LLukas22/scidocs huggingface dataset:
Curing profile of bulk-fill resin-based composites.

OBJECTIVE
To evaluate the curing profile of bulk-fill resin-based composites (RBC) using micro-Raman spectroscopy (μRaman).


METHODS
Four bulk-fill RBCs were compared to a conventional RBC. RBC blocks were light-cured using a polywave LED light-curing unit. The 24-h degree of conversion (DC) was mapped along a longitudinal cross-section using μRaman. Curing profiles were constructed and 'effective' (>90% of maximum DC) curing parameters were calculated. A statistical linear mixed effects model was constructed to analyze the relative effect of the different curing parameters.


RESULTS
Curing efficiency differed widely with the flowable bulk-fill RBCs presenting a significantly larger 'effective' curing area than the fibre-reinforced RBC, which on its turn revealed a significantly larger 'effective' curing area than the full-depth bulk-fill and conventional (control) RBC. A decrease in 'effective' curing depth within the light beam was found in the same order. Only the flowable bulk-fill RBCs were able to cure 'effectively' at a 4-mm depth for the whole specimen width (up to 4mm outside the light beam). All curing parameters were found to statistically influence the statistical model and thus the curing profile, except for the beam inhomogeneity (regarding the position of the 410-nm versus that of 470-nm LEDs) that did not significantly affect the model for all RBCs tested.


CONCLUSIONS
Most of the bulk-fill RBCs could be cured up to at least a 4-mm depth, thereby validating the respective manufacturer's recommendations.


CLINICAL SIGNIFICANCE
According to the curing profiles, the orientation and position of the light guide is less critical for the bulk-fill RBCs than for the conventional RBC.
Characteristics, complications, and gaps in evidence-based interventions in rheumatic heart disease: the Global Rheumatic Heart Disease Registry (the REMEDY study).

AIMS
Rheumatic heart disease (RHD) accounts for over a million premature deaths annually; however, there is little contemporary information on presentation, complications, and treatment.


METHODS AND RESULTS
This prospective registry enrolled 3343 patients (median age 28 years, 66.2% female) presenting with RHD at 25 hospitals in 12 African countries, India, and Yemen between January 2010 and November 2012. The majority (63.9%) had moderate-to-severe multivalvular disease complicated by congestive heart failure (33.4%), pulmonary hypertension (28.8%), atrial fibrillation (AF) (21.8%), stroke (7.1%), infective endocarditis (4%), and major bleeding (2.7%). One-quarter of adults and 5.3% of children had decreased left ventricular (LV) systolic function; 23% of adults and 14.1% of children had dilated LVs. Fifty-five percent (n = 1761) of patients were on secondary antibiotic prophylaxis. Oral anti-coagulants were prescribed in 69.5% (n = 946) of patients with mechanical valves (n = 501), AF (n = 397), and high-risk mitral stenosis in sinus rhythm (n = 48). However, only 28.3% (n = 269) had a therapeutic international normalized ratio. Among 1825 women of childbearing age (12-51 years), only 3.6% (n = 65) were on contraception. The utilization of valvuloplasty and valve surgery was higher in upper-middle compared with lower-income countries.


CONCLUSION
Rheumatic heart disease patients were young, predominantly female, and had high prevalence of major cardiovascular complications. There is suboptimal utilization of secondary antibiotic prophylaxis, oral anti-coagulation, and contraception, and variations in the use of percutaneous and surgical interventions by country income level.
Stress Responsiveness of the Hypothalamic–Pituitary–Adrenal Axis: Age-Related Features of the Vasopressinergic Regulation

The hypothalamic-pituitary-adrenal (HPA) axis plays a key role in adaptation to environmental stresses. Parvicellular neurons of the hypothalamic paraventricular nucleus secrete corticotrophin releasing hormone (CRH) and arginine vasopressin (AVP) into pituitary portal system; CRH and AVP stimulate adrenocorticotropic hormone (ACTH) release through specific G-protein-coupled membrane receptors on pituitary corticotrophs, CRHR1 for CRH and V1b for AVP; the adrenal gland cortex secretes glucocorticoids in response to ACTH. The glucocorticoids activate specific receptors in brain and peripheral tissues thereby triggering the necessary metabolic, immune, neuromodulatory, and behavioral changes to resist stress. While importance of CRH, as a key hypothalamic factor of HPA axis regulation in basal and stress conditions in most species, is generally recognized, role of AVP remains to be clarified. This review focuses on the role of AVP in the regulation of stress responsiveness of the HPA axis with emphasis on the effects of aging on vasopressinergic regulation of HPA axis stress responsiveness. Under most of the known stressors, AVP is necessary for acute ACTH secretion but in a context-specific manner. The current data on the AVP role in regulation of HPA responsiveness to chronic stress in adulthood are rather contradictory. The importance of the vasopressinergic regulation of the HPA stress responsiveness is greatest during fetal development, in neonatal period, and in the lactating adult. Aging associated with increased variability in several parameters of HPA function including basal state, responsiveness to stressors, and special testing. Reports on the possible role of the AVP/V1b receptor system in the increase of HPA axis hyperactivity with aging are contradictory and requires further research. Many contradictory results may be due to age and species differences in the HPA function of rodents and primates.
Multiple sclerosis and extract of cannabis: results of the MUSEC trial.

OBJECTIVE
Multiple sclerosis (MS) is associated with chronic symptoms, including muscle stiffness, spasms, pain and insomnia. Here we report the results of the Multiple Sclerosis and Extract of Cannabis (MUSEC) study that aimed to substantiate the patient based findings of previous studies.


PATIENTS AND METHODS
Patients with stable MS at 22 UK centres were randomised to oral cannabis extract (CE) (N=144) or placebo (N=135), stratified by centre, walking ability and use of antispastic medication. This double blind, placebo controlled, phase III study had a screening period, a 2 week dose titration phase from 5 mg to a maximum of 25 mg of tetrahydrocannabinol daily and a 10 week maintenance phase. The primary outcome measure was a category rating scale (CRS) measuring patient reported change in muscle stiffness from baseline. Further CRSs assessed body pain, spasms and sleep quality. Three validated MS specific patient reported outcome measures assessed aspects of spasticity, physical and psychological impact, and walking ability.


RESULTS
The rate of relief from muscle stiffness after 12 weeks was almost twice as high with CE than with placebo (29.4% vs. 15.7%; OR 2.26; 95% CI 1.24 to 4.13; p=0.004, one sided). Similar results were found after 4 weeks and 8 weeks, and also for all further CRSs. Results from the MS scales supported these findings.


CONCLUSION
The study met its primary objective to demonstrate the superiority of CE over placebo in the treatment of muscle stiffness in MS. This was supported by results for secondary efficacy variables. Adverse events in participants treated with CE were consistent with the known side effects of cannabinoids. No new safety concerns were observed.


TRIAL REGISTRATION NUMBER
NCT00552604.
A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.
Energy Conserving Routing in Wireless Ad-hoc Networks

An ad-hoc network of wireless static nodes is considered as it arises in a rapidly deployed, sensor based, monitoring system. Information is generated in certain nodes and needs to reach a set of designated gateway nodes. Each node may adjust its power within a certain range that determines the set of possible one hop away neighbors. Traffic forwarding through multiple hops is employed when the intended destination is not within immediate reach. The nodes have limited initial amounts of energy that is consumed in different rates depending on the power level and the intended receiver. We propose algorithms to select the routes and the corresponding power levels such that the time until the batteries of the nodes drain-out is maximized. The algorithms are local and amenable to distributed implementation. When there is a single power level, the problem is reduced to a maximum flow problem with node capacities and the algorithms converge to the optimal solution. When there are multiple power levels then the achievable lifetime is close to the optimal (that is computed by linear programming) most of the time. It turns out that in order to maximize the lifetime, the traffic should be routed such that the energy consumption is balanced among the nodes in proportion to their energy reserves, instead of routing to minimize the absolute consumed power. Keywords— energy-sensitive routing, wireless ad-hoc networks, sensor networks
Investor Psychology and Asset Pricing

The basic paradigm of asset pricing is in vibrant f lux. The purely rational approach is being subsumed by a broader approach based upon the psychology of investors. In this approach, security expected returns are determined by both risk and misvaluation. This survey sketches a framework for understanding decision biases, evaluates the a priori arguments and the capital market evidence bearing on the importance of investor psychology for security prices, and reviews recent models. The best plan is . . . to profit by the folly of others. — Pliny the Elder, from John Bartlett, comp. Familiar Quotations, 9th ed. 1901. IN THE MUDDLED DAYS BEFORE THE RISE of modern finance, some otherwisereputable economists, such as Adam Smith, Irving Fisher, John Maynard Keynes, and Harry Markowitz, thought that individual psychology affects prices.1 What if the creators of asset-pricing theory had followed this thread? Picture a school of sociologists at the University of Chicago proposing the Deficient Markets Hypothesis: that prices inaccurately ref lect all available information. A brilliant Stanford psychologist, call him Bill Blunte, invents the Deranged Anticipation and Perception Model ~or DAPM!, in which proxies for market misvaluation are used to predict security returns. Imagine the euphoria when researchers discovered that these mispricing proxies ~such * Hirshleifer is from the Fisher College of Business, The Ohio State University. This survey was written for presentation at the American Finance Association Annual Meetings in New Orleans, January, 2001. I especially thank the editor, George Constantinides, for valuable comments and suggestions. I also thank Franklin Allen, the discussant, Nicholas Barberis, Robert Bloomfield, Michael Brennan, Markus Brunnermeier, Joshua Coval, Kent Daniel, Ming Dong, Jack Hirshleifer, Harrison Hong, Soeren Hvidkjaer, Ravi Jagannathan, Narasimhan Jegadeesh, Andrew Karolyi, Charles Lee, Seongyeon Lim, Deborah Lucas, Rajnish Mehra, Norbert Schwarz, Jayanta Sen, Tyler Shumway, René Stulz, Avanidhar Subrahmanyam, Siew Hong Teoh, Sheridan Titman, Yue Wang, Ivo Welch, and participants of the Dice Finance Seminar at Ohio State University for very helpful discussions and comments. 1 Smith analyzed how the “overweening conceit” of mankind caused labor to be underpriced in more enterprising pursuits. Young workers do not arbitrage away pay differentials because they are prone to overestimate their ability to succeed. Fisher wrote a book on money illusion; in The Theory of Interest ~~1930!, pp. 493–494! he argued that nominal interest rates systematically fail to adjust sufficiently for inf lation, and explained savings behavior in relation to self-control, foresight, and habits. Keynes ~1936! famously commented on animal spirits in stock markets. Markowitz ~1952! proposed that people focus on gains and losses relative to reference points, and that this helps explain the pricing of insurance and lotteries. THE JOURNAL OF FINANCE • VOL. LVI, NO. 4 • AUGUST 2001
Breaking Barriers to Effective Type 2 Diabetes Management: Findings from the use of the OPTIMA© Questionnaire in Clinical Practice

BACKGROUND
The OPTIMA© (MSD, Courbevoie, France) questionnaire was developed to promote shared decisions and the set-up of specific micro-objectives in clinical practice by optimizing communication between type 2 diabetes (T2DM) patients and their physicians. The present study aimed to assess OPTIMA in clinical practice.


METHODS
A cross-sectional multicenter observational study was conducted in France from 2012 to 2014. During routine consultation, patients completed one of the five modules of the OPTIMA questionnaire (Physical activity, Diet, Treatment, Knowledge of the disease or Self-monitoring of blood glucose). The rate of SMART (specific, measurable, acceptable, realistic, timely) micro-objective set-up following the use of the questionnaire was assessed. Data on how patients felt about their diabetes management (beliefs concerning actions, how easy they were to do and how often they were done in practice) were gathered. Finally, patients' and physicians' opinions on OPTIMA were assessed using the PRAgmatic Content and face validity Test (PRAC-Test© (Mapi, Lyon, France) evaluation questionnaire.


RESULTS
Overall, 807 patients were included by 186 physicians. While 92.7 % of consultations led to the set-up of a micro-objective, only 22.3 % were SMART micro-objectives: Physical activity module (34.3 %), Diet module (9.6 %), Treatment module (16.4 %), Knowledge of the disease module (25.2 %), and self-monitoring of blood glucose module (29.5 %). Among patients completing the Physical activity module, 79.0 % reported that they believed physical activity was useful, 35.0 % that it was easy, and 25.8 % that they regularly practised it. PRAC-Test results showed that OPTIMA was a useful and easy-to-use questionnaire that promotes communication between physicians and their patients according to 92.8 % of patients and 69.4 % of physicians.


CONCLUSION
The OPTIMA questionnaire facilitates communication between patients and their physicians and promotes the set-up of micro-objectives concerning T2DM management. The Physical activity module was the most likely of the five modules in the questionnaire to lead to the set-up of SMART micro-objectives.


FUNDING
MSD France.
Assembling a New and Improved Transposition Distance Database

Determining the transposition distance of permutations is NP-hard, but the problem of the transposition diameter is still open and it is known only for n ≤ 15. Previously, every diametral permutation for n ≤ 13 was found, but only a few instances have been described for n = 14 and 15. In this work, we calculate the transposition distance of every permutation for n ≤ 14 via a breadth-first search on the Cayley graph of permutations of n elements, using toric equivalences to reduce the search space. As a consequence, we have determined and identified all diametral permutations for n = 14. We also provide a look-up table having the distance of every permutation of up to 14 elements.
Multidimensional data classification with chordal distance based kernel and Support Vector Machines

In contemporary machine learning multidimensional rather than pure vector like data are frequently encountered. Traditionally, such multidimensional objects, such as color images or video sequences, are first transformed to a vector representation, and then processed by the classical learning algorithms operating with vectors. However, such multi-to-one dimension transformations usually lead to loss of important information. Thus, proposing novel methods for representing and learning with complex and multidimensional data is in focus of current machine learning research. In this paper, we propose a new method for efficient classification of multidimensional data based on a tensor-based kernel applied to the Support Vector Machines. We represent data as tensors, in order to preserve data dimensionality and to allow for processing of complex structures. To allow for an effective classification, we augment a Support Vector Machine (SVM) trained with Sequential Minimal Optimization (SMO) procedure with a chordal distance-based kernel for efficient classification of tensor-like objects. We also discuss different optimization methods for SVM, as well as present implementation details with computational time analysis. The proposed method is evaluated in both binary and multi-class classification problems. Comprehensive experimental analysis carried on a number of multidimensional benchmarks shows high usefulness of the proposed approach. & 2015 Elsevier Ltd. All rights reserved.
Optimal selection of wavelet basis function applied to ECG signal denoising

Over the years ElectroCardioGram (ECG) signal has been used to assess the cardiovascular condition of humans. In practice, real time acquisition and transmission of the ECG may contain noise signals superimposed on it. In general, the signal processing algorithms employed for denoising provide optimal performance and eliminate the high frequency noise between any two beats contained in a continuous ECG signal. Despite their optimal performance, the signal processing algorithms significantly attenuate the peaks of characteristics wave of the ECG signal. This paper presents a selection procedure of mother wavelet basis functions applied for denoising of the ECG signal in wavelet domain while retaining the signal peaks close to their full amplitude. The obtained wavelet based denoised ECG signals retain the necessary diagnostics information contained in the original ECG signal. © 2006 Elsevier Inc. All rights reserved.
ITS Data Fusion

A road interpretation module is presented! which is part of a real-time vehicle guidance system for autonomous driving. Based on bifocal computer vision, the complete system is able to drive a vehicle on marked or unmarked roads, to detect obstacles, and to react appropriately. The hardware is a network of 23 transputers, organized in modular clusters. Parallel modules performing image analysis, feature extraction, object modelling, sensor data integration and vehicle control, are organized in hierarchical levels. The road interpretation module is based on the principle of recursive state estimation by Kalman filter techniques. Internal 4-D models of the road, vehicle position, and orientation are updated using data produced by the image-processing module. The system has been implemented on two vehicles (VITA and VaMoRs) and demonstrated in the framework of PROMETHEUS, where the ability of autonomous driving through narrow curves and of lane changing were demonstrated. Meanwhile, the system has been tested on public roads in real traffic situations, including travel on a German Autobahn autonomously at speeds up to 85 km/h. Belcastro, C.M., Fischl, R., and M. Kam. “Fusion Techniques Using Distributed Kalman Filtering for Detecting Changes in Systems.” Proceedings of the 1991 American Control Conference. 26-28 June 1991: Boston, MA. American Autom. Control Council, 1991. Vol. 3: (2296-2298).
A multinational, observational study to investigate the efficacy, safety and tolerability of acarbose as add-on or monotherapy in a range of patients: the Gluco VIP study.

BACKGROUND AND OBJECTIVES
The burden of type 2 diabetes mellitus is growing rapidly, particularly in the Asia-Pacific region. The aim of this international, large-scale, observational study was to investigate the efficacy and tolerability of the antidiabetic agent acarbose as add-on or monotherapy in a range of patients with type 2 diabetes, including those with cardiovascular morbidities. The majority of practices were included from high-burden regions (predominantly those in the Asia-Pacific region).


METHODS
This was an observational study conducted in 15 countries/regions. Adults with pre-treated or untreated type 2 diabetes prescribed acarbose as add-on or monotherapy were eligible. Two-hour postprandial blood glucose (2-h PPG), glycosylated haemoglobin (HbA1c) and fasting blood glucose (FBG) were measured over a 3-month observation period.


RESULTS
A total of 15,034 patients were valid for the efficacy analysis and 15,661 for the safety analysis (mean age was 57.6 years and 92.6 % of patients were Asian). Mean (SD) 2-h PPG decreased by -71.9 (62.3) mg/dL, to 170.2 (46.5) mg/dL at final visit (after 12.8 [4.1] weeks). Mean HbA1c decreased by -1.1 % (1.3) to 7.2 % (1.1) and mean FBG decreased by -33.0 (43.3) mg/dL to 124.8 (30.5) mg/dL. Acarbose was effective regardless of the presence of cardiovascular co-morbidities or diabetic complications. The efficacy of acarbose was rated 'very good' or 'good' in 85.5 % of patients, and tolerability as 'very good' or 'good' in 84.9 % of patients. Drug-related adverse events, mainly gastrointestinal, were reported in 490/15,661 patients (3.13 %).


CONCLUSION
The results of this observational study support the notion that acarbose is effective, safe and well tolerated in a large cohort of Asian patients with type 2 diabetes.