Parallel-group thorough QT/QTc studies focus on the change of QT/QTc values at several time-matched points from a pre-treatment day (baseline) to a post-treatment day for different groups of treatment. The International Council for Harmonisation (ICH) E14 stresses that QTc prolongation beyond a threshold represents high cardiac risk and calls for a test on the largest time-matched treatment effect (QTc prolongation). QT/QTc analysis usually assumes a jointly multivariate normal (MVN) distribution of pre-treatment and post-treatment QT/QTc values, with a blocked compound symmetry covariance matrix. Existing methods use an analysis of covariance model including day-averaged baseline as a covariate to deal with the MVN model. However, the analysis of covariance model tends to underestimate the variation of the estimator for treatment effects, resulting in the inflation of empirical type I error rate when testing whether the largest QTc prolongation is beyond a threshold. In this paper, we propose two new methods to estimate the time-matched treatment effects under the MVN model, including maximum likelihood estimation and ordinary-least-square-based two-stage estimation. These two methods take advantage of the covariance structure and are asymptotically efficient. Based on these estimators, powerful tests for QT/QTc prolongation are constructed. Simulation shows that the proposed estimators have smaller mean square error, and the tests can control the type I error rate with high power. The proposed methods are applied on testing the carryover effect of diltiazem to inhibit dofetilide in a randomized phase 1 trial.
Oxidation of sulfapyridine (SPY) by typical oxidant, hydrogen peroxide (H2O2) and/or potassium peroxydisulfate (PDS), was used as a pre-treatment for antibiotic wastewater. The degradation dynamics showed that SPY was successfully removed, and the trend was fitted to the first-order reaction kinetics. H2O2 removed SPY more efficiently in acid condition than in basic condition, while PDS was the opposite. Better performance was achieved by using PDS than using H2O2, but combined using of PDS and H2O2 got the best performance. Although SPY was oxidized by those oxidants and biodegradability was improved, the intermediates still exhibited antibacterial activity. The degradation pathways and mechanism of SPY were deduced through density functional theory (DFT) and evidenced by intermediates product detection. Nucleophilic attack and radical attack were determined to be the major attack pathways in H2O2 and PDS systems, respectively. The SPY degradation pathways proposed in the two systems were based on the cleavage of bonds and hydroxyl substitution. Additionally, intermediate ΔG value showed that stubborn molecules remained in the wastewater even after pre-oxidation, which is harmful for further bio-treatment. This study provides a new insight for the improvement of biodegradability and the efficient degradation of SPY in antibiotic wastewater.
Two-dimensional (2D) materials have drawn much attention in recent years ascribing to their unique properties associated with atomic thickness. Besides graphene, which has aroused tremendous research interest, other 2D materials such as [Bi2O2]-based layered compounds, i.e., Bi2O2Se, BiOCl, and Bi2Sr2CaCu2Ox, have also been studied widely and show promising application prospects in electronics, optoelectronics, photocatalysis fields, and so on. In this Perspective, we systematically review the progress on preparation methods of 2D [Bi2O2]-based layered materials, discuss the strengths and drawbacks of different methods, and give an outlook toward future research directions.
Spiking Neural Networks (SNNs) have been attached great importance due to their biological plausibility and high energy-efficiency on neuromorphic chips. As these chips are usually resource-constrained, the compression of SNNs is thus crucial along the road of practical use of SNNs. Most existing methods directly apply pruning approaches in artificial neural networks (ANNs) to SNNs, which ignore the difference between ANNs and SNNs, thus limiting the performance of the pruned SNNs. Besides, these methods are only suitable for shallow SNNs. In this paper, inspired by synaptogenesis and synapse elimination in the neural system, we propose gradient rewiring (Grad R), a joint learning algorithm of connectivity and weight for SNNs, that enables us to seamlessly optimize network structure without retraining. Our key innovation is to redefine the gradient to a new synaptic parameter, allowing better exploration of network structures by taking full advantage of the competition between pruning and regrowth of connections. The experimental results show that the proposed method achieves minimal loss of SNNs' performance on MNIST and CIFAR-10 datasets so far. Moreover, it reaches a ~3.5% accuracy loss under unprecedented 0.73% connectivity, which reveals remarkable structure refining capability in SNNs. Our work suggests that there exists extremely high redundancy in deep SNNs. Our codes are available at https://github.com/Yanqi-Chen/Gradient-Rewiring.
Both naphthalene and perylene derivatives bearing six-membered-ring dicarboximide groups are proven valuable modules for preparing organic electron-transporting semiconductors. However, obtaining their analogue with pyrene appeared challenging, as all previous endeavors resulted in 5- instead of 6-membered dicarboximide rings. Here, we report the first successful synthesis of pyrene-1,5,6,10-tetracarboxyl diimide (PyDI), a centro-symmetric structure comprising two 6-membered dicarboximide groups. Moreover, this molecule undergoes regioselective dihalogenation to afford a 3,8-dibromo-substituted derivative, which may conveniently be incorporated into conjugated polymers via cross-coupling with suitable comonomers. Two representative conjugated polymers, PyDI-T and PyDI-TT, are thus prepared, composed of alternating PyDI and thiophene or bithiophene units. OFETs are then fabricated using these polymers under solution-processing conditions. An optimal electron mobility of 0.335 cm(2) V(−1) s(−1) is achieved by PyDI-TT, which clearly demonstrates the potential of 1,5,6,10-PyDI as a potent building block for developing new high-performance electronic-transporting materials.
Stabilized Criegee intermediates (SCIs) have the potential to oxidize trace species and to produce secondary organic aerosols (SOA), making them important factors in tropospheric chemistry. This study quantitatively investigates the performance of SCIs in SOA formation at different relative humidity (RH), and the first- and second-generation oxidations of endo- and exo-cyclic double bonds ozonated in limonene ozonolysis are studied separately. Through regulating SCIs scavengers, the yields and rate constants of SCIs in reaction system were derived, and the amounts of SCIs were calculated. The amount of SOA decreased by more than 20% under low-humidity conditions (10–50% RH), compared to that under dry conditions due to the reactions of SCIs with water, while the inhibitory effect of water on SOA formation was not observed under high-humidity conditions (60–90% RH). When using excessive SCIs scavengers to exclude SCIs reactions, it was found that the effect of water on SOA formation with the presence of SCIs was different from that without the presence of SCIs, suggesting that SCIs reactions were relevant to the non-monotonic impact of water. The fractions of SCIs contribution to SOA were similar between dry and high-humidity conditions, where the SCIs reactions accounted for ~ 63% and ~ 73% in SOA formation in the first- and second-generation oxidation, however, marked differences in SOA formation mechanisms were observed. SOA formation showed a positive correlation with the amount of SCIs, and the SOA formation potential of SCIs under high-humidity conditions was more significant than that under dry and low-humidity conditions. It was estimated that 20–30% of SCIs could convert into SOA under high-humidity conditions, while this value decreased nearly by half under dry and low-humidity conditions. The typical contribution of limonene-derived SCIs to SOA formation is calculated to be (8.21 ± 0.15) × 10–2 μg m–3 h–1 in forest, (4.26 ± 0.46) × 10–2 μg m–3 h–1 in urban area, and (2.52 ± 0.28) × 10–1 μg m–3 h–1 in indoor area. Water is an uncertainty on the role of SCIs playing in SOA formation, and the contribution of SCIs to SOA formation needs consideration even under high RH in the atmosphere.