Miracle-dz/UniFAR-FTUs huggingface dataset:
An Artificial Market Model of a Foreign Exchange Market

In this study, we proposed a new approach to foreign exchange market studies, an artificial market approach. The artificial market approach integrated fieldwork studies and multiagent models in order to explain the micro and macro relation in markets. The artificial market approach has the three steps: First, in order to investigate the learning patterns of actual dealers, we carried out both interviews and questionnaires. These field data made it clear that each dealer improved his or her prediction method by replacing (a part of) his or her opinions about factors with other dealers’ opinion which can forecast more accurately. Second, we constructed a multiagent model of a foreign exchange market. Considering the result of the analysis of the field data, the interaction of agents’ learning is described with genetic algorithms in our model. Finally, the emergent phenomena at the market level were analyzed on the basis of the simulation results of the model. The results showed that rate bubbles were caused by the interaction between the agents’ forecasts and the relationship of demand and supply. The other emergent phenomena were explained by the concept of the phase transition of forecast variety. The filed data also supported this simulation results. This approach therefore integrates the fieldwork and the multiagent model, and provides quantitative explanation of the micro-macro relation in markets.
Phase 2 trial of dasatinib in target-selected patients with recurrent glioblastoma (RTOG 0627).

BACKGROUND We conducted a phase II trial to evaluate the efficacy of dasatinib, a multitargeted tyrosine kinase inhibitor, for adults with recurrent glioblastoma (GBM). METHODS Eligibility requirements were Karnofsky performance status ≥ 60%; no concurrent hepatic enzyme-inducing anticonvulsants; prior treatment with surgery, radiotherapy, and temozolomide exclusively; and activation or overexpression of ≥ 2 putative dasatinib targets in GBM (ie, SRC, c-KIT, EPHA2, and PDGFR). Using a 2-stage design, 77 eligible participants (27 in stage 1, if favorable, and then 50 in stage 2) were needed to detect an absolute improvement in the proportion of patients either alive and progression-free patients at 6 months (6mPFS) or responding (any duration) from a historical 11% to 25%. RESULTS A high rate of ineligibility (27%) to stage 1 precluded a powered assessment of efficacy, but there was also infrequent treatment-related toxicity at 100 mg twice daily. Therefore, the study was redesigned to allow intrapatient escalation by 50 mg daily every cycle as tolerated (stage 1B) before determining whether to proceed to stage 2. Escalation was tolerable in 10 of 17 (59%) participants evaluable for that endpoint; however, among all eligible patients (stages 1 and 1B, n = 50), there were no radiographic responses, median overall survival was 7.9 months, median PFS was 1.7 months, and the 6mPFS rate was 6%. The clinical benefit was insufficient to correlate tested biomarkers with efficacy. The trial was closed without proceeding to stage 2. CONCLUSIONS Intraparticipant dose escalation was feasible, but dasatinib was ineffective in recurrent GBM. Clinical trials.gov identified. NCT00423735 (available at http://clinicaltrials.gov/ct2/show/NCT00423735).
Natural Language Multitasking: Analyzing and Improving Syntactic Saliency of Hidden Representations

We train multi-task autoencoders on linguistic tasks and analyze the learned hidden sentence representations. The representations change significantly when translation and part-of-speech decoders are added. The more decoders a model employs, the better it clusters sentences according to their syntactic similarity, as the representation space becomes less entangled. We explore the structure of the representation space by interpolating between sentences, which yields interesting pseudo-English sentences, many of which have recognizable syntactic structure. Lastly, we point out an interesting property of our models: The difference-vector between two sentences can be added to change a third sentence with similar features in a meaningful way.
Ensemble of Adaptive Rule-Based Granular Neural Network Classifiers for Multispectral Remote Sensing Images

Information granulation opens ample scope to design likely transparent neural networks called granular neural networks (GNNs). The paper proposes a classification model in the framework of ensemble of GNN-based classifiers, and justifies its improved performance in classifying land use/cover classes of multispectral remote sensing (RS) images. The model also provides an adaptive method for fuzzy rules extraction from the fuzzified input variables for GNN and thus avoid the uncertainty in empirical search of rules for output class labels. The superiority of the proposed model to other similar methods is established both visually and quantitatively for land use/cover classification of multispectral RS images. Comparative analysis revealed that GNN with multiple rules performed better than GNN with single rule assigned for each of the classes, and ensemble of GNNs outperformed all other methods. Various performance measures, such as overall accuracy, producer's accuracy, user's accuracy, kappa coefficient, and measure of dispersion estimation, are used for comparative analysis.
Test-Retest Reliability and Factor Stability of the Behavioral Evaluation for Epidemiology Studies Test Battery

The Behavioral Evaluation for Epidemiology Studies test battery uses touch-screen technology and novel methodologies to enhance neurobehavioral assessment. Scores generally show differential stability from the first trial with individual test reliabilities at or above 80 when normalized to a 3-min. administration. Six highly reliable (r ≥.87) factors were identified that cover functions known to be sensitive to neurotoxicants and physical exposures. These results strongly support recommendation of the new test battery for use in repeated-measures epidemiologic studies where first trial stability is desired.
A Neurocognitive Protocol System to Support Health and Care of Abused Children

Abused children is highly endangered of developing critical cognitive dysfunctions. Clinical observation has encountered many related cases of abuse and poor learning performance. Authorities unaware of these conditions may take longer to act, detrimentally to the child welfare. This work provides a wide coverage of medical protocols for every area concerned with endangered children procedures. These protocols were researched with the collaboration of specialist in each area to achieve the most detailed and conspicuous information of children status. These protocols are proposed as a Web system available to all concerning professionals and authorities to input and access the relevant information. This data can be processed and analyzed to provide decision support and handling indications derived from statistical and heuristic treatment of the whole information.
A study of oxygen transfer in shake flasks using a non‐invasive oxygen sensor

We describe a study of oxygen transfer in shake flasks using a non‐invasive optical sensor. This study investigates the effect of different plugs, presence of baffles, and the type of media on the dissolved oxygen profiles during Escherichia coli fermentation. We measured the volumetric mass transfer coefficient (kLa) under various conditions and also the resistances of the various plugs. Finally, we compared shake flask kLa with that from a stirred tank fermentor. By matching kLa's we were able to obtain similar growth and recombinant protein product formation kinetics in both a fermentor and a shake flask. These results provide a quantitative comparison of fermentations in a shake flask vs. a bench‐scale fermentor and should be valuable in guiding scale‐up efforts. © 2003 Wiley Periodicals, Inc. Biotechnol Bioeng 84: 351–358, 2003.
International Franchising: Evidence from Us and Canadian Franchisors in Mexico

The contracting practices of franchisors outside of theirdomestic markets have received limited attention in the empirical literature on franchising, mostly due to data limitations. We exploit a newly assembled data set that allows us not only to describe the contracting practices of US and Canadian franchisors in Mexico but, most importantly, to compare them to their domestic counterparts. We briefly but systematically review the two theoretical frameworks that have been used most to study franchisors' domestic and international operations, namely agency and internationalization theory, and use implications derived from these to guide our analyses. We focus in turn on franchisors' decision to operate in the Mexican market, their propensity to enter via company-owned versus franchised units as compared to the same decision domestically, and finally the financial contract terms they adopt (royalty rate, franchise fee and advertising fee) for their franchise agreements in Mexico compared to their home market. Our empirical results confirm hypotheses derived from the theories, particularly with respect to the decision to operate in Mexico. But we also find some surprises - for example, the vast majority of US and Canadian franchisors employ exactly the same financial contract terms in Mexico as in their home market. We argue that this tendency is probably best explained by the same arguments used in the franchising literature to explain contract uniformity within domestic markets. Further implications for future research and practice are also discussed.
Genetic characterisation of multidrug-resistant Salmonella enterica serotypes isolated from poultry in Cairo, Egypt

Background Food-borne diseases pose serious health problems, affecting public health and economic development worldwide. Methods Salmonella was isolated from samples of chicken parts, skin samples of whole chicken carcasses, raw egg yolks, eggshells and chicken faeces. Resulting isolates were characterised by serogrouping, serotyping, antimicrobial susceptibility testing and detection of extended-spectrum β-lactamase (ESBL) production. Antibiotic resistance genes and integrons were identified by polymerase chain reaction (PCR). Results The detection rates of Salmonella were 60%, 64% and 62% in chicken parts, skin, and faeces, respectively, whereas the egg yolks and eggshells were uniformly negative. Salmonella Kentucky and S. Enteritidis serotypes comprised 43.6% and 2.6% of the isolates, respectively, whilst S. Typhimurium was absent. Variable resistance rates were observed against 16 antibiotics; 97% were resistant to sulfamethoxazole, 96% to nalidixic acid and tetracycline and 76% to ampicillin. Multidrug resistance was detected in 82% (64/78) of the isolates and ESBL production was detected in 8% (6/78). The β-lactamase blaTEM-1 gene was detected in 57.6% and blaSHV-1 in 6.8% of the isolates, whilst the blaOXA gene was absent. The sul1 gene was detected in 97.3% and the sul2 gene in 5.3% of the isolates. Sixty-four of the 78 isolates (82%) were positive for the integrase gene (int I) from class 1 integrons, whilst int II was absent. Conclusion This study reveals the presence of an alarming number of multidrug-resistant Salmonella isolates in the local poultry markets in Cairo. The high levels of drug resistance suggest an emerging problem that could impact negatively on efforts to prevent and treat poultry and poultry-transmitted human diseases in Egypt.
Observation-driven configuration of complex software systems

The ever-increasing complexity of software systems makes them hard to comprehend, predict and tune due to emergent properties and non-deterministic behaviour. Complexity arises from the size of software systems and the wide variety of possible operating environments: the increasing choice of platforms and communication policies leads to ever more complex performance characteristics. In addition, software systems exhibit different behaviour under different workloads. Many software systems are designed to be configurable so that policies can be chosen to meet the needs of various stakeholders. For complex software systems it can be difficult to accurately predict the effects of a change and to know which configuration is most appropriate. This thesis demonstrates that it is useful to run automated experiments that measure a selection of system configurations. Experiments can find configurations that meet the stakeholders' needs, find interesting behavioural characteristics, and help produce predictive models of the system's behaviour. The design and use of ACT (Automated Configuration Tool) for running such experiments is described, in combination a number of search strategies for deciding on the configurations to measure. Design Of Experiments (DOE) is discussed, with emphasis on Taguchi Methods. These statistical methods have been used extensively in manufacturing, but have not previously been used for configuring software systems. The novel contribution here is an industrial case study, applying the combination of ACT and Taguchi Methods to DC-Directory, a product from Data Connection Ltd (DCL). The case study investigated the applicability of Taguchi Methods for configuring complex software systems. Taguchi Methods were found to be useful for modelling and configuring DC- Directory, making them a valuable addition to the techniques available to system administrators and developers.
Interacting with Customers for Knowledge Creation

Our concern is with how interaction with customers affects knowledge creation in product development projects. Customers have a crucial role in stimulating innovation, but previous research has not identified what effects the interaction has on knowledge creation nor at what point in time interaction with customers should be sought. Through case research in high velocity industries we identify the effect customer interaction has on knowledge creation processes inside new product development projects and therefore ultimately innovation. In particular we highlight the effects the interaction has on tacit and explicit knowledge, and the need to acknowledge the difference between the two.
Chorionic Sculpturing in Eggs of Lycaenidae

It has long been thought that the egg stage of butterflies has both an actual and. a potential value in determining or understanding the phylogeny and evolution of members of the order (Scudder, 1889; Chapman, 1896a, 1896b). * Within the Lycaenidae, several works beginning with Doherty (1886) and as recent as Clark and Dickson 's (1956, 1971) excellent research in South Africa, have indicated the taxonomic usefulness of the egg stage. Recently, more life history studies of particular lycaenid genera (Shields, 1973, 1974)+ or species (Nakamura, 1976; Downey and Allyn, 1979) have included scan electron photographs of the egg stage, and provided a new and detailed ultrastructu,ral view. Most of these studies presented only the photographs or descriptions, but did not attempt to analyze similarities or differences of the included eggs with others. In our own ultrastructural studies, we have become increasingly aware of the lack of comparative details in order to assess the importance of observed differences. With this in mind, it was decided to reassess the chorionic sculpturing of available lycaenid eggs by means of scan electron microscopy. As incomplete as such a survey might be, it might still provide a comparative basis against which descriptions of single species in the future might be evaluated. We hope it will promote greater attention to this interesting stage of butterfly morphology. The present study is a quest for an essential geometry in the chorionic sculpturing --an attempt to reduce the apparent complexities of egg structure, and to identify homologies between species. The immediate problem is one of elemental topology, that is, trying to determine what to describe and measure. Scudder (1889, pl. 65, 68) figured the eggs and micropylar regions of 16 species of Nearctic Lycaenidae including Feniseca. All were done with the light microscope; some
Heat Adaptation Alters Escherichia coli O157:H7 Membrane Lipid Composition and Verotoxin Production

ABSTRACT The influence of heat adaptation (growth at 42 and 45°C) on changes in membrane lipid composition and verotoxin concentration of Escherichia coli O157:H7 (ATCC 43895), an rpoS mutant of ATCC 43895 (FRIK 816-3), a verotoxin mutant E. coli O157:H7 (B6-914), and nonpathogenic E. coli (ATCC 25922) was investigated. D values (57°C) of heat-adapted cells were up to 3.9 min longer than those of control cells for all four strains. Heat adaptation increased the amounts of palmitic acid (16:0) and cis-vaccenic acid (18:1ω7c) in membrane lipids of ATCC 43895 and the rpoS mutant, whereas there was a reduction and no change in the amount of cis-vaccenic acid in nonpathogenic and verotoxin mutant E. coli, respectively. The ratio of palmitic to cis-vaccenic acids decreased in ATCC 43895 and in the rpoS mutant, whereas the ratio increased in nonpathogenic E. coli and was not different in the verotoxin mutant with elevated growth temperature. Total verotoxin concentration decreased due to a reduction in intracellular verotoxin amount in heat-adapted ATCC 43895 and rpoS mutant strains. However, extracellular verotoxin concentration increased in heat-adapted cells. The rpoS gene did not influence membrane lipid composition changes although it did affect heat resistance. Results suggest that increased membrane fluidity may have caused increased verotoxin secretion.
On the error exponent for woven convolutional codes with outer warp

The error exponent and the decoding complexity of binary woven convolutional codes with outer warp and with binary convolutional codes as outer and inner codes are studied. It is shown that an error probability that is exponentially decreasing with the product of the outer and inner code memories can be achieved with a non-exponentially increasing decoding complexity.
An Investigation of Thresholds in Air Pollution-Mortality E ¤ ects June 2004 Running Title : Air pollution

In this paper we introduce and implement new techniques to investigate threshold e¤ects in air pollution-mortality relationships. Our key interest is in measuring the dose-response relationship above and below a given threshold level where we allow for a large number of potential explanatory variables to trigger the threshold e¤ect. This is in contrast to existing approaches that usually focus on a single threshold trigger. We allow for a myriad of threshold e¤ects within a Bayesian statistical framework that accounts for model uncertainty (i.e. uncertainty about which threshold trigger and explanatory variables are appropriate). We apply these techniques in an empirical exercise using daily data from Toronto for 1992-1997. We investigate the existence and nature of threshold e¤ects in the relationship between mortality and ozone (O3), total particulate matter (PM) and an index of other conventionally occurring air pollutants. In general, we nd the e¤ects of our considered pollutants on mortality to be statistically indistinguishable from zero with no evidence of thresholds. The one exception is ozone, for which results present an ambiguous picture. Ozone has no signi cant e¤ect on mortality when we exclude threshold e¤ects from the analysis. Allowing for thresholds we nd a positive and signi cant e¤ect for this pollutant when the threshold trigger is the average change in ozone two days ago. However, this signi cant e¤ect is not observed after controlling for PM.
An Ethological Model for Implementation in Mobile Robots

This article describes a neuroethological model of learning and motivation that accounts for many of the behavioral phenomena observed in animals. Unusual predictions from the model have been tested and shown to be demonstrable in laboratory Siamese fighting fish. In addition, the model is sufficiently mathematically well defined to be implementable in a robot or in computer simulation. A trial implementation in a mobile robot was carried out as part of this work. This article describes a simplified version of the model that was programmed into the robot, a thought experiment designed to show the main features of the model, and the preliminary robot experiments that were carried out. Using robots for ethological models of animal behavior is interesting for both robotics and ethological research: The study of robot autonomy can be enhanced through an understanding of complex and realistic models of animal autonomy, and ethological research should benefit from a supply of guaranteed "naive" agents on which rigorous testing of such models is tractable.
Essais on firms' heterogeneity and the productivity of exporters

This thesis contributes to both theoretical and empirical aspects of the literature on firm heterogeneity in international trade. On the theoretical side, I provide insights of the consequences of trade liberalisation when firms are heterogeneous and countries are asymmetric. On the empirical side, I discuss the causality of the relationship between performances and trading status of firms. Do more productive firms self-select into international markets? Do firms become more productive because they enter international markets? These hypotheses are not mutually exclusive and my work provides support for both of them.
Optoelectronic properties of graphene silicon nano-texture

Graphene on silicon with silicon dioxide quantum dots is a promising opto-electronic material. The optical band gap and the corresponding optical conductivity are estimated using the density functional approach with the combination of molecular dynamics. The regular repeating unit cell of graphene silicon nano-texture is identified using the classical molecular dynamics simulations. Electronic calculations predict the optical band gap is around 0.2 eV and the optical conductivity is identified to be 0.3 times the quantum conductance.
Absorptive Capacity and Technology Spillovers: A Case From Turkey

Due to the increase of technological capacity by reverse engineering, learning by doing and imitation effects, the interaction of production units with each other will lead productivity increases through exchanging and utilizing new and more variety of intermediate and capital goods. Departing from the assumption that technology spillovers which emerge as externalities resulting from R&D investments that take place through the inputs of intermediate and capital goods, this study examines the domestic technology spillovers in Turkish manufacturing industry within the framework of absorptive capacity. Considering that the relation between technology spillovers and absorptive capacity may not be linear, threshold regression techniques are applied to manufacturing industry data over the period 1992-2001. The results of the analyses show the existence of domestic technology spillovers through imports in Turkish Manufacturing Industry. The main result of threshold regression analyses is that the efficiency of spillovers are differentiated with respect to the industry specific absorptive capacities.