246 research outputs found
Ball: An R package for detecting distribution difference and association in metric spaces
The rapid development of modern technology facilitates the appearance of
numerous unprecedented complex data which do not satisfy the axioms of
Euclidean geometry, while most of the statistical hypothesis tests are
available in Euclidean or Hilbert spaces. To properly analyze the data of more
complicated structures, efforts have been made to solve the fundamental test
problems in more general spaces. In this paper, a publicly available R package
Ball is provided to implement Ball statistical test procedures for K-sample
distribution comparison and test of mutual independence in metric spaces, which
extend the test procedures for two sample distribution comparison and test of
independence. The tailormade algorithms as well as engineering techniques are
employed on the Ball package to speed up computation to the best of our
ability. Two real data analyses and several numerical studies have been
performed and the results certify the powerfulness of Ball package in analyzing
complex data, e.g., spherical data and symmetric positive matrix data
Learning Robust and Correct Controllers from Signal Temporal Logic Specifications Using BarrierNet
In this paper, we consider the problem of learning a neural network
controller for a system required to satisfy a Signal Temporal Logic (STL)
specification. We exploit STL quantitative semantics to define a notion of
robust satisfaction. Guaranteeing the correctness of a neural network
controller, i.e., ensuring the satisfaction of the specification by the
controlled system, is a difficult problem that received a lot of attention
recently. We provide a general procedure to construct a set of trainable High
Order Control Barrier Functions (HOCBFs) enforcing the satisfaction of formulas
in a fragment of STL. We use the BarrierNet, implemented by a differentiable
Quadratic Program (dQP) with HOCBF constraints, as the last layer of the neural
network controller, to guarantee the satisfaction of the STL formulas. We train
the HOCBFs together with other neural network parameters to further improve the
robustness of the controller. Simulation results demonstrate that our approach
ensures satisfaction and outperforms existing algorithms.Comment: Submitted to CDC 202
Ball: An R Package for Detecting Distribution Difference and Association in Metric Spaces
The rapid development of modern technology has created many complex datasets in non-linear spaces, while most of the statistical hypothesis tests are only available in Euclidean or Hilbert spaces. To properly analyze the data with more complicated structures, efforts have been made to solve the fundamental test problems in more general spaces (Lyons 2013; Pan, Tian, Wang, and Zhang 2018; Pan, Wang, Zhang, Zhu, and Zhu 2020). In this paper, we introduce a publicly available R package Ball for the comparison of multiple distributions and the test of mutual independence in metric spaces, which extends the test procedures for the equality of two distributions (Pan et al. 2018) and the independence of two random objects (Pan et al. 2020). The Ball package is computationally efficient since several novel algorithms as well as engineering techniques are employed in speeding up the ball test procedures. Two real data analyses and diverse numerical studies have been performed, and the results certify that the Ball package can detect various distribution differences and complicated dependencies in complex datasets, e.g., directional data and symmetric positive definite matrix data
Association between High-Sensitivity C-Reactive Protein and N-Terminal Pro-B-Type Natriuretic Peptide in Patients with Hepatitis C Virus Infection
Background. Prior study showed HCV-infected patients have increased serum N-Terminal Pro-B-Type Natriuretic Peptide (NT-proBNP) and a possible left ventricular diastolic dysfunction. The objectives of the present paper were to investigate the characteristics of hs-CRP and its correlation with clinical profiles including NT-proBNP and echocardiographic variables in HCV-infected patients. Methods and Results. A total of 106 HCV-infected patients and 106 control healthy individuals were enrolled. The level of serum hs-CRP (median 1.023 mg/L, range 0.03∼5.379 mg/L) was significantly lower in all 106 patients than that in controls (median 3.147 mg/L, range 0.08~7.36 mg/L, P = 0.012). Although hs-CRP did not correlate significantly with NT-proBNP when all patients and controls were included (r = 0.169, P = 0.121), simple regression analysis demonstrated a statistically significant linear correlation between hs-CRP and NT-proBNP in HCV-infected patients group (r = 0.392, P = 0.017). Independent correlates of hs-CRP levels (R2 = 0.13) were older age (β′ = 0.031, P = 0.025) and NT proBNP (β′ = 0.024, P = 0.017). Conclusions. Although the level of serum hs-CRP decreased significantly, there was a significant association between hs-CRP and NT-proBNP in HCV-infected patients
Improving Neural Relation Extraction with Positive and Unlabeled Learning
We present a novel approach to improve the performance of distant supervision
relation extraction with Positive and Unlabeled (PU) Learning. This approach
first applies reinforcement learning to decide whether a sentence is positive
to a given relation, and then positive and unlabeled bags are constructed. In
contrast to most previous studies, which mainly use selected positive instances
only, we make full use of unlabeled instances and propose two new
representations for positive and unlabeled bags. These two representations are
then combined in an appropriate way to make bag-level prediction. Experimental
results on a widely used real-world dataset demonstrate that this new approach
indeed achieves significant and consistent improvements as compared to several
competitive baselines.Comment: 8 pages, AAAI-202
Qiliqiangxin Affects L Type Current in the Normal and Hypertrophied Rat Heart
Qiliqiangxin capsule is newly developed Chinese patent drug and proved to be effective and safe for the treatment of patients with chronic heart failure. We compared the effects of different dose Qiliqiangxin on L type Ca2+ current between normal and hypertrophied myocytes. A total of 40 healthy Sprague—Dawley rats were used in the study. The rats were randomly divided into two groups (control group and hypertrophy group). Cardiac hypertrophy was induced by pressure overload produced by partial ligation of the abdominal aorta. The control group was the sham-operated group. After 1 month, cardiac ventricular myocytes were isolated from the hearts of rats. Ventricular myocytes were exposed to 10 and 50 μmol/L Qiliqiangxin, and whole cell patch-clamp technique was used to study the effects of Qiliqiangxin on . The current densities of
were similar in control group
and in hypertrophy group . They were not statistically significant. 10 and 50 μmol/L Qiliqiangxin can decrease peak current and in control group. However, the peak current was only reduced by 50 μmol/L Qiliqiangxin in hypertrophied myocytes. The inhibited action of Qiliqiangxin on
of hypertrophy group was lower than in control group. Qiliqiangxin affected L-type Ca2+ channel and blocked , as well as affected cardiac function finally. Qiliqiangxin has diphasic action that is either class IV antiarrhythmic agent or the agent of effect cardiac function
- …