To explore the dynamic expression and role of Aquaporin5 ( AQP5) in lung development and hyperoxia lung injury, gestation 21-day Sprague-Dawley (SD) rats (term=22 days) were ran- domly assigned to air group and hypero...To explore the dynamic expression and role of Aquaporin5 ( AQP5) in lung development and hyperoxia lung injury, gestation 21-day Sprague-Dawley (SD) rats (term=22 days) were ran- domly assigned to air group and hyperoxia group within 12-24 h after birth. The rats in hypreoxia group were continuously exposed to about 85% oxygen and those in air group to room air. After 1 to 14 days of exposure, total lung RNA was extracted and the expression of AQP5 mRNA was detected by reverse transcription polymerase chain reaction (RT-PCR). Immunohistochemistry and west- ern-blot were used to detect the expression of AQP5 protein. The results showed that the expression of AQP5 in premature rats lung could be detected at various time points after birth, and the positive staining was restricted to the type Ⅰ alveolar epithelial cells. In air group, the AQP5 expression was detected in a very low level at day 1, but exhibited a persistent increase after birth. Compared with the air group, the expression of AQP5 in hyperoxia group was increased at day 1, and had significant difference in mRNA level (P<0.05), but decreased significantly in mRNA and protein levels after 4 to 14 days (P<0.01 or P<0.05 respectively). It was concluded that AQP5 might play a key role in the alveolar period of premature rats by regulating the lung water balance. Hyperoxia exposure leads to a down-regulation of the AQP5 expression, which may be an important factor for the development of hyperoxia lung injury.展开更多
The rapid advancement of wireless communication is forming a hyper-connected 5G network in which billions of linked devices generate massive amounts of data.The traffic control and data forwarding functions are decoup...The rapid advancement of wireless communication is forming a hyper-connected 5G network in which billions of linked devices generate massive amounts of data.The traffic control and data forwarding functions are decoupled in software-defined networking(SDN)and allow the network to be programmable.Each switch in SDN keeps track of forwarding information in a flow table.The SDN switches must search the flow table for the flow rules that match the packets to handle the incoming packets.Due to the obvious vast quantity of data in data centres,the capacity of the flow table restricts the data plane’s forwarding capabilities.So,the SDN must handle traffic from across the whole network.The flow table depends on Ternary Content Addressable Memorable Memory(TCAM)for storing and a quick search of regulations;it is restricted in capacity owing to its elevated cost and energy consumption.Whenever the flow table is abused and overflowing,the usual regulations cannot be executed quickly.In this case,we consider lowrate flow table overflowing that causes collision flow rules to be installed and consumes excessive existing flow table capacity by delivering packets that don’t fit the flow table at a low rate.This study introduces machine learning techniques for detecting and categorizing low-rate collision flows table in SDN,using Feed ForwardNeuralNetwork(FFNN),K-Means,and Decision Tree(DT).We generate two network topologies,Fat Tree and Simple Tree Topologies,with the Mininet simulator and coupled to the OpenDayLight(ODL)controller.The efficiency and efficacy of the suggested algorithms are assessed using several assessment indicators such as success rate query,propagation delay,overall dropped packets,energy consumption,bandwidth usage,latency rate,and throughput.The findings showed that the suggested technique to tackle the flow table congestion problem minimizes the number of flows while retaining the statistical consistency of the 5G network.By putting the proposed flow method and checking whether a packet may move from point A to point B without breaking certain regulations,the evaluation tool examines every flow against a set of criteria.The FFNN with DT and K-means algorithms obtain accuracies of 96.29%and 97.51%,respectively,in the identification of collision flows,according to the experimental outcome when associated with existing methods from the literature.展开更多
A major challenge for the future wireless network is to design the self-organizing architecture.The reactive self-organizing model of traditional networks needs to be transformed into an active self-organizing network...A major challenge for the future wireless network is to design the self-organizing architecture.The reactive self-organizing model of traditional networks needs to be transformed into an active self-organizing network.Due to the user mobility and the coverage of small cells,the network load often becomes unbalanced,resulting in poor network performance.Mobility management has become an important issue to ensure seamless communication when users move between cells,and proactive mobility management is one of the important functions of the active Self-Organizing Network(SON).This paper proposes a proactive mobility management framework for active SON,which transforms the original reactive load balancing into a forward-aware and proactive load balancing.The proposed framework firstly uses the BART model to predict the users’temporal and spatial mobility based on a weekly cycle and then formulate the MLB optimization problem based on the soft load.Two solutions are proposed to solve the above MLB problem.The simulation results show that the proposed method can better optimize the network performance and realize intelligent mobile management for the future network.展开更多
Eleven climate system models that participate in the Coupled Model Intercomparison Project phase 5(CMIP5)were evaluated based on an assessment of their simulated meridional transports in comparison with the Sverdrup t...Eleven climate system models that participate in the Coupled Model Intercomparison Project phase 5(CMIP5)were evaluated based on an assessment of their simulated meridional transports in comparison with the Sverdrup transports.The analyses show that the simulated North Pacifi c Ocean circulation is essentially in Sverdrup balance in most of the 11 models while the Argo geostrophic meridional transports indicate signifi cant non-Sverdrup gyre circulation in the tropical North Pacifi c Ocean.The climate models overestimated the observed tropical and subtropical volume transports signifi cantly.The non-Sverdrup gyre circulation leads to non-Sverdrup heat and salt transports,the absence of which in the CMIP5 simulations suggests defi ciencies of the CMIP5 model dynamics in simulating the realistic meridional volume,heat,and salt transports of the ocean.展开更多
基金a grant from National Natural Sciences Foundation of China (No. 30471824)
文摘To explore the dynamic expression and role of Aquaporin5 ( AQP5) in lung development and hyperoxia lung injury, gestation 21-day Sprague-Dawley (SD) rats (term=22 days) were ran- domly assigned to air group and hyperoxia group within 12-24 h after birth. The rats in hypreoxia group were continuously exposed to about 85% oxygen and those in air group to room air. After 1 to 14 days of exposure, total lung RNA was extracted and the expression of AQP5 mRNA was detected by reverse transcription polymerase chain reaction (RT-PCR). Immunohistochemistry and west- ern-blot were used to detect the expression of AQP5 protein. The results showed that the expression of AQP5 in premature rats lung could be detected at various time points after birth, and the positive staining was restricted to the type Ⅰ alveolar epithelial cells. In air group, the AQP5 expression was detected in a very low level at day 1, but exhibited a persistent increase after birth. Compared with the air group, the expression of AQP5 in hyperoxia group was increased at day 1, and had significant difference in mRNA level (P<0.05), but decreased significantly in mRNA and protein levels after 4 to 14 days (P<0.01 or P<0.05 respectively). It was concluded that AQP5 might play a key role in the alveolar period of premature rats by regulating the lung water balance. Hyperoxia exposure leads to a down-regulation of the AQP5 expression, which may be an important factor for the development of hyperoxia lung injury.
基金Taif University Researchers supporting Project number(TURSP-2020/215),Taif University,Taif,Saudi Arabia.
文摘The rapid advancement of wireless communication is forming a hyper-connected 5G network in which billions of linked devices generate massive amounts of data.The traffic control and data forwarding functions are decoupled in software-defined networking(SDN)and allow the network to be programmable.Each switch in SDN keeps track of forwarding information in a flow table.The SDN switches must search the flow table for the flow rules that match the packets to handle the incoming packets.Due to the obvious vast quantity of data in data centres,the capacity of the flow table restricts the data plane’s forwarding capabilities.So,the SDN must handle traffic from across the whole network.The flow table depends on Ternary Content Addressable Memorable Memory(TCAM)for storing and a quick search of regulations;it is restricted in capacity owing to its elevated cost and energy consumption.Whenever the flow table is abused and overflowing,the usual regulations cannot be executed quickly.In this case,we consider lowrate flow table overflowing that causes collision flow rules to be installed and consumes excessive existing flow table capacity by delivering packets that don’t fit the flow table at a low rate.This study introduces machine learning techniques for detecting and categorizing low-rate collision flows table in SDN,using Feed ForwardNeuralNetwork(FFNN),K-Means,and Decision Tree(DT).We generate two network topologies,Fat Tree and Simple Tree Topologies,with the Mininet simulator and coupled to the OpenDayLight(ODL)controller.The efficiency and efficacy of the suggested algorithms are assessed using several assessment indicators such as success rate query,propagation delay,overall dropped packets,energy consumption,bandwidth usage,latency rate,and throughput.The findings showed that the suggested technique to tackle the flow table congestion problem minimizes the number of flows while retaining the statistical consistency of the 5G network.By putting the proposed flow method and checking whether a packet may move from point A to point B without breaking certain regulations,the evaluation tool examines every flow against a set of criteria.The FFNN with DT and K-means algorithms obtain accuracies of 96.29%and 97.51%,respectively,in the identification of collision flows,according to the experimental outcome when associated with existing methods from the literature.
基金supported in part by the Guangdong Basic and Applied Basic Research Foundation under grant 2020A1515110269.
文摘A major challenge for the future wireless network is to design the self-organizing architecture.The reactive self-organizing model of traditional networks needs to be transformed into an active self-organizing network.Due to the user mobility and the coverage of small cells,the network load often becomes unbalanced,resulting in poor network performance.Mobility management has become an important issue to ensure seamless communication when users move between cells,and proactive mobility management is one of the important functions of the active Self-Organizing Network(SON).This paper proposes a proactive mobility management framework for active SON,which transforms the original reactive load balancing into a forward-aware and proactive load balancing.The proposed framework firstly uses the BART model to predict the users’temporal and spatial mobility based on a weekly cycle and then formulate the MLB optimization problem based on the soft load.Two solutions are proposed to solve the above MLB problem.The simulation results show that the proposed method can better optimize the network performance and realize intelligent mobile management for the future network.
基金Supported by the National Natural Foundation of China(Nos.41421005,41720104008,91858204)the National Basic Research Program of China(973 Program)(No.2012CB956001)+2 种基金the Qingdao National Laboratory for Marine Science and Technology(No.2016ASKJ04)the Chinese Academy of Science(No.XDA11010205)the Shandong Provincial Projects(Nos.2014GJJS0101,U1406401)。
文摘Eleven climate system models that participate in the Coupled Model Intercomparison Project phase 5(CMIP5)were evaluated based on an assessment of their simulated meridional transports in comparison with the Sverdrup transports.The analyses show that the simulated North Pacifi c Ocean circulation is essentially in Sverdrup balance in most of the 11 models while the Argo geostrophic meridional transports indicate signifi cant non-Sverdrup gyre circulation in the tropical North Pacifi c Ocean.The climate models overestimated the observed tropical and subtropical volume transports signifi cantly.The non-Sverdrup gyre circulation leads to non-Sverdrup heat and salt transports,the absence of which in the CMIP5 simulations suggests defi ciencies of the CMIP5 model dynamics in simulating the realistic meridional volume,heat,and salt transports of the ocean.
