LLukas22/scidocs huggingface dataset:
Optical Coherence Tomography of Retinal Lesions in Infants With Congenital Zika Syndrome.

Importance
Zika virus (ZIKV) can cause severe changes in the retina and choroid that may result in marked visual impairment in infants with congenital Zika syndrome (CZS), the term created for a variety of anomalies associated with intrauterine ZIKV infection.


Objective
To evaluate the affected retinal layers in infants with CZS and associated retinal abnormalities using optical coherence tomography (OCT).


Design, Setting, and Participants
This cross-sectional, consecutive case series included 8 infants (age range, 3.0-5.1 months) with CZS. Optical coherence tomographic images were obtained in the affected eyes of 7 infants with CZS who had undergone previous ophthalmologic examinations on March 17, 2016, and in 1 infant on January 1, 2016. An IgM antibody-capture enzyme-linked immunosorbent assay for ZIKV was performed on the cerebrospinal fluid samples of 7 of the 8 infants (88%), and other congenital infections were ruled out.


Main Outcomes and Measures
Observation of retinal and choroidal findings in the OCT images.


Results
Among the 8 infants included in the study (3 male; 5 female; mean [SD] age at examination, 4.1 [0.7] months), 7 who underwent cerebrospinal fluid analysis for ZIKV had positive findings for IgM antibodies. Eleven of the 16 eyes (69%) of the 8 infants had retinal alterations and OCT imaging was performed in 9 (82%) of them. Optical coherence tomography was also performed in 1 unaffected eye. The main OCT findings in the affected eyes included discontinuation of the ellipsoid zone and hyperreflectivity underlying the retinal pigment epithelium in 9 eyes (100%), retinal thinning in 8 eyes (89%), choroidal thinning in 7 eyes (78%), and colobomatouslike excavation involving the neurosensory retina, retinal pigment epithelium, and choroid in 4 eyes (44%).


Conclusions and Relevance
Zika virus can cause severe damage to the retina, including the internal and external layers, and the choroid. The colobomatouslike finding seen in the OCT images relate to the excavated chorioretinal scar observed clinically.
Risk Factors of Pre-Eclampsia/Eclampsia and Its Adverse Outcomes in Low- and Middle-Income Countries: A WHO Secondary Analysis

BACKGROUND
Pre-eclampsia has an immense adverse impact on maternal and perinatal health especially in low- and middle-income settings. We aimed to estimate the associations between pre-eclampsia/eclampsia and its risk factors, and adverse maternal and perinatal outcomes.


METHODS
We performed a secondary analysis of the WHO Global Survey on Maternal and Perinatal Health. The survey was a multi-country, facility-based cross-sectional study. A global sample consisting of 24 countries from three regions and 373 health facilities was obtained via a stratified multi-stage cluster sampling design. Maternal and offspring data were extracted from records using standardized questionnaires. Multi-level logistic regression modelling was conducted with random effects at the individual, facility and country levels.


RESULTS
Data for 276,388 mothers and their infants was analysed. The prevalence of pre-eclampsia/eclampsia in the study population was 10,754 (4%). At the individual level, sociodemographic characteristics of maternal age ≥30 years and low educational attainment were significantly associated with higher risk of pre-eclampsia/eclampsia. As for clinical and obstetric variables, high body mass index (BMI), nulliparity (AOR: 2.04; 95%CI 1.92-2.16), absence of antenatal care (AOR: 1.41; 95%CI 1.26-1.57), chronic hypertension (AOR: 7.75; 95%CI 6.77-8.87), gestational diabetes (AOR: 2.00; 95%CI 1.63-2.45), cardiac or renal disease (AOR: 2.38; 95%CI 1.86-3.05), pyelonephritis or urinary tract infection (AOR: 1.13; 95%CI 1.03-1.24) and severe anemia (AOR: 2.98; 95%CI 2.47-3.61) were found to be significant risk factors, while having >8 visits of antenatal care was protective (AOR: 0.90; 95%CI 0.83-0.98). Pre-eclampsia/eclampsia was found to be a significant risk factor for maternal death, perinatal death, preterm birth and low birthweight.


CONCLUSION
Chronic hypertension, obesity and severe anemia were the highest risk factors of preeclampsia/eclampsia. Implementation of effective interventions prioritizing risk factors, provision of quality health services during pre-pregnancy and during pregnancy for joint efforts in the areas of maternal health are recommended.
Pulmonary vein isolation using transvenous catheter cryoablation for treatment of atrial fibrillation without risk of pulmonary vein stenosis.

OBJECTIVES
We sought to evaluate the efficacy and safety of pulmonary vein (PV) isolation using transvenous cryoablation for the treatment of atrial fibrillation (AF).


BACKGROUND
Although electrical isolation of PVs with radiofrequency energy for the treatment of AF is feasible, it is associated with a significant risk of PV stenosis. Cryoablation is a new alternative therapy allowing ablation of tissue while preserving its underlying architecture.


METHODS
In 52 patients with paroxysmal (n = 45) or persistent (n = 7) AF, PV isolation using the CryoCor cryoablation system (CyroCor Inc., San Diego, California) with a 10F deflectable transvenous catheter was performed as guided by ostial PV potentials. Cryoablation was applied twice at each targeted site (2.5 to 5 min/application). Computed tomography (CT) of the thorax was performed at baseline and at 3 and 12 months to evaluate for PV stenosis.


RESULTS
All targeted PVs were completely isolated in 49 (94%) of 52 of patients. Of 152 PVs targeted, 147 (97%) were successfully isolated (mean 3.0 PVs isolated per patient). After a mean period of 12.4 +/- 5.5 months of follow-up, 37 (71%) of 52 patients had no recurrence of AF or were clinically improved, including 29 patients (56%) who had no recurrence of AF with (n = 11) or without the use of anti-arrhythmic drugs. At 3 and 12 months, the CT scan showed no evidence of PV stenosis associated with cryoablation in any patients.


CONCLUSIONS
Transvenous catheter cryoablation is an effective method to create PV electrical isolation for the treatment of AF. A clinically satisfactory result can be achieved in 71% of patients with AF, without the risk of PV stenosis.
Improving diabetes prevention with benefit based tailored treatment: risk based reanalysis of Diabetes Prevention Program

OBJECTIVE
To determine whether some participants in the Diabetes Prevention Program were more or less likely to benefit from metformin or a structured lifestyle modification program.


DESIGN
Post hoc analysis of the Diabetes Prevention Program, a randomized controlled trial.


SETTING
Ambulatory care patients.


PARTICIPANTS
3060 people without diabetes but with evidence of impaired glucose metabolism.


INTERVENTION
Intervention groups received metformin or a lifestyle modification program with the goals of weight loss and physical activity.


MAIN OUTCOME MEASURE
Development of diabetes, stratified by the risk of developing diabetes according to a diabetes risk prediction model.


RESULTS
Of the 3081 participants with impaired glucose metabolism at baseline, 655 (21%) progressed to diabetes over a median 2.8 years' follow-up. The diabetes risk model had good discrimination (C statistic=0.73) and calibration. Although the lifestyle intervention provided a sixfold greater absolute risk reduction in the highest risk quarter than in the lowest risk quarter, patients in the lowest risk quarter still received substantial benefit (three year absolute risk reduction 4.9% v 28.3% in highest risk quarter; numbers needed to treat of 20.4 and 3.5, respectively). The benefit of metformin, however, was seen almost entirely in patients in the top quarter of risk of diabetes. No benefit was seen in the lowest risk quarter. Participants in the highest risk quarter averaged a 21.4% three year absolute risk reduction (number needed to treat 4.6).


CONCLUSIONS
Patients at high risk of diabetes have substantial variation in their likelihood of receiving benefit from diabetes prevention treatments. Using this knowledge could decrease overtreatment and make prevention of diabetes far more efficient, effective, and patient centered, provided that decision making is based on an accurate risk prediction tool.
Risk-Neutral Skewness: Evidence from Stock Options

We investigate the relative importance of various factors in explaining the volatility skew observed in the prices of stock options traded on the Chicago Board Options Exchange. The skewness of the risk-neutral density implied by individual stock option prices tends to be more negative for stocks that have larger betas, suggesting that market risk is important in pricing individual stock options. Also, implied skewness tends to be more negative in periods of high market volatility, and when the risk-neutral density for index options is more negatively skewed. Other firm-specific factors, including firm size and trading volume also help explain cross-sectional variation in skewness. However, we find no robust relationship between skewness and the firm's leverage. Nor do we find evidence that skewness is related to the put/call ratio, which may be viewed as a proxy for trading pressure or market sentiment. Overall, firm-specific factors seem to be more important than systematic factors in explaining the variation in the skew for individual firms.
Learning Human-Object Interactions by Graph Parsing Neural Networks

This paper addresses the task of detecting and recognizing human-object interactions (HOI) in images and videos. We introduce the Graph Parsing Neural Network (GPNN), a framework that incorporates structural knowledge while being differentiable end-to-end. For a given scene, GPNN infers a parse graph that includes i) the HOI graph structure represented by an adjacency matrix, and ii) the node labels. Within a message passing inference framework, GPNN iteratively computes the adjacency matrices and node labels. We extensively evaluate our model on three HOI detection benchmarks on images and videos: HICO-DET, V-COCO, and CAD-120 datasets. Our approach significantly outperforms state-of-art methods, verifying that GPNN is scalable to large datasets and applies to spatial-temporal settings.
Robust Automated Detection of Microstructural White Matter Degeneration in Alzheimer’s Disease Using Machine Learning Classification of Multicenter DTI Data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer's disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample.
Acupuncture and Meditation for Military Veterans: First Steps of Quality Management and Future Program Development

Veterans of all war eras have a high rate of chronic disease, mental health disorders, and chronic multi-symptom illnesses (CMI).(1-3) Many veterans report symptoms that affect multiple biological systems as opposed to isolated disease states. Standard medical treatments often target isolated disease states such as headaches, insomnia, or back pain and at times may miss the more complex, multisystem dysfunction that has been documented in the veteran population. Research has shown that veterans have complex symptomatology involving physical, cognitive, psychological, and behavioral disturbances, such as difficult to diagnose pain patterns, irritable bowel syndrome, chronic fatigue, anxiety, depression, sleep disturbance, or neurocognitive dysfunction.(2-4) Meditation and acupuncture are each broad-spectrum treatments designed to target multiple biological systems simultaneously, and thus, may be well suited for these complex chronic illnesses. The emerging literature indicates that complementary and integrative medicine (CIM) approaches augment standard medical treatments to enhance positive outcomes for those with chronic disease, mental health disorders, and CMI.(5-12.)
Short intervals induce superior training adaptations compared with long intervals in cyclists - an effort-matched approach.

The purpose of this study was to compare the effects of 10 weeks of effort-matched short intervals (SI; n = 9) or long intervals (LI; n = 7) in cyclists. The high-intensity interval sessions (HIT) were performed twice a week interspersed with low-intensity training. There were no differences between groups at pretest. There were no differences between groups in total volume of both HIT and low-intensity training. The SI group achieved a larger relative improvement in VO(2max) than the LI group (8.7% ± 5.0% vs 2.6% ± 5.2%), respectively, P ≤ 0.05). Mean effect size (ES) of the relative improvement in all measured parameters, including performance measured as mean power output during 30-s all-out, 5-min all-out, and 40-min all-out tests revealed a moderate-to-large effect of SI training vs LI training (ES range was 0.86-1.54). These results suggest that the present SI protocol induces superior training adaptations on both the high-power region and lower power region of cyclists' power profile compared with the present LI protocol.
Research on the physical properties of geothermal reservoir rocks. Progress report 2, September 1, 1976--January 10, 1977

Textural properties, including porosity and density, of rock samples collected from Cenozoic volcanic fields in the western U.S. were studied. Resistivity and acoustic wave speed measurements were also made. (JGB)
Improved coil design for functional magnetic stimulation of expiratory muscles

The authors' studies have demonstrated effective stimulation of the expiratory muscles in patients with spinal cord injury (SCI) using functional magnetic stimulation (FMS). The observed contraction of the expiratory muscles and functional improvement of the pulmonary functions make functional magnetic stimulation an appropriate tool for expiratory muscle training. To fully capitalize on the benefits of FMS for expiratory muscle training, this study aimed to optimize the magnetic coils (MCs). The primary goal of this study was to investigate how two parameters of the MC size and winding structure, would affect expiratory muscle training. By varying these parameters, the authors' approach was to conceptualize and evaluate the induced electric field and nerve activation function distributions of six coils, round 9.2, 13.7, and 20 cm, and spiral 9.2-, 13.7-, and 20-cm coils in the computer modeling phase. Round 9.2 cm, spiral 13.7 cm, and spiral 20-cm coils were also evaluated in experimental studies for induced electrical field and in clinical studies of expiratory muscles. Both the computer models and experimental measurements indicated that the spiral 20-cm coil can not only stimulate more expiratory spinal nerves but can also stimulate them more evenly. In addition, coils with larger diameters had better penetration than those with smaller diameters. The clinical results showed that the spiral 20-cm coil produced higher expiratory pressure, flow and volume in five able-bodied subjects, and it was the coil of choice among the subjects when asked their preferences. In the authors' attempt to optimize MC design for FMS of expiratory muscle training, they followed the designing guidelines set out in their previous study and arrived at a more effective tool.
Why You Can ' t Find a Taxi in the Rain and Other Labor Supply Lessons from Cab Drivers

Why You Can’t Find a Taxi in the Rain and Other Labor Supply Lessons from Cab Drivers In a seminal paper, Camerer, Babcock, Loewenstein, and Thaler (1997) find that the wage elasticity of daily hours of work New York City (NYC) taxi drivers is negative and conclude that their labor supply behavior is consistent with target earning (having reference dependent preferences). I replicate and extend the CBLT analysis using data from all trips taken in all taxi cabs in NYC for the five years from 2009-2013. Using the model of expectations-based reference points of Koszegi and Rabin (2006), I distinguish between anticipated and unanticipated daily wage variation and present evidence that only a small fraction of wage variation (about 1/8) is unanticipated so that reference dependence (which is relevant only in response to unanticipated variation) can, at best, play a limited role in determining labor supply. The overall pattern in my data is clear: drivers tend to respond positively to unanticipated as well as anticipated increases in earnings opportunities. This is consistent with the neoclassical optimizing model of labor supply and does not support the reference dependent preferences model. I explore heterogeneity across drivers in their labor supply elasticities and consider whether new drivers differ from more experienced drivers in their behavior. I find substantial heterogeneity across drivers in their elasticities, but the estimated elasticities are generally positive and only rarely substantially negative. I also find that new drivers with smaller elasticities are more likely to exit the industry while drivers who remain learn quickly to be better optimizers (have positive labor supply elasticities that grow with experience). JEL Classification: J22, D01, D03
Death from Ingestion of E-Liquid.

BACKGROUND
The use of e-liquids is becoming more prevalent. There is a risk that such liquids may be ingested by mouth rather than being vaped/ inhaled. Due to the high concentration of drugs such as nicotine in these liquids, there may be toxic, and possibly fatal consequences.


CASE REPORT
We report the death of a 32-year-old male who ingested nicotine-containing e-liquid while under the influence of alcohol. A serum sample taken 24 h after collapse contained nicotine at a concentration of 1600 ng/mL of nicotine. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: Death secondary to e-liquid ingestion is still very rare, but has the potential for causing deaths due to the easy access of such liquids to the general public. Such toxicity should be considered in individuals who present in the early phases with symptoms of stimulant toxicity, but also in the latter phase where there may be autonomic depressive effects.
Wavelet transform based new interpolation technique for satellite image resolution enhancement

In this research paper, we propose a new interpolation technique based on the Stationary Wavelet Transform (SWT) and iterative back projection (IBP) for satellite images. Firstly the low resolution image is interpolated by using bicubic interpolation and then decomposed into different subband images by SWT. Each subband is decimated to four lower low resolution images. The four low resolution images are interpolated and registered by using bicubic interpolation and IBP respectively. Inverse SWT (ISWT) is used to generate a Super-resolved output image. The proposed interpolation technique has been tested on several remote sensing images. The quantitative PSNR and SSIM results as well as the visual results show the superiority of the proposed interpolation technique over the other interpolation and image resolution enhancement techniques. For one of the images the PSNR of the proposed method has achieved 3.84dB, 2.11dB, and 1.1dB more improvements than bicubic interpolation, Irani and Peleg technique, and Wavlet Zero Padding technique respectively.
Decomposing Coverings and the Planar Sensor Cover Problem

We show that a k-fold covering using translates of an arbitrary convex polygon can be decomposed into Omega(k) covers (using an efficient algorithm). We generalize this result to obtain a constant factor approximation to the sensor cover problem where the ranges of the sensors are translates of a given convex polygon. The crucial ingredient in this generalization is a constant factor approximation algorithm for a one-dimensional version of the sensor cover problem, called the Restricted Strip Cover (RSC) problem, where sensors are intervals of possibly different lengths. Our algorithm for RSC improves on the previous O(log log log n) approximation.
An Environment for Automated Test Case Generation from Statechart-based and Finite State Machine-based Behavioral Models

Automated test case generation from behavioral models like finite state machines (FSMs) and statecharts has long been studied. Environments that enable a test designer to model a real complex software and to obtain test cases to validate such a software are mandatory in an automated test approach. This paper presents an environment, GTSC, which enables test sequences to be obtained from both Statechart-based and FSM-based behavioral models. The environment supports test case generation from some test methods for FSM, such as switch cover, DS and UIO methods, and also from some test criteria for Statecharts based on the SCCF family. Two case studies involving embedded software developed for two computers of scientific experiments of a satellite under development at National Institute for Space Research (INPE) are presented in order to show the usefulness of the environment.