Miracle-dz/UniFAR-FTUs huggingface dataset:
Complexity Reduction in the Negotiation of New Lexical Conventions

In the process of collectively inventing new words for new concepts in a population, conflicts can quickly become numerous, in the form of synonymy and homonymy. Remembering all of them could cost too much memory, and remembering too few may slow down the overall process. Is there an efficient behavior that could help balance the two? The Naming Game is a multi-agent computational model for the emergence of language, focusing on the negotiation of new lexical conventions, where a common lexicon self-organizes but going through a phase of high complexity. Previous work has been done on the control of complexity growth in this particular model, by allowing agents to actively choose what they talk about. However, those strategies were relying on ad hoc heuristics highly dependent on fine-tuning of parameters. We define here a new principled measure and a new strategy, based on the beliefs of each agent on the global state of the population. The measure does not rely on heavy computation, and is cognitively plausible. The new strategy yields an efficient control of complexity growth, along with a faster agreement process. Also, we show that short-term memory is enough to build relevant beliefs about the global lexicon.
An investigation of factors determining industrial tourism attractiveness

This study explores the opinions of an expert panel on the factors determining the attractiveness of industrial tourism generally and factory tours in particular. Thirty-four determinants were derived from previous studied conducted about visits to both operational and nonoperational industrial sites. They were then categorized in a four-level hierarchical structure based on “4 A’s” of tourism destination management practices, namely, attractions, access, amenities, and ancillary services. The relative importance of these determinants was analyzed by a panel of experts using the analytical hierarchy process method. The expert panel was composed of government officials, industry practitioners, and academic researchers who are knowledgeable of the subject matter being studied and their evaluations could offer the highest degree of accuracy. Given that the sample was limited to such particular subgroups of the population, snowball sampling was undertaken in order to recruit a wide range of key informants. The results showed that on-site attractions, safety and security systems, and external access are the major dimensions in determining industrial tourism attractiveness. While the observation of production process is an essential and important component of tourism factories, the provision of transport services and on-site restaurants constitutes a supporting role in enhancing industrial tourism attractiveness. It is concluded that Taiwan has a strong industrial base and its industrial sites, either operational or nonoperational, represent an opportunity to develop sustainable forms of tourism. The integration of industrial sites in tourism would not only strengthen the island’s economic and environmental sustainability, but also diversify its tourism offering, enhancing its profile as one of Asia’s leading tourism destinations. The major implications are threefold: enhancing the availability of transport services, providing visitors with more diverse experience packages, and ensuring on-site safety and security.
J-MeDic: A Japanese Disease Name Dictionary based on Real Clinical Usage

Medical texts such as electronic health records are necessary for medical AI development. Nevertheless, it is difficult to use data directly because medical texts are written mostly in natural language, requiring natural language processing (NLP) for medical texts. To boost the fundamental accuracy of Medical NLP, a high coverage dictionary is required, especially one that fills the gap separating standard medical names and real clinical words. This study developed a Japanese disease name dictionary called “ J-MeDic ” to fill this gap. The names that comprise the dictionary were collected from approximately 45,000 manually annotated real clinical case reports. We allocated the standard disease code (ICD-10) to them with manual, semi-automatic, or automatic methods, in accordance with its frequency. The J-MeDic covers 7,683 concepts (in ICD-10) and 51,784 written forms. Among the names covered by J-MeDic, 55.3% (6,391/11,562) were covered by SDNs; 44.7% (5,171/11,562) were covered by names added from the CR corpus. Among them, 8.4% (436/5,171) were basically coded by humans), and 91.6% (4,735/5,171) were basically coded automatically. We investigated the coverage of this resource using discharge summaries from a hospital; 66.2% of the names are matched with the entries, revealing the practical feasibility of our dictionary.
Background-free detection and mixed-species crystals in micro- and macroscopic ion-traps for scalable QIP

Background-free detection and mixed-species crystals in microand macroscopic ion-traps for scalable QIP A thesis submitted for the degree of Doctor of Philosophy Michaelmas Term 2012 Norbert M. Linke New College, Oxford Scalability and the implementation of fault tolerant quantum gates are the two main challenges which must be overcome in order to unlock the vast potential of quantum computing. This thesis describes work with calcium ions trapped in both microscopic and macroscopic linear Paul traps addressing both of these issues. We describe the assembly of a microstructured multi-zone ion trap which forms part of our group’s contribution to the European “Microtrap” collaboration. We report the successful trapping of ions and characterization of the trap as well as a measurement of the heating rate. In miniaturized trap structures such as this one, background scattered light from the cooling beam causes difficulties. We introduce and demonstrate experimentally two techniques to overcome this problem. The first achieves background-free detection of ions using different repumping methods to enable the filtering out of the excitation wavelength. The second makes possible background-free readout of trapped ion qubits by separating in time the excitation and detection steps. The second half of the thesis describes our experimental efforts towards implementing a two-qubit entangling gate with a mixed-species crystal. We describe the setup and characterization of a new macroscopic trap including the trapping and coherent manipulation of the internal states of both 40Ca+ and 43Ca+ ions. We accomplish the simultaneous independent readout of two qubits implemented in a 40Ca+−43Ca+ ion pair. We also present the setup and characterization of two injection-locked frequency-doubled Raman lasers and demonstrate coherent manipulation as well as a measurement of the off-resonant photon scattering error they introduce. Finally, we use them to achieve sideband cooling to the motional ground state of a mixed species ion crystal.
In Vitro Priming of Adoptively Transferred T Cells with a RORγ Agonist Confers Durable Memory and Stemness In Vivo.

Adoptive T-cell transfer therapy is an FDA- approved treatment for leukemia that relies on the ex vivo expansion and reinfusion of a patient's immune cells, which can be engineered with a chimeric antigen receptor (CAR) for more efficient tumor recognition. Type 17 T cells, controlled transcriptionally by RORγ, have been reported to mediate potent antitumor effects superior to those observed with conventionally expanded T cells. Here, we demonstrate that addition of a synthetic, small-molecule RORγ agonist during ex vivo expansion potentiates the antitumor activity of human Th17 and Tc17 cells redirected with a CAR. Likewise, ex vivo use of this agonist bolstered the antitumor properties of murine tumor-specific CD4+ and CD8+ T cells. Expansion in the presence of the RORγ agonist enhanced IL17A production without compromising IFNγ secretion in vitroIn vivo, cytokine neutralization studies revealed that IFNγ and IL17A were required to regress murine melanoma tumors. The enhanced antitumor effect of RORγ agonist treatment was associated with recovery of more donor T cells in the tumor and spleen; these cells produced elevated levels of cytokines months after infusion and expressed markers of long-lived stem and central memory cells such as Tcf7 and CD62L. Conversely, untreated cells mainly exhibited effector phenotypes in the tumor. Cured mice previously treated with agonist-primed T cells were protected from tumor rechallenge. Collectively, our work reveals that in vitro treatment with a RORγ agonist generates potent antitumor Type 17 effector cells that persist as long-lived memory cells in vivoSignificance: RORγ agonists can be used in vitro during T-cell expansion to enhance the efficacy of adoptive cell therapy (e.g., CAR-T) and to provide long-term protection against tumors.Graphical Abstract: http://cancerres.aacrjournals. org/content/canres/78/14/3888/F1.large. jpg Cancer Res; 78(14); 3888-98. ©2018 AACR.
Collection of Multimodal Dialog Data and Analysis of the Result of Annotation of Users’ Interest Level

The Human-System Multimodal Dialogue Sharing Corpus Building Group is acting as a working group of SIG-SLUD for the purpose of constructing a corpus for evaluating elemental technologies of the multimodal dialogue system. In this paper, we report the results of recording chat dialogue data between a human and a virtual agent by the Wizard of OZ method conducted in 2016, and the results of the analysis of annotations of users’ interest level in the data
G9a stimulates CRC growth by inducing p53 Lys373 dimethylation-dependent activation of Plk1

Rationale: G9a is genetically deregulated in various tumor types and is important for cell proliferation; however, the mechanism underlying G9a-induced carcinogenesis, especially in colorectal cancer (CRC), is unclear. Here, we investigated if G9a exerts oncogenic effects in CRC by increasing polo-like kinase 1 (Plk1) expression. Thus, we further characterized the detailed molecular mechanisms. Methods: The role of Plk1 in G9a aberrant CRC was determined by performing different in vitro and in vivo assays, including assessment of cell growth by performing cell viability assay and assessment of signaling transduction profiles by performing immunoblotting, in the cases of pharmacological inhibition or short RNA interference-mediated suppression of G9a. Detailed molecular mechanisms underlying the effect of G9a on Plk1 expression were determined by performing point mutation analysis, chromatin immunoprecipitation analysis, and luciferase reporter assay. Correlation between G9a and Plk1 expression was determined by analyzing clinical samples of patients with CRC by performing immunohistochemistry. Results: Our study is the first to report a significant positive correlation between G9a and Plk1 levels in 89 clinical samples of patients with CRC. Moreover, G9a depletion decreased Plk1 expression and suppressed CRC cell growth both in vitro and in vivo, thus confirming the significant correlation between G9a and Plk1 levels. Further, we observed that G9a-induced Plk1 regulation depended on p53 inhibition. G9a dimethylated p53 at lysine 373, which in turn increased Plk1 expression and promoted CRC cell growth. Conclusions: These results indicate that G9a-induced and p53-dependent epigenetic programing stimulates the growth of colon cancer, which also suggests that G9a inhibitors that restore p53 activity are promising therapeutic agents for treating colon cancer, especially for CRC expressing wild-type p53.
Property Taxation of Multifamily Housing: An Empirical Analysis of Vertical and Horizontal Equity

This study used the hedonic price technique to focus on a housing characteristic that has been studied infrequently: whether a home is site-built or manufactured. Two hedonic price regression models were used to determine the predictive power of construction type on home price. The ? rst, which controlled for factors found to relate to home prices in previous research, showed a signi? cant difference between the prices of the two types of homes. The second, which also included other variables through a stepwise regression, found that the type of construction had more predictive power than any other explanatory variable in the model.
Open ASR for Icelandic: Resources and a Baseline System

Developing language resources is an important task when creating a speech recognition system for a less-resourced language. In this paper we describe available language resources and their preparation for use in a large vocabulary speech recognition (LVSR) system for Icelandic. The content of a speech corpus is analysed and training and test sets compiled, a pronunciation dictionary is extended, and text normalization for language modeling performed. An ASR system based on neural networks is implemented using these resources and tested using different acoustic training sets. Experimental results show a clear increase in word-error-rate (WER) when using smaller training sets, indicating that extension of the speech corpus for training would improve the system. When testing on data with known vocabulary only, the WER is 7.99%, but on an open vocabulary test set the WER is 15.72%. Furthermore, impact of the content of the acoustic training corpus is examined. The current results indicate that an ASR system could proﬁt from carefully selected phonotactical data, however, further experiments are needed to verify this impression. The language resources are available on http://malfong.is and the source code of the project can be found on https://github.com/cadia-lvl/ice-asr/tree/master/ice-kaldi.
Daclatasvir Plus Asunaprevir for the Treatment of Patients with Hepatitis C Virus Genotype 1b Infection: Real-World Efficacy, Changes in Liver Stiffness and Fibrosis Markers, and Safety

Background/Aims The treatment with daclatasvir plus asunaprevir (DCV+ASV) is associated with potent antiviral effects in patients with genotype 1b hepatitis C virus (HCV) infection. We investigated the real-world efficacy, changes in liver stiffness and noninvasive fibrosis markers, and the safety of DCV+ASV treatment in Korean patients. Methods In total, 363 patients with chronic hepatitis C were treated with DCV+ASV between August 2015 and January 2017. Finally, we analyzed the data of 270 patients who were monitored for at least 12 weeks after the end of treatment. Results The mean age was 60.7 years, and females predominated (60.4%). Most patients (64.8%) were treatment-naïve, and 56 patients (20.7%) had cirrhosis. Two hundred fifty-seven (95.2%) and 251 (93.0%) patients achieved end-of-treatment responses and sustained virological responses at 12 weeks posttreatment (SVR12), respectively. The SVR12 rates were higher in patients who were <65 years of age, males, without cirrhosis and had lower HCV RNA levels. All LS values and fibrosis-4 and aspartate aminotransferase-to-platelet ratio index values declined from baseline to the time of assessment of SVR12. Conclusions The DCV+ASV therapy resulted in a high SVR12 and improved liver fibrosis; the treatment was well tolerated in patients with genotype 1b HCV infections.
Inference and analysis across spatial supports in the big data era: Uncertain point observations and geographic contexts

The ways in which geographic information are produced have expanded rapidly over recent decades. These advances have provided new opportunities for geographical information science and spatial analysis—allowing the tools and theories to be expanded to new domain areas and providing the impetus for theory and methodological development. In this light, old problems of inference and analysis are rediscovered and need to be reinterpreted, and new ones are made apparent. This article describes a new typology of geographical analysis problems that relates to uncertainties in the relationship between individual‐level data, represented as point features, and the geographic context(s) that they are associated with. We describe how uncertainty in context linkage (uncertain geographic context problem) is also related to, but distinct from, uncertainty in point‐event locations (uncertain point observation problem) and how these issues can impact spatial analysis. A case study analysis of a geosocial dataset demonstrates how alternative conclusions can result from failure to account for these sources of uncertainty. Sources of point observation uncertainties common in many forms of user‐generated and big spatial data are outlined and methods for dealing with them are reviewed and discussed.
Chemical composition of barks from Quercus faginea trees and characterization of their lipophilic and polar extracts

The bark from Quercus faginea mature trees from two sites was chemically characterized for the first time. The barks showed the following composition: ash 14.6%, total extractives 13.2%, suberin 2.9% and lignin 28.2%. The polysaccharides were composed mainly of glucose and xylose (50.3% and 35.1% of all monosaccharides respectively) with 4.8% of uronic acids. The suberin composition was: ω-hydroxyacids 46.3% of total compounds, ɑ,ω-alkanoic diacids 22.3%, alkanoic acids 5.9%, alkanols 6.7% and aromatics 6.9% (ferulic acid 4.0%). Polar extracts (ethanol-water) had a high phenolic content of 630.3 mg of gallic acid equivalents (GAE)/g of extract, condensed tannins 220.7 mg of catechin equivalents (CE)/g extract, and flavonoids 207.7 mg CE/g of extract. The antioxidant activity was very high corresponding to 1567 mg Trolox equivalents/g of extract, and an IC50 of 2.63 μg extract/ml. The lipophilic extracts were constituted mainly by glycerol and its derivatives (12.3% of all compounds), alkanoic acids (27.8%), sterols (11.5%) and triterpenes (17.8%). In view of an integrated valorization, Quercus faginea barks are interesting sources of polar compounds including phenols and polyphenols with possible interesting bioactivities, while the sterols and triterpenes contained in the lipophilic extracts are also valuable bioactive compounds or chemical intermediates for specific high-value market niches, such as cosmetics, pharmaceuticals and biomedicine.
Corpora with Part-of-Speech Annotations for Three Regional Languages of France: Alsatian, Occitan and Picard

This article describes the creation of corpora with part-of-speech annotations for three regional languages of France: Alsatian, Occitan and Picard. These manual annotations were performed in the context of the RESTAURE project, whose goal is to develop resources and tools for these under-resourced French regional languages. The article presents the tagsets used in the annotation process as well as the resulting annotated corpora.
Medicinal Chemistry Approaches to Neglected Diseases Drug Discovery

The prevalence of a variety of neglected diseases is an increasing serious public health problem in developing countries, particularly in the poorest and most remote areas with very little or no access to medical care. The consequences in terms of morbidity and mortality due to these infections are devastating and have a major social and economic impact in several relevant aspects. According to the World Health Organization, these diseases are one of the most important scientific and technological challenges that face humankind in the 21st century. Although they affect more than a billion people around the world, there are only a few safe and effective drugs currently available. The urgent need for new drugs has led pharmaceutical and academic R&D centers to employ more knowledge-based platforms, as an unprecedented opportunity to make a significant impact on the lives of disadvantaged people through the discovery of novel therapeutic options. In this perspective we discuss the successful application of modern medicinal chemistry approaches to neglected diseases.
THE RELATIONSHIP BETWEEN EXTERNAL DEBT, ECONOMIC GROWTH AND INFLATION IN TURKEY: VAR APPROACH (1980-2013)

Osman Cenk KANCA Yrd. Doç. Dr., Kafkas Üniversitesi, İktisadi ve İdari Bilimler Fakültesi, İktisat Bölümü osmancenkkanca@hotmail.com z: Dış borç, Türkiye gibi gelişmekte olan ülke ekonomileri için en önemli makro iktisadi problemlerden birisi durumundadır. Bu çalışmada, dış borç, ekonomik büyüme ve enflasyon ilişkisi Türkiye ekonomisi özelinde irdelenmiştir. Bu doğrultuda 1980–2013 dönemi için söz konusu veriler, VAR tekniği kapsamında ADF birim kök analizi, Granger nedensellik testi, Varyans ayrıştırması ve Etki-Tepki fonksiyonları yardımı ile analiz edilmiştir. Araştırma sonuçları, Türkiye’de ekonomik büyümeden enflasyon ve dış borçlanmaya doğru tek yönlü bir nedensellik ilişkisi olduğunu, büyüme oranındaki bir şokun dış borçlar üzerinde güçlü bir etkiye sahip olduğunu ortaya çıkarmıştır. Varyans ayrıştırmasına ait sonuçlar ise, dış borçlardaki herhangi bir değişmenin enflasyon oranı üzerinde anlamlı bir etkide bulunduğuna işaret etmektedir.
Seeking the Good Life in Fiji: Managing Educational Transitions

Abstract This article describes Kai Viti High School (KVHS), a rural school on Kadavu Island, Fiji. Ecological levels of analysis are used as the instruments to describe both the school and the context in which it functions. Recent political and cultural disagreements between indigenous-and Indo-Fijians has been partly attributed to their contrasting beliefs in business and education. Indigenous Fijians are less likely to own a business or attain the educational levels as compared with those of Indo-Fijians. A new discourse has arisen admonishing indigenous Fijians to re-evaluate those cultural beliefs and practices that are impeding their children from receiving an education. Students in rural areas are less likely to enter tertiary education due to poverty and a reluctance to leave their family and home village. Of those who do enter this arena, only approximately 25 percent successfully complete their studies, and some of this attrition has been ascribed to culture shock resulting from the jump from a rural to urban environment. It is suggested that a transition program to prepare students for this new environment would be beneficial in helping students to psychologically adjust prior to going off to further education, and therefore lead to greater success.
Physics-based control of walking virtual characters in low frequency simulations

Physics-based control of virtual characters traditionally uses high simulation frequencies of 1 to 2 kHz. While lowering the simulation frequency frees computation time, it usually introduces instabilities within the simulation. In this paper, we propose a control strategy that can be used for high and low simulation frequencies, down to 225 Hz. The inherent instabilities were reduced by optimizing control parameters and by introducing a novel control feedback for the stance leg. We also show how lower frequencies hold a more restrictive space of possible control parameters than higher ones. Our controller shows equal robustness as high frequency controllers while requiring in average only 0.8 ms per simulation step.