LLukas22/scidocs huggingface dataset:
Differential effects of beta-blockers in patients with heart failure: A prospective, randomized, double-blind comparison of the long-term effects of metoprolol versus carvedilol.

BACKGROUND
Both metoprolol and carvedilol produce hemodynamic and clinical benefits in patients with chronic heart failure; carvedilol exerts greater antiadrenergic effects than metoprolol, but it is unknown whether this pharmacological difference results in hemodynamic and clinical differences between the 2 drugs.


METHODS AND RESULTS
We randomized 150 patients with heart failure (left ventricular ejection fraction </=0.35) to double-blind treatment with either metoprolol or carvedilol. When compared with metoprolol (124+/-55 mg/d), patients treated with carvedilol (49+/-18 mg/d) showed larger increases in left ventricular ejection fraction at rest (+10.9+/-11.0 versus +7.2+/-7.7 U, P=0.038) and in left ventricular stroke volume and stroke work during exercise (both P<0. 05) after 13 to 15 months of treatment. In addition, carvedilol produced greater decreases in mean pulmonary artery pressure and pulmonary wedge pressure, both at rest and during exercise, than metoprolol (all P<0.05). In contrast, the metoprolol group showed greater increases in maximal exercise capacity than the carvedilol group (P=0.035), but the 2 drugs improved symptoms, submaximal exercise tolerance, and quality of life to a similar degree. After a mean of 23+/-11 months of follow-up, 21 patients in the metoprolol group and 17 patients in the carvedilol group died or underwent urgent transplantation.


CONCLUSIONS
The present study demonstrates that during long-term therapy, carvedilol improves cardiac performance to a greater extent than metoprolol when administered to patients with heart failure in the doses shown to be effective in clinical trials. These differences were likely related to a greater antiadrenergic activity of carvedilol.
Computational Thinking Patterns

The iDREAMS project aims to reinvent Computer Science education in K-12 schools, by using game design and computational science for motivating and educating students through an approach we call Scalable Game Design, starting at the middle school level. In this paper we discuss the use of Computational Thinking Patterns as the basis for our Scalable Game Design curriculum and professional development and present results from measuring student learning outcomes using our unique Computational Thinking Pattern Analysis.
Cross-representation mediation of user models

Personalization is considered a powerful methodology for improving the effectiveness of information search and decision making. It has led to the dissemination of systems capable of suggesting relevant and personalized information (or items) to the users, according to their characteristics and preferences, as represented by a User Model (UM). Since the quality of the personalization largely depends on the size and accuracy of the managed UMs, it would be beneficial to enrich the UMs by mediating, i.e., importing and integrating, UMs built by other personalization systems. This work discusses and evaluates a cross-representation mediation of UMs from collaborative filtering to content-based recommender systems. According to this approach, a content-based recommender system, having partial or no UM data, can generate recommendations for users by mediating UM data of the same users, collected by a collaborative filtering system. The mediation process transforms the UMs from the collaborative filtering ratings to the content-based weighted item features. The mediation process exploits the item descriptions that are typically not used by the collaborative filtering recommender systems. An experimental evaluation conducted in the domain of movies shows that for users with small collaborative filtering UMs, i.e., users with few item ratings, the accuracy of the recommendations provided using the mediated content-based UMs is superior to that using the original collaborative filtering UMs. Moreover, it shows that the mediation can be used to improve a content-based recommender system by incrementally mediating collaborative filtering UM data (item ratings) and enriching the available content-based UMs.
Color and texture for corn seed classification by machine vision

Machine vision has been applied to various food materials inspection process of agricultural industry in order to achieve fast and accurate operation. In this paper, we proposed a method to classify more than ten categories of seed defects by using color, texture features and support vector machine (SVM) type classifier. We also developed an image capturing machine that is able to support large volume of seed samples. The image capturing machine was designed to control uncertainty light level, reflection and shadow appeared on seed samples. Therefore, quality of images that can be obtained from the machine in term of accurate color and exposure is high. In addition, the designed image capturing machine also provides support to background subtraction and touching object segmentation processes. In the image classification part, color histograms in RGB and HSV color space together with texture based on Grey level co-occurrence matrix (GLCM) and Local binary pattern (LBP) is adopted as features. The proposed systems were evaluated from more than 10,000 sample images. The obtained accuracies are 95.6% for normal seed type and 80.6% for group of defect seed types. The preliminary results of this study are useful information for future development of the quality control technique in practical usage.
Comparing strategies for treating emotion perception deficits in traumatic brain injury.

OBJECTIVE
To compare the efficacy of 2 strategies, errorless learning (EL) and self-instruction training (SIT), for remediating emotion perception deficits in individuals with traumatic brain injury (TBI).


DESIGN
Randomized controlled trial comparing groups receiving 25 hours (across 10 weeks) of treatment with either EL or SIT with waitlist control.


SETTING AND PARTICIPANTS
Eighteen adult outpatient volunteers with severe TBI who were at least 6 months postinjury.


MAIN OUTCOMES MEASURES
Photograph-based emotion recognition tasks, The Awareness of Social Inferences Test, and questionnaire measures, for example, the Sydney Psychosocial Reintegration Scale.


RESULTS
Both treatment groups showed modest improvement in emotion perception ability. Limited evidence suggests that SIT may be a favorable approach for this type of remediation.


CONCLUSIONS
Although further research is needed, there are reasons for optimism regarding rehabilitation of emotion perception following TBI.
Design and rationale for the Patient and Provider Assessment of Lipid Management (PALM) registry.

BACKGROUND
Despite improvements in diagnosis and treatment, the prevalence of hyperlipidemia among adults in the United States remains high. Data are limited on treatment patterns and patient perceptions of cardiovascular disease risk since the release of new lipid guidelines.


OBJECTIVES
The objectives of the PALM registry are to assess contemporary patterns of lipid-lowering therapy use among adults receiving care in a nationally representative cohort of community clinics, determine consistency of treatment with varying lipid guidelines, identify factors affecting use of lipid-lowering therapy including patient-reported statin intolerance, and assess patient and provider knowledge of cardiovascular risk reduction goals.


STUDY DESIGN
The PALM registry will enroll 7,500 patients likely to be considered for lipid-lowering therapy from 175 cardiology, primary care, and endocrinology practices across the United States. In this cross-sectional, observational registry, a novel tablet-based platform will be used to collect patient-reported knowledge, attitudes, and beliefs regarding cardiovascular risk reduction and lipid management. Chart abstraction and core laboratory lipid levels will describe current lipid management. Provider surveys will assess perception of current lipid-lowering goals and barriers to optimal cardiovascular risk reduction.


CONCLUSION
The PALM registry will allow for better understanding of current practice patterns, patient experiences, and patient and provider attitudes toward cholesterol management for cardiovascular disease risk reduction. These data can be used to better understand gaps in care and design targeted interventions to improve uptake of lipid-lowering therapies for cardiovascular risk reduction.
Green Communication in Energy Renewable Wireless Mesh Networks: Routing, Rate Control, and Power Allocation

The increasing demand for wireless services has led to a severe energy consumption problem with the rising of greenhouse gas emission. While the renewable energy can somehow alleviate this problem, the routing, flow rate, and power still have to be well investigated with the objective of minimizing energy consumption in multi-hop energy renewable wireless mesh networks (ER-WMNs). This paper formulates the problem of network-wide energy consumption minimization under the network throughput constraint as a mixed-integer nonlinear programming problem by jointly optimizing routing, rate control, and power allocation. Moreover, the min-max fairness model is applied to address the fairness issue because the uneven routing problem may incur the sharp reduction of network performance in multi-hop ER-WMNs. Due to the high computational complexity of the formulated mathematical programming problem, an energy-aware multi-path routing algorithm (EARA) is also proposed to deal with the joint control of routing, flow rate, and power allocation in practical multi-hop WMNs. To search the optimal routing, it applies a weighted Dijkstra's shortest path algorithm, where the weight is defined as a function of the power consumption and residual energy of a node. Extensive simulation results are presented to show the performance of the proposed schemes and the effects of energy replenishment rate and network throughput on the network lifetime.
Quantitative and Localization Diagnosis of a Defective Ball Bearing Based on Vertical–Horizontal Synchronization Signal Analysis

A novel method is proposed for quantitative and localization diagnosis of a bearing outer ring defect in this paper. This method aims to distinguish these defects with different angular positions and different sizes based on the natural multiples of the ball angular spacing. Defects that differ in size by natural multiples of the ball angular spacing will have the same time interval, which may lead to misdiagnosis. Distinguishing such defects accurately is the goal for some industries. Therefore, the synchronized signal in the vertical and horizontal directions of the bearing systems with different angular positions and different size defects are quantitatively analyzed based on the presented five indices to explore the mechanism and method of distinguishing these defects. The simulation and experimental results show that the vertical–horizontal synchronized root mean square (VHSRMS) index can distinguish such defects effectively, and the defect angle position can be diagnosed using the VHSRMS–1 . More importantly, the VHS analysis method expands the location of the outer ring defect to 265–275° in quantitative diagnosis and realizes the localization diagnosis of the defect angle position. The research results provide a new approach and method for quantitative and localization diagnosis of a defective bearing.
Tailored internet-administered treatment of anxiety disorders for primary care patients: study protocol for a randomised controlled trial

BACKGROUND
Internet-administered cognitive behavioural therapy (ICBT) has been found to be effective for a range of anxiety disorders. However, most studies have focused on one specific primary diagnosis and co-morbidity has not been considered. In primary care settings, patients with anxiety often suffer from more than one psychiatric condition, making it difficult to disseminate ICBT for specific conditions. The aim of this study will be to investigate if ICBT tailored according to symptom profile can be a feasible treatment for primary care patients with anxiety disorders. It is a randomised controlled trial aimed to evaluate the treatment against an active control group.


METHODS
Participants with anxiety disorders and co-morbid conditions (N = 128), will be recruited from a primary care population. The Clinical Outcome in Routine Evaluation (CORE-OM) will serve as the primary outcome measure. Secondary measures include self-reported depression, anxiety, quality of life and loss of production and the use of health care. All assessments will be collected via the Internet and measure points will be baseline, post treatment and 12 months post treatment.


DISCUSSION
This trial will add to the body of knowledge on the effectiveness of ICBT for anxiety disorders in primary care. The trial will also add knowledge on the long term effects of ICBT when delivered for regular clinic patients


TRIAL REGISTRATION
ClinicalTrials.gov: NCT01390168.
Mechanomyography versus Electromyography, in monitoring the muscular fatigue

BACKGROUND
The use of the mechanomyogram (MMG) which detects muscular vibrations generated by fused individual fiber twitches has been refined. The study addresses a comparison of the MMG and surface electromyogram (SEMG) in monitoring muscle fatigue.


METHODS
The SEMG and MMG were recorded simultaneously from the same territory of motor units in two muscles (Biceps, Brachioradialis) of the human (n = 18), during sustained contraction at 25 % MVC (maximal voluntary contraction).


RESULTS
The RMS (root mean square) of the SEMG and MMG increased with advancing fatigue; MF (median frequency) of the PSD (power density spectra) progressively decreased from the onset of the contraction. These findings (both muscles, all subjects), demonstrate both through the SEMG and MMG a central component of the fatigue. The MF regression slopes of MMG were closer to each other between men and women (Biceps 1.55%; Brachialis 13.2%) than were the SEMG MF slopes (Biceps 25.32%; Brachialis 17.72%), which shows a smaller inter-sex variability for the MMG vs. SEMG.


CONCLUSION
The study presents another quantitative comparison (MF, RMS) of MMG and SEMG, showing that MMG signal can be used for indication of the degree of muscle activation and for monitoring the muscle fatigue when the application of SEMG is not feasible (chronical implants, adverse environments contaminated by electrical noise).
Factors to Consider in the Association Between Soy Isoflavone Intake and Breast Cancer Risk

It has been suggested that soy isoflavones have protective effects against breast cancer. However, data from epidemiological studies are not conclusive. A recent meta-analysis showed that soy intake was inversely associated with breast cancer risk in Asian but not Western populations, which indicates that protection against breast cancer may require that women consume levels of soy typical in Asian diets. In addition to the amount of soy isoflavones consumed, the form and food source of isoflavones, timing of isoflavone exposure, estrogen receptor status of tumors, and equol-producer status and hormonal profile of individuals may modify the association between soy isoflavone intake and the risk of breast cancer. These factors might explain the heterogeneity of results from studies. This present report contrasts background data from Japanese and Western women to identify the potential modifying of these factors.
AIDA - Abstraction for Advanced In-Database Analytics

With the tremendous growth in data science and machine learning, it has become increasingly clear that traditional relational database management systems (RDBMS) are lacking appropriate support for the programming paradigms required by such applications, whose developers prefer tools that perform the computation outside the database system. While the database community has attempted to integrate some of these tools in the RDBMS, this has not swayed the trend as existing solutions are often not convenient for the incremental, iterative development approach used in these fields. In this paper, we propose AIDA an abstraction for advanced in-database analytics. AIDA emulates the syntax and semantics of popular data science packages but transparently executes the required transformations and computations inside the RDBMS. In particular, AIDA works with a regular Python interpreter as a client to connect to the database. Furthermore, it supports the seamless use of both relational and linear algebra operations using a unified abstraction. AIDA relies on the RDBMS engine to efficiently execute relational operations and on an embedded Python interpreter and NumPy to perform linear algebra operations. Data reformatting is done transparently and avoids data copy whenever possible. AIDA does not require changes to statistical packages or the RDBMS facilitating portability. PVLDB Reference Format: Joseph Vinish D’silva, Florestan De Moor, Bettina Kemme. AIDA Abstraction for Advanced In-Database Analytics. PVLDB, 11(11): 1400-1413, 2018. DOI: https://doi.org/10.14778/3236187.3236194
Prenatal exposure to maternal depression and cortisol influences infant temperament.

BACKGROUND
Accumulating evidence indicates that prenatal maternal and fetal processes can have a lasting influence on infant and child development. Results from animal models indicate that prenatal exposure to maternal stress and stress hormones has lasting consequences for development of the offspring. Few prospective studies of human pregnancy have examined the consequences of prenatal exposure to stress and stress hormones.


METHOD
In this study the effects of prenatal maternal psychosocial (anxiety, depression, and perceived stress) and endocrine (cortisol) indicators of stress on infant temperament were examined in a sample of 247 full-term infants. Maternal salivary cortisol and psychological state were evaluated at 18-20, 24-26, and 30-32 weeks of gestation and at 2 months postpartum. Infant temperament was assessed with a measure of negative reactivity (the fear subscale of the Infant Temperament Questionnaire) at 2 months of age.


RESULTS
Elevated maternal cortisol at 30-32 weeks of gestation, but not earlier in pregnancy, was significantly associated with greater maternal report of infant negative reactivity. Prenatal maternal anxiety and depression additionally predicted infant temperament. The associations between maternal cortisol and maternal depression remained after controlling for postnatal maternal psychological state.


CONCLUSIONS
These data suggest that prenatal exposure to maternal stress has consequences for the development of infant temperament.
Evaluating React Native and Progressive Web App development using ISO 25010

The vast supply of different smartphone makes and models, along with their accompanying operating systems, increase the demand for an all-in-one development solution. Quite a few approaches to solving this problem have cropped up over the years, ranging from purely web-oriented solutions to something more akin to a native application. React Native and Progressive Web App development are two different approaches, both new and promising, on this spectrum. This thesis evaluates these approaches in a standardized way using the ISO 25010 Product Quality Model to gain insight into these types of cross-platform development as well as how well such an evaluation works in this context. The results show that, while not a perfect fit, a standardized evaluation brings forward less obvious aspects of the development process and contributes with a helpful structure to the evaluation process. Author
The emerging roles of ADAMTS-7 and ADAMTS-12 matrix metalloproteinases

The a disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS) comprise a family of secreted zinc metalloproteinases with a precisely ordered modular organization. These enzymes play an important role in the turnover of extracellular matrix proteins in various tissues and their dysregulation has been implicated in disease-related processes such as arthritis, atherosclerosis, cancer, and inflammation. ADAMTS-7 and ADAMTS-12 share a similar domain organization to each other and form a subgroup within the ADAMTS family. Emerging evidence suggests that ADAMTS-7 and ADAMTS-12 may play an important role in the development and pathogenesis of various kinds of diseases. In this review, we summarize what is currently known about the roles of these two metalloproteinases, with a special focus on their involvement in chondrogenesis, endochondral ossification, and the pathogenesis of arthritis, atherosclerosis, and cancer. The future study of ADAMTS-7 and ADAMTS-12, as well as the molecules with which they interact, will help us to better understand a variety of human diseases from both a biological and therapeutic standpoint.
First Japanese case of congenital generalized hypertrichosis with a copy number variation on chromosome 17q24.

Hypertrichosis is defined as excessive hair growth compared with individuals of the same age, race and sex [1]. Congenital generalized hypertrichosis (CGH) is a rare syndrome characterized by universal hair overgrowth which is not caused by androgen stimulation [1,2]. In addition to hypertrichosis, patients with CGH can have other associated abnormalities, such as cardiomyopathy and gingival hyperplasia [1,2]. CGH can show X-linked recessive (OMIM 307150), autosomal dominant or autosomal recessive (OMIM 135400) inheritance trait, and recent advances in molecular genetics have gradually disclosed the pathogenesis of CGH [3– 6]. Of these findings, it has been reported that autosomal dominant form of CGH with or without gingival hyperplasia is caused by copy number variations (CNVs) on chromosome (Ch) 17q24.2-q24.3 [4]. Interestingly, SOX9 gene, which is known to play a role in maintenance of hair follicle (HF) stem cells [7,8], is located close to the region of the CNVs, and it has been demonstrated that a CNV on Ch17q24.2-q24.3 resulted in reduced expression of the SOX9mRNA, most likely due to a position effect [6]. Furthermore, autosomal recessive form of CGH has been shown to be caused by a loss-of-function mutation in ABCA5 gene encoding a member of the ABC transporter [6]. Importantly, the ABCA5 gene resides on Ch17q24.3, where the CNVs occurred in patients with autosomal
The EM Algorithm

The Expectation-Maximization (EM) algorithm is a broadly applicable approach to the iterative computation of maximum likelihood (ML) estimates, useful in a variety of incomplete-data problems. Maximum likelihood estimation and likelihood-based inference are of central importance in statistical theory and data analysis. Maximum likelihood estimation is a general-purpose method with attractive properties. It is the most-often used estimation technique in the frequentist framework; it is also relevant in the Bayesian framework (Chapter III.11). Often Bayesian solutions are justified with the help of likelihoods and maximum likelihood estimates (MLE), and Bayesian solutions are similar to penalized likelihood estimates. Maximum likelihood estimation is an ubiquitous technique and is used extensively in every area where statistical techniques are used. We assume that the observed data y has probability density function (p.d.f.) g(y; Ψ ), where Ψ is the vector containing the unknown parameters in the postulated form for the p.d.f. of Y . Our objective is to maximize the likelihood L(Ψ ) = g(y; Ψ ) as a function of Ψ , over the parameter space Ω. That is, ∂L(Ψ )/∂Ψ = 0,