored. In this work, we propose a novel bidirectional network called recurrent network in fully convolutional network (RiFCN), which is end-to-end trainable. It has a forward stream and a backward stream. The former is a classification CNN architecture for feature extraction, which takes an input image and produces multi-level convolutional feature maps from shallow to deep; while in the later, to achieve accurate boundary inference and semantic segmentation, boundary-aware high resolution feature maps in shallower layers and high-level but low-resolution features are recursively embedded into the learning framework (from deep to shallow) to generate a fused feature representation that draws a holistic picture of not only high-level semantic information but also low-level fine-grained details. Experimental results on two widely-used high resolution remote sensing data sets for semantic segmentation tasks, ISPRS Potsdam and Inria Aerial Image Labeling Data Set, demonstrate competitive performance obtained by the proposed methodology compared to other studied approaches.
The Economics of Public-Private Partnerships: A Basic Guide

If you ally dependence such a referred the economics of public private partnerships a basic guide book that will come up with the money for you worth, get the definitely best seller from us currently from several preferred authors. If you desire to entertaining books, lots of novels, tale, jokes, and more fictions collections are next launched, from best seller to one of the most current released.
Risk Factors Associated With Small Bowel Adenocarcinoma in Crohn's Disease: A Case–Control Study

BACKGROUND AND AIMS:It is well established that Crohn's disease (CD) is associated with an increased risk of small bowel adenocarcinoma (SBA). The data concerning SBA risk factors in CD are scanty. The aim of this study was to identify them.METHODS:In 11 French centers affiliated with the GETAID (Groupe d'Etude Thérapeutique des Affections Inflammatoires du Tube Digestif), we identified 29 patients with CD and SBA. Eighty-seven CD controls without SBA recruited in a single center were matched to the cases for sex, age, duration, and CD site. A conditional logistic regression, taking into account the matching between cases and controls, was performed.RESULTS:In univariate analysis, the cases had had significantly less small bowel resection and received prolonged treatment with salicylates (more than 2 yr), less often than the controls (odds ratio, OR [95% confidence interval, CI] 0.07 [0.01–0.32] and 0.29 [0.10–0.82], respectively). In multivariate analysis, both associations remained significant (OR 0.04 [0.01–0.28], P= 0.001; OR 0.16 [0.03–0.79], P= 0.02, respectively). CONCLUSION:This study suggests that small bowel resection and prolonged salicylates use may protect against SBA in CD patients.
Competitive selling mechanisms: the delegation principle and farsighted stability

We analyze the problem of competitive mechanism design within the context of a model of product differentiated oligopoly. In our model, ﬁrms compete via their catalogs, that is, via the sets of products (broadly deﬁned) and prices ﬁrms offer to the market (i.e., catalogs are the primitives, while selling mechanisms are derived). In an oligopoly setting, participation by an agent in any one ﬁrm’s catalog is endogenously determined. This fact leads naturally to a modiﬁcation of the classical notion of incentive compatibility for mechanisms. We extend the classical notion of incentive compatibility to take into account endogenous participation, introducing the notion of participation incentive compatibility (PIC). Our main contribution is a characterization of all PIC selling mechanisms in terms of catalogs. In particular, we show that a selling mechanism is PIC if and only if there exists a unique, minimal catalog proﬁle which implements the mechanisms. We call this characterization the delegation principle (Theorem 4). Using the delegation principle, we conclude that in order to solve the problem of competitive mechanism design, an essentially cooperative problem, it is sufficient to consider only the underlying noncooperative problem of catalog choice by ﬁrms. Moreover, using the delegation principle we show that corresponding to each PIC mechanism there is a unique proﬁle of nonlinear pricing schedules which implements the mechanism - thus, extending the taxation principle to problems of competitive nonlinear pricing (Theorem 5). A second contribution is our application of the notion of farsighted stability to the problem of competitive mechanism design. We show that for any approximating ﬁnite subgame (of catalog choice), the farsightedly stable set of catalog proﬁles (and hence the farsightedly stable set of nonlinear pricing schedules) is nonempty (Theorem 10).
Dissociating Two Stages of Preparation in the Stop Signal Task Using fMRI

Often we must balance being prepared to act quickly with being prepared to suddenly stop. The stop signal task (SST) is widely used to study inhibitory control, and provides a measure of the speed of the stop process that is robust to changes in subjects’ response strategy. Previous studies have shown that preparation affects inhibition. We used fMRI to separate activity that occurs after a brief (500 ms) warning stimulus (warning-phase) from activity that occurs during responses that follow (response-phase). Both of these phases could contribute to the preparedness to stop because they both precede stop signals. Warning stimuli activated posterior networks that signal the need for top-down control, whereas response phases engaged prefrontal and subcortical networks that implement top-down control. Regression analyses revealed that both of these phases affect inhibitory control in different ways. Warning-phase activity in the cerebellum and posterior cingulate predicted stop latency and accuracy, respectively. By contrast, response-phase activity in fronto-temporal areas and left striatum predicted go speed and stop accuracy, in pre-supplementary motor area affected stop accuracy, and in right striatum predicted stop latency and accuracy. The ability to separate hidden contributions to inhibitory control during warning-phases from those during response-phases can aid in the study of models of preparation and inhibitory control, and of disorders marked by poor top-down control.
Bcl6 middle domain repressor function is required for T follicular helper cell differentiation and utilizes the corepressor MTA3

Significance Most vaccines protect from infections by eliciting a long-lived antibody response. B-cell CLL/lymphoma 6 (Bcl6) is a transcriptional repressor that is essential for the generation of long-lived antibody responses by promoting the differentiation of T follicular helper (Tfh) and germinal center B cells. Currently, the mechanisms by which Bcl6 directs Tfh cell differentiation is unclear. We show that mutations in the middle domain of Bcl6 prevent full differentiation of Tfh cells by loss of repression of key target genes. This study reveals a role for the middle domain of Bcl6 in the differentiation and function of Tfh cells. T follicular helper (Tfh) cells are essential providers of help to B cells. The transcription factor B-cell CLL/lymphoma 6 (Bcl6) is a lineage-defining regulator of Tfh cells and germinal center B cells. In B cells, Bcl6 has the potential to recruit distinct transcriptional corepressors through its BTB domain or its poorly characterized middle domain (also known as RDII), but in Tfh cells the roles of the Bcl6 middle domain have yet to be clarified. Mimicked acetylation of the Bcl6 middle domain (K379Q) in CD4 T cells results in significant reductions in Tfh differentiation in vivo. Blimp1 (Prdm1) is a potent inhibitor of Tfh cell differentiation. Although Bcl6 K379Q still bound to the Prdm1 cis-regulatory elements in Tfh cells, Prdm1 expression was derepressed. This was a result of the failure of Bcl6 K379Q to recruit metastasis-associated protein 3 (MTA3). The loss of Bcl6 function in Bcl6 K379Q-expressing CD4 T cells could be partially rescued by abrogating Prdm1 expression. In addition to Prdm1, we found that Bcl6 recruits MTA3 to multiple genes involved in Tfh cell biology, including genes important for cell migration, cell survival, and alternative differentiation pathways. Thus, Bcl6 middle domain mediated repression is a major mechanism of action by which Bcl6 controls CD4 T-cell fate and function.
Combination of a urease inhibitor and a plant essential oil to control coliform bacteria, odour production and ammonia loss from cattle waste

Aim: To evaluate urea hydrolysis, volatile fatty acid (VFA) production (odour) and coliforms in cattle waste slurries after a urease inhibitor N‐(n‐butyl) thiophosphoric triamide (NBPT) and a plant oil component (thymol) were added.
Using Narratives to Enhance Moral Education in Sport

JOPERD • Volume 77 No. 4 • April 2006 S tories play an integral role in our lives. They provide a context for us, a backdrop against which to measure our efforts. We learn through these stories or narratives—about the world, our ancestors, and our geographic region. We learn about values, beliefs and ideas, good and evil. Stories can also reinforce moral standards important for society, providing models for living congruent with values such as honesty, integrity, and so forth. Narratives, whether read or told, hold an important place within moral education in large part because of their unique characteristics. Lickona (1991) wrote that stories have been used for centuries because they “teach by attraction rather than compulsion; they invite rather than impose. They capture the imagination and touch the heart” (p. 79). The purpose of this article is to explore the use of narrative as means for moral education in sport. It is assumed that sport is a viable means for promoting moral education, even though, at times, individuals and groups involved with sport act in unethical ways. There are, of course, many forms of stories: fi ctional and factual, short stories, and extended novels. This article focuses on published accounts of sport participants and their actions at various levels of competition and on the possibilities of sharing these types of stories with athletes (primarily in youth sports and high school) as a way to develop and preserve the moral culture in sport. As a means of examining the theory behind the moral life, this article refers to R. M. Hare (1981) who wrote extensively on moral issues and identifi ed two levels of moral thinking. Because these levels help explain how people come to grips with moral issues in their lives, Hare’s levels are used as a paradigm for examining sport stories and their place in moral education. Since stories are so central to this analysis, it is important to share two sporting narratives in the fi rst section. The second section introduces and explains Hare’s levels of moral thinking as well as their relationship with narratives. The fi nal section addresses the educators’ role in using stories for the purpose of moral education, in addition to applications for physical educators.
Informatics issues for nursing's future

Automated clinical databases are crucial to the future of nursing but presently are not meeting the needs of clinicians, administrators, educators, or researchers. This article examines theoretical, empirical, and practical issues relating to the development of automated nursing clinical databases that will foster safe, effective practice and further nursing's knowledgebase. A series of key questions are identified relevant to each issue. These issues must be resolved if nurses are to take full advantage of the possibilities inherent in the evolving information technology.