LLukas22/scidocs huggingface dataset:
Use of tissue velocity imaging in the diagnosis of fetal cardiac arrhythmias.

BACKGROUND
Precise diagnosis of cardiac arrhythmias in the fetus is crucial for a managed therapeutic approach. However, many technical, positional, and gestational age-related limitations may render conventional methods, such as M-mode and Doppler flow methodologies, or newer techniques, such as fetal electrocardiography or magnetocardiography, difficult to apply, or these techniques may be unsuitable for the diagnosis of fetal arrhythmias.


METHODS AND RESULTS
In this prospective study, we describe a novel method based on raw scan-line tissue velocity data acquisition and analysis. The raw data are available from high-frame-rate 2D tissue velocity images and allow simultaneous sampling of right and left atrial and ventricular wall velocities to yield precise temporal analysis of atrial and ventricular events. Using this timing data, a ladder diagram-like "fetal kinetocardiogram" was developed to diagram and diagnose arrhythmias and to provide true intervals. This technique was feasible and fast, yielding diagnostic results in all 31 fetuses from 18 to 38 weeks of gestation. Analysis of various supraventricular and ventricular arrhythmias was readily obtained, including arrhythmias that conventional methods fail to diagnose.


CONCLUSIONS
The fetal kinetocardiogram opens a new window to aid in the diagnosis and understanding of fetal arrhythmias, and it provides a tool for studying the action of antiarrhythmic drugs and their effects on electrophysiological conduction in the fetal heart.
Reinforcement Learning Applications in Dynamic Pricing of Retail Markets

In this paper, we investigate the use of reinforcement learning (RL) techniques to the problem of determining dynamic prices in an electronic retail market. As representative models, we consider a single seller market and a two seller market, and formulate the dynamic pricing problem in a setting that easily generalizes to markets with more than two sellers. We first formulate the single seller dynamic pricing problem in the RL framework and solve the problem using the Q-learning algorithm through simulation. Next we model the two seller dynamic pricing problem as a Markovian game and formulate the problem in the RL framework. We solve this problem using actor-critic algorithms through simulation. We believe our approach to solving these problems is a promising way of setting dynamic prices in multi-agent environments. We illustrate the methodology with two illustrative examples of typical retail markets.
An efficient two-pass MAP-MRF algorithm for motion estimation based on mean field theory

This paper presents a two-pass algorithm for estimating motion vectors from image sequences. In the proposed algorithm, the motion estimation is formulated as a problem of obtaining the maximum a posteriori in the Markov random field (MAP-MRF). An optimization method based on the mean field theory(MFT) is opted to conduct the MAP search. The estimation of motion vectors is modeled by only two MRF’s, namely, the motion vector field and unpredictable field. Instead of utilizing the line field, a truncation function is introduced to handle the discontinuity between the motion vectors on neighboring sites. In this algorithm, a “double threshold” preprocessing pass is first employed to partition the sites into three regions, whereby the ensuing MFT-based pass for each MRF is conducted on one or two of the three regions. With this algorithm, no significant difference exists between the block-based and pixel-based MAP searches any more. Consequently, a good compromise between precision and efficiency can be struck with ease. To render our algorithm more resilient against noises, themean absolute differenceinstead of mean square erroris selected as the measure of difference, which is more reliable according to the knowledge of robust statistics. This is supported by our experimental results from both synthetic and real-world image sequences. The proposed two-pass algorithm is much faster than any other MAP-MRF motion estimation method reported in the literature so far.
Predicting ad click-through rates via feature-based fully coupled interaction tensor factorization

In the real-time bidding (RTB) display advertising ecosystem, when receiving a bid request, the demandside platform (DSP) needs to predict the click-through rate (CTR) for ads and calculate the bid price according to the CTR estimated. In addition to challenges similar to those encountered in sponsored search advertising, such as data sparsity and cold start problems, more complicated feature interactions involving multi-aspects, such as the user, publisher and advertiser, make CTR estimation in RTB more difficult. We consider CTR estimation in RTB as a tensor complement problem and propose a fully coupled interactions tensor factorization (FCTF) model based on Tucker decomposition (TD) to model three pairwise interactions between the user, publisher and advertiser and ultimately complete the tensor complement task. FCTF is a special case of the Tucker decomposition model; however, it is linear in runtime for both learning and prediction. Different from pairwise interaction tensor factorization (PITF), which is another special case of TD, FCTF is independent from the Bayesian personalized ranking optimization algorithm and is applicable to generic third-order tensor decomposition with popular simple optimizations, such as the least square method or mean square error. In addition, we also incorporate all explicit information obtained from different aspects into the FCTF model to alleviate the impact of cold start and sparse data on the final performance. We compare the performance and runtime complexity of our method with Tucker decomposition, canonical decomposition and other popular methods for CTR prediction over real-world advertising datasets. Our experimental results demonstrate that the improved model not only achieves better prediction quality than the others due to considering fully coupled interactions between three entities, user, publisher and advertiser but also can accomplish training and prediction with linear runtime. 2016 Elsevier B.V. All rights reserved.
The Influence of Prebiotic Arabinoxylan Oligosaccharides on Microbiota Derived Uremic Retention Solutes in Patients with Chronic Kidney Disease: A Randomized Controlled Trial

UNLABELLED
The colonic microbial metabolism is a key contributor to uremic retention solutes accumulating in patients with CKD, relating to adverse outcomes and insulin resistance. Whether prebiotics can reduce intestinal generation of these microbial metabolites and improve insulin resistance in CKD patients not yet on dialysis remains unknown. We performed a randomized, placebo-controlled, double-blind, cross-over study in 40 patients with eGFR between 15 and 45 ml/min/1.73 m2. Patients were randomized to sequential treatment with prebiotic arabinoxylan oligosaccharides (AXOS) (10 g twice daily) and maltodextrin for 4 weeks, or vice versa, with a 4-week wash-out period between both intervention periods. Serum levels and 24h urinary excretion of p-cresyl sulfate, p-cresyl glucuronide, indoxyl sulfate, trimethylamine N-oxide and phenylacetylglutamine were determined at each time point using liquid chromatography-tandem mass spectrometry. In addition, insulin resistance was estimated by the homeostatic model assessment (HOMA-IR). A total of 39 patients completed the study. We observed no significant effect of AXOS on serum p-cresyl sulfate (P 0.42), p-cresyl glucuronide (P 0.59), indoxyl sulfate (P 0.70) and phenylacetylglutamine (P 0.41) and a small, albeit significant decreasing effect on serum trimethylamine N-oxide (P 0.04). There were neither effect of AXOS on 24h urinary excretion of p-cresyl sulfate (P 0.31), p-cresyl glucuronide (P 0.23), indoxyl sulfate (P 0.87) and phenylacetylglutamine (P 0.43), nor on 24h urinary excretion of trimethylamine N-oxide (P 0.97). In addition, we observed no significant change in HOMA-IR (P 0.93). In conclusion, we could not demonstrate an influence of prebiotic AXOS on microbiota derived uremic retention solutes and insulin resistance in patients with CKD not yet on dialysis. Further study is necessary to elucidate whether prebiotic therapy with other characteristics, higher cumulative exposure or in different patient populations may be of benefit.


TRIAL REGISTRATION
Clinicaltrials.gov NCT02141815.
Finding Pictures of Objects in Large Collections of Images

Retrieving images from very large collections using image content as a key is becoming an important problem. Users prefer to ask for pictures using notions of content that are strongly oriented to the presence of objects, which are quite abstractly defined. Computer programs that implement these queries automatically are desirable but are hard to build because conventional object recognition techniques from computer vision cannot recognize very general objects in very general contexts.
A Double-Sided Rounded Bow-Tie Antenna (DSRBA) for UWB Communication

A double-sided rounded bow-tie antenna (DSRBA) for ultrawideband (UWB) communication is proposed. The antenna covers the UWB spectrum from 3.1 to 10.6 GHz, and has return loss below -10 dB throughout the entire band. The antenna has also omnidirectional radiation characteristics and reasonable gain values over the same frequency band. Two different substrates, Rogers RO3006 and Liquid Crystal Polymer (LCP), are considered. Both materials have very low loss tangent. Results regarding return loss, far-field pattern, and gain are presented
Are Catholic primary schools more effective than public primary schools

This paper assesses the causal effects of Catholic primary schooling on student outcomes such as test scores, grade retention, and behavior. Catholic school students have substantially better average outcomes than do public school students throughout the primary years, but we present evidence that selection bias is entirely responsible for these advantages. Estimates based on several empirical strategies, including an approach developed by Altonji et al. (2005a) to use selection on observables to assess the bias arising from selection on unobservables, imply that Catholic schools do not appreciably boost test scores. All of the empirical strategies point to sizeable negative effects of Catholic schooling on mathematics achievement. Similarly, we find very little evidence that Catholic schooling improves behavioral and other non-cognitive outcomes once we account for selection on unobservables.
Prediction of Embankment Dam Breach Parameters

have provided many helpful comments in review of the document. Robert Rood and Larissa Casey assisted with the editing and final preparation of the manuscript and made many significant improvements to the final product. assisted with the organization and hosting of the February 1998 technical workshop on dam breach processes and also provided many helpful source documents for the literature review. Figure 15. — Comparison of case study data and proposed relations for peak outflow as a function of the product of height and storage parameters .. This peer-reviewed report examines the role, importance, and methods for predicting embankment dam breach parameters needed for analysis of potential dam-failure floods. Special emphasis is given to dam breach analysis within the context of the risk assessment process used by the Bureau of Reclamation (Reclamation). Current methods for predicting embankment dam breach parameters and numerically modeling dam breach events are reviewed, and the needs and opportunities for developing improved technologies are discussed. Recent technical advances that could contribute to improvements in dam breach simulation are identified. In addition to this literature review, Reclamation and the Agricultural Research Service (ARS) cosponsored an international workshop on dam breach processes February 10-11, 1998, attended by about 35 leading professionals working in this field. The workshop provided an opportunity to review and discuss the state-of-the-art, ongoing research, and future needs for dam breach analysis tools. Key findings from this literature review and the workshop include: • There is presently both a need and opportunity to achieve significant improvements in technology used to analyze embankment dam breach processes. The potential benefits to be achieved from this effort may significantly aid risk assessment studies, in which thresholds of dam failure, probabilities of failure, and consequences of failure are all of prime importance. • When population centers are located close to dams, accurate prediction of breach parameters is crucial to development of effective emergency action plans, design of early warning systems, and characterization of threats to lives and property. • Warning time is the most important parameter affecting potential loss of life due to dam failure. • The primary benefits of improved prediction of breach initiation and formation times will accrue to the population within a few kilometers of the structure, but this is also the region which historically has the greatest risk for loss of life. • The distinction between breach initiation time and breach formation time has not …
Effects of a combination of niacin and chromium(III)-chloride on the skin and lungs of hyperlipemic rats

The aim of this study was to investigate the biochemical effects of niacin and chromium(III)-chloride on serum lipid peroxidation, uric and sialic acids, and the extent of lipid peroxidation and glutathione levels in skin and lung tissues of hyperlipidemic rats. In this study, female Swiss albino rats, 12 mo old, were used. They were randomly divided into four groups. Group I animals were fed with a standard pellet diet and water ad libitium. Group II rats were fed with a standard pellet diet and were treated with a dose of 250 μg/kg body weight CrCI3·6H2O and 100 mg/kg body weight niacin, for 45 d, by the gavage technique. Group III rats were fed a lipogenic diet in which 2% cholesterol, 0.5% cholic acid, and 20% sunflower oil were added to the pellet chow. In addition, the animals in this group drank water containing 3% ethanol. This regime was maintained for 60 d. The rats in group IV were maintained in the same food and drink regime as the animals in group III. After 2 wk, the animals showed symptoms of hyperlipemia and they were treated with 250 μg/kg body weight CrCI3·6H2O and 100 mg/kg body weight niacin, by gavage, for 45 d. On d 60, the blood and the skin and lungs samples were taken from animals. In the hyperlipemic groups, a reduction of the lung glutathione level and an increase in serum, lung, and skin lipid peroxidation levels and in serum sialic and uric acid were observed. In rats treated with a combination of niacin and Cr(III), the skin and serum lipid peroxidation and the sialic and uric acid levels decreased while showing an increase of lung glutathione activity. These results suggest that niacin and Cr(III), when administered in combination, have a protective effect against skin and lung tissues damage as a result of hyperlipidemia.
Cluster Based Under-Sampling for Unbalanced Cardiovascular Data

Most medical datasets are not balanced in their class labels. Indeed in some cases it has been no ticed that the given class labels do not accurately represent characteristics of the data record. Most existing classification methods tend not to perform well on minority class examples when the dataset is extremely imbalanced. This is because they aim to optimize the overall accuracy without considering the relative distribution of each class. In this paper we propose a cluster based under sampling technique that solves the class imbalance problem for our cardiovascular data. It shows significant better performance than existing methods. Keywords— class imbalance, under-sampling, oversampling, clustering, SMOTE.
Socio-demographic characteristics associated with cigarettes smoking, drug abuse and alcohol drinking among male medical university students in Iran.

BACKGROUND
Substance abuse is one of the most complicated social problems. Understanding socio-demographic characteristics of those who abuse substances could help deal with this problem more efficiently. The main objective of this study was to determine socio-demographic characteristics associated with alcohol drinking, cigarettes smoking and drug abuse among a sample of male medical university students in Iran.


METHODS
This cross-sectional study was conducted in 2014 among 425 male medical college students randomly selected with the proportional to size among different faculties in Isfahan and Kermanshah medical universities in Iran. A self-report written questionnaire was applied to collect data. Data were analyzed by the SPSS-20.


RESULTS
Mean age of the respondents was 19.9 yr (ranging from 18 to 22 yr). About 19.4%, 3.9%, and 10.1% of the respondents had history of cigarette smoking, drug use, and alcohol drinking during the past three months, respectively. Logistic regression showed that mother's educational level, living place, economic status, and parents' divorce were the most influential predictive factors on substance abuse.


CONCLUSIONS
Considering the high prevalence of substance abuse (especially smoking and alcohol drinking), it seems essential to design educational interventions to prevent substance abuse, paying attention to predictive factors mentioned above, among college students.
The Next 25 Years in EDA: A Cloudy Future?

h AT THE 50TH Design Automation Conference, Soha Hassoun organized a session to review the first 50 years of EDA and predict the next 25. While Bill Joyner [1] could draw upon the vast paper resources that MPA collected during the first 25 years of DAC and Rob Rutenbar [2] was able to apply some amazing analytics to the second 25 years of DAC proceedings, I turned to crowd sourcing to solicit input on the next 25 years. It was clear from Bill’s and Rob’s presentations that many people were drawn to the EDA industry for the same reason I got hooked: EDA was on the forefront of computing. Many of the largest computational problems that needed to be solved were EDA problems. The university groups focusing on EDA had the largest and fastest computers. If one wanted to solve largescale computer science problems, EDA was the place to be for most of the last 50 years. Is that still the case? The replies to the ‘‘next 25 years of EDA’’ survey pointed out many of the challenges that EDA tools will need to address in the next decade. Key challenges will come from next lithography solutions such as Triple Patterning, EUV, DSA (direct selfassembly) or Ebeam. Many respondents pointed to the problems that next generation nanodevices such as photonics, bio based circuits, quantum, and carbon might bring. However, as shown in Figure 1, a large number of participants pointed out how IT and specifically cloud computing will have a major impact on the way EDA tools will be used. This is particularly interesting because in the ‘‘EDAC Forecast Meeting’’ on 14 March 2013 [4], the impression was left that cloud and EDA do not mix well. Earlier DAC panels [5] also pointed out the significant hurdles to overcome for EDA to be cloud friendly. In this article, I decided to zoom in on this one aspect of the next 25 years of EDA and will outline why we need to bring Cloud Computing and EDA together to deliver the next leap of design productivity and at the same time, restore the excitement in the EDA discipline.
Is the operative delivery rate in low-risk women dependent on the level of birth care? A randomised controlled trial

OBJECTIVE
To investigate possible differences in operative delivery rate among low-risk women, randomised to an alongside midwifery-led unit or to standard obstetric units within the same hospital.


DESIGN
Randomised controlled trial.


SETTING
Department of Obstetrics and Gynaecology, Østfold Hospital Trust, Tromsø, Norway.


POPULATION
A total of 1111 women assessed to be at low risk at onset of spontaneous labour.


METHODS
Randomisation into one of three birth units: the special unit; the normal unit; or the midwife-led unit.


MAIN OUTCOME MEASURES
Total operative delivery rate, augmentation, pain relief, postpartum haemorrhage, sphincter injuries and intrapartum transfer, Apgar score <7 at 5 minutes, metabolic acidosis and transfer to neonatal intensive care unit.


RESULTS
There were no significant differences in total operative deliveries between the three units: 16.3% in the midwife-led unit; 18.0% in the normal unit; and 18.8% in the special unit. There were no significant differences in postpartum haemorrhage, sphincter injuries or in neonatal outcomes. There were statistically significant differences in augmentation (midwife-led unit versus normal unit RR 0.73, 95% CI 0.59-0.89; midwife-led unit versus special unit RR 0.69, 95% CI 0.56-0.86), in epidural analgesia (midwife-led unit versus normal unit RR 0.68, 95% CI 0.52-0.90; midwife-led unit versus special unit RR 0.64, 95% CI 0.47-0.86) and in acupuncture (midwife-led unit versus normal unit RR 1.45, 95% CI 1.25-1.69; midwife-led unit versus special unit RR 1.45, 95% CI 1.22-1.73).


CONCLUSIONS
The level of birth care does not significantly affect the rate of operative deliveries in low-risk women without any expressed preference for level of birth care.
Signatures of new physics at 14 TeV

I give an overview of the ideas and of the problems that orient the expectations for new physics at the Large Hadron Collider and, whenever I can, I describe the corresponding signals.
Familial aggregation of atrial fibrillation: a study in Danish twins.

BACKGROUND
Heritability may play a role in nonfamilial atrial fibrillation (AF). We hypothesized that a monozygotic (MZ) twin whose co-twin was diagnosed with AF would have an increased risk of the disease compared with a dizygotic (DZ) twin in the same situation.


METHODS AND RESULTS
A sample of 1137 same-sex twin pairs (356 MZ and 781 DZ pairs) in which one or both members were diagnosed with AF were identified in The Danish Twin Registry. Concordance rates were twice as high for MZ pairs than for DZ pairs regardless of sex (22.0% versus 11.6%, P<0.0001). In a Cox regression of event-free survival times, we compared the time span between occurrences of disease in MZ and DZ twins. The unaffected twin was included when his or her twin-sibling (the index twin) was diagnosed with AF. After adjustment for age at entry, MZ twins had a significantly shorter event-free survival time (hazard ratio, 2.0; 95% CI, 1.3 to 3.0), thereby indicating a genetic component. Using biometric models, we estimated the heritability of AF to be 62% (55% to 68%), due to additive genetics. There were no significant differences across sexes.


CONCLUSIONS
All the analyses of twin similarities in the present study indicate that genetic factors play a substantial role in the risk of AF for both sexes. The recurrence risk for co-twins (12% to 22%) is clinically relevant and suggests that co-twins of AF-affected twins belong to a high-risk group for AF.