LLukas22/scidocs huggingface dataset:
Auto-Context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging

Brain extraction or whole brain segmentation is an important first step in many of the neuroimage analysis pipelines. The accuracy and the robustness of brain extraction, therefore, are crucial for the accuracy of the entire brain analysis process. The state-of-the-art brain extraction techniques rely heavily on the accuracy of alignment or registration between brain atlases and query brain anatomy, and/or make assumptions about the image geometry, and therefore have limited success when these assumptions do not hold or image registration fails. With the aim of designing an accurate, learning-based, geometry-independent, and registration-free brain extraction tool, in this paper, we present a technique based on an auto-context convolutional neural network (CNN), in which intrinsic local and global image features are learned through 2-D patches of different window sizes. We consider two different architectures: 1) a voxelwise approach based on three parallel 2-D convolutional pathways for three different directions (axial, coronal, and sagittal) that implicitly learn 3-D image information without the need for computationally expensive 3-D convolutions and 2) a fully convolutional network based on the U-net architecture. Posterior probability maps generated by the networks are used iteratively as context information along with the original image patches to learn the local shape and connectedness of the brain to extract it from non-brain tissue. The brain extraction results we have obtained from our CNNs are superior to the recently reported results in the literature on two publicly available benchmark data sets, namely, LPBA40 and OASIS, in which we obtained the Dice overlap coefficients of 97.73% and 97.62%, respectively. Significant improvement was achieved via our auto-context algorithm. Furthermore, we evaluated the performance of our algorithm in the challenging problem of extracting arbitrarily oriented fetal brains in reconstructed fetal brain magnetic resonance imaging (MRI) data sets. In this application, our voxelwise auto-context CNN performed much better than the other methods (Dice coefficient: 95.97%), where the other methods performed poorly due to the non-standard orientation and geometry of the fetal brain in MRI. Through training, our method can provide accurate brain extraction in challenging applications. This, in turn, may reduce the problems associated with image registration in segmentation tasks.
Morehouse Community Physicians Network (CPN) hypertension registry: patterns of care and opportunities for targeted medical education.

BACKGROUND
Provider-focused strategies for improving outcomes in hypertension have produced mixed results. Studies suggest that the effectiveness of a chosen strategy increases when it is tailored to the specific situation. The hypertension registry includes data on African-American hypertensives who receive care in community-based primary care settings. We examined the registry to identify patterns of care and opportunities for provider-focused interventions to improve patient outcomes.


METHODS AND RESULTS
The registry will include all records of hypertensive patients from 50 community-based primary care practices at full enrollment. Data from nine practices were manually abstracted into an electronic database and analyzed. Seven hundred and ten records were included in this report. Approximately 70% are female, average age 47 +/- 13 years, 5.3% are uninsured, and more than 60% have at least a high school education. Registry patients have multiple co-morbid conditions: 28% are diabetic, 8% have left ventricular hypertrophy, 5% have congestive heart failure, 6.5% have renal insufficiency, 5% have cerebrovascular disease, 3.5% have previous myocardial infarction and 2% have peripheral vascular disease. Among those with diabetes, mean glycosylated hemoglobin was 7.4 +/- 2. Pattern of antihypertensive use showed 43% on diuretics, 28% on calcium channel blockers, 24% on angiotensin converting enzyme inhibitors, 20% on beta blockers and 16% on angiotensin receptor blockers. Overall, 37% were at goal blood pressure and among those with diabetes, only 16% reached goal blood pressure.


CONCLUSION
We conclude that the blood pressure control rates of African Americans in the registry trail those of the general population. This provides a unique opportunity to study the underlying factors and design tailored interventions to address this disparity in health outcome.
Full control of the spin-wave damping in a magnetic insulator using spin-orbit torque.

It is demonstrated that the threshold current for damping compensation can be reached in a 5  μm diameter YIG(20  nm)|Pt(7  nm) disk. The demonstration rests upon the measurement of the ferromagnetic resonance linewidth as a function of I(dc) using a magnetic resonance force microscope (MRFM). It is shown that the magnetic losses of spin-wave modes existing in the magnetic insulator can be reduced or enhanced by at least a factor of 5 depending on the polarity and intensity of an in-plane dc current I(dc) flowing through the adjacent normal metal with strong spin-orbit interaction. Complete compensation of the damping of the fundamental mode by spin-orbit torque is reached for a current density of ∼3×10(11)  A·m(-2), in agreement with theoretical predictions. At this critical threshold the MRFM detects a small change of static magnetization, a behavior consistent with the onset of an auto-oscillation regime.
Neural nets versus conventional techniques in credit scoring in Egyptian banking

Neural nets have become one of the most important tools using in credit scoring. Credit scoring is regarded as a core appraised tool of commercial banks during the last few decades. The purpose of this paper is to investigate the ability of neural nets, such as probabilistic neural nets and multi-layer feed-forward nets, and conventional techniques such as, discriminant analysis, probit analysis and logistic regression, in evaluating credit risk in Egyptian banks applying credit scoring models. The credit scoring task is performed on one bank’s personal loans’ data-set. The results so far revealed that the neural nets-models gave a better average correct classification rate than the other techniques. A one-way analysis of variance and other tests have been applied, demonstrating that there are some significant differences amongst the means of the correct classification rates, pertaining to different techniques. 2007 Elsevier Ltd. All rights reserved. JEL Classification: G21; G32
Evolving Neural Networks for Word Sense Disambiguation

We propose a supervised approach to word sense disambiguation based on neural networks combined with evolutionary algorithms. Large tagged datasets for every sense of a polysemous word are considered, and used to evolve an optimized neural network that correctly disambiguates the sense of the given word considering the context in which it occurs. The viability of the approach has been demonstrated through experiments carried out on a representative set of polysemous words.
Lambda Calculus and Intuitionistic Linear Logic

The Curry-Howard isomorphism 1 is the basis of typed functional programming. By means of this isomorphism, the intuitionistic proof of a formula can be seen as a functional program, whose type is the formula itself. In this way, the computation process has its logic realization in the proof normalization procedure. Both the implicative fragment of the intuitionistic propositional logic together with the simply typed λ-calculus [3], and the second order propositional logic together with the second order λ-calculus of Girard and Reynold [8, 19] are examples of such an isomorphism. The linear logic, introduced by Girard [9], seems to be particularly interesting from the computational point of view. It is more refined than the classical logic: the use of the structural rules is explicitly controlled through a modal connective, denoted by the unary operator !. In other words, weakening and contraction can be applied only to modal formulas. Since weakening and contraction rules are naturally related to the operations of erasing and copying information, respectively, the linear logic can be seen as a model for a computational environment with an explicit control of the resource management. These features can be effectively studied using a language corresponding to the intuitionistic fragment of the linear logic, through the Curry-Howard isomorphism. Until now, some languages inspired by this isomorphism have been designed. First of all, Lafont [13] defined a calculus of combinators, corresponding to the intuitionistic linear logic (ILL in the following), where combinators were suggested from the categorical interpretation of the logic. Then, he defined a linear abstract machine for the evaluation of his calculus. Abramsky [1] has been the first one proposing a “linear λ-calculus”. His language is inspired to the classical λ-calculus and it is defined using ILL as type assignment for it. The functional language is obtained by “decorating” with terms the rules of the sequent calculus for ILL. Abramsky also proposed an extension of the SECD machine for
Cardiovascular transition to extrauterine life in growth-restricted neonates: relationship with prenatal Doppler findings.

OBJECTIVE
Cardiovascular status in fetal growth restriction (FGR) can be classified by the severity of individual Doppler abnormalities (early and late) or by the rate of clinical progression. We tested the hypothesis that aspects of the fetal cardiovascular status in FGR affect neonatal cardiovascular findings.


STUDY DESIGN
FGR cases [abdominal circumference <5th percentile and an elevated umbilical (MCA) artery (UA) pulsatility index] had UA, middle cerebral artery and ductus venosus (DV) Doppler. Positive UA end-diastolic velocity and/or a low MCA pulsatility index denoted early and absent/reversed UA end-diastolic velocity, whereas an increased DV pulsatility index for veins denoted late responses. The rate of progression was classified into mild, progressive and severe. After delivery, shunt dynamics and blood flow across the patent ductus arteriosus (PDA), foramen ovale and atriaventricular valves, myocardial contractility and pharmacologic pressor requirement were noted at neonatal echocardiography. These findings were related to prenatal Doppler parameters.


RESULTS
In 94 patients, only individual Doppler parameters related to neonatal echocardiographic findings. Absent/reversed UA DV significantly predicted PDA with right to left shunt (p = 0.016). The pressor need for cardiovascular instability was observed in neonates with abnormal prenatal DV Doppler and with lower birth weights delivered at earlier gestational age (p < 0.0001 for both). Pressor need was significantly related to neonatal death (Nagelkerke R² = 0.35, p = 0.002).


CONCLUSION
A markedly abnormal UA Doppler predisposes growth-restricted neonates to persistence of fetal circulation associated with right to left shunting. Abnormal venous Doppler is a risk factor for cardiovascular instability which in turn significantly contributes to neonatal mortality. Further clarification of the neonatal cardiovascular transition may be helpful in guiding early neonatal assessment and management.
Near-Infrared Spectroscopy with Treadmill Exercise to Assess Lower Limb Ischemia in Patients with Atherosclerotic Occlusive Disease

We used near-infrared spectroscopy (NIRS) to measure exercise-induced ischemia in patients with intermittent claudication, and compared these results with those obtained by ankle-brachial pressure index (ABPI) analysis. Sixty-two patients with intermittent claudication caused by atherosclerotic occlusive disease exercised on a treadmill until reaching the maximal tolerated walking distance. We measured the ABPI at rest and after exercise until it returned to the baseline value. A NIRS probe was positioned on the patient’s calf, which allowed the continuous monitoring of oxygen saturation (StO2), oxygenated hemoglobin (Oxy Hb), and deoxygenated hemoglobin (Deoxy Hb) in the calf muscles before, during, and after exercise. During exercise, the StO2 and Oxy Hb decreased, and the Deoxy Hb increased. The time taken for each measurement to return to the baseline value was defined as the recovery time. The recovery times obtained by NIRS and ABPI were compared. The recovery time for ABPI correlated well with that for StO2 (ρs = 0.73), Oxy Hb (ρs = 0.63), and Deoxy Hb (ρs = 0.65); however, the recovery times measured by NIRS were shorter than the recovery time for the ABPI. Near-infrared spectroscopy is a reliable method for monitoring peripheral circulation during and after exercise, although the data generated provided slightly different information than the results obtained by ABPI.
Evaluation of the Patient with Nasal Obstruction.

Nasal obstruction is often multifactorial and knowledge of the contributing factors is critical to appropriate evaluation, diagnosis, and execution of a treatment plan. Recognizing and appropriately managing all components of nasal obstruction will increase the likelihood of symptomatic improvement and patient satisfaction.
Tweets as impact indicators: Examining the implications of automated "bot" accounts on Twitter

This brief communication presents preliminary findings on automated Twitter accounts distributing links to scientific papers deposited on the preprint repository arXiv. It discusses the implication of the presence of such bots from the perspective of social media metrics (altmetrics), where mentions of scholarly documents on Twitter have been suggested as a means of measuring impact that is both broader and timelier than citations. We present preliminary findings that automated Twitter accounts create a considerable amount of tweets to scientific papers and that they behave differently than common social bots, which has critical implications for the use of raw tweet counts in research evaluation and assessment. We discuss some definitions of Twitter cyborgs and bots in scholarly communication and propose differentiating between different levels of engagement from tweeting only bibliographic information to discussing or commenting on the content of a paper. Introduction The so-called altmetrics movement promotes the use of metrics generated from social media platforms as broader and timelier evidence of research impact than citations (Priem, Taraborelli, Groth, & Neylon, 2010). Among these social media platforms, the microblogging platform Twitter has been shown to be one of the most frequently used social media tools that mentions scholarly documents (Costas, Zahedi, & Wouters, 2014; Haustein et al., 2014b; 2014c). As of July 2014, Twitter reported 500 million tweets per day and 255 million monthly active users with 16% of the U.S. population purportedly on Twitter. Scholarly use is proportionally less: it is estimated that between 3% and 15% of researchers utilize this service (Priem & Costello, 2010; Pscheida, Albrecht, Herbst, Minet, & Köhler, 2013; Rowlands, Nicholas, Russell, Canty, & Watkinson, 2011). Therefore, some authors have argued that Twitter is potentially able to capture the impact of scholarly documents on a nonresearching public and might, thus, serve as a measure of broader impact of research. However, systematic evidence as to whether tweets are valid markers of actual societal and/or scientific impact
Individual- and Family-Level Psychosocial Correlates of HIV Risk Behavior Among Youth in Rural Kenya

Associations between individual- and family-level psychosocial factors and sexual behavior were examined among 325 adolescents ages 10–18 in rural Kenya. History of sexual activity was reported by 51% of males and 30% of females. Among those reporting sex within the past year, 64% of males and 32% of females had multiple partners; 85% of males and 54% of females reported not using a condom at last sex. Multivariate logistic regression modeling demonstrated sexually active adolescents were significantly more likely to be older, male, more accepting of risky behavior, and have greater perceived HIV risk, caregiver social support, social support related to HIV, and emotional problems. Youths reporting high-risk behavior (unprotected sex or multiple partners) were significantly more likely to be younger, male, and have lower sex-related self-efficacy, lower caregiver monitoring, and more externalizing problems. Future studies should evaluate HIV prevention interventions targeting improvements in mental health and family relationships.
Transformation of limonene into high added value products over acid activated natural montmorillonite

Abstract Eight samples of activated montmorillonite were prepared by treating natural montmorillonite with HCl and HNO 3 aqueous solutions in order to investigate the influence of several treatment parameters on its physicochemical characteristics and its catalytic activity for limonene transformation to high added value products (isomers and p-cymene). The samples were characterized using various techniques (SEM-EDS, TEM/HRTEM, XRD, ATR-FTIR, nitrogen adsorption-desorption isotherms, microelectrophoresis and determination of equilibrium pH) and evaluated in the transformation of limonene to isomers and p-cymene utilizing atmospheric oxygen as a green oxidant. The acid treatment, even under mild conditions, caused the removal of the sodium and calcium ions from the interlayer regions of the triple layers without disturbing the crystal structure of the triple layers, the plate-like morphology of the mineral at nanoscale and the pore morphology as well. Only the treatment under the hardest conditions (6 M HCl for 2 h) caused the transformation of plate-like particle morphology into granular one and the pore morphology from slit like-pores developed between plate-like particles into internal voids of irregular shape and broad pore size distributions. In contrast, the acid treatment brings about the reorganization/dislocation of the triple layers inside a plate-shaped particle causing the development of small mesopores, mainly in the range of 3–3.5 nm, and consequently the increase in the specific surface from 62 to 155 m 2 /g. In parallel, the removal of the sodium and calcium ions/phases brings about the development of negatively charged surface sites. These are transformed into Bronsted acid sites by adsorbing hydronium ions (H 3 O + ). The above sites are catalytically active in the transformation of the limonene into intermediate isomers and undesired “polymers”. The intermediate isomers are transforming into p-cymene and additional “polymers” through a catalyst-free mechanism, in the presence of atmospheric oxygen acting as a green oxidant. The drastic decrease of the amount of the undesired “polymers” ( The low reaction temperature (100 °C), the use of limonene as a renewable reactant, the use of natural montmorillonite as a natural catalyst and the use of atmospheric oxygen as a green oxidant render the proposed process actually green.
A wireless sensor network compatible wearable u-healthcare monitoring system using integrated ECG, accelerometer and SpO2

This paper presents the design and development of a wearable ubiquitous healthcare monitoring system using integrated electrocardiogram (ECG), accelerometer and oxygen saturation (SpO2) sensors. In this design, non-intrusive healthcare system was designed based on wireless sensor network (WSN) for wide area coverage with minimum battery power to support RF transmission. We have developed various devices such as wearable ubiquitous sensor network (USN) node, wearable chest sensor belt and wrist pulse oximeter for this system. Low power ECG, accelerometer and SpO2 sensors board was integrated to the wearable USN node for user's health monitoring. The wearable ubiquitous healthcare monitoring system allows physiological data to be transmitted in wireless sensor network using IEEE 802.15.4 from on-body wearable sensor devices to a base-station which is connected to a server PC. Physiological data can be displayed and stored in the server PC continuously.
Long working hours and alcohol use: systematic review and meta-analysis of published studies and unpublished individual participant data

OBJECTIVE
To quantify the association between long working hours and alcohol use.


DESIGN
Systematic review and meta-analysis of published studies and unpublished individual participant data.


DATA SOURCES
A systematic search of PubMed and Embase databases in April 2014 for published studies, supplemented with manual searches. Unpublished individual participant data were obtained from 27 additional studies.


REVIEW METHODS
The search strategy was designed to retrieve cross sectional and prospective studies of the association between long working hours and alcohol use. Summary estimates were obtained with random effects meta-analysis. Sources of heterogeneity were examined with meta-regression.


RESULTS
Cross sectional analysis was based on 61 studies representing 333,693 participants from 14 countries. Prospective analysis was based on 20 studies representing 100,602 participants from nine countries. The pooled maximum adjusted odds ratio for the association between long working hours and alcohol use was 1.11 (95% confidence interval 1.05 to 1.18) in the cross sectional analysis of published and unpublished data. Odds ratio of new onset risky alcohol use was 1.12 (1.04 to 1.20) in the analysis of prospective published and unpublished data. In the 18 studies with individual participant data it was possible to assess the European Union Working Time Directive, which recommends an upper limit of 48 hours a week. Odds ratios of new onset risky alcohol use for those working 49-54 hours and ≥ 55 hours a week were 1.13 (1.02 to 1.26; adjusted difference in incidence 0.8 percentage points) and 1.12 (1.01 to 1.25; adjusted difference in incidence 0.7 percentage points), respectively, compared with working standard 35-40 hours (incidence of new onset risky alcohol use 6.2%). There was no difference in these associations between men and women or by age or socioeconomic groups, geographical regions, sample type (population based v occupational cohort), prevalence of risky alcohol use in the cohort, or sample attrition rate.


CONCLUSIONS
Individuals whose working hours exceed standard recommendations are more likely to increase their alcohol use to levels that pose a health risk.
The Chinese medicine Kuan-Sin-Yin improves liver function in patients with chronic hepatitis C: A randomised and placebo-controlled trial.

BACKGROUND & AIMS
This study examined the effects of a traditional Chinese medicine decoction, Kuan-Sin-Yin (KSY), on patients with chronic hepatitis C (CHC) in a randomised and placebo-controlled clinical trial.


METHODS
This trial enrolled 70 subjects with CHC who were randomised into 2 groups each with 35 participants. In total, 29 participants in the therapeutic group took 100mL of the herbal decoction daily, whereas 28 in the control group took an herbal placebo with the same dose and frequency for the 6-week study. The primary outcomes were liver function and viral load. Secondary measurements included haematopoietic and biochemical profiles, safety parameters, and a quality of life survey. All measurements were collected at the beginning of the study and after 6 weeks.


RESULTS
In within-group analysis, significant decreases of glutamate pyruvate transaminase (GPT) 31.7±75.2IU/L and glutamate oxaloacetate transaminase (GOT) 20.3±45.7IU/L were found in the KSY group (p=0.031 and 0.024, respectively). In the between-group analysis, KSY reduced serum GOT and GPT levels by more than 20IU/L (p=0.027 and 0.047, respectively). KSY also significantly decreased viral load by 0.3 log units (p=0.047). In addition, KSY significantly decreased serum triglyceride 16.9±27.5mg/dL (p=0.024).


CONCLUSIONS
This study demonstrates that taking the KSY herbal decoction for 6 weeks improves liver function and serum triglyceride levels and is safe for patients with CHC. The potential long-term effects of KSY on lipid metabolism related hepatoprotection and viral clearance warrant further investigation.