Miracle-dz/UniFAR-FTUs huggingface dataset:
High Resolution Esophageal Manometry in Patients with Chagas Disease: A Cross-Sectional Evaluation

Introduction Gastrointestinal involvement affects 30–40% of the patients with chronic Chagas disease. Esophageal symptoms appear once the structural damage is established. Little is known about the usefulness of high resolution manometry to early identification of esophageal involvement. Method We performed a cross-sectional study at the Vall d’Hebron University Hospital (Barcelona, Spain) between May 2011 and April 2012. Consecutive patients diagnosed with Chagas disease in the chronic phase were offered to participate. All patients underwent a structured questionnaire about digestive symptoms, a barium esophagogram (Rezende classification) and an esophageal high resolution manometry (HRM). A control group of patients with heartburn who underwent an esophageal HRM in our hospital was selected. Results 62 out of 73 patients that were included in the study fulfilled the study protocol. The median age of the Chagas disease group (CG) was 37 (IQR 32–45) years, and 42 (67.7%) patients were female. Twenty-seven (43.5%) patients had esophageal symptoms, heartburn being the most frequent. Esophagogram was abnormal in 5 (8.77%). The esophageal HRM in the CG showed a pathological motility pattern in 14 patients (22.6%). All of them had minor disorders of the peristalsis (13 with ineffective esophageal motility and 1 with fragmented peristalsis). Hypotonic lower esophageal sphincter was found more frequently in the CG than in the control group (21% vs 3.3%; p<0.01). Upper esophageal sphincter was hypertonic in 22 (35.5%) and hypotonic in 1 patient. When comparing specific manometric parameters or patterns in the CG according to the presence of symptoms or esophagogram no statistically significant association were seen, except for distal latency. Conclusion The esophageal involvement measured by HRM in patients with chronic Chagas disease in our cohort is 22.6%. All the patients with esophageal alterations had minor disorders of the peristalsis. Symptoms and esophagogram results did not correlate with the HRM results.
Reinvention in the Innovation Process

innovations (Rogers et al., 1977 and 1978), beginning with Ryan and Gross’s analysis (1943) of farmers who adopted the use of hybrid corn. This tremendous diffusion of diffusion studies has received attention by authors such as Downs and Mohr (1976) who attempt to explain the phenomenon. They suggest that reference to change as a product of diffusion allows generalizability of the discussion from a particular case to a common process. And, they argue, association with the wide body of diffusion studies and theory also adds a touch of class to a study of change. This generality, and status by association, may often be a strength, improving the diffusion of the research results; but it may also be a weakness, increasing the possibility of more contradictions in the diffusion literature. One model of the innovation process has been developed as a tool for the analysis of technology transfer decisions (Eveland et al., 1977). The process of adopting (and, at some stages, rejecting) an innovation is
A characterization of the sensitivity of query optimization to storage access cost parameters

Most relational query optimizers make use of information about the costs of accessing tuples and data structures on various storage devices. This information can at times be off by several orders of magnitude due to human error in configuration setup, sudden changes in load, or hardware failure. In this paper, we attempt to answer the following questions:• Are inaccurate access cost estimates likely to cause a typical query optimizer to choose a suboptimal query plan? • If an optimizer chooses a suboptimal plan as a result of inaccurate access cost estimates, how far from optimal is this plan likely to be? To address these issues, we provide a theoretical, vector-based framework for analyzing the costs of query plans under various storage parameter costs. We then use this geometric framework to characterize experimentally a commercial query optimizer. We develop algorithms for extracting detailed information about query plans through narrow optimizer interfaces, and we perform the characterization using database statistics from a published run of the TPC-H benchmark and a wide range of storage parameters.We show that, when data structures such as tables, indexes, and sorted runs reside on different storage devices, the optimizer can derive significant benefits from having accurate and timely information regarding the cost of accessing storage devices.
ECNU: Expression- and Message-level Sentiment Orientation Classification in Twitter Using Multiple Effective Features

Microblogging websites (such as Twitter, Facebook) are rich sources of data for opinion mining and sentiment analysis. In this paper, we describe our approaches used for sentiment analysis in twitter (task 9) organized in SemEval 2014. This task tries to determine whether the sentiment orientations conveyed by the whole tweets or pieces of tweets are positive, negative or neutral. To solve this problem, we extracted several simple and basic features considering the following aspects: surface text, syntax, sentiment score and twitter characteristic. Then we exploited these features to build a classifier using SVM algorithm. Despite the simplicity of features, our systems rank above the average.
Fast speaker adaptation of large vocabulary continuous density HMM speech recognizer using a basis transform approach

Maximum likelihood transformation-adaptation techniques have proven successful, but it is believed that faster convergence to speaker dependent (SD) performance can be achieved if we incorporate some form of a-priori knowledge in the adaptation process. In this paper, instead of estimating one linear transform per class of models for each new speaker, we transform the speaker-independent (SI) models using multiple linear transforms and a weight vector. To reduce the number of adaptation parameters, the multiple linear transforms are generated from training speakers and the adaptation parameters consist of a single weight vector per class. This can be seen as incorporating a-priori knowledge to our estimation process. Experiments conducted on the Spoken Language Translator database in the Swedish language using SRI's DECIPHER/sup TM/ system, show that the new method outperforms maximum likelihood linear regression on very limited adaptation data.
The Gordon Gekko Effect: The Role of Culture in the Financial Industry

Culture is a potent force in shaping individual and group behavior, yet it has received scant attention in the context of financial risk management and the recent financial crisis. I present a brief overview of the role of culture according to psychologists, sociologists, and economists, and then describe a specific framework for analyzing culture in the context of financial practices and institutions, a framework in which three questions are addressed: (1) What is culture? (2) Does it matter? and (3) Can it be changed? I illustrate the utility of this framework by applying it to five concrete situations — the collapse of Long-Term Capital Management, the fall of AIG Financial Products, the use by Lehman Brothers of “Repo 105,” Societe Generale’s rogue trader, and the Securities and Exchange Commission’s handling of the Madoff Ponzi scheme — and conclude with a proposal to change culture via “behavioral risk management. ”
A Prediction Model for Taiwan Tourism Industry Stock Index

Investors and scholars pay continuous attention to the stock market, as each day, many investors attempt to use different methods to predict stock price trends. However, as stock price is affected by economy, politics, domestic and foreign situations, emergency, human factor, and other unknown factors, it is difficult to establish an accurate prediction model. This study used a back-propagation neural network (BPN) as the research approach, and input 29 variables, such as international exchange rate, indices of international stock markets, Taiwan stock market analysis indicators, and overall economic indicators, to predict Taiwan’s monthly tourism industry stock index. The empirical findings show that the BPN prediction model has better predictive accuracy, Absolute Relative Error is 0.090058, and correlation coefficient is 0.944263. The model has low error and high correlation, and can serve as reference for investors and relevant industries.
ESET methylates UBF at K232/254 and regulates nucleolar heterochromatin plasticity and rDNA transcription

The remodeling of chromatin in the nucleolus is important for the control of ribosomal DNA (rDNA) transcription and ribosome biogenesis. Herein, we found that upstream binding factor (UBF) interacts with ESET, a histone H3K9 methyltransferase and is trimethylated at Lys (K) 232/254 by ESET. UBF trimethylation leads to nucleolar chromatin condensation and decreased rDNA transcriptional activity. UBF mutations at K232/254A and K232/254R restored rDNA transcriptional activity in response to ESET. Both ESET-ΔSET mutant and knockdown of ESET by short hairpin RNA reduced trimethylation of UBF and resulted in the restoration of rDNA transcription. Atomic force microscopy confirmed that UBF trimethylated by ESET modulates the plasticity of nucleolar chromatin. We further demonstrated that UBF trimethylation at K232/254 by ESET deregulates rDNA transcription in a cell model of Huntington’s disease. Together, our findings show that a novel epigenetic modification of UBF is linked to impaired rDNA transcription and nucleolar chromatin remodeling, which may play key roles in the pathogenesis of neurodegeneration.
The Intensity of the Insight Experience in Problem Solving: Structural and Dynamic Properties

iii Acknowledgements.iv Table of contents.v List of Tables . ix List of Figures . x List of Figures . x Introduction.1 1. Research on insight . 4 1.1. Gestalt research on insight . 4 1.2. Information processing theories of insight . 9 1.2.1. Suddenness of insight . 9 1.2.2. Taxonomy of insight problems . 10 1.2.3. Explanations of insight . 12 1.2.3.1. Incubation stage hypotheses . 12 1.2.3.2. Search for a new representation.14 1.2.3.3. Representational change theory . 15 1.2.3.4. Progress monitoring theory.17 1.2.4. Sources of difficulty in insight problems.19 1.2. 5. Measuring restructuring . 21 1.2. 6. Dynamic properties of insight problem solving.23 1.3. Critical summary.24 2. Theoretical framework.26 2.1. Degree of restructuring . 27 2.1.1. The amount of change in insight problems.28 2.1.2. Quantification of restructuring proposed by Knoblich and colleagues (1999) 31 2.1.2.1. Levels of problem representation.31 2.1.2.2. Constraints in matchstick equations.31 2.1.2.3. Mapping between constraints and levels of representation . 32 2.1.2.4. Evaluation of the approach . 33
Mapping ethnic migration in mainland China from the early 1960s to 2010

This study aims to map ethnic migration activities associated with a significant change in the mix of ethnicities for a given area in China from the early 1960s to 2010, and to ascertain where and among which ethnic groups such activities were prevalent in the past 50 years. To our knowledge, this is the first effort toward a nationwide mapping of ethnic migration in China in the past 50 years that has been undertaken. To achieve this, we utilized the Geo-referencing of ethnic groups (GREG) dataset, a widely used ethnic distribution dataset developed by Weidmann et al. (2010); the LandScan 2010 population grid; and 2010 census data for China. The original data in the GREG dataset are drawn from the well-known 1964 Soviet Atlas Narodov Mira. The methodology used builds on the following rationale: if there is no ethnic migration, then for each administrative region such as a county, the estimated population for each ethnic group using GREG and LandScan should be consistent with the ethnic population census data within that county. Otherwise, we can assume that there have been several ethnic migration activities during the analysis period. We thus overlay the GREG data with the national county administrative map and censusadjusted LandScan 2010 to derive the estimated ethnic population for each county in 2010 and compare this data array with the 2010 population census data at the county level and compute Pearson’s r. If there has not been significant ethnic migration from the early 1960s to 2010, Pearson’s r should be very close to 1; otherwise, it should be closer to 0. The first map shows trends in ethnic migrations activities during the analysis period using a rule of thumb for interpreting correlation coefficients by Hinkle et al. (2003) (Figure 1). For counties with moderate, substantial, and extensive ethnic migration activities (Pearson’s r lower than 0.7), we identified major ethnic groups that penetrated the living areas of other ethnic groups as well as ethnic groups whose living areas were penetrated by other ethnic groups. Based on the results, we drew up five maps for the Han, and identified four ethnic
Differential regulation of transcription termination occurring at two different sites on the μ–δ gene complex

The progression of polymerases across the m‐d Ig heavy chain gene complex is characterized by two termination events occurring at different sites on the transcription unit and at different times during B cell differentiation. We have utilized two mouse strains to analyze the regulatory determinants for these events in primary B cells. In the transgenic pm.mdRatt strain a 1160 bp intervening DNA segment (the att site) has been inverted. This mutation results in the abrogation of transcription termination that occurs in early B cells. Using a novel method that takes advantage of an internal ribosome entry site we have further restricted the size of the segment that is needed for inducing transcription termination in transfectants. This 200 bp termination-inducing sequence operates in tumor equivalents of early but not mature B cells and the activity is correlated with differential binding of nuclear proteins. To explore the regulatory basis for the change in site of transcription termination upon B cell activation we have examined the mS ‐/‐ deletion mutant strain in which the μS poly(A) site has been eliminated. The results suggest that polyadenylation at the μS site plays a dominant but not exclusive role in regulating transcription termination in activated B cells.
The outburst duration and duty cycle of GRS 1915+105

The extraordinarily long outburst of GRS 1915+105 makes it one of the most remarkable lowmass X-ray binaries (LMXBs). It has been in a state of constant outburst since its discovery in 1992, an eruption which has persisted � 100 times longer than those of more typical LXMBs. The long orbital period of GRS 1915+105 implies that it contains large and massive accretion disc which is able to fuel its extreme outburst. In this p aper, we address the longevity of the outburst and quiescence phases of GRS 1915+105 using Smooth Particle Hydrodynamics (SPH) simulations of its accretion disc through many outburst cycles. Our model is set in the two-α framework and includes the effects of the thermo-viscous instability, tidal torques, irradiation by central X-rays and wind mass loss. We explore the model parameter space and the examine the impact of the various ingredients. We predict that the outburst of GRS 1915+105 should last a minimum of 20 years and possibly up to � 100 years if X-ray irradiation is very significant. The predicted recurrence times are of the o rder of 10 4 years, making the X-ray duty cycle a few 0.1%. Such a low duty cycle may mean that GRS 1915+105 is not an anomaly among the more standard LMXBs and that many similar, but quiescent, systems could be present in the Galaxy.
ON COMPUTER-BASED AND HANDWRITTEN ESSAY TESTS

The purpose of this study was to determine if there were differences in postsecondary marketing student performance on essay tests based on test format (i.e., computer-based or handwritten). Specifically, the variables of performance, test completion time, and gender were explored for differences based on essay test format. Results of the study indicate that there was no significant difference in postsecondary marketing student scores based on test format. There was, however, a significant difference in test completion time based on essay format. Postsecondary marketing students completed the computer-based essay test significantly faster than they did the handwritten essay test. Implications for postsecondary marketing educator are also discussed.
Prediction of Market Capital for Trading Firms through Data Mining Techniques

The ultimate goal of data mining is prediction- and predictive data mining is the most common type of data mining and one that has most direct business applications. This paper discusses how one can apply data mining to design a market capital prediction system for trading firms[1]. The dataset is normalized and trained. The paper delves into the field of neural networks and shows how it can be utilized, in combination with the Graphical user Interface of MATLAB, GUIDE, to make accurate predictions. When implemented, the trained system can be used to forecast the market capital for a particular combination of input parameters. The accuracy of this method demonstrates its utility as a predictive tool.
An Exploratory Study of the Impact of Code Smells on Software Change-proneness

Code smells are poor implementation choices, thought to make object-oriented systems hard to maintain. In this study, we investigate if classes with code smells are more change-prone than classes without smells. Specifically, we test the general hypothesis: classes with code smells are not more change prone than other classes. We detect 29 code smells in 9 releases of Azureus and in 13 releases of Eclipse, and study the relation between classes with these code smells and class change-proneness. We show that, in almost all releases of Azureus and Eclipse, classes with code smells are more change-prone than others, and that specific smells are more correlated than others to change-proneness. These results justify a posteriori previous work on the specification and detection of code smells and could help focusing quality assurance and testing activities.
Problems of Accuracy in the Prediction of Software Quality from Directed Tests(cid:0)

Whensoftwarequalityistobeevaluatedfromtestdata,theevaluationmethodofchoiceisusuallytoconstructa reliabilitymodel. Thesemodelsuseempiricaldataandassumptionsaboutthesoftwaredevelopmentprocess,andthey usuallyresultinestimatesofthesoftware’spronenesstofailure. Butanotherparadigm—onethatseekstoestablish acertainconﬁdencethatthesoftwarehashighquality—alsoappearsoccasionally. Inthispaper,weattempttogivea unifyingdescriptionofthatparadigm,andwediscussitsusefulnessinsoftwaretesting. This analysis method, which we call probable approximate correctness analysis after a similar paradigm in machinelearning,emphasizestheaccuracyofqualityestimates. Wewilldiscussitsuseintwosituationswhereithas notpreviouslybeenapplied: thecasewheresoftwareisbeingdevelopedormaintained,andthecasewheresoftware testingisnotrepresentativeoftheenvironmentwheretheprogramwilleventuallybeused. Ourgoalistoexplicatethe presentusefulness,limitations,andfuturepromiseofthisdevelopingparadigm.
LaSEWeb: automating search strategies over semi-structured web data

We show how to programmatically model processes that humans use when extracting answers to queries (e.g., "Who invented typewriter? ", "List of Washington national parks") from semi-structured Web pages returned by a search engine. This modeling enables various applications including automating repetitive search tasks, and helping search engine developers design micro-segments of factoid questions. We describe the design and implementation of a domain-specific language that enables extracting data from a webpage based on its structure, visual layout, and linguistic patterns. We also describe an algorithm to rank multiple answers extracted from multiple webpages. On 100,000+ queries (across 7 micro-segments) obtained from Bing logs, our system LaSEWeb answered queries with an average recall of 71%. Also, the desired answer(s) were present in top-3 suggestions for 95%+ cases.
Two-Factor Worm Propagation Model in Cloud Security Network

Based on the review of recent development of evolutionary computation and the principle of free energy minimization of thermodynamics, a new thermodynamics evolutionary algorithm (TDEA) for solving six-hump camel back function optimization problem is proposed. Numerical experiments are conducted to measure the performance of thermodynamics evolutionary algorithm. The results show that thermodynamics evolutionary algorithm is of potential to obtain global optimum or more accurate solutions than other evolutionary methods.
A study on several machine learning methods for estimating cabin occupant equivalent temperature

Occupant comfort oriented Heating, Ventilation and Air Conditioning (HVAC) control rises to the challenge of delivering comfort and reducing the energy budget. Equivalent temperature represents a more accurate predictor for thermal comfort than air temperature in the car cabin environment, as it integrates radiant heat and airflow. Several machine learning methods were investigated with the purpose of estimating cabin occupant equivalent temperature from sensors throughout the cabin, namely Multiple Linear Regression, MultiLayer Perceptron, Multivariate Adaptive Regression Splines, Radial Basis Function Network, REPTree, K-Nearest Neighbour and Random Forest. Experimental equivalent temperature and cabin data at 25 points was gathered in a variety of environmental conditions. A total of 30 experimental hours were used for training and evaluating the estimators' performance. Most machine learning tehniques provided a Root Mean Square Error (RMSE) between 1.51 °C and 1.85 °C, while the Radial Basis Function Network performed the worst, with an average RMSE of 3.37 °C. The Multiple Linear Regression had an average RMSE of 1.60 °C over the eight body part equivalent temperatures and also had the fastest processing time, enabling a straightforward real-time implementation in a car's engine control unit.
Unit Testing Tool Competition — Round Four

This paper describes the methodology and results of the 4th edition of the Java Unit Testing Tool Competition. This year's competition features a number of infrastructure improvements, new test effectiveness metrics, and the evaluation of the test generation tools for multiple time budgets. Overall, the competition evaluated four automated test generation tools. This paper details the methodology and contains the full results of the competition.
Generating high quality data for the protection of modern critical infrastructures

This paper discusses the main issues regarding the procedures for generating High Quality Data (HQD) as support for conducting realistic cyber security studies on Modern Critical Infrastructures (CI). It identifies the most important requirements of what constitutes HQD: accuracy/realism, representation, and completeness. Based on these requirements, it discusses two strategies to achieve these requirements: the data collection strategy and the data generation strategy. While in the traditional Information & Technologies Communication (ICT) sector we find a variety of freely available datasets, in CI research data sources are scarce and of limited size. On the other hand, the data generation strategy has given birth to a new body of research built on the development of simulation software and of research testbeds. The paper describes two frameworks aimed at facilitating the generation of HQD for CI security research. Experimental results including the Tennessee-Eastman chemical process and the IEEE 14-bus electricity grid demonstrate the effectiveness of the developed frameworks.