Mining Weighted Frequent Closed Episodes over Multiple Sequences

Frequent episode discovery is introduced to mine useful and interesting temporal patterns from sequential data. The existing episode mining methods mainly focused on mining from a single long sequence consisting of events with time constraints. However, there can be multiple sequences of different importance as the persons or entities associated with each sequence can be of different importance. Aiming to mine episodes in multiple sequences of different importance, we first define a new kind of episodes, i.e., the weighted frequent closed episodes, to take sequence importance, episode distribution and occurrence frequency into account together. Secondly, to facilitate the mining of such new episodes, we present a new concept called maximal duration serial episodes to cut a whole sequence into multiple maximum episodes using duration constraints, and discuss its properties for episode shrinking processing. Finally, based on the theoretical properties, we propose a two-phase approach to efficiently mine these new episodes. In Phase I, we adopt a level-wise episode shrinking framework to discover the candidate frequent closed episodes with the same prefixes, and in Phase II, we match the candidates with different prefixes to find the frequent close episodes. Experiments on simulated and real datasets demonstrate that the proposed episode mining strategy has good mining effectiveness and efficiency

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

Affective computing model for natural interaction based on large-scale self-built dataset

Article Highlights 1. In this paper, we describe a way to make a new face expression dataset by putting together open source and self-collected datasets. 2. This allows us to create the largest face expression dataset in the industry, which is better in quality and has more data. 3. When we use this new dataset to train a face expression recognition model, it performs the best in the current industry

Transcriptomic analysis of seed germination improvement of Andrographis paniculata responding to air plasma treatment.

The plasma seed treatment is effective for promoting seed germination in many crops. However, the biological mechanism remains unclear. Therefore, mRNA sequencing was used to screen differentially expressed genes in the germination process of Andrographis paniculata seeds treated with air plasma (power density = 8.99 J/cm3). Following plasma treatment, the germination percentages were significantly higher than those of the control, they were 3.5±0.6% vs. 0 at 28 hours after sowing (HAS) and 50.3±2.6% vs. 37.3±1.7% at 48 HAS. After unigenes were assembled and annotated, 125 differentially expressed genes (DEGs) were detected at 28 HAS, compared with nine DEGs at 48 HAS, but no DEGs were detected at 0 HAS, indicating that air plasma treatment mainly changed the gene expression of A. paniculata seeds at 28 HAS. The NCED5 expression level of the treated group was less than one-fifth of the control, and the expressions of three ethylene response factors were significantly higher than the control at 28 HAS, indicating that lower abscisic acid levels play an important role and ethylene signal transduction also participates in radicle protrusion. ACO, NRT1 and PRP3 expressions were significantly higher than in the control at 48 HAS, suggesting that higher ethylene levels cause the endosperm cap to weaken and start to grow root hairs and lateral roots earlier. These findings reveal that plasma promotes seed germination mainly by regulating the expression of hormone-related genes. And the possible signal transduction of related hormones was discussed

Algebraic synthesis of time-optimal unitaries in SU(2) with alternating controls

We present an algebraic framework to study the time-optimal synthesis of arbitrary unitaries in SU(2), when the control set is restricted to rotations around two non-parallel axes in the Bloch sphere. Our method bypasses commonly used control-theoretical techniques and easily imposes necessary conditions on time-optimal sequences. In a straightforward fashion, we prove that time-optimal sequences are solely parametrized by three rotation angles and derive general bounds on those angles as a function of the relative rotation speed of each control and the angle between the axes. Results are substantially different whether both clockwise and counterclockwise rotations about the given axes are allowed, or only clockwise rotations. In the first case, we prove that any finite time-optimal sequence is composed at most of five control concatenations, while for the more restrictive case, we present scaling laws on the maximum length of any finite time-optimal sequence. The bounds we find for both cases are stricter than previously published ones and severely constrain the structure of time-optimal sequences, allowing for an efficient numerical search of the time-optimal solution. Our results can be used to find the time-optimal evolution of qubit systems under the action of the considered control set and thus potentially increase the number of realizable unitaries before decoherence

Trigeminal nerve stimulation for prolonged disorders of consciousness: A randomized double-blind sham-controlled study

Background: Trigeminal nerve stimulation (TNS) has been proposed as a promising intervention for coma awakening. However, the effect of TNS on patients with prolonged disorders of consciousness (pDoC) is still unclear. Objective: This study aimed to investigate the therapeutic effects of TNS in pDoC caused by stroke, trauma, and anoxia. Methods: A total of 60 patients (male =25, female =35) aged over 18 who were in a vegetative state or minimally conscious state were randomly assigned to the TNS (N = 30) or sham TNS (N = 30) groups. 4 weeks of intervention and a followed up for 8 weeks were performed. The Glasgow Coma Scale (GCS) and Coma Recovery Scale-Revised (CRS-R) scores as primary outcomes were assessed at baseline and at 2, 4, 8, and 12 weeks. Results: The score changes in the TNS group over time for CRS-R (2-week: mean difference = 0.9, 95% CI = [0.3, 1.5], P = 0.006; 4-week: 1.6, 95% CI = [0.8, 2.5], P < 0.001; 8-week: mean difference = 2.4, 95% CI = [1.3, 3.5], P < 0.001; 12-week: mean difference = 2.3, 95% CI = [1.1, 3.4], P < 0.001) and GCS (4-week: mean difference = 0.7, 95% CI = [0.3, 1.2], P = 0.002; 8-week: mean difference = 1.1, 95% CI = [0.6, 1.7], P < 0.001; 12-week: 1.1, 95% CI = [0.5, 1.7], P = 0.003) were higher than those in the sham group. 18-Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) revealed that the metabolism of the right parahippocampal cortex, right precuneus, and bilateral middle cingulate cortex was significantly increased in TNS group. Conclusion: The results of this study indicate that TNS could increase local brain metabolism and may promote functional recovery in patients with prolonged disorders of consciousness. Registration information: Name of the registry: Chinese Clinical Trial Registry. Registration number: ChiCTR1900025573. The date that the study was submitted to a registry: 2019-09-01. The date when the first patient was enrolled was 2021-01-20

NMR data for novel flavonoids from Lonicera japonica flower buds

The data presented in this article are associated with the research article entitled “Novel flavonoids from Lonicera japonica flower buds and validation of their anti-hepatoma and hepatoprotective activity in vitro studies” (Ge et al., 2018) [1]. The aim of this data was to provide the NMR spectrum of novel flavonoids from Lonicera japonica flower buds. Samples were isolated from EtOAc fraction of Lonicera japonica flower buds extracts, then dissolved in DMSO-d6 before NMR testing