Monitoring and diagnosis of complex production process based on free energy of Gaussian–Bernoulli restricted Boltzmann machine

Online monitoring and diagnosis of production processes face great challenges due to the nonlinearity and multivariate of complex industrial processes.Traditional process monitoring methods employ kernel function or multilayer neural networks to solve the nonlinear mapping problem of data.However,the above methods increase the model complexity and are not interpretable,leading to difficulties in subsequent fault recognition/diagnosis/location.A process monitoring and diagnosis method based on the free energy of Gaussian-Bernoulli restricted Boltzmann machine(GBRBM-FE)was proposed.Firstly,a GBRBM network was established to make the probability distribution of the reconstructed data as close as possible to the probability distribution of the raw data.On this basis,the weights and biases in GBRBM network were used to construct F statistics,which represents the free energy of the sample.The smaller the energy of the sample is,the more normal the sample is.Therefore,F statistics can be used to monitor the production process.To diagnose fault variables,the F statistic for each sample was decomposed to obtain the Fv statistic for each variable.By analyzing the deviation degree between the corresponding variables of abnormal samples and normal samples,the cause of process abnormalities can be accurately located.The application of converter steelmaking process demonstrates that the proposed method outperforms the traditional methods,in terms of fault monitoring and diagnosis performance.

Efficacy and safety of chimeric antigen receptor-T cells in the treatment of B cell lymphoma:a systematic review and meta-analysis

Background:Conventional treatment has limited efficacy in relapsed/refractory B-cell lymphoma.Since chimeric antigen receptor T-cell(CAR-T)technology has shown high safety and results in high remission rates,we investigated its efficacy and safety in B-cell lymphoma treatment and analyzed potential affecting factors to provide evidence for therapeutic strategies and applications.Methods:We searched databases including PubMed,Embase,and Cochrane up to July 2019.Meta-analysis 1 was conducted to study the efficacy of CAR-T cell for treating B-cell lymphoma,measuring the response rate and complete remission rate as outcomes.Sub-group analysis was performed for age,pathological type,target antigen,co-stimulatory molecule,and conditioning chemotherapy.Meta-analysis 2 was undertaken on the safety of the treatment with the incidence rate of toxicity(cytokine-releasing syndrome[CRS],neurotoxicity)as an outcome.Results:Seventeen studies were included in the systematic review and meta-analysis.It was found that CAR-T cells had good therapeutic effects in the following cases:B-cell lymphoma(patients≥65 years old);diffuse large B-cell lymphoma pathological type;patients with treatment target antigen other than CD19;patients treated with co-stimulatory molecules other than CD28,including 4-1BB+CD28 or 4-1BB;and patients treated with cyclophosphamide/fludarabine pre-treatment protocol conditioning chemotherapy.Although the CRS and neurotoxicity incidences were high,most were reversible with minimal risk of death.Conclusion:CAR-T cell treatment is safe for clinical application;however,toxicity effects should be monitored.