Miracle-dz/UniFAR-FTUs huggingface dataset:
Projecting individualized absolute invasive breast cancer risk in Asian and Pacific Islander American women.

BACKGROUND The Breast Cancer Risk Assessment Tool (BCRAT) of the National Cancer Institute is widely used for estimating absolute risk of invasive breast cancer. However, the absolute risk estimates for Asian and Pacific Islander American (APA) women are based on data from white women. We developed a model for projecting absolute invasive breast cancer risk in APA women and compared its projections to those from BCRAT. METHODS Data from 589 women with breast cancer (case patients) and 952 women without breast cancer (control subjects) in the Asian American Breast Cancer Study were used to compute relative and attributable risks based on the age at menarche, number of affected mothers, sisters, and daughters, and number of previous benign biopsies. Absolute risks were obtained by combining this information with ethnicity-specific data from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) program and with US ethnicity-specific mortality data to create the Asian American Breast Cancer Study model (AABCS model). Independent data from APA women in the Women's Health Initiative (WHI) were used to check the calibration and discriminatory accuracy of the AABCS model. RESULTS The AABCS model estimated absolute risk separately for Chinese, Japanese, Filipino, Hawaiian, Other Pacific Islander, and Other Asian women. Relative and attributable risks for APA women were comparable to those in BCRAT, but the AABCS model usually estimated lower-risk projections than BCRAT in Chinese and Filipino, but not in Hawaiian women, and not in every age and ethnic subgroup. The AABCS model underestimated absolute risk by 17% (95% confidence interval = 1% to 38%) in independent data from WHI, but APA women in the WHI had incidence rates approximately 18% higher than those estimated from the SEER program. CONCLUSIONS The AABCS model was calibrated to ethnicity-specific incidence rates from the SEER program for projecting absolute invasive breast cancer risk and is preferable to BCRAT for counseling APA women.
The Chinese Version of Ruminative Responses Scale in High School Students:Its Reliability and Validity

Objective:To examine the reliability and validity of Ruminative Responses Scale.Methods:593 high school students were surveyed with RRS and CES-D.Results:①Because the path coefficient of item 14 was-0.07,the item was deleted.In confirmatory factor analysis,GFI=0.946,IFI=0.913,CFI=0.912,RMSEA=0.066;②The correlation coefficients between RRS\the three factors and CES-D ranged from 0.127-0.637;③The Cronbach's α coefficient of RRS was 0.85,and the Cronbach's α coefficients of the three subscales ranged from 0.63-0.82;the mean interitem correlation coefficients ranged from0.22-0.31. Conclusion:RRS-R has 21 items and acceptable psychometric quality.
Bacteriological Quality of Foods and Water Sold by Vendors and in Restaurants in Nsukka, Enugu State, Nigeria: A Comparative Study of Three Microbiological Methods

Bacterial count in prepared food or water is a key factor in assessing the quality and safety of food. It also reveals the level of hygiene adopted by food handlers in the course of preparation of such foods. This comparative study evaluated the bacteriological quality of food and water consumed in Nsukka, Enugu state, Nigeria, using three bacteria enumeration methods. Data obtained are assumed to reflect the level of personal and environmental hygiene in the study population. Ten types of foods—beans, yam, abacha, okpa, moimoi, pear, cassava foofoo, rice, agidi, and garri—and 10 water samples were evaluated for bacteriological quality, precisely determining the level of coliform contamination, using the most probable number (MPN), lactose fermentation count (LFC), and Escherichia coli count (ECC) methods. Bacterial counts differed significantly (p<0.05) among the various food samples. However, this did not differ significantly in the three methods used for the enumeration of coliforms, suggesting that any of the three methods could be validly used for such studies with confidence. Escherichia coli and Klebsiella pneumoniae were the two major coliforms identified among 98 coliform isolates obtained from the various food samples, of which 78 (79.6%) were assumed to be of human origin on account of their ability to grow at 44 °C. The level of coliform contamination in the food samples from vendors and restaurants (geometric mean count 7.64-9.21; MPN ≥50) were above the accepted 104 colony-forming unit/g or MPN ≤10 limits. The results of the study, therefore, call for stringent supervision and implementation of food-safety practices and regular education on food and personal hygiene among food vendors.
Developing a MOOC experimentation platform: insights from a user study

In 2011, the phenomenon of MOOCs had swept the world of education and put online education in the focus of the public discourse around the world. Although researchers were excited with the vast amounts of MOOC data being collected, the benefits of this data did not stand to the expectations due to several challenges. The analyses of MOOC data are very time-consuming and labor-intensive, and require and require a highly advanced set of technical skills, often not available to the education researchers. Because of this MOOC data analyses are rarely done before the courses end, limiting the potential of data to impact the student learning outcomes and experience. In this paper we introduce MOOCito (MOOC intervention tool), a user-friendly software platform for the analysis of MOOC data, that focuses on conducting data-informed instructional interventions and course experimentations. We cover important design principles behind MOOCito and provide an overview of the trends in MOOC research leading to its development. Although a work-in-progress, in this paper, we outline the prototype of MOOCito and the results of a user evaluation study that focused on system's perceived usability and ease-of-use. The results of the study are discussed, as well as their practical implications.
The State and Poverty Alleviation in Advanced Capitalist Democracies

We analyze the impact of the state on the incidence of poverty in the working-age population of 14 advanced capitalist democracies between 1970 and 1997 using an unbalanced panel design. We utilize poverty measures based on micro-level data from the Luxembourg Income Study in conjunction with pooled time series data from the Huber, Ragin and Stephens (1997) database. We argue that economic factors including de-industrialization and unemployment largely explain pre-tax, pre-transfer poverty rates of the working age population in advanced capitalist states. These rates, however, are theoretical as advanced democracies redistribute resources through taxes and transfers. We show that the extent of redistribution (measured as poverty reduction via taxes and transfers) is explained directly by welfare state generosity as well as constitutional structure (number of veto points) and the strength of the left, both in unions and in government.
Concolic Metamorphic Debugging

Debugging is challenging and labor-intensive. Debugging programs with weak or no oracle is even more difficult due to lack of passing and failing test runs as well as their comparisons. To address these challenges, we exploit metamorphic relations to construct new programs that are enhanced with synthesized oracle, and combine concolic testing and branch-switching debugging to localize potentially faulty places in original programs. We name our approach concolic metamorphic debugging (or Comedy for short). We experimentally evaluated Comedy with real-world Java programs. The experimental results reported that Comedy successfully generated debugging report for 88.4% of 2,330 faulty programs. The average branch distance between the reported locations and the real fault places is only 1.68. Besides, 36% of the debugging reports precisely locate the fault.
A novel Type-2 fuzzy directed hybrid post-filtering technique for efficient JPEG image artifact reduction

Image and video compression become very popular and intense field in recent decades, due to fast and high quality communication demand of visual information. Currently, JPEG and JPEG2000 are the most popularly used codec's for achieving image compression. Practically, on the low bit rate compression, it has been observed that the JPEG compressed images suffer from multifarious visual distortions. To address this problem effectively, this paper proposed an innovative Type-2 fuzzy directed hybrid post filtering technique, which is framed to suppress the artifacts generated in JPEG compressed images at low bit rate compression. The proposed technique addresses all three types of JPEG image artifacts: blocking, edges blurring, and aliasing. Furthermore, the proposed technique is structured with two stages to enhance the quality of JPEG compressed images. The first stage removes blocking artifacts using boundary smoothing and guided filtering techniques. The second stage reduces blurring and aliasing around the edges through Type-2 fuzzy directed local edge regeneration. To prove higher artifacts reduction efficiency of proposed work, a complete comparative performance evaluation with other existing JPEG artifact removal techniques has been also presented. This extensive performance analysis includes visual quality assessment of post-filtered images along with a subjective quality assessment on the basis of Peak Signal to Noise Ratio (PSNR) parameter. Performance evaluation illustrates that the proposed approach is efficient; provides PSNR improvement in the range of 0.2 to 1.1 dB as compared to the state of the art algorithms for all bitrates.
A Survey of Parallel Genetic Algorithms

Genetic algorithms (GAs) are powerful search techniques that are used successfully to solve problems in many different disciplines. Parallel GAs are particularly easy to implement and promise substantial gains in performance. As such, there has been extensive research in this field. This survey attempts to collect, organize, and present in a unified way some of the most representative publications on parallel genetic algorithms. To organize the literature, the paper presents a categorization of the techniques used to parallelize GAs, and shows examples of all of them. However, since the majority of the research in this field has concentrated on parallel GAs with multiple populations, the survey focuses on this type of algorithms. Also, the paper describes some of the most significant problems in modeling and designing multi-population parallel GAs and presents some recent advancements.
A Statistical Test for Information Leaks Using Continuous Mutual Information

We present a statistical test for detecting information leaks in systems with continuous outputs. We use continuous mutual information to detect the information leakage from trial runs of a probabilistic system. It has been shown that there is no universal rate of convergence for sampled mutual information, however when the leakage is zero, and under some reasonable conditions, we establish a rate for the sampled estimate, and show that it can converge to zero very quickly. We use this result to develop a statistical test for information leakage, and we use our new test to analyse a number of possible fixes for a time-based information leak in e-passports. We compare our new test with existing statistical methods, and we find that our test outperforms these other tests in almost all cases, and in one case in particular, ours is the only statistical test that can detect an information leak.
One-dimensional simulation of transmural heterogeneity of cardiac cellular electromechanics

Cardiac tissue exhibits transmural heterogeneous electromechanical characteristics which are responsible for normal activation, repolarization, contraction and relaxation in healthy hearts. Under abnormal conditions such as myocardial ischemia (MI), the original heterogeneity will be disrupted and may cause the heart out of function. In this paper, a transmural heterogeneous cellular electromechanics model has been developed. We used the model to simulate and validate transmural heterogeneity of the electrical properties and mechanical properties. In addition, the developed model was also used to simulate ventricular electrocardiograms (ECG) under normal and ischemia conditions on the multi-cellular 1-D fiber model. The results showed that our model could reproduce many transmural heterogeneous electromechanical features of the heart, and were in good accordance with experimental observations. The ECG under normal and ischemia conditions were compared to demonstrate the importance of the precise transmural heterogeneity.
Seeing a home away from the home : Distilling proto-neighborhoods from incidental data with Latent Topic Modeling

We report our initial experiments on a computational approach to neighborhood detection from community-authored location annotated content. Automated discerning of context from the physical environment is an important challenge in the age of mobile computing, where context awareness can often be a critical component in the design of pervasive applications. Furthermore, defining the context of a location, or a “neighborhood,” in an urban landscape is often a difficult task, since neighborhoods are often defined by intangible qualities such as shared function or community structure, rather than the prescribed geopolitical jurisdictions. In this study we seek to develop a data-driven definition of a neighborhood using topic modeling and socially annotated location data. We treat the question as a matter of latent topic discovery. Using incidental, geo-coded data gathered from locationsharing social networks, we show that we can discover canonical neighborhoods by analyzing co-occurence patterns in place categories. We report a qualitative evaluation of our approach, and interpret the validity of the discovered prototypical neighborhoods. We also discus future work and potential implications of our approach to the social sciences.
Online measurements of the emissions of intermediate-volatility and semi-volatile organic compounds from aircraft

Abstract. A detailed understanding of the climate and air quality impacts of aviation requires measurements of the emissions of intermediate-volatility and semi-volatile organic compounds (I/SVOCs) from aircraft. Currently both the amount and chemical composition of aircraft I/SVOC emissions remain poorly characterized. Here we characterize I/SVOC emissions from aircraft, using a novel instrument for the online, quantitative measurement of the mass loading and composition of low-volatility organic vapors. Emissions from the NASA DC8 aircraft were sampled on the ground 143 m downwind of the engines and characterized as a function of engine power from idle (4% maximum rated thrust) through 85% power. Results show that I/SVOC emissions are highest during engine idle operating conditions, with decreasing but non-zero I/SVOC emissions at higher engine powers. Comparison of I/SVOC emissions with total hydrocarbon (THC) measurements, VOC measurements, and an established emissions profile indicates that I/SVOCs comprise 10–20% of the total organic gas-phase emissions at idle, and an increasing fraction of the total gas-phase organic emissions at higher powers. Positive matrix factorization of online mass spectra is used to identify three distinct types of I/SVOC emissions: aliphatic, aromatic and oxygenated. The volatility and chemical composition of the emissions suggest that unburned fuel is the dominant source of I/SVOCs at idle, while pyrolysis products make up an increasing fraction of the I/SVOCs at higher powers. Oxygenated I/SVOC emissions were detected at lower engine powers (≤30%) and may be linked to cracked, partially oxidized or unburned fuel components.
Constructing identities

This article presents research undertaken with female headteachers in UK primary schools and explores several influential discourses in relation to female headteachers’ identities. It considers themes inherent in women’s narratives as they reflect upon their professional lives and discusses various identities inhabited by female leaders which emerge from the data. It also explores dominant discourses related to the masculine construction of leadership, women’s domestic responsibilities and women as enablers, which have a significant impact on women’s professional lives and upon the ways in which they are positioned. It notes that women’s narratives are shot through with ambiguity as they may inhabit several contradictory identities revealing qualities, characteristics and leadership styles which diverge from socially prescribed gender-appropriate behaviours. The article suggests that although there may appear to be a variety of identities from which women may select, there are limits to agency. It concludes that powerful discourses exist which constrain or facilitate ways of being, so impacting on leadership work and the professional lives of female headteachers. Consequently, the complex negotiations of women as they take up leadership roles in schools should be acknowledged.
Spoken Term Detection and Spoken Content Retrieval: Evaluations on NTCIR 11 SpokenQuery&Doc Task

In this paper, we report out experiments on NTCIR-11 SpokenDoc&Query task for spoken term detection (STD) and spoken content retrieval (SCR). In STD, we consider acoustic feature similarity between utterances over both word and sub-word lattices to deal with the general problem of open vocabulary retrieval with queries of variable length. In SCR, we modify term frequency using expected term frequency in the vector space model (VSM) to deal with the errors in the speech recognition. In addition, we utilize three techniques to improve the relevance of the rst-pass retrieval, that is, pseudo relevance feedback called Rocchio algorithm, query expansion using recurrent neural network language model (RNNLM), and lecture slide similarity feedback using random walk. Experiment results are shown for each task to indicate the improvement of the techniques we apply.
Republic of Korea

International migration in the Republic of Korea consists of the migration of foreign workers into the country and the migration of Koreans to other countries. The need for human capital has made it a destination country for foreign workers while economic development has given its nationals the option to emigrate. As a destination country, the share of foreigners to the total population is relatively small compared to other destination countries in Asia. The Ministry of Justice and the Ministry of Labor are the main sources for collecting data on international migration. Further improvements in data collection, production and dissemination are areas that need to be addressed.
The Educational Theory of John Dewey and its Influence on Educational Policy and Practice in Macedonia

The paper gives an overview of the impact that the educational theory of the American philosopher and educator John Dewey has had on education in Macedonia since the establishment of the educational system after the Second World War. Within this framework two periods are identified and analysed. One refers to forty-five years of socialist development, during which the traces of Dewey’s presence and influence are recognized in the policy documents that shaped the education in the Socialist Republic of Macedonia as part of the former Yugoslav federation. The analysis of the second period covers the last twenty-five years of development of education in the socio-political context of a sovereign state, and is focused on reform initiatives for improving the teaching process introduced in the 90s of the past century. They are marked by the implementation of three major international projects that altered the traditional teaching organization and methodology in elementary and secondary public schools in Macedonia: Active teaching-Interactive learning , Step by step and Reading and writing for critical thinking . The theoretical foundations of these projects are explored, and common elements that can be traced back to Dewey’s educational concepts and values are identified and discussed.
Training time reduction and performance improvements from multilingual techniques on the BABEL ASR task

In the IARPA sponsored program BABEL we are faced with the challenge of training automatic speech recognition systems in sparse data conditions in very little time. In this paper we show that by using multilingual bootstrapping techniques in combination with multilingual deep belief bottle neck features that are only fine tuned on the target language the training time of an LVCSR system can be essentially halved while the word error rate stays the same. We show this for recognition systems on Tagalog, making use of multilingual systems trained on the other four languages of the Babel base period: Cantonese, Pashto, Turkish, and Vietnamese.
Search-Based Testing of Ajax Web Applications

Ajax is an emerging Web engineering technology that supports advanced interaction features that go beyond Webpage navigation. The Ajax technology is based on asynchronous communication with the Web server and direct manipulation of the GUI, taking advantage of reflection.Correspondingly, new classes of Web faults are associated with Ajax applications.In previous work, we investigated a state-based testing approach, based on semantically interacting events. The main drawback of this approach is that exhaustive generation of semantically interacting event sequences limits quite severely the maximum achievable length, while longer sequences would have higher fault exposing capability. In this paper, we investigate a search-based algorithm for the exploration of the huge space of long interaction sequences, in order to select those that are most promising, based on a measure of test case diversity.