An empirical comparison of several recent epistatic interactions detection methods

ABSTRACT Motivation: Many new methods have recently been proposed for detecting epistatic interactions in GWAS data. There is however no in-depth independent comparison of these methods yet. Results: Five recent methods-TEAM, BOOST, SNPHarvester, SNPRuler, and Screen and Clean (SC)-are evaluated here in terms of power, type-1 error rate, scalability, and completeness. In terms of power, TEAM performs best on data with main effect and BOOST performs best on data without main effect. In terms of type-1 error rate, TEAM and BOOST have higher type-1 error rates than SNPRuler and SNPHarvester. SC does not control type-1 error rate well. In terms of scalability, we tested the five methods using a dataset with 100,000 SNPs on a 64-bit Ubuntu system, with Intel (R) Xeon(R) CPU 2.66GHz, 16G memory. TEAM takes ∼36 days to finish and SNPRuler reports heap allocation problems. BOOST scales up to 100,000 SNPs and the cost is much lower than that of TEAM. SC and SNPHarvester are the most scalable. In terms of completeness, we study how frequently the pruning techniques employed by these methods incorrectly prune away the most significant epistatic interactions. We find that, on average, 20% of datasets without main effect and 60% of datasets with main effect are pruned incorrectly by BOOST, SNPRuler, and SNPHarvester

Study on particle plugging in propagating fractures based on CFD-DEM

In the drilling and completion process of fractured formations, wellbore stability is a key factor affecting the safety of drilling and completing engineering. Previous studies have demonstrated that propping moderately and plugging fractures with soluble particles can improve formation fracture pressure. When it comes to particle transport in 3D rough propagation fractures, the interactions between particle-fracture-fluid need to be considered. Meanwhile, size-exclusion, particle bridging/strain effects all influence particle transport behavior and ultimately particle plugging effectiveness. However, adequate literature review shows that fracture plugging, and fracture propagation have not been considered together. In this study, a coupled CFD-DEM method was put forward to simulate the particle plugging process of propagating fracture, and the effects of positive pressure difference, fracture roughness, particle concentration, and particle shape on the plugging mechanism were examined. It is concluded through the study that: 1) Positive pressure difference too large will lead to excessive fracture aperture, making the particles unable to form effective plugging in the middle of the fracture; positive pressure difference too small will lead to fracture aperture too small, making particles unable to enter into and plug the fracture. 2) No matter how the concentration, particle size and friction coefficient change, they mainly affect the thickness of the plugging layer, while the front end of the particle is still dominated by single-particle bridging, and double-particles bridging and multiple-particles bridging are hardly ever seen. For the wellbore strengthening approaches, such as stress cages, fracture tip sealing, etc., specific analysis should be carried out according to the occurrence of extended fractures. For example, for fractures with low roughness, the particles rarely form effective tight plugging in the middle of the fracture, so it is more suitable for fracture tip sealing; For the fracture with high roughness, if the positive pressure difference is controlled properly to ensure reasonable fracture extension, the particle plugging effect will be good, and the stress cage method is recommended for borehole strengthening

Towards exploratory hypothesis testing and analysis

10.1109/ICDE.2011.5767907Proceedings - International Conference on Data Engineering745-75

Identification of 27 abnormalities from multi-lead ECG signals: An ensembled Se-ResNet framework with Sign Loss function

Cardiovascular disease is a major threat to health and one of the primary causes of death globally. The 12-lead ECG is a cheap and commonly accessible tool to identify cardiac abnormalities. Early and accurate diagnosis will allow early treatment and intervention to prevent severe complications of cardiovascular disease. In the PhysioNet/Computing in Cardiology Challenge 2020, our objective is to develop an algorithm that automatically identifies 27 ECG abnormalities from 12-lead ECG recordings

Blood Pressure Changes in Relation to Arsenic Exposure in a U.S. Pregnancy Cohort

Background: Inorganic arsenic exposure has been related to the risk of increased blood pressure based largely on cross-sectional studies conducted in highly exposed populations. Pregnancy is a period of particular vulnerability to environmental insults. However, little is known about the cardiovascular impacts of arsenic exposure during pregnancy. Objectives: We evaluated the association between prenatal arsenic exposure and maternal blood pressure over the course of pregnancy in a U.S. population. Methods: The New Hampshire Birth Cohort Study is an ongoing prospective cohort study in which \u3e 10% of participant household wells exceed the arsenic maximum contaminant level of 10 μg/L established by the U.S. EPA. Total urinary arsenic measured at 24–28 weeks gestation was measured and used as a biomarker of exposure during pregnancy in 514 pregnant women, 18–45 years of age, who used a private well in their household. Outcomes were repeated blood pressure measurements (systolic, diastolic, and pulse pressure) recorded during pregnancy. Results: Using linear mixed effects models, we estimated that, on average, each 5-μg/L increase in urinary arsenic was associated with a 0.15-mmHg (95% CI: 0.02, 0.29; p = 0.022) increase in systolic blood pressure per month and a 0.14-mmHg (95% CI: 0.02, 0.25; p = 0.021) increase in pulse pressure per month over the course of pregnancy. Conclusions: In our U.S. cohort of pregnant women, arsenic exposure was associated with greater increases in blood pressure over the course of pregnancy. These findings may have important implications because even modest increases in blood pressure impact cardiovascular disease risk

Efficient Multiplicative-to-Additive Function from Joye-Libert Cryptosystem and Its Application to Threshold ECDSA

Threshold ECDSA receives interest lately due to its widespread adoption in blockchain applications. A common building block of all leading constructions involves a secure conversion of multiplicative shares into additive ones, which is called the multiplicative-to-additive (MtA) function. MtA dominates the overall complexity of all existing threshold ECDSA constructions. Specifically, $O(n^2)$ invocations of MtA are required in the case of $n$ active signers. Hence, improvement of MtA leads directly to significant improvements for all state-of-the-art threshold ECDSA schemes. In this paper, we design a novel MtA by revisiting the Joye-Libert (JL) cryptosystem. Specifically, we revisit JL encryption and propose a JL-based commitment, then give efficient zero-knowledge proofs for JL cryptosystem which are the first to have standard soundness. Our new MtA offers the best time-space complexity trade-off among all existing MtA constructions. It outperforms state-of-the-art constructions from Paillier by a factor of $1.85$ to $2$ in bandwidth and $1.2$ to $1.7$ in computation. It is $7\times$ faster than those based on Castagnos-Laguillaumie encryption only at the cost of $2\times$ more bandwidth. While our MtA is slower than OT-based constructions, it saves $18.7\times$ in bandwidth requirement. In addition, we also design a batch version of MtA to further reduce the amotised time and space cost by another $25$%