The Sudbury Neutrino Observatory

The Sudbury Neutrino Observatory is a second generation water Cherenkov detector designed to determine whether the currently observed solar neutrino deficit is a result of neutrino oscillations. The detector is unique in its use of D2O as a detection medium, permitting it to make a solar model-independent test of the neutrino oscillation hypothesis by comparison of the charged- and neutral-current interaction rates. In this paper the physical properties, construction, and preliminary operation of the Sudbury Neutrino Observatory are described. Data and predicted operating parameters are provided whenever possible.Comment: 58 pages, 12 figures, submitted to Nucl. Inst. Meth. Uses elsart and epsf style files. For additional information about SNO see http://www.sno.phy.queensu.ca . This version has some new reference

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

Improved automated essay scoring using Gaussian Multi-Class SMOTE for dataset sampling

Automated Essay Scoring (AES) research efforts primarily focus on feature engineering and the building of machine learning models to attain higher consensus with human graders. In academic grading such as essay scoring, the scores will naturally result in a normal distribution, more commonly referred to as the bell curve. However, the datasets used do not always have such distribution and are often overlooked in most machine learning environments. This paper proposes a Gaussian Multi-Class Synthetic Minority Over-sampling Technique (GMC-SMOTE) for imbalanced datasets. The proposed GMC-SMOTE generates new synthetic data to complement the existing datasets to produce scores that are in a normal distribution. Using several labeled essay sets, some of which already have a substantial agreement between the machine learning model and human graders, learning from normal distribution datasets yields significant improvements. Improvements of 0.038 QWK score (5.8\\%) over the imbalanced dataset were observed. The experimental result has also shown that naturally occurring distribution in the automated essay scoring domain contributes to the most appropriate training dataset for machine learning purposes

Integrative genomics identifies RAB23 as an invasion mediator gene in diffuse-type gastric cancer

10.1158/0008-5472.CAN-07-5870Cancer Research68124623-4630CNRE

Linseed essential oil - source of lipids as active ingredients for pharmaceuticals and nutraceuticals

Linseed - also known as flaxseed - is known for its beneficial effects on animal health attributed to its composition. Linseed comprises linoleic and ?-linolenic fatty acids, various dietary fibers and lignans, which are beneficial to health because they reduce the risk of cardiovascular diseases, as well as cancer, decreasing the levels of cholesterol and relaxing the smooth muscle cells in arteries increasing the blood flow. Essential fatty acids from flax participate in several metabolic processes of the cell, not only as structuring components of the cell membrane but also as storage lipids. Flax, being considered a functional food, can be consumed in a variety of ways, including seeds, oil or flour, contributing to basic nutrition. Several formulations containing flax are available on the market in the form of e.g. capsules and microencapsulated powders having potential as nutraceuticals. This paper revises the different lipid classes found in flaxseeds and their genomics. It also discusses the beneficial effects of flax and flaxseed oil and their biological advantages as ingredients in pharmaceuticals and in nutraceuticals products.The authors wish to acknowledge the financial support from the Portuguese Science and Technology Foundation, Ministry of Science and Education (FCT/MEC) through national funds, and co-financed by FEDER, under the Partnership Agreement PT2020 for the project M-ERA-NET/0004/2015-PAIRED.info:eu-repo/semantics/publishedVersio