LLukas22/scidocs huggingface dataset:
Speechreading: illusion or window into pattern recognition

In the Fuzzy Logical Model of Perception (FLMP) perceivers are conceptualized as forming perceptual judgments by evaluating and integrating multiple ambiguous sources of information, in an optimal manner based on relative goodness of match. This model has been tested favorably against a variety of competing theories and models. Recent extensions of the FLMP are described in this article along with empirical applications and verification, and progress in the study of speech perception by ear and eye is reviewed within this general theoretical framework. The model illuminates the differences that are observed across different languages in terms of information as opposed to information-processing. Pattern recognition of bimodal speech is representative of pattern recognition in a variety of other domains, such as emotion perception, and there are several domain-dependent reasons why multimodal presentation of audible and visible speech is particularly conducive to accurate pattern recognition. We believe that the positive outcome of this research provides a framework for the development of computer-animated agents, which can serve as language tutors and as conversational characters in other domains, easing the interaction of humans and machines.
Choice of and satisfaction with methods of medical and surgical abortion among U.S. clinic patients.

CONTEXT
Abortion induced by drugs is now a viable alternative to surgically induced abortion for U. S. women. Women's willingness to use these new methods of medical abortion hinges on the extent to which they prove acceptable, however.


METHODS
Among 304 women participating in a clinical trial of medical abortion, 186 received a methotrexate-induced abortion and 118 were offered the option of a medical abortion but chose a surgical procedure instead. Study participants completed self-administered questionnaires before the abortion and again at a follow-up visit.


RESULTS
Women in the medical and surgical abortion groups did not differ significantly with regard to demographic and other background characteristics: Their mean age was about 27, more than two-thirds were white, and three-quarters were unmarried and worked either part-time or full-time. However, women's ratings of seven attributes of abortion methods were significant predictors of choosing a medical abortion: Women were more likely to choose medical abortion if they placed greater importance on a method that was nonsurgical, one that resembled a miscarriage or one that could take place at home (odds ratios, 2.0-3.3). Conversely, women were less likely to choose medical abortion if they valued methods that were quick, that did not involve painful cramping or seeing blood or blood clots and that needed a doctor or nurse to be present (odds ratios, 0.3-0.5). Compared with those who had a surgical abortion, women who had a methotrexate-induced abortion expected more bleeding (mean scores, 3.5 vs. 3. 1) and reported more pain (3.4 vs. 2.9), heavier bleeding (3.4 vs. 2.5) and bleeding of longer duration (3.3 vs. 2.6). The overwhelming majority of women in the medical and surgical abortion groups reported that they were either very or somewhat satisfied with their abortion method (81% and 82%, respectively), would recommend it to others (82% and 78%) and would choose the method again (89% and 93%).


CONCLUSIONS
Factors affecting the choice of abortion method appear to be numerous and complex. Providers need to be sensitive to differences in women's values and life circumstances when counseling them about an abortion method. In particular, providers should incorporate into their counseling sessions what women need to know about the characteristics of abortion methods and help women to identify what is the best option for them.
FRACTAL ANTENNAS : DESIGN , CHARACTERISTICS AND APPLICATION

1 University of Banjaluka, Faculty of Electrical Engineering, Patre 5, 78000 Banjaluka, Bosnia and Herzegovina, E-mail: nemanjapoprzen@gmail 2 University of Banjaluka, Faculty of Electrical Engineering, Patre 5, 78000 Banjaluka, Bosnia and Herzegovina, E-mail: bilchy@blic.net Abstract: This report will describe the theories and techniques for shrinking the size of an antenna through the use of fractals. Fractal antennas can obtain radiation pattern and input impedance similar to a longer antenna, yet take less area due to the many contours of the shape. Fractal antennas are a fairly new research area and are likely to have a promising future in many applications.
Smoothing Techniques for Arabic Diacritics Restoration

An algorithm to restore Arabic diacritics using dynamic programming approach was presented in [1]. The possible word sequences with diacritics are assigned scores using statistical n-gram language modeling approach. Using the assigned scores, it is possible to search the most likely sequence using a dynamic programming algorithm. The maximum likelihood (ML) estimation of the stochastic language model parameters leads to poor diacritization accuracy due to data sparse problem. Smoothing aims to handle this problem by taking some probability mass from the observed n-gram and distribute it to the unseen n-grams. In this paper, we show that applying smoothing techniques dramatically improve the diacritization accuracy. The interpolated version of the absolute discounting method leads to the best results for different model orders.
Temporal Convolutional Networks: A Unified Approach to Action Segmentation

The dominant paradigm for video-based action segmentation is composed of two steps: first, compute low-level features for each frame using Dense Trajectories or a Convolutional Neural Network to encode local spatiotemporal information, and second, input these features into a classifier such as a Recurrent Neural Network (RNN) that captures high-level temporal relationships. While often effective, this decoupling requires specifying two separate models, each with their own complexities, and prevents capturing more nuanced long-range spatiotemporal relationships. We propose a unified approach, as demonstrated by our Temporal Convolutional Network (TCN), that hierarchically captures relationships at low-, intermediate, and high-level time-scales. Our model achieves superior or competitive performance using video or sensor data on three public action segmentation datasets and can be trained in a fraction of the time it takes to train an RNN.
Action recognition for depth video using multi-view dynamic images

Dynamic imaging is a recently proposed action description paradigm for simultaneously capturing motion and temporal evolution information, particularly in the context of deep convolutional neural networks (CNNs). Compared with optical flow for motion characterization, dynamic imaging exhibits superior efficiency and compactness. Inspired by the success of dynamic imaging in RGB video, this study extends it to the depth domain. To better exploit three-dimensional (3D) characteristics, multi-view dynamic images are proposed. In particular, the raw depth video is densely projected with ∗Corresponding author. Tel.: +86 27 87558918 Email addresses: Yang Xiao@hust.edu.cn (Yang Xiao), chenjun2015@hust.edu.cn (Jun Chen), yancheng wang@hust.edu.cn (Yancheng Wang), zgcao@hust.edu.cn (Zhiguo Cao), zhouty@ihpc.a-star.edu.sg (Joey Tianyi Zhou), xbai@hust.edu.cn (Xiang Bai) Preprint submitted to Information Sciences December 31, 2018 ar X iv :1 80 6. 11 26 9v 3 [ cs .C V ] 2 7 D ec 2 01 8 respect to different virtual imaging viewpoints by rotating the virtual camera within the 3D space. Subsequently, dynamic images are extracted from the obtained multi-view depth videos and multi-view dynamic images are thus constructed from these images. Accordingly, more view-tolerant visual cues can be involved. A novel CNN model is then proposed to perform feature learning on multi-view dynamic images. Particularly, the dynamic images from different views share the same convolutional layers but correspond to different fully connected layers. This is aimed at enhancing the tuning effectiveness on shallow convolutional layers by alleviating the gradient vanishing problem. Moreover, as the spatial occurrence variation of the actions may impair the CNN, an action proposal approach is also put forth. In experiments, the proposed approach can achieve state-of-the-art performance on three challenging datasets.
Advanced Enzymology, Expression Profile and Immune Response of Clonorchis sinensis Hexokinase Show Its Application Potential for Prevention and Control of Clonorchiasis

BACKGROUND
Approximately 35 million people are infected with Clonorchis sinensis (C. sinensis) globally, of whom 15 million are in China. Glycolytic enzymes are recognized as crucial molecules for trematode survival and have been targeted for vaccine and drug development. Hexokinase of C. sinensis (CsHK), as the first key regulatory enzyme of the glycolytic pathway, was investigated in the current study.


PRINCIPAL FINDINGS
There were differences in spatial structure and affinities for hexoses and phosphate donors between CsHK and HKs from humans or rats, the definitive hosts of C. sinensis. Effectors (AMP, PEP, and citrate) and a small molecular inhibitor regulated the enzymatic activity of rCsHK, and various allosteric systems were detected. CsHK was distributed in the worm extensively as well as in liver tissue and serum from C. sinensis infected rats. Furthermore, high-level specific IgG1 and IgG2a were induced in rats by immunization with rCsHK. The enzymatic activity of CsHK was suppressed by the antibody in vitro. Additionally, the survival of C. sinensis was inhibited by the antibody in vivo and in vitro.


CONCLUSIONS/SIGNIFICANCE
Due to differences in putative spatial structure and enzymology between CsHK and HK from the host, its extensive distribution in adult worms, and its expression profile as a component of excretory/secretory products, together with its good immunogenicity and immunoreactivity, as a key glycolytic enzyme, CsHK shows potential as a vaccine and as a promising drug target for Clonorchiasis.
Sentinel injuries in infants evaluated for child physical abuse.

OBJECTIVE
Relatively minor abusive injuries can precede severe physical abuse in infants. Our objective was to determine how often abused infants have a previous history of "sentinel" injuries, compared with infants who were not abused.


METHODS
Case-control, retrospective study of 401, <12-month-old infants evaluated for abuse in a hospital-based setting and found to have definite, intermediate concern for, or no abuse after evaluation by the hospital-based Child Protection Team. A sentinel injury was defined as a previous injury reported in the medical history that was suspicious for abuse because the infant could not cruise, or the explanation was implausible.


RESULTS
Of the 200 definitely abused infants, 27.5% had a previous sentinel injury compared with 8% of the 100 infants with intermediate concern for abuse (odds ratio: 4.4, 95% confidence interval: 2.0-9.6; P < .001). None of the 101 nonabused infants (controls) had a previous sentinel injury (P < .001). The type of sentinel injury in the definitely abused cohort was bruising (80%), intraoral injury (11%), and other injury (7%). Sentinel injuries occurred in early infancy: 66% at <3 months of age and 95% at or before the age of 7 months. Medical providers were reportedly aware of the sentinel injury in 41.9% of cases.


CONCLUSIONS
Previous sentinel injuries are common in infants with severe physical abuse and rare in infants evaluated for abuse and found to not be abused. Detection of sentinel injuries with appropriate interventions could prevent many cases of abuse.
Psychological stress in seafarers: a review.

BACKGROUND
Seafaring is a particular profession, in which workers are usually exposed to several stressors that are related to the different duties on board ships. This paper has reviewed the main publications on different factors affecting seafarers with the purpose of identifying specific stress factors related to a particular duty on board.


MATERIALS AND METHODS
A literature search was conducted using the online databases PubMed and OvidSP. A survey on health, stress, and fatigue of Australian Seafarers published by the Australian Maritime Safety Authority (AMSA) fulfilling the selection criteria was also examined. This publication provided relevant data obtained from a large sample of seafarers.


RESULTS
Our analysis confirmed that seafaring is associated with mental, psychosocial, and physical stressors. The most important factors were separation from family, loneliness on board, fatigue, multi-nationality, limited recreation activity, and sleep deprivation. The AMSA report gave a more detailed analysis on lifestyle and relevant factors inducing psychological distress. Stressors affecting seafarers working in the engine room were different from those involving the deck crew. Sleep quality and duration were reported to be poor mainly in pilots, whereas deck crew tended to be less adherent to physical exercise and healthy lifestyle recommendations.


CONCLUSIONS
Seafaring is still associated with relevant mental health risks. Information on known stress factors on board should be provided to seafarers to help them in lowering stress perception. Strategies for coping with "inevitable" stress conditions should also be investigated and developed. Strategies to decrease risks of stress should be directed to the different categories of seafarers, and the results of specific interventions should be evaluated.
SentiCR: A customized sentiment analysis tool for code review interactions

Sentiment Analysis tools, developed for analyzing social media text or product reviews, work poorly on a Software Engineering (SE) dataset. Since prior studies have found developers expressing sentiments during various SE activities, there is a need for a customized sentiment analysis tool for the SE domain. On this goal, we manually labeled 2000 review comments to build a training dataset and used our dataset to evaluate seven popular sentiment analysis tools. The poor performances of the existing sentiment analysis tools motivated us to build SentiCR, a sentiment analysis tool especially designed for code review comments. We evaluated SentiCR using one hundred 10-fold cross-validations of eight supervised learning algorithms. We found a model, trained using the Gradient Boosting Tree (GBT) algorithm, providing the highest mean accuracy (83%), the highest mean precision (67.8%), and the highest mean recall (58.4%) in identifying negative review comments.
Pre-pregnancy and pregnancy predictors of obesity

Obesity has progressively become a global epidemic that constitutes one of the biggest current health problems worldwide. Pregnancy is a risk factor for excessive weight gain. Factors that may predict development of obesity in later life mainly include gestational weight gain, pre-pregnancy nutritional status, age, parity and race. Change in lifestyle factors, such as eating habits, enrollment in physical activity, smoking and duration of lactation, in addition to the above factors, may also contribute to the development of obesity but are still not fully understood. Women who retain more body weight after pregnancy have, in general, larger pregnancy body weight gain, higher pre-pregnancy body mass index, marked weight changes in previous pregnancies, lactate slightly less and stop smoking during pregnancy to a larger extent. In addition, irregular eating habits and decreased leisure time activity after delivery influence postpartum weight retention. Taking into consideration the epidemic of obesity, with all its adverse long-term consequences, there is an increasing need to promote counseling before, during and after pregnancy on the role of diet and physical activity in reproductive health.
Quality of life of individuals with stroke and their caregivers in a city of Triângulo Mineiro.

OBJECTIVE
To compare the quality of life (QoL) of individuals with stroke and their caregivers.


METHODS
This is an observational cross-sectional survey, involving 83 individuals who suffered a stroke. The participants were divided into four groups: group of individuals with stroke who have caregivers (44), group of individuals with stroke without caregivers (39), group of caregivers (44) and a reference group (83) in the period of March to May 2010. To assess QoL, the instrument used was the WHOQOL-bref.


RESULTS
The highest scores for the four fields were observed increasingly for the group of individuals with stroke with caregivers, the stroke group without caregivers followed by the group of caregivers and the reference group. The comparison of scores between groups showed that the presence of stroke and the fact of being caregiver affect QoL in all domains of WHOQOL-bref.


CONCLUSION
It was possible to understand the negative impact that stroke causes in the lives of the affected ones and their caregivers, in order to better target public health policies.
The First Question Generation Shared Task Evaluation Challenge

The paper briefly describes the First Shared Task Evaluation Challenge on Question Generation that took place in Spring 2010. The campaign included two tasks: Task A – Question Generation from Paragraphs and Task B – Question Generation from Sentences. An overview of each of the tasks is provided.
Low uptake of eye services in rural India: a challenge for programs of blindness prevention.

OBJECTIVES
To investigate service uptake in a rural Indian population served by outreach eye camps and to identify barriers to uptake.


PARTICIPANTS AND METHODS
A routine eye camp was conducted within 5 km of each of 48 randomly selected villages of typically Hindu, backward-caste communities. Subsequently, participatory rural appraisal-community mapping, focus groups, matrix ranking, and semistructured interviews-was undertaken to explore community views of eye problems. An eye examination was conducted on persons with eye problems who did not attend the eye camp. Predictors of attendance were identified by multilevel regression analysis.


RESULTS
Of 749 adults with an eye problem, 51 (6.8%) attended the eye camp. Independent predictors of attendance were being male (odds ratio = 2.3; 95% confidence interval, 1.2-4.5) and living within 3 km of the camp (odds ratio = 4.5; 95% confidence interval, 1.7-12.5). Of the 552 persons who did not attend the eye camps and had an eye examination, 242 (43.8%) had low vision (visual acuity <6/18 to > or =3/60 in presenting better eye) and 38 (6.9%) were blind in both eyes. Cataract surgery was recommended for 197 (35.8%) of the persons who did not attend the eye camps. Of 109 persons with a previous cataract operation, 42 (38.5%) had low vision and 11 (10.1%) were blind. Fear (principally of eye damage), cost (direct and indirect), family responsibilities, ageism, fatalism, and an attitude of being able to cope (with low or no vision) were the principal barriers to attending the eye camps.


CONCLUSIONS
A high proportion of people who could have benefited from eye treatment were not using available services. Poor visual outcomes were observed in surgically treated persons.
Can e-learning replace classroom learning?

In an e-learning environment that emphasizes learner-centered activity and system interactivity, remote learners can outperform traditional classroom students.
An Ultra-Low Voltage Level Shifter Using Revised Wilson Current Mirror for Fast and Energy-Efficient Wide-Range Voltage Conversion from Sub-Threshold to I/O Voltage

This paper presents a novel ultra-low voltage level shifter for fast and energy-efficient wide-range voltage conversion from sub-threshold to I/O voltage. By addressing the voltage drop and non-optimal feedback control in a state-of-the-art level shifter based on Wilson current mirror, the proposed level shifter with revised Wilson current mirror significantly improves the delay and power consumption while achieving a wide voltage conversion range. It also employs mixed-Vt device and device sizing aware of inverse narrow width effect to further improve the delay and power consumption. Measurement results at 0.18 μm show that compared with the Wilson current mirror based level shifter, the proposed level shifter improves the delay, switching energy and leakage power by up to 3×, 19×, 29× respectively, when converting 0.3 V to a voltage between 0.6 V and 3.3 V. More specifically, it achieves 1.03 (or 1.15) FO4 delay, 39 (or 954) fJ/transition and 160 (or 970) pW leakage power, when converting 0.3 V to 1.8 V (or 3.3 V), which is better than several state-of-the-art level shifters for similar range voltage conversion. The measurement results also show that the proposed level shifter has good delay scalability with supply voltage scaling and low sensitivity to process and temperature variations.
Assessment of the hepatic veins in poor contrast conditions using dual energy CT: evaluation of a novel monoenergetic extrapolation software algorithm.

PURPOSE
To evaluate a novel monoenergetic post-processing algorithm (MEI+) in patients with poor intrahepatic contrast enhancement.


MATERIALS AND METHODS
25 patients were retrospectively included in this study. Late-phase imaging of the upper abdomen, which was acquired in dual-energy mode (100/140 kV), was used as a model for poor intrahepatic contrast enhancement. Traditional monoenergetic images (MEI), linearly weighted mixed images with different mixing ratios (MI), sole 100 and 140 kV and MEI+ images were calculated. MEI+ is a novel technique which applies frequency-based mixing of the low keV images and an image of optimal keV from a noise perspective to combine the benefits of both image stacks. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the intrahepatic vasculature (IHV) and liver parenchyma (LP) were objectively measured and depiction of IHV was subjectively rated and correlated with portal venous imaging by two readers in consensus.


RESULTS
MEI+ was able to increase the SNR of the IHV (5.7 ± 0.4 at 40keV) and LP (4.9 ± 1.0 at 90keV) and CNR (2.1 ± 0.6 at 40keV) greatly compared to MEI (5.1 ± 1.1 at 80keV, 4.7 ± 1.0 at 80keV, 1.0 ± 0.4 at 70keV), MI (5.2 ± 1.1 M5:5, 4.8 ± 1.0 M5:5, 1.0 ± 3.5 M9:1), sole 100 kV images (4.4 ± 1.0, 3.7 ± 0.8, 1.0 ± 0.3) and 140 kV images (2.8 ± 0.5, 3.1 ± 0.6, 0.1 ± 0.2). Subjective assessment rated MEI+ of virtual 40 keV superior to all other images.


CONCLUSION
MEI+ is a very promising algorithm for monoenergetic extrapolation which is able to overcome noise limitations associated with traditional monoenergetic techniques at low virtual keV levels and consequently does not suffer from a decline of SNR and CNR at low keV values. This algorithm allows an improvement of IHV depiction in the presence of poor contrast.


KEY POINTS
• The evaluated new image-based algorithm for virtual monoenergetic imaging allows calculating low virtual keV images from dual energy datasets with significantly improved contrast-to-noise ratios. • The image based novel monoenergetic extrapolation algorithm applies frequency-based mixing of the low keV images and an image of optimal keV from a noise perspective to combine the benefits of both image stacks.• When compared to traditional monoenergetic images, the novel monoenergetic algorithm has improved contrast-to-noise ratios for both low and high virtual keV images.• Contrast-enhanced dual energy images with poor contrast conditions can be significantly improved, e.g. late phase imaging of the liver.