Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of adherence to nutrition-related cancer prevention guidelines among African American breast cancer survivors

Background Mortality rate for breast cancer is higher among African American (AA) women than for women of other racial/ethnic groups. Obesity, also higher among AA women, may increase the risk of breast cancer development and recurrence. Lifestyle factors such as healthy nutrition can reduce the rate of obesity and breast cancer. This study examined the determinants of adherence to nutrition-related cancer prevention guidelines among AA breast cancer survivors. Methods AA breast cancer survivors (n=240) were recruited from a breast cancer support group to complete a lifestyle assessment tool for this cross-sectional study. Chi-square test and ordinal logistic regression analysis were used to examine the relationship between adherence to nutrition-related cancer prevention guidelines and potential predictors of adherence. Results Majority of the survivors met the guideline for red and processed meat (n=191, 83.4%), but did not meet the guideline for fruits and vegetables (n=189, 80.4%). For survivors with annual household incomes < $25,000, the odds of meeting or partially meeting the guideline for fruits and vegetables was 75.4% less than for participants with incomes > $50,000 (OR= 0.25, 95% CI: 0.08, 0.80). Poor physical functioning (OR= 38.48, 95% CI: 2.26, 656.58), sleep disturbances (OR= 60.84, 95% CI: 1.61, 2296.02), and income > $50,000 (OR= 51.02, 95% CI: 1.13, 2311.70) were associated with meeting the guideline for red and processed meat. Conclusions Many AA breast cancer survivors are not meeting the nutrition-related cancer prevention guidelines. For this population, more interventions that enhance access to and consumption of healthy diets are needed.
The Nature of the Metal-Rich Thick Disk

We have traced the Galactic thick disk to its, to date, highest metallicities. Based on high-resolution spectroscopic observations of 187 F and G dwarf stars that kinematically can be associated either with the thin disk (60 stars) or with the thick disk (127 stars), we find that the thick disk stars reach at least solar metallicities, and maybe even higher. This finding is independent of the U_LSR, V_LSR and W_LSR velocities of the stars.
Distributed Detection and Fusion in a Large Wireless Sensor Network of Random Size

For a wireless sensor network (WSN) with a random number of sensors, we propose a decision fusion rule that uses the total number of detections reported by local sensors as a statistic for hypothesis testing. We assume that the signal power attenuates as a function of the distance from the target, the number of sensors follows a Poisson distribution, and the locations of sensors follow a uniform distribution within the region of interest (ROI). Both analytical and simulation results for system-level detection performance are provided. This fusion rule can achieve a very good system-level detection performance even at very low signal-to-noise ratio (SNR), as long as the average number of sensors is sufficiently large. For all the different system parameters we have explored, the proposed fusion rule is equivalent to the optimal fusion rule, which requires much more prior information. The problem of designing an optimum local sensor-level threshold is investigated. For various system parameters, the optimal thresholds are found numerically by maximizing the deflection coefficient. Guidelines on selecting the optimal local sensor-level threshold are also provided.
Novel Function of Sprouty4 as a Regulator of Stemness and Differentiation of Embryonic Stem Cells

Sprouty (Spry) genes encode inhibitors of the receptor tyrosine kinase signaling cascade, which plays important roles in stem cells. However, the role of Spry4 in the stemness of embryonic stem cells has not been fully elucidated. Here, we used mouse embryonic stem cells (mESCs) as a model system to investigate the role of Spry4 in the stem cells. Suppression of Spry4 expression results in the decreases of cell proliferation, EB formation and stemness marker expression, suggesting that Spry4 activity is associated with stemness of mESCs. Teratoma assay showed that the cartilage maturation was facilitated in Spry4 knocked down mESCs. Our results suggest that Spry4 is an important regulator of the stemness and differentiation of mESCs.
The Effects of R&amp;D Expenditures on Bondholders in Listed Firms

Research and development (R&D) investment is a kind of strategic behavior filled with high uncertainty and risk. Currently domestic relevant research on the R&D input value mostly emphasizes the enterprise R&D investment impact on shareholder wealth, and less about the trade-off between R&D investment impact on bondholders and shareholders. The present study uses revealed 42 listed Companies' R&D spending in 2007-2011 as the sample to examine the impact on firms stock value and debt value from the perspective of protecting the interests of bondholders. The results show that: For firms with high default risk, R&D increases have a positive impact on bond risk premium. Further, there is a wealth transfer from bondholders to stockholders. Neither of these results is found for firms with low default risk.
Tactile Object Familiarity in the Blind Brain Reveals the Supramodal Perceptual-Mnemonic Nature of the Perirhinal Cortex

This study is the first to investigate the neural underpinnings of tactile object familiarity in the blind during both perception and memory. In the sighted, the perirhinal cortex (PRC) has been implicated in the assessment of visual object familiarity—a crucial everyday task—as evidenced by reduced activation when an object becomes familiar. Here, to examine the PRC’s role in tactile object familiarity in the absence of vision, we trained blind participants on a unique memory-guided drawing technique and measured brain activity while they perceptually explored raised-line drawings, drew them from tactile memory, and scribbled (control). Functional magnetic resonance imaging (fMRI) before and after a week of training revealed a significant decrease in PRC activation from pre- to post-training (i.e., from unfamiliar to familiar) during perceptual exploration as well as memory-guided drawing, but not scribbling. This familiarity-based reduction is the first evidence that the PRC represents tactile object familiarity in the blind. Furthermore, the finding of this effect during both tactile perception and tactile memory provides the critical link in establishing the PRC as a structure whose representations are supramodal for both perception and memory.
A Probability Sampling Approach for Variance Minimization

A number of techniques for probability sampling without replacement (SWOR) have been suggested, although it is not clear which method is consistently superior in terms of statistical efficiency. Rao and Bayless (1969) empirically studied the stability of estimators of the population total for a variety of methods of unequal probability SWOR when selecting two units per stratum. One of their major conclusions is that when a stable estimator is required, Murthy’s (1957) method is preferred over the methods of Lahiri (1951), Raj (1956), Rao, Hartley and Cochran (1962), Brewer (1963), Fellegi (1963), Hanurav (1967), and probability proportional to size (PPS) sampling with replacement. One the other hand, Jessen (1969) proposed four interesting sampling schemes. One of them, labeled method 4, shows high efficiency in comparisons of variances of estimators relative to those of alternative SWOR selection schemes, including some of the above-mentioned methods. However, Jessen’s method may be difficult to employ in practical problems due to the arbitrariness and complexities of trials to determine the inclusion probabilities that are required for the variance formula for the estimator of the total population. In this paper, we first review Jessen’s method. Second, we suggest two probability sampling schemes using non-linear programming approaches to overcome certain disadvantages in carrying out Jessen’s method. Finally, we illustrate the practicality and statistical efficiency of our methods through application to several examples from the literature.
General Deformable Model Approach for Model-Based Reconstruction

In this paper we propose a general approach for performing both model-based reconstruction and segmentation. We extract geometric models from 3D datasets by deforming a reference model. Classical approaches either perform registration of a template by evaluating global transformations or use the deformable models framework to apply free-form deformations. Some authors have proposed to combine both approaches. In our approach we introduce an a priori knowledge about the geometry and the topology of the objects to recover. Furthermore we show in this paper the link between computing a global transformation on a model and applying an external force field to a deformable model. We thus deduce a computer-efficient hybrid deformation scheme allowing to control the number of degrees of freedom of the deformable models through a single parameter. We then present a general framework integrating registration, hybrid and free-form deformations that performs robust reconstruction and segmentation. We insist on the geometric quality of the retrieved models.
Text categorization on a multi-lingual corpus

This paper presents experiments with a hierarchical text categorizer on a multi-lingual (English, French) corpus. The results obtained are very similar for both languages. The results allow us to apply in the near future cross-language text categorization that can be used to support automatic translation to create multi-lingual topic glossary.
Efficient Content-Based Image Retrieval In a Distributed Environment

With the recent advances of distributed computing, those limitations of information retrieval from a centralized image collection can be removed by allowing distributed image data sources to interact with each other for both data storage sharing and query computation sharing. In this paper, we present our initial study of the design of a distributed image database system using the current Peer-to-Peer (P2P) Network. We propose a Firework Query Model for distributed information retrieval which aims to reduce the network traffic. We carry out experiments to show the distributed image retrieval system and the Firework information retrieval algorithm. The results show that the algorithm reduces the network traffic while increases the recall performance.
MusicGuide : Album Reviews on the Go

The cameras on mobile phones have untapped potential as input devices. In this paper, we present MusicGuide, an application that can be used to provide the user information on a music album on the go by simply using a photo of the album cover as the input. Relevant data on the album such as reviews and track samples are then collected from various sources on the web and presented to the user. Our experiments show that MusicGuide is robust against various transforms and artifacts in the input images, and it also has good performance in terms of accuracy, with recognition rates above 90%.
ANALYSIS OF FIELDER STARTS AND BENCH ABILITY ON AMERICAN PROFESSIONAL BASEBALL PLAYERS

The development of athletes or players depends on two aspects: nature and nurture. The former is the talent and qualification of the players themselves, while the latter is the training that consumes human, material and financial resources. Take professional baseball players as an example. Matching the talents of players and referring to the relevant starting rules of the professional baseball league, when the up-and-coming players are first discovered, focused training are used on them. By doing so, the value of the players would be effectively enhanced and the players are helped to seek a better way out. This can form a virtuous circle: the pellets get quality players, and the players get better results. That is to say, strengthening the training for the shortcomings of the players with the potential of the starting players can avoid unnecessary training and huge training expenses behind them, and greatly reduce the risk of career, so that the players have higher security in their short career, and get a win-win-win situation. This study is aimed at the schedule information of the American Baseball League teams. Through feature selection of data mining, this study analyzes the main relationships and key differences between starting player and bench player of second baseman and shortstop in League of Nations teams. It is found that the on base percentage and speed of the infielders is an important ability indicator for the starting position; whereas, the second baseman emphasizes on the attack and the shortstop focuses on fielding. This feature is verified by comparing the opinions of experts and commentators. Article visualizations:
Electromagnetic form factors of the nucleon and Compton scattering

▪ Abstract We review the experimental and theoretical status of elastic electron scattering and elastic low-energy photon scattering (with both real and virtual photons) from the nucleon. As a consequence of new experimental facilities and new theoretical insights, these subjects are advancing with unprecedented precision. These reactions provide many important insights into the spatial distributions and correlations of quarks in the nucleon.
Voting Coalitions and Minority Governments in Canada

In this paper, we analyze voting coalitions under the minority governments in the 38 th and 39 th Canadian Parliaments. We demonstrate that minority government support is driven by electoral incentives and policy issues. The main contention of this project is that voting coalitions are more likely to form along ideological lines—the Axelrod (1970)’s thesis. However, the analysis also demonstrates that voting coalitions form along a second dimension in the Canadian Parliament; mainly on issues related to federalism and the province of Quebec. We also provide some evidence to show that expected electoral gains can help explain why certain parties choose to support the government more. This study ultimately validates dierent theories of coalition voting under minority governments.
The five-factor model and individualism and collectivism in South Africa: Implications for personality assessment

The five-factor model (FFM) of personality is one of the prominent models in contemporary psychology and defines personality in terms of five broad factors, namely Neuroticism, Extraversion, Openness to Experience, Agreeableness and Conscientiousness. Recent research, however, questions the applicability of the FFM in non-Western cultures, suggesting that it is not exhaustive enough and that it does not account for some other personality factors, most notably Individualism and Collectivism. Yet, it remains the gold standard against which all personality instruments are compared. This study investigated whether the FFM of personality is related to Individualism and/or Collectivism in a sample of 272 South Africans from the general Johannesburg area. Individuals completed a questionnaire consisting of a demographic section, the Horizontal–Vertical Individualism/Collectivism scale and the NEO-PI-3. Exploratory factor analysis was used to analyse the data. The results indicated support for an Individualism–Collectivism dimension. These results are discussed within the context of the universal applicability of the FFM.
Assaying multiple 125I seeds with the well-ionization chamber SourceCheck4π 33005 and a new insert

Purpose To provide a practical solution that can be adopted in clinical routine to fulfill the AAPM-ESTRO recommendations regarding quality assurance of seeds used in prostate permanent brachytherapy. The aim is to design a new insert for the well-ionization chamber SourceCheck4π 33005 (PTW, Germany) that allows evaluating the mean air-kerma strength of up to ten 125I seeds with one single measurement instead of measuring each seed individually. Material and methods The material required is: a) the SourceCheck4π 33005 well-ionization chamber provided with a PTW insert to measure the air-kerma strength S K of one single seed at a time; b) a newly designed insert that accommodates ten seeds in one column, which allows measuring the mean S K of the ten seeds in one single measurement; and c) a container with ten seeds from the same batch and class of the seeds used for the patient implant, and a set of nine non-radioactive seeds. The new insert is characterized by determining its calibration coefficient, used to convert the reading of the well-chamber when ten seeds are measured to their mean S K. The proposed method is validated by comparing the mean S K of the ten seeds obtained from the new insert with the individual measurement of S K of each seed, evaluated with the PTW insert. Results The ratio between the calibration coefficient of the new insert and the calibration coefficient of the PTW insert for the SourceCheck4π 33005 is 1.135 ± 0.007 (k = 1). The mean S K of a set of ten seeds evaluated with this new system is in agreement with the mean value obtained from measuring independently the S K of each seed. Conclusions The new insert and procedure allow evaluating the mean S K of ten seeds prior to the implant in a single measurement. The method is faster and more efficient from radiation protection point of view than measuring the individual S K of each seed.
A speeded-up affine invariant detector

Local features extraction is one of the most important image processing algorithms, which can be widely used in object recognition, image registration, tracking, etc. To extract key points of an image, SIFT (Scale Invariant Feature Transform) is scale invariant and SURF (Speeded Up Robust Features) is more than three times faster than SIFT. But neither of them works well under large viewpoint angle change. ASIFT (Affine SIFT) is fully affine invariant thus working well when viewpoint angle is huge; but it cannot reach computational efficiency due to its complexity. A speeded-up affine invariant detector for local features extraction is proposed in this paper, which makes use of the affine invariance of ASIFT and the efficiency of SURF. Experimental results on image features extraction and matching demonstrate the robustness and efficiency of the proposed algorithm. Compared with the state-of-art methods, the proposed detector can keep affine invariant as ASIFT by only a quarter of its time consuming.
Design of Simulink Model to denoise ECG signal using various IIR & FIR filters

Electrocardiogram ECG signal is usually corrupted by several artifacts and these must be removed before diagnosis. This paper therefore presents the design of various FIR filters like Kaiser, Rectangular, Hamming, Hanning, Gaussian and Bartllet window techniques and FIR Equiripple Filter. IIR filters like Butterworth, Chebychev I & II and Elliptic Filters are also explored to remove the artifacts in ECG signal. To verify the usability of designed filters, noisy ECG signal is generated by adding random noise, white noise and 50 Hz interference (hum) to the 100m.mat ECG data sample taken from MIT-BIH database. Signal to noise ratio (SNR) is calculated to compare the performance of different filtering methods using Simulink Model. Results obtained show that FIR Equiripple filter gives a SNR of 7.71 for a 3rd order filter and IIR Elliptic filter has SNR of for first order filter and are therefore recommended.
A Middleware for Open CNC Architecture

The computer numerical control (CNC) system made up of personal computer plus motion controller card is a kind of the most popular open CNC system. For such system, a middleware is proposed whose function is to resolve the problem of G-code decoding. With the middleware, the G-code program can be compiled into the special object code sequence and then the machine control can be expediently implemented by the motion controller card according to the sequence. Being an independent component with highly general capability, the middleware improves the traditional interpret-mode. This paper describes the open CNC architecture and its solution based on the middleware, and expatiates the design and the object code format of the middleware as well.
Smoking is associated with first-ever incidence of mental disorders: a prospective population-based study.

AIMS It is well established that tobacco use is associated with mental disorders. However, the association between tobacco use and mental disorders has not yet been examined sufficiently in prospective, population-based studies. The current study is aimed at examining whether smoking is associated with first-ever incidence of mental disorders. DESIGN, SETTING AND PARTICIPANTS We conducted a prospective, population-based epidemiological study (the Netherlands Mental Health Survey and Incidence Study: NEMESIS) in which a representative sample of adults aged 18-64 years (n = 7076) were interviewed to establish the presence of a broad range of mental disorders. We re-interviewed them at 1 year (n = 5618; response 79.4%) and 3 years (n = 4796; 67.8%) after baseline. MEASUREMENTS The presence of mental disorders was assessed according to DSM-III-R criteria with the Composite International Diagnostic Interview (CIDI), which was administered by trained lay interviewers. Tobacco use was assessed by asking respondents whether they had smoked in the past year, and how many cigarettes they smoked. FINDINGS Subjects who smoked but never had a mental disorder in their life, had an increased risk of developing a mental disorder (P < 0.01), and this remained significant after correcting for major risk indicators of mental disorders. CONCLUSIONS Smoking is associated not only with the prevalence, but also with first-ever incidence of mental disorders. More research is needed to study the causal pathways.
Adjacency Pair Recognition in Wikipedia Discussions using Lexical Pairs

Adjacency pair recognition, a necessary component of discussion thread reconstruction, is the task of recognizing reply-to relations between pairs of discussion turns. Previously, dialogue act classification and metadata-based features have been shown useful in adjacency pair recognition. However, for certain forums such as Wikipedia discussions, metadata is not available, and existing dialogue act typologies are inapplicable. In this work, we show that adjacency pair recognition can be performed using lexical pair features, without a dialogue act typology or metadata, and that this is robust to controlling for topic bias of the discussions.
Text Clustering via Term Semantic Units

How best to represent text data is an important problem in text mining tasks including information retrieval, clustering, classification and etc. In this paper, we proposed a compact document representation with term semantic units which are identified from the implicit and explicit semantic information. Among it, the implicit semantic information is extracted from syntactic content via statistical methods such as latent semantic indexing and information bottleneck. The explicit semantic information is mined from the external semantic resource (Wikipedia). The proposed compact representation model can map a document collection in a low-dimension space (term semantic units which are much less than the number of all unique terms). Experimental results on real data sets have shown that the compact representation efficiently improve the performance of text clustering.