Miracle-dz/UniFAR-FTUs huggingface dataset:
Women with false positive screening mammograms: how do they cope?

Objectives To assess the long term psychological impact on women who were recalled for further investigation after mammography screening and to find any factors that might predict coping ability in order to identify those subjects who require additional support at an earlier stage. Setting Counties of Västerbotten and Västernorrland, Sweden. Methods A prospective design was used in which 252 recalled women completed questionnaires twice—once within a week of having received the all-clear and again at follow up six months later. A group of 1104 randomly selected, screen negative women were followed up in the same way for comparison. The questionnaire included the Psychological Consequences Questionnaire (PCQ) and basic sociodemographic data. The main outcome measure was the total score on the PCQ at six months. Results Of the 252 women, 235 (93%) completed both questionnaires. In the control group, 987 (89.4%) women responded. Six months after the all-clear, recalled women were still significantly more anxious (p<0.001) than those who had been screened but not recalled. The strongest predictor of psychological distress at six months was the PCQ score at the first measurement. Other predictors were a low level of education, living in high density urban areas, and having only one child or no children at all. Widows appeared to cope better than other women. Conclusions It is possible to define a group of women with false positive results who are already at risk of coping less effectively at the time of recall. Offering these women counselling or other types of support should be considered.
Big Data and Analytics in the Modern Audit Engagement: Research Needs

SUMMARY: Modern audit engagements often involve examination of clients that are using Big Data and analytics to remain competitive and relevant in today's business environment. Client systems now are integrated with the cloud, the Internet of Things, and external data sources such as social media. Furthermore, many engagement clients are now integrating this Big Data with new and complex business analytical approaches to generate intelligence for decision making. This scenario provides almost limitless opportunities and the urgency for the external auditor to utilize advanced analytics. This paper first positions the need for the external audit profession to move toward Big Data and audit analytics. It then reviews the regulations regarding audit evidence and analytical procedures, in contrast to the emerging environment of Big Data and advanced analytics. In a Big Data environment, the audit profession has the potential to undertake more advanced predictive and prescriptive-oriented analytics. The next s.
Analysis-Aware Approach to Improving Social Data Quality

In the era of real time big data stream processing, the past decade has witnessed emergence of wide variety of applications to tap into live social data feed to gain awareness about events, opinions and sentiments of the community. Social data has the potential to bring new functionalities and improvements in a wide variety of domains from Emergency Response to Political Analysis. Thus, there is an increasing demand for executing up-to-the-minute analysis tasks on top of these dynamic data sources by modern applications. Such new requirements have created new challenges for traditional data processing techniques. In this thesis, we respond to some of these challenges.First, we explore the problem of online adaptive topic focused tweet acquisition. Specifically, we propose a Tweet Acquisition System (TAS), that iteratively selects phrases to track according to a reinforcement learning algorithm. The selection follows an explore-exploit policy to approximate the effectiveness of different phrases in retrieving relevant tweets based on Bayesian inferences. We also develop a tweet relevance model, which enables checking the relevance of collected tweets to the topic of interest based on multiple criteria. The objective of TAS is to improve the recall of collected relevant tweets. Our experimental studies show significant improvements over the state-of-the-art, furthermore the performance gap increases when the topics are more specific.Subsequently, efficient processing of top-k mentioned entities query posed on a stream of tweets has become a key part of a broad class of real-time applications, ranging from content search to marketing. Given that words are often ambiguous, entity linking becomes an important step towards answering such queries. Furthermore, the continuous and fast generation of tweets makes it crucial for such applications to process those queries at an equally fast pace. In order to address these requirements, we propose TkET (pronounced ticket) as an analysis-aware entity linking framework for efficiently answering top-k entities query over Twitter stream in an sliding window fashion. The comprehensive empirical evaluation of the proposed solution demonstrates its significant advantage in terms of efficiency over the traditional techniques for the given problem settings.
Comparison of shear strength of soldered SMD resistors for various solder alloys

Mechanical stability of solder joints has influence on total reliability of electronic products. Mechanical stress affect on properties of solder joints during function, transport and storage of the electronic products. A method which is commonly used in electronic industry to classify the mechanical properties and reliability of solder joints is shear test. This article deals with the comparison of mechanical stability of soldered joints from the point of shear strength of soldered SMD resistors. Three types of solder pastes, one lead Sn62Pb36Ag2 and two lead free Sn42Bi58 and Sn96.5Ag3Cu0. 5, were used for solder joint preparation. In addition, influence of solder paste amount on shear strength of soldered SMD component, were compared. The type of solder paste and its applied amount together with the temperature profile are interesting parameters from point of economic aspects, especially in case of mass production, where it is possible to achieve considerable savings. The results shows, that the amount of solder paste has influence on the share strength of solder joins. The best results, highest share strength, have been achieved for Sn96.5Ag3Cu0. 5 solder paste.
Joint Lifetime Financial, Work and Health Decisions: Thrifty and Healthy Enough for the Long Run?

Lifetime financial-, work- and health-related decisions made by agents are intertwined with one another. Understanding how these decisions are made is essential to gauge if saving in financial, retirement and human assets is adequate or not. This paper numerically solves, simulates, and structurally estimates a dynamic life cycle model of allocations (consumption/savings, leisure/work and health expenditures), statuses (health, financial and pension wealth) and welfare, allowing for (partially) adjustable exposure to morbidity and mortality risks. Using the simulated life cycle variables as benchmark, our results show that observed choices are not fully consistent with an optimal, forward-looking strategy. Whereas financial savings and pension claims are both adequate, individuals in the data are not healthy enough, and consequently face a shorter life horizon than expected. Moreover, full insurance, and age-increasing wages would optimally point to more spending and less leisure to maintain health than currently observed. As a consequence, observed post-retirement income is too low, and explains a sharp drop in consumption after 65 that is inconsistent with optimizing behavior. Relaxing assumptions on full insurance and pension regimes only partially alleviates these discrepancies.
Tobacco quitlines need to assess and intervene with callers' hazardous drinking.

BACKGROUND Based on published data showing that daily smokers have high rates of hazardous drinking and higher rates of smoking relapse, we hypothesized that New York State Smokers' Quitline (NYSSQL) callers would exhibit elevated rates of risky drinking and risky drinking callers would report lower rates of smoking cessation. METHODS We assessed rates of hazardous drinking among 88,479 callers to the NYSSQL using modified NIAAA guidelines. Using 2 routine NYSSQL short-term follow-up interviews (n = 14,123 and n = 24,579) and a 3-month follow-up interview (n = 2,833), we also compared smoking cessation rates for callers who met criteria for hazardous drinking compared to moderate drinkers and nondrinkers. RESULTS At baseline, 56% of callers reported drinking, and 23% reported hazardous drinking using modified NIAAA guidelines. Hazardous drinkers did not differ on measures of smoking cessation outcomes compared to nondrinkers but did have lower smoking cessation rates compared to persons who reported moderate alcohol consumption for the enhanced services program 1-week follow-up (adjusted OR [95% CI] = 1.09 [1.01, 1.17], p = 0.04) and the standard 2-week follow-up (adjusted OR [95% CI] = 1.17 [1.07, 1.29], p = 0.001). CONCLUSIONS Nearly a quarter of smokers calling the NYSSQL reported a hazardous drinking pattern, which was associated with lower cessation outcomes compared to those who reported a moderate drinking profile. Given the large number of high-risk drinkers who can be identified through a quitline, tobacco quitlines may provide a venue for providing brief alcohol interventions to these high-risk drinkers. Future studies should evaluate whether a brief alcohol intervention would result in improved smoking cessation rates for hazardous drinking smokers.
Cigarette Smoking and Depressive Symptoms Among Hispanic/Latino Adults: Results From the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).

INTRODUCTION In the present study, we investigated associations among cigarette smoking, smoking cessation treatment, and depressive symptoms in Hispanic/Latino adults. METHODS The multisite prospective population-based Hispanic Community Health Study/Study of Latinos (HCHS/SOL) enrolled a cohort of Hispanic/Latino adults (aged 18-74) from diverse backgrounds (n = 16,412) in 4U.S. communities (Chicago, San Diego, Miami, and Bronx). Households were selected using a stratified 2-stage probability sampling design and door-to-door recruitment, and sampling weights calibrated to the 2010U.S. Population Census. Hispanic/Latino individuals of Dominican, Central American, South American, Cuban, Mexican, and Puerto Rican background were considered. Cigarette smoking, smoking cessation treatment, and depressive symptoms were measured by self-report. RESULTS Results indicated that current smokers had greater odds for significant depressive symptoms (CES-D score ≥ 10) than never smokers in all Hispanic background groups [odds ratio (OR) > 1.5]. Depressed persons were not more likely to receive prescribed smoking cessation medications from a doctor (OR = 1.43, 95% CI = 0.98-2.08), take over-the-counter medications (OR = 1.11, 95% CI = 0.75-1.66), or receive psychotherapy (OR = 1.02, 95% CI = 0.57-1.85). CONCLUSIONS In conclusion, these findings suggest that the positive association between smoking status and depressive symptoms is present in all examined Hispanic/Latino background groups.
Combinando Multi-Visões através de um Algoritmo de Nuvens de Partículas

Classification problems can use several representations to express the same concept. Videos, for example, can be represented by their image or sound features. In recent years, researchers start to integrate these representations into models called multi-view, which can significantly improve the outcome of classification. This paper presents a study on two multi-view datasets, and introduces a new algorithm based on particle swarm optimization to weight views according to their relevance. As a result, we create MultiViL, an open-source tool for multi-view classification. Resumo. Problemas de classificação podem utilizar diversas representações de um domı́nio do conhecimento. Por exemplo, um vı́deo pode ser representado utilizando caracterı́sticas de som ou imagem. Nos últimos anos, pesquisadores passaram a integrar essas representações em modelos denominados multivisão, que integram atributos de visões diferentes para tornar a classificação mais robusta. Este artigo apresenta um estudo sobre o aprendizado multivisão em duas bases de dados, e introduz um algoritmo baseado em nuvens de partı́culas para ponderar as visões dos classificadores de acordo com sua significância. Como resultado, geramos a MultiViL, uma ferramenta de código aberto para classificação multi-visão.
The Political Cost of Corruption: Scandals, Campaign Finance, and Reelection in the Brazilian Chamber of Deputies

While corruption is widely disapproved of, some corrupt politicians continue to win elections. We tackle this paradox by examining the effects of malfeasance scandals in politicians’ behavior. In particular, we focus on their campaign finance strategies and career choices. We explore these issues empirically with an original dataset that includes all lower-house members of Congress (MCs) in Brazil from 1995 to 2010. Although tainted incumbents tend to be penalized electorally, we show that campaign spending attenuates this effect. These results are robust, controlling for a host of potential confounders and biases. Hence, we offer a first exploration of incumbents’ strategies to avoid the electoral cost of their publicized wrongdoings. Above a certain threshold of funding, Brazilian members of Congress become impervious to negative exposure, regardless of the severity of their ethical and/or criminal violations. These results carry important normative consequences in terms of regulating campaign financing as a means of improving accountability.
Housing Booms and Busts and Local Fiscal Policy

This paper examines how local governments adjust their spending, savings and taxes in response to a temporary revenue windfall generated by a housing boom and how they cope with the inevitable shortfall that appears during the bust. We focus on Spanish local governments given the intensity of the last housing boom-bust experienced there and the large share of construction-related revenues they obtain. We find, first, that just a small share of the boom windfall was saved, with revenues being used primarily to increase spending (above all, current spending) and (to a lesser extent) cut taxes. Second, we find that the failure to save during the boom is higher in places with less informed voters and more contested elections. Third, we also examine what happens during the bust, and find that these governments had to cut abruptly their spending (above all, capital), raise taxes, and allow deficits to grow. Finally, in places wit less informed voters and more contested elections local governments had more trouble in adjusting during the bust, and they tend to rely more on spending cuts than on tax increases.
Tunnel junctions of unconventional superconductors.

The phenomenology of Josephson tunnel junctions between unconventional superconductors is developed further. In contrast to s-wave superconductors, for d-wave superconductors the direction dependence of the tunnel matrix elements that describe the barrier is relevant. We find the full I-V characteristics and comment on the thermodynamical properties of these junctions. They depend sensitively on the relative orientation of the superconductors. The I-V characteristics differ from the normal s-wave RSJ-like behavior.
A State-Space Approach to Robust Multiuser Detection

In this paper, we develop a state-space approach to the blind multiuser detection problem with robustness against mismatches in the desired user signature and the time-varying number of users in the channel. The solution is obtained adaptively using a second-order extended Kalman filter (EKF) and requires only O(L2) operations per iteration, where L is the dimension of the subspace containing the signatures of all the users. We also present a state-space approach to the decision directed multiuser detection problem and an algorithm for switching between robust blind and decision directed detection. The proposed switching algorithm is based on using the normalized innovation square (NIS) of the blind detector to test for its convergence and the NIS of the decision directed detector to detect nonstationarities. Thus, it combines the advantages of both these detection schemes and can achieve an output signal- to-interference-plus-noise ratio (SINR) comparable to that of the minimum mean square error (MMSE) detector without any training, even in the presence of mismatches in the desired user signature. Therefore, it is well suited to practical nonstationary environments where users repeatedly enter and leave the system making the cost of retraining un affordable.
Modified PAXgene™ method allows for isolation of high-integrity total RNA from microlitre volumes of mouse whole blood

Analysis of gene expression is often used to evaluate the effects of experimental manipulations in laboratory animals. Blood is a rich source of potential biomarkers, including gene expression information, which may be obtained from whole blood. When compared with the end of a study, when whole blood samples can be easily obtained for gene expression measurements, the limiting volumes of whole blood obtainable from animals during the course of an experiment requires a method for RNA isolation from a minimal volume of whole blood. The PAXgene™ Blood RNA Extraction System originally designed for isolation of total RNA from 2.5 mL of human whole blood, was modified and successfully used to isolate high-integrity total RNA from as little as 50 μL of mouse whole blood. Fifty microlitres of mouse whole blood yielded an average of 2.3 μg highly intact total RNA, of sufficient quality and quantity allowing for multiple gene expression determinations. The utility of this method was demonstrated by confirming the time- and dose-dependent upregulation of haem oxygenase-1 (Hmox1) mRNA in response to a single injection of cobalt protoporphyrin. The successful isolation of total RNA from small volumes of mouse whole blood can allow for serial sampling on the same animals, thereby reducing the number of animals required for experimentation.
Shadow detecting algorithms research for moving objects base on self-adaptive background

The main difficulties in intelligent video monitor is how to detect and eliminate the shadow in the scene. It uses an improved detecting algorithm which is based on self-adaptive background to detect the position and the shape of objects. Then according to the shadow's characters such as the color variation and the structure, two shadow detection algorithms which respectively based on the RGB color model and the HSV color model are introduced. In simulation experiment, the two shadow detection algorithms are analyzed on the shadow detection rate, the shadow discriminating rate, the complexity and the real-time capability, and made the comparison with them. The results of experiment show that the shadow detection algorithms are adaptive and favourable effect on detecting shadow, and can be applied on different fields according to their advantages and disadvantages.
Binding of alpha-actinin to titin: implications for Z-disk assembly.

Titin is an exceptionally large protein (M.Wt. approximately 3 MDa) that spans half the sarcomere in muscle, from the Z-disk to the M-line. In the Z-disk, it interacts with alpha-actinin homodimers that are a principal component of the Z-filaments linking actin filaments. The interaction between titin and alpha-actinin involves repeating approximately 45 amino acid sequences (Z-repeats) near the N-terminus of titin and the C-lobe of the C-terminal calmodulin-like domain of alpha-actinin. The conformation of Z-repeat 7 (ZR7) of titin when complexed with the 73-amino acid C-terminal portion of alpha-actinin (EF34) was studied by heteronuclear NMR spectroscopy using (15)N-labeling of ZR7 and found to be helical over a stretch of 18 residues. Complex formation resulted in the protection of one site of preferential cleavage of EF34 at Phe14-Leu17, as determined by limited proteolysis experiments coupled to mass spectrometry measurements. Intermolecular NOEs show Val16 of ZR7 to be positioned close in space to the backbone of EF34 around Phe14. These observations suggest that the mode of binding of ZR7 to EF34 is similar to that of troponin I to troponin C and of peptide C20W to calmodulin. These complexes would appear to represent a general alternative binding mode of calmodulin-like domains to target peptides.
Precompetition Warm-up in Elite and Subelite Rhythmic Gymnastics

Guidetti L, di Cagno A, Gallota MC, Battaglia C, Piazza M, and Baldari C. Precompetition warm-up in elite and subelite rhythmic gymnastics. J Strength Cond Res 23(6): 1877-1882, 2009-The aim of this study was to investigate which precompetition warm-up methodologies resulted in the best overall performance in rhythmic gymnastics. The coaches of national and international clubs (60 elite and 90 subelite) were interviewed. The relationship between sport performance and precompetition warm-up routines was examined. A total of 49% of the coaches interviewed spent more than 1 hour to prepare their athletes for the competition, including 45 minutes dedicated to warm-up exercises. In spite of previous studies' suggestions, the time between the end of warm-up and the beginning of competition was more than 5 minutes for 68% of those interviewed. A slow run was the activity of choice used to begin the warm-up (96%). Significant differences between elite and subelite gymnasts were found concerning the total duration of warm-up, duration of slow running, utilization of rhythmic steps and leaps during the warm-up, the use of dynamic flexibility exercises, competition performances repetition (p < 0.01), and utilization of imagery (p < 0.05). A precompetition warm-up in rhythmic gymnastics would include static stretching exercises at least 60 minutes prior to the competition starting time and the active stretching exercises alternated with analytic muscle strengthening aimed at increasing muscle temperature. Rhythmic gymnastics coaches at all levels can use this data as a review of precompetition warm-up practices and a possible source of new ideas.
Directional performance of an algorithm used to locate microseismic events in underground mines

Locating local, low-intensity earthquakes, also referred to as microseismic events, in the vicinity of an underground mine is an important problem for both mine safety and mine planning. A microseismic event produces a finite time-duration acoustic signal that may have a small time-bandwidth product and passively locating such an event is a challenging task. Here a localization algorithm is described that hypothesizes a source location and aligns the sensor signals by removing the propagation delay for that hypothesized location. The hypothesized source location with the maximum energy, calculated from the sum of the aligned signals, is the estimate of the source position. This paper extends the algorithm to include signal weighting. An expression for the variance of location error is presented for the weighted algorithm and compared with the unweighted variance. A unique aspect of the variance expression is that it provides the performance in a direction specified by a three dimensional unit vector, eƒ, which is very useful for applications that restrict operations to tunnel structures, such as mining seismic and in-building acoustics.