Network intrusion detection plays a very important role in protecting computer network security. The abnormal traffic detection and analysis by extracting the statistical features of flow is the main analysis method in the field of network intrusion detection. However, these features need to be designed and extracted manually, which often loses the original information of the flow and leads to poor detection efficiency. In this paper, we do not manually design the features of the flow but directly extract the raw data information of the flow for analysis. In addition, we first proposed a new network intrusion detection model named the deep hierarchical network, which integrates the improved LeNet-5 and LSTM neural network structures, while learning the spatial and temporal features of flow. By designing a reasonable network cascading method, we can train our proposed hierarchical network at the same time instead of training two networks separately. In this paper, we use the CICIDS2017 dataset and the CTU dataset. The number and types of flow in these two datasets are large, and the attack types are relatively new. The experimental results show that the performance of the proposed hierarchical network model is significantly better than other network intrusion detection models, which can achieve the best detection accuracy. Finally, we also present an analysis method for traffic features which has an important contribution to abnormal traffic detection and gives the actual meanings of these important features. INDEX TERMS Network intrusion detection, deep hierarchical network, raw feature, feature importance.

PurposeTo explore the efficacy and safety of prophylactic temporary balloon occlusion of the infrarenal abdominal aorta during caesarean for the management of patients with placenta praevia accreta.MethodsTwo hundred and sixty-eight cases of placenta praevia accreta from January 2012 to June 2015 were retrospectively reviewed. Group A included two hundred and thirty patients who underwent prophylactic temporary balloon occlusion of infrarenal abdominal aorta followed by caesarean section. Group B included thirty-eight patients who underwent caesarean without endovascular intervention. The parameters including operating room time, estimated blood loss, blood transfusion volume, PT (prothrombin time) during operation, days in the intensive care unit, and total hospital days were compared between the two groups.ResultsThe operating room time, estimated blood loss, PT, the incidence of hysterectomy, blood transfusion volume, postpartum haemorrhage, and days in intensive care unit were lower in group A than in group B, with statistical significance (P < 0.05). There was no significant difference in the Apgar scores of the neonates and the incidences of thrombosis in lower limbs between the two groups (P > 0.05). No patient in the group with prophylactic temporary balloon occlusion of the infrarenal abdominal aorta was performed hysterectomy, while three patients in group B were performed hysterectomy because of uncontrollable haemorrhage.ConclusionsThe results indicate that prophylactic temporary balloon occlusion of infrarenal abdominal aorta followed by caesarean section is safe and effective to control intraoperative blood loss and greatly decreases the risk of hysterectomy in patients with placenta praevia accreta.

Network attack behavior detection using deep learning is an important research topic in the field of network security. Currently, there are still many challenges in detecting multi-class imbalanced abnormal traffic data. This paper proposed a new intrusion detection network based on deep learning, named parallel cross convolutional neural network (PCCN), to improve the detection performance of imbalanced abnormal flows. By fusing the flow features learned from the two branch convolutional neural networks (CNN), PCCN can better learn the flow features with fewer samples, to improve the detection results of the imbalanced abnormal flows. We proposed an improved feature extraction method of the original flow to extract multi-class flow features at the same time. The proposed algorithm not only reduces the number of useless elements for network learning, but also accelerates network convergence. In addition, we proposed four improved versions of the PCCN network structure to meet the real-time requirements of network intrusion detection in the current big data computing. These networks can achieve almost the same detection results as the PCCN, but greatly reduce the detection time of data. Through the analysis of highorder evaluation metrics, the proposed PCCN algorithm is significantly better than the traditional machine learning algorithms. Compared with the current hierarchical network model, PCCN can also achieve better performance in term of overall accuracy. INDEX TERMS Network intrusion detection, cross network, deep learning, feature fusion.

Medications that can mitigate against radiation injury are limited. In this study, we investigated the ability of recombinant human growth hormone (rhGH) to mitigate against radiation injury in mice and nonhuman primates. BALB/c mice were irradiated with 7.5 Gy and treated post-irradiation with rhGH intravenously at a once daily dose of 20 µg/dose for 35 days. rhGH protected 17 out of 28 mice (60.7%) from lethal irradiation while only 3 out of 28 mice (10.7%) survived in the saline control group. A shorter course of 5 days of rhGH post-irradiation produced similar results. Compared with the saline control group, treatment with rhGH on irradiated BALB/c mice significantly accelerated overall hematopoietic recovery. Specifically, the recovery of total white cells, CD4 and CD8 T cell subsets, B cells, NK cells and especially platelets post radiation exposure were significantly accelerated in the rhGH-treated mice. Moreover, treatment with rhGH increased the frequency of hematopoietic stem/progenitor cells as measured by flow cytometry and colony forming unit assays in bone marrow harvested at day 14 after irradiation, suggesting the effects of rhGH are at the hematopoietic stem/progenitor level. rhGH mediated the hematopoietic effects primarily through their niches. Similar data with rhGH were also observed following 2 Gy sublethal irradiation of nonhuman primates. Our data demonstrate that rhGH promotes hematopoietic engraftment and immune recovery post the exposure of ionizing radiation and mitigates against the mortality from lethal irradiation even when administered after exposure.

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We report a QM (including TD-DFT and CASSCF) and ONIOM (QM:MM) study on the fluorescence quenching in methanol solution and fluorescence enhancement in crystal for a styrene derivative, namely 4-diethylamino-2 benzylidene malonic acid dimethyl ester (BIM) that possesses push−pull structure and AIE properties. The results showed that in methanol solution the weakening of ethylenic CC bond after photoexcitation initiates a barrierless relaxation via one-bond rotation around it, until the reactive molecule reaches a lowenergy intermediate with strong charge-transfer character, then a S 1 /S 0 conical intersection optimized near the charge-transfer intermediate is responsible for the fluorescence quenching in the dilute solution. The existences of charge-transfer intermediate as well as the conical intersection in the vicinity, which has not been observed in other symmetric (or less polar) phenylethylenebased luminophores, are the major features of BIM in solution. While in crystalline phase, the excited-state deactivation channels via torsional motions, either via one-bond rotation or via hula-twist mechanism, are restricted by steric hindrance and electrostatic repulsion from surrounding molecules, and thus fluorescence is enhanced.

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