Convergence of operators semigroups generated by elliptic operators

Röckner M, Zhang TS. Convergence of operators semigroups generated by elliptic operators. Osaka Journal of Mathematics. 1997;34(4):923-932

Errata for Stochastic calculus for symmetric Markov processes

This erratum corrects the article arXiv:0806.2044 published in Ann. Probab. 36 (2008) 931--970Comment: Published in at http://dx.doi.org/10.1214/11-AOP684 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

Simultaneously suppressing the dendritic lithium growth and polysulfides migration by a polyethyleneimine grafted bacterial cellulose membrane in lithium-sulfur batteries

Owing to the ultrahigh theoretical energy density and low-cost, lithium-sulfur (Li-S) batteries hold broad prospects as one of the promising substitutes for commercial lithium-ion batteries. The polysulfides shuttling originated from sulfur cathode and the lithium dendrite growth from lithium anode are the main challenges that hinder the commercial survival of Li-S batteries. Herein, thermal stable bacterial cellulose (BC) separator is successfully fixed with polyethyleneimine (PEI) by a scalable chemical grafting. The hydroxyl groups and amino groups in PEI grafted BC (PEI@BC) separator can participate in the formation of Li2O and Li3N, respectively, contributing to robust solid electrolyte interface with high ionic conductivity. Therefore, the lithium deposition is well regulated, resulting in a spherical and dendrite-free Li deposit pattern. The Li/Li symmetrical cell assembled with PEI@BC separator exhibits excellent cyclic stability, which can continuously plate/stripe for more than 820 h with an overpotential of ∼ 40 mV at 2 mA cm−2. Meanwhile, the polar amino group can restrain the polysulfides migration via chemosorption. As a consequence of these merits, ultrahigh initial capacity (1402 mAh g−1 at 0.1C) and excellent rate performance (440.5 mAh g−1 at 2C) for Li-S full cell are achieved, presenting new insights into the fabrication of multifunctional separators for Li-S batteries

Corrigendum to “Simultaneously suppressing the dendritic lithium growth and polysulfides migration by a polyethyleneimine grafted bacterial cellulose membrane in lithium-sulfur batteries” [Appl. Surf. Sci. 597 (2022) 153683]

The authors regret the error in the first author's name and the correct author list is updated as above. The authors would like to apologise for any inconvenience caused.</p

Many-objective optimization-based intrusion detection for in-vehicle network security

In-vehicle network security plays a vital role in ensuring the secure information transfer between vehicle and Internet. And existing research is still facing great difficulties in balancing the conflicting factors for the in-vehicle network security and hence to improve intrusion detection performance. To challenge this issue, we construct a many-objective intrusion detection model by including information entropy, accuracy, false positive rate and response time of anomaly detection as the four objectives, which represent the key factors influencing intrusion detection performance. We then design an improved intrusion detection algorithm based on many-objective optimization to optimize the detection model parameters. The designed algorithm has double evolutionary selections. Specifically, an improved differential evolutionary operator produces new offspring of the internal population, and a spherical pruning mechanism selects the excellent internal solutions to form the selected pool of the external archive. The second evolutionary selection then produces new offspring of the archive, and an archive selection mechanism of the external archive selects and stores the optimal solutions in the whole detection process. An experiment is performed using a real-world in-vehicle network data set to verify the performance of our proposed model and algorithm. Experimental results obtained demonstrate that our algorithm can respond quickly to attacks and achieve high entropy and detection accuracy as well as very low false positive rate with a good trade-off in the conflicting objective landscape

The Effects of Modified Simiao Decoction in the Treatment of Gouty Arthritis: A Systematic Review and Meta-Analysis

The modified Simiao decoctions (MSD) have been wildly applied in the treatment of gouty arthritis in China. However, the evidence needs to be evaluated by a systematic review and meta-analysis. After filtering, twenty-four randomised, controlled trials (RCTs) comparing the effects of MSD and anti-inflammation medications and/or urate-lowering therapies in patients with gouty arthritis were included. In comparison with anti-inflammation medications, urate-lowering therapies, or coadministration of anti-inflammation medications and urate-lowering therapies, MSD monotherapy significantly lowered serum uric acid (p<0.00001, mean difference = −90.62, and 95% CI [−128.38, −52.86]; p<0.00001, mean difference = −91.43, and 95% CI [−122.38, −60.49]; p=0.02, mean difference = −40.30, and 95% CI [−74.24, −6.36], resp.). Compared with anti-inflammation medications and/or urate-lowering therapies, MSD monotherapy significantly decreased ESR (p<0.00001; mean difference = −8.11; 95% CI [−12.53, −3.69]) and CRP (p=0.03; mean difference = −3.21; 95% CI [−6.07, −0.36]). Additionally, the adverse effects (AEs) of MSD were fewer (p<0.00001; OR = 0.08; 95% CI [0.05, 0.16]). MSD are effective in the treatment of gouty arthritis through anti-inflammation and lowering urate. However, the efficacy of MSD should be estimated with more RCTs

Hybrid edge-cloud collaborator resource scheduling approach based on deep reinforcement learning and multi-objective optimization

Collaborative resource scheduling between edge ter- minals and cloud centers is regarded as a promising means of effectively completing computing tasks and enhancing quality of service. In this paper, to further improve the achievable perfor- mance, the edge cloud resource scheduling (ECRS) problem is transformed into a multi-objective Markov decision process based on task dependency and features extraction. A multi-objective ECRS model is proposed by considering the task completion time, cost, energy consumption and system reliability as the four objectives. Furthermore, a hybrid approach based on deep reinforcement learning (DRL) and multi-objective optimization are employed in our work. Specifically, DRL preprocesses the workflow, and a multi-objective optimization method strives to find the Pareto-optimal workflow scheduling decision. Various experiments are performed on three real data sets with different numbers of tasks. The results obtained demonstrate that the proposed hybrid DRL and multi-objective optimization design outperforms existing design approaches

An investigation of the health value and self-care capabilities of the elderly in urban-rural fringe area nursing homes and the related influencing factors

AbstractObjectiveTo investigate the health value and self-care capabilities of the elderly living in urban-rural fringe area nursing homes and the factors that influence these variables.MethodsA cluster sampling method was used to select 280 elderly individuals from seven urban-rural fringe communities in Xianning to complete a survey regarding their health value and self-care capabilities.ResultsThe total health value and self-care capability scores of the elderly were 7.45 ± 1.45 and 100.25 ± 22.56, respectively. Both of these scores significantly differed by age, education level, marital status, and income (P < 0.05, P < 0.01). Self-care capability was correlated with health value (r = 0.521). A multivariate linear regression analysis showed that health value, marital status, and age predicted self-care capability.ConclusionsElderly people living in the urban-rural fringe area with higher health values also had higher self-care capabilities. The self-care capabilities of the elderly can be enhanced by improving their health value using the “knowing-trusting-acting” model

pirScan: a webserver to predict piRNA targeting sites and to avoid transgene silencing in C. elegans

pirScan is a web-based tool for identifying C. elegans piRNA-targeting sites within a given mRNA or spliced DNA sequence. The purpose of our tool is to allow C. elegans researchers to predict piRNA targeting sites and to avoid the persistent germline silencing of transgenes that has rendered many constructs unusable. pirScan fulfills this purpose by first enumerating the predicted piRNA-targeting sites present in an input sequence. This prediction can be exported in a tabular or graphical format. Subsequently, pirScan suggests silent mutations that can be introduced to the input sequence that would allow the modified transgene to avoid piRNA targeting. The user can customize the piRNA targeting stringency and the silent mutations that he/she wants to introduce into the sequence. The modified sequences can be re-submitted to be certain that any previously present piRNA-targeting sites are now absent and no new piRNA-targeting sites are accidentally generated. This revised sequence can finally be downloaded as a text file and/or visualized in a graphical format. pirScan is freely available for academic use at http://cosbi4.ee.ncku.edu.tw/pirScan/