The quantum entropic uncertainty relation and entanglement witness in the two-atom system coupling with the non-Markovian environments are studied by the time-convolutionless master-equation approach. The influence of non-Markovian effect and detuning on the lower bound of the quantum entropic uncertainty relation and entanglement witness is discussed in detail. The results show that, only if the two non-Markovian reservoirs are identical, increasing detuning and non-Markovian effect can reduce the lower bound of the entropic uncertainty relation, lengthen the time region during which the entanglement can be witnessed, and effectively protect the entanglement region witnessed by the lower bound of the entropic uncertainty relation. The results can be applied in quantum measurement, quantum cryptography task and quantum information processing.

Quantum coherence and non-Markovianity of an atom in a dissipative cavity under weak measurement are investigated in this work. We find that: the quantum coherence obviously depends on the initial atomic state, the strength of the weak measurement and its reversal, the atom-cavity coupling constant and the non-Markovian effect. It is obvious that the weak measurement effect protects the coherence better. The quantum coherence is preserved more efficiently for larger atomcavity coupling. The stronger the non-Markovian effect is, the more slowly the coherence reduces. The quantum coherence can be effectively protected by means of controlling these physical parameters.

Received XX; revised manuscript received X XX) Analytical solution and entanglement swapping of a double Jaynes-Cummings model in non-Markovian environments are investigated by the timeconvolutionless master equation method. We obtain the analytical solution of this model and discuss in detail the influence of atom-cavity coupling, non-Markovian effect and initial state purity on entanglement dynamics. The results show that, in the non-Markovian environments, the entanglement between two cavities can be swapped to other bipartite subsystems by interaction between an atom and its own cavity. Due to the dissipation of environment, the entanglements of all bipartite subsystems will eventually decay to zero when the atom couples weakly to its cavity and the non-Markovian effect is also weak. All bipartite subsystems can tend to steady entanglement states if and only if there is the strong atom-cavity coupling or the strong non-Markovian effect. The steady state of the subsystem composed of an atom and its own cavity is independent on the purity but the steady states of other bipartite subsystems are dependent on the purity.

ObjectivesTo build and evaluate a deep learning radiomics nomogram (DLRN) for preoperative prediction of lung metastasis (LM) status in patients with soft tissue sarcoma (STS).MethodsIn total, 242 patients with STS (training set, n=116; external validation set, n=126) who underwent magnetic resonance imaging were retrospectively enrolled in this study. We identified independent predictors for LM-status and evaluated their performance. The minimum redundancy maximum relevance (mRMR) method and least absolute shrinkage and selection operator (LASSO) algorithm were adopted to screen radiomics features. Logistic regression, decision tree, random forest, support vector machine (SVM), and adaptive boosting classifiers were compared for their ability to predict LM. To overcome the imbalanced distribution of the LM data, we retrained each machine-learning classifier using the synthetic minority over-sampling technique (SMOTE). A DLRN combining the independent clinical predictors with the best performing radiomics prediction signature (mRMR+LASSO+SVM+SMOTE) was established. Area under the receiver operating characteristics curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the performance and clinical applicability of the models.ResultComparisons of the AUC values applied to the external validation set revealed that the DLRN model (AUC=0.833) showed better prediction performance than the clinical model (AUC=0.664) and radiomics model (AUC=0.799). The calibration curves indicated good calibration efficiency and the DCA showed the DLRN model to have greater clinical applicability than the other two models.ConclusionThe DLRN was shown to be an accurate and efficient tool for LM-status prediction in STS.

Background: Very low birth weight premature (VLBW) infants with bronchopulmonary dysplasia (BPD) often need prolonged respiratory support, which is associated with worse outcomes. The application of neurally adjusted ventilatory assist ventilation (NAVA) in infants with BPD has rarely been reported. This study investigated whether NAVA is safe and can reduce the duration respiratory support in VLBW premature infants with established or evolving BPD. Methods: This retrospective matched-cohort study included patients admitted to our NICU between April 2017 to April 2019 who were born at <32 weeks' gestation with birthweight of <1,500 g. The study groups (NAVA group) were infants who received NAVA ventilation as a sequel mode of ventilation after at least 2 weeks of traditional respiratory support after birth. The control group were preterm infants who required traditional respiratory support beyond first 2 weeks of life and were closely matched to the NAVA patients by gestational age and birthweight. The primary outcome was to compare the total duration of respiratory support between the NAVA group and the control group. The secondary outcomes were comparisons of duration of invasive and non-invasive support, oxygen therapy, length of stay, severity of BPD, weight gain and sedation need between the groups. Results: There were no significant differences between NAVA group and control group in the primary and most of the secondary outcomes (all P > 0.05). However, NAVA was well tolerated and there was a decrease in the need of sedation (p = 0.012) after switching to NAVA. Conclusion: NAVA, when used as a sequel mode of ventilation, in premature neonates <1,500 g with evolving or established BPD showed a similar effect compared to conventional ventilation in respiratory outcomes. NAVA can be safely used in this patient population and potentially can decrease the need of sedation.