Autonomic end-to-end quality-of-service assurance over QKD-secured optical networks.

Quantum key distribution (QKD) provides future-proof security for data communications over optical networks. Currently, sophisticated QKD systems are developed and the scale of QKD-secured optical networks (QKD-ONs) becomes larger. Given the complex network conditions and dynamic end-to-end security services in QKD-ONs, autonomic management and control becomes a promising paradigm to support end-to-end quality-of-service (QoS) assurance in an efficient and stable way without requiring human intervention. Hence, to enable and utilize the autonomic functionalities over QKD-ONs for realizing the end-to-end QoS assurance becomes a challenge. This work enhances the software defined networking (SDN) technique to tackle this challenge because SDN can add programmability and flexibility for QKD-ON's management and control. A new architecture of SDN-based QKD-ONs supporting autonomic end-to-end QoS assurance is designed, where a knowledge engine with autonomic control loops is developed in the SDN controller. We present the autonomic end-to-end QoS assurance procedure, and the cross-layer collaborative QoS assurance (CLC-QA) strategy for implementing the autonomic functionalities in the network level over QKD-ONs. We also establish an experimental testbed of SDN-based QKD-ONs supporting autonomic end-to-end QoS assurance, and perform the numerical simulation to verify our proposed approaches. Experimental results demonstrate that our presented approaches can achieve the millisecond-level overall latency of 337 ms and 618 ms, during the first and second autonomic adjustment without human intervention in case of the autonomic QoS protection. Moreover, the CLC-QA strategy is evaluated under different traffic loads by being compared with the baseline strategy without cross-layer collaboration. It can improve 22.5% protection success ratio and save 5.7% average key consumption.

Developing a competency model for Chinese general practitioners: a mixed-methods study.

BACKGROUND: The Chinese government has formulated a series of policies and strengthened training of general practitioners (GPs) to support their role as "gatekeepers" of residents' health. This study aimed to explore the core competencies of Chinese GPs and develop a competency framework in line with China's actual conditions, which can provide a more scientific basis for the education, training, and evaluation of GPs. METHODS: Literature analysis and behaviour event interviews were conducted to build the competency dictionary and the initial version of the competency model. Two rounds of Delphi were performed to gain consensus on the final model. The questionnaire survey was carried out in 10 provinces (municipalities, autonomous regions) of China, and GPs were invited to score the importance of each competency item. The total sample was randomly divided into two groups. One group was for exploratory factor analysis (EFA), and the other was for confirmatory factor analysis (CFA) to examine the scale's reliability and validity. RESULTS: The dictionary of general practitioners' competency including 107 competency items was constructed. After two rounds of Delphi, a consensus was reached on 60 competencies in 6 domains. A total of 1917 valid questionnaires were obtained in the nationwide survey. The average importance score of all second-level indicators is 4.53 ± 0.45. The Cronbach's α coefficient is 0.984. The results of the five factors extracted by EFA showing the 68.16% cumulative explained variance variation is considered to be consistent with the six dimensions obtained by Delphi after thorough discussion. The model fitness indexes obtained by CFA were acceptable (χ2/df = 4.909, CFI = 0.869, NFI = 0.841, RMSEA = 0.065). The values of the composite reliability (CR) of the six dimensions were all greater than 0.7 (0.943, 0.927, 0.937, 0.927, 0.943, 0.950), and the average of variance extracted (AVE) were all greater than 0.5 (0.562, 0.613, 0.649, 0.563, 0.626, 0.635). The results showed that the model has good reliability and validity. CONCLUSION: A competency model for GPs suited to China has been developed, which may offer guidance for future training and medical licensing examinations of GPs.

Topology Abstraction-Based Routing Scheme for Secret-Key Provisioning in Hybrid GEO/LEO Quantum Satellite Networks.

Quantum key distribution (QKD) is a promising technique to resist the threat against quantum computers. However, the high loss of quantum signals over a long-distance optical fiber is an obstacle for QKD in the intercontinental domain. In this context, the quantum satellite network is preferred over the terrestrial quantum optical network. Due to the mobility of satellites, the satellite topology is dynamic in the quantum satellite network, which remains a challenge for routing. In hybrid geostationary-earth-orbit (GEO)/low-earth-orbit (LEO) quantum satellite networks, the lack of an efficient scheduling scheme for GEO/LEO satellites also limits the construction of quantum satellite networks. Therefore, this paper provides a topology abstraction-based routing scheme for secret-key provisioning, where the dynamic physical topology is translated into a quasi-static abstracted topology. This scheme contributes to saving the precious secret key resources. In order to improve the success probability of long-distance QKD requests, three novel resource-scheduling heuristic algorithms are proposed in hybrid GEO/LEO quantum satellite networks. Simulation results indicate that the proposed algorithms can improve the success probability of QKD requests by 47% compared to the benchmark.

Comparative transcriptome analysis revealed the molecular mechanism of the effect of light intensity on the accumulation of rhynchophylline and isorhynchophylline in Uncaria rhynchophylla.

Rhynchophylline (RIN) and isorhynchophylline (IRN), the main medicinal components in plant Uncaria rhynchophylla, have potential effects on Alzheimer's disease. Understanding the influence of environmental factors, especially light intensity, on the production of these active ingredients will help to improve cultivation techniques. Compared with the 100% light intensity (CK), the contents of RIN and IRN in U. rhynchophylla leaves significantly increased at 20% light intensity (HS) after 7 and 21 days. Short-term shading (21d) changed some morphological indicators of U. rhynchophylla, but did not affect its biomass. Transcriptome profile analysis was performed on data from two groups (7 and 21 days) of CK and HS samples and yielded 79,817 unigenes with an average length of 1023 bp. Concurrently, 2391 and 2136 differentially expressed genes were identified in the transcriptome data for, respectively, 7 and 21 days of shade treatment. Notably, unigenes known to be involved upstream in the biosynthesis of RIN and IRN, such as G8O, IO, 7-DLGT, LAMT, TDC, and STR, were mostly upregulated. In addition, 1065 putative transcription factors (TFs) were identified and grouped into 55 TF families; 26 TFs showed differential expression in the shade treatment after 7 and 21 days. HY5 and PIFs, two important TFs of the light signaling pathway, also showed differential expression. This study provides insight into how gene expression was affected by light intensity during RIN and IRN accumulation in U. rhynchophylla. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-022-01142-2.

Dynamic secret-key provisioning in quantum-secured passive optical networks (PONs).

Quantum cryptography (QC) is currently under investigation to build highly secure optical communication networks. QC requires distribution of quantum keys (also called "secret" keys) on separate wavelength channels than those used to transmit the encrypted data. Hence, we propose a quantum-secured passive optical network (QS-PON) that supports both i) the traditional wavelength channels for secured data transmission, and ii) a quantum key distribution network (QKDN) running on separate dedicated wavelengths. The QKDN generates and stores secret keys that are then assigned to users' demands served on traditional PON channels. To generate secret keys, quantum transmitters at the optical network units (ONUs) exchange qubits with a quantum receiver at the optical line terminal (OLT). Then, the generated secret keys are stored in quantum key pools (QKPs) installed at both OLT and the ONUs and assigned to users' demands. Point-to-multipoint QKD systems have been experimentally demonstrated over various forms of quantum access networks (QANs), showing that an efficient mechanism to generate and assign quantum keys based on traffic requests is a critical component of QANs. In this study, we present a new QS-PON architecture, and we propose a dynamic secret-key provisioning (DSKP) algorithm that effectively generates and assigns secret keys from users' demands. Our proposed DSKP algorithm features two phases, the lowest-first secret-key generation (LF-SKG) phase and the hierarchical-clustering secret-key consumption (HC-SKC) phase. In this study, we also provide an analytical model that describes how secret keys are generated and consumed in QKPs. In our illustrative numerical evaluation, we compare our algorithm for secret-key provisioning with a baseline IPACT-based solution in terms of service-rejection ratio, time-slot utilization, and guard- and relay-time saving. Results show that DSKP reduces service-rejection ratio and guard- and relay-time of about 16% and 39.54%, respectively.

Multi-path-based quasi-real-time key provisioning in quantum-key-distribution enabled optical networks (QKD-ON).

With its information-theoretic security, quantum-key-distribution-enabled optical networks (QKD-ON) have become a promising candidate for future optical networks. The concept of quantum key pool (QKP) was introduced to offer an effective strategy for storing quantum keys. However, with the loss on its theoretical security due to storing these keys, balancing the storage of quantum keys and the security requirements of QKD-ONs poses a major challenge in their practical deployments. Hence, in this paper a concept of quasi-real-time key provisioning (QRT-KP) is introduced to address the tradeoff between quantum key storage and the degree of security. To satisfy the practical deployment of QRT-KP and the requirement of high-traffic flow, we propose a multi-path based QRT-KP (MP-QRT-KP) algorithm. Simulation results show that the MP-QRT-KP effectively enhances the performance of QKD-ONs in different scenarios, and it turns out that the algorithm performs better than single-path based QRT-KP (SP-QRT-KP) in terms of the success probability of key-allocation requests and key-resources utilization.

Auxiliary graph based routing, wavelength, and time-slot assignment in metro quantum optical networks with a novel node structure.

Nowadays, critical sectors in government, finance, and military are facing increasingly high security challenges. However, traditional public-key crypto-systems based on computational complexity are likely to suffer from upgrade computational power. Quantum key distribution (QKD) is a promising technology to effectively address the challenge by providing secret keys due to the laws of quantum physics. Limited by the transmission distance of quantum communications, remote parties have to share secret keys by exchanging keys through the trusted relay nodes hop by hop. However, if relaying hop by hop is still used in metro quantum-optical networks (MQON), a large amount of key resources will be wasted since the distance between any two nodes is short. Therefore, the problem of how to distribute quantum keys with lower waste of key resources over MQON is urgent. In order to solve this problem, we design a novel quantum node structure that is able to bypass itself. Also, by extending the connectivity graph, auxiliary graphs are constructed to describe the adjacency of quantum nodes in different levels influenced by the physical distance. Based on the novel node, two routing, wavelength and time-slot assignment algorithms are proposed, in which some middle nodes can be bypassed to reduce the resource consumption as long as the distance between the two parties meets the requirement of quantum key distribution. Simulations have been conducted to verify the performance of the proposed algorithms in terms of blocking probability, resource utilization, number of bypassed nodes, and security rate per service. Numerical results illustrate that our algorithms perform better on resource utilization than a traditional scheme without bypass. Furthermore, a tradeoff between the keys saved and blocking probability is analyzed and discussed in our paper.

Multi-tenant secret-key assignment over quantum key distribution networks.

Quantum key distribution (QKD) networks are promising to progress towards widespread practical deployment over existing fiber infrastructures in the near future. Given the high cost and difficulty of deploying QKD networks, multi-tenancy becomes promising to improve cost efficiency for future QKD networks. In a multi-tenant QKD network, multiple QKD tenants can share the same QKD network infrastructure to obtain secret keys for securing their data transfer. Since the secret-key resources are finite and precious in QKD networks, how to achieve efficient multi-tenant secret-key assignment (MTKA) to satisfy the secret-key demands of multiple QKD tenants over QKD networks becomes a significant problem. In this regard, this study addresses the MTKA problem over QKD networks. A new multi-tenant QKD network architecture is proposed based on software defined networking (SDN) and quantum key pool (QKP) techniques. A secret-key rate sharing scheme is presented and a heuristic algorithm is designed to implement efficient MTKA over QKD networks. A new performance metric, namely matching degree (MD) that reflects the balance between QKD network secret-key resources and QKD tenant requests, is defined and evaluated. Simulation studies indicate that high QKD tenant requests accommodation and efficient secret-key resource usage can be achieved via maximizing the value of MD.

SDQaaS: software defined networking for quantum key distribution as a service.

Quantum key distribution (QKD) holds the potential of providing long-term integrity and confidentiality for data and communications. Currently, many fiber-based QKD systems have been commercialized and several QKD networks have been deployed. Given the high cost and complexity of QKD network deployment, QKD as a service (QaaS) becomes a promising pattern for future QKD networks. The QaaS concept is that multiple users can apply for QKD services to obtain their required secret-key rates (SKRs) from the same QKD network infrastructure instead of deploying their dedicated QKD networks. Accordingly, how to provide efficient and flexible QaaS for fulfilling the SKR requirements of multiple users over a QKD network infrastructure becomes a new challenge. This study introduces the software defined networking (SDN) technique to overcome this challenge, since SDN can add flexibility together with efficient QKD network management. A new framework of SDN for QaaS (SDQaaS) is proposed, where the QaaS functions are developed in the SDN controller. We present the protocol extension, intercommunication workflow, and routing and SKR assignment strategy for QaaS implementation in the SDQaaS framework. We also establish a SDQaaS experimental testbed and perform the numerical simulation to verify our presented approaches. Experimental results demonstrate that our presented approaches can achieve efficient and flexible QaaS over the QKD network. Moreover, simulation results indicate that the success probability of QKD service requests can be increased via lowering the flexibility of SKR requirements for QKD service creation, sacrificing more cost to produce higher SKR over the QKD network, or gradually reducing SKR requirements with the modification of QKD service.

Joint balancing of IT and spectrum resources for selecting virtualized network function in inter-datacenter elastic optical networks.

With network functions decoupled from specific hardware, network function virtualization (NFV) is a promising technology to accelerate service provisioning in datacenter (DC) networks. In inter-datacenter elastic optical networks, each virtualized network function (VNF) is usually deployed in multiple DCs for the sake of survivability. In service provisioning, different VNF selections greatly affect IT resources in DCs as well as spectrum resources in optical networks. This paper investigates how to select appropriate VNFs for service requests to achieve joint load balancing of IT and spectrum resources. Two joint balancing factors are proposed to quantify the impact of different VNF selections on network load. Furthermore, a Joint-Optimization Selection (JOS) algorithm is designed to select VNFs in a joint load balancing manner. The performance of the proposed algorithm is evaluated in terms of resource utilization, blocking probability and average path length. Simulation results indicate that the proposed algorithm outperforms the benchmark algorithm.

Crosstalk-aware spectrum defragmentation by re-provisioning advance reservation requests in space division multiplexing enabled elastic optical networks with multi-core fiber.

Space division multiplexing enabled elastic optical networks (SDM-EONs) with multi-core fiber (MCF) have become a promising candidate for future optical transport networks, due to their high capacity and flexibility. Meanwhile, driven by the development of cloud computing and data centers, more types of requests are allowed in the networks, i.e., the usual immediate reservation (IR) requests, which need to be served immediately, and advance reservation (AR) requests, which support initial-delay tolerance services. However, with the introduction of AR requests, spectrum fragments occur frequently in both spatial and time dimension as lightpaths are set up and torn down, and the issue of spectrum fragmentation could be much more serious in SDM-EONs than in simple EONs. To measure fragments status in both spatial and time dimension in SDM-EONs, we first design a metric, i.e., time-dimensional spectrum compactness (TSC). Then, based on TSC, we propose a crosstalk-aware AR requests re-provisioning algorithm with two strategies to optimize the fragments in SDM-EONs. The performance of the proposed algorithm is evaluated via software simulation in terms of spectrum compactness, blocking probability, spectrum utilization, average moving times, average re-provisioning latency and average start time delay. The results show that the proposed re-provisioning algorithm can effectively improve spectrum compactness and spectrum efficiency of the networks. We also evaluate the proposed re-provisioning algorithm in different TSC thresholds, and it turns out that the proposed re-provisioning algorithm in higher threshold performs better in terms of spectrum compactness and spectrum utilization.

Dirty-data-based alarm prediction in self-optimizing large-scale optical networks.

Machine-learning-based solutions are showing promising results for several critical issues in large-scale optical networks. Alarm (caused by failure, disaster, etc.) prediction is an important use-case, where machine learning can assist in predicting events, ahead of time. Accurate prediction enables network administrators to undertake preventive measures. For such alarm prediction applications, high-quality data sets for training and testing are crucial. However, the collected performance and alarm data from large-scale optical networks are often dirty, i.e., these data are incomplete, inconsistent, and lack certain behaviors or trends. Such data are likely to contain several errors, when collected from old-fashioned optical equipment, in particular. Even after appropriate data preprocessing, feature distribution can be extremely unbalanced, limiting the performance of machine learning algorithms. This paper demonstrates a Dirty-data-based Alarm Prediction (DAP) method for Self-Optimizing Optical Networks (SOONs). Experimental results on a commercial large-scale field topology with 274 nodes and 487 links demonstrate that the proposed DAP method can achieve high accuracy for different types of alarms.

Thyroid Function and Risk of Non-Alcoholic Fatty Liver Disease in Euthyroid Subjects.

INTRODUCTION AND AIMS: The association between thyroid function and non-alcoholic fatty liver disease (NAFLD) remained controversial. A large cross-sectional study aimed to explore the relationship in euthyroid population. MATERIAL AND METHODS: A total of 1773 euthyroid subjects who underwent health check-up during one-year period were enrolled. NAFLD was diagnosed by ultrasound and fatty liver index (FLI). Fibrosis was estimated by BARD score. Thyroid function parameters, including thyroid-stimulating hormone (TSH), free triiodothyronine (FT3), and free thyroxine (FT4), were recorded. Multivariate logistic regression analyses were performed to identify the independent risk factors. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. RESULTS: NAFLD was diagnosed by ultrasound in 638 (35.98%) subjects and by FLI ≥ 60 in 694 (39.14%) subjects. Regardless of ultrasound or FLI, the overall analysis demonstrated that TSH and FT3 levels were significantly higher in subjects with NAFLD than subjects without NAFLD, but FT4 level was not significantly different between them. This association remained in middle-age subjects, but not elderly subjects. In the multivariate logistic regression analysis, TSH (OR = 1.108, 95%CI = 1.056-1.398, P = 0.024) and FT3 (OR = 1.258, 95%CI = 1.123-1.409, P = 0.000) levels were independently associated with the risk of NAFLD diagnosed by ultrasound; and only FT3 level (OR = 1.252, 95%CI = 1.074 - 1.460, P = 0.004) was independently associated with the risk of NAFLD estimated by FLI ≥ 60. Additionally, FT3 level (OR = 1.178, 95%CI = 1.025 - 1.354, P = 0.021) was independently associated with the risk of fibrosis estimated by BARD score ≥ 2 in NAFLD subjects. CONCLUSION: Among the euthyroid population, FT3 and TSH levels were positively associated with the risk of NAFLD.

Key on demand (KoD) for software-defined optical networks secured by quantum key distribution (QKD).

Software-defined optical networking (SDON) will become the next generation optical network architecture. However, the optical layer and control layer of SDON are vulnerable to cyberattacks. While, data encryption is an effective method to minimize the negative effects of cyberattacks, secure key interchange is its major challenge which can be addressed by the quantum key distribution (QKD) technique. Hence, in this paper we discuss the integration of QKD with WDM optical networks to secure the SDON architecture by introducing a novel key on demand (KoD) scheme which is enabled by a novel routing, wavelength and key assignment (RWKA) algorithm. The QKD over SDON with KoD model follows two steps to provide security: i) quantum key pools (QKPs) construction for securing the control channels (CChs) and data channels (DChs); ii) the KoD scheme uses RWKA algorithm to allocate and update secret keys for different security requirements. To test our model, we define a security probability index which measures the security gain in CChs and DChs. Simulation results indicate that the security performance of CChs and DChs can be enhanced by provisioning sufficient secret keys in QKPs and performing key-updating considering potential cyberattacks. Also, KoD is beneficial to achieve a positive balance between security requirements and key resource usage.

Data analysis-based autonomic bandwidth adjustment in software defined multi-vendor optical transport networks.

Network operators generally provide dedicated lightpaths for customers to meet the demand for high-quality transmission. Considering the variation of traffic load, customers usually rent peak bandwidth that exceeds the practical average traffic requirement. In this case, bandwidth provisioning is unmetered and customers have to pay according to peak bandwidth. Supposing that network operators could keep track of traffic load and allocate bandwidth dynamically, bandwidth can be provided as a metered service and customers would pay for the bandwidth that they actually use. To achieve cost-effective bandwidth provisioning, this paper proposes an autonomic bandwidth adjustment scheme based on data analysis of traffic load. The scheme is implemented in a software defined networking (SDN) controller and is demonstrated in the field trial of multi-vendor optical transport networks. The field trial shows that the proposed scheme can track traffic load and realize autonomic bandwidth adjustment. In addition, a simulation experiment is conducted to evaluate the performance of the proposed scheme. We also investigate the impact of different parameters on autonomic bandwidth adjustment. Simulation results show that the step size and adjustment period have significant influences on bandwidth savings and packet loss. A small value of step size and adjustment period can bring more benefits by tracking traffic variation with high accuracy. For network operators, the scheme can serve as technical support of realizing bandwidth as metered service in the future.

Protection of endothelial cells against Ang II-induced impairment: Involvement of both PPARα and PPARγ via PI3K/Akt pathway.

The aim of our study is to explore the involvement of PPARα and PPARγ in Ang II-induced endothelial injury. We found that Ang II significantly elevated the oxidative stress in HUVECs, causing apoptosis and cellular impairment in a time-dependent pattern. Activation of either PPARα by docosahexaenoic acid (DHA) or PPARγ by rosiglitazone protected the endothelial cells. Interestingly, a more significant effect was observed when DHA and rosiglitazone were administrated together. Moreover, we found that this protection was mediated through the PI3K/Akt pathway. Our study may help to understand the mechanism of endothelial dysfunction, contributing to the treatment of hypertension and other endothelial-related diseases.

A population-based study on health-related quality of life among urban community residents in Shenyang, Northeast of China.

BACKGROUND: Due to the rising standard of living environment and advances in public health and medical care in China, it has been a tendency in recent years that health-related quality of life (HRQoL) has been increasingly acknowledged in community health management. However, large-scale population-based study on evaluating HQRoL in northeast of China was not conducted. This article aims to investigate the HRQoL in community residents in Northeast China and explore the associated factors. METHODS: Stratified multiple-stage sampling method was used in the cross-sectional survey to investigate HRQoL of community residents in northeast of China. Univariate analysis and multiple linear regressions were used to analyze the factors associated to HRQoL of the community residents. RESULTS: The results were confirmed that HRQoL in general population was well performed for the first time in northeast of China in a large scale population. Community residents had better mental health than physical health. The factors influencing HRQoL included gender, age, educational level, marital status, ethnic group, chronic disease status, having breakfast frequency weekly and sleep quality. However, drinking and smoking habits did not affect residents' HRQoL. CONCLUSIONS: In this study, the result of the large-scale survey was satisfactory in northeast of China, providing HRQoL status of community residents. Policies on specific health management in community public health would emphasize on lifestyle behaviors especially eating habits in order to improving HRQoL.

Identification and Application of CLE Peptides for Drought Resistance in Solanaceae Crops.

The CLE (CLAVATA3/Embryo Surrounding Region-related) family, a group of peptides with hormone-like features, plays a pivotal role in plant growth, development, and adaptation to stress. Through homology-based blast analysis of 32 Arabidopsis thaliana CLE peptide sequences, we have identified 5, 14, and 10 CLE family members in Nicotiana tabacum, Capsicum annuum, and Solanum melongena, respectively. Chemical synthesis and functional assays of the peptides led to the discovery that NtCLE3 substantially enhances the drought resistance of these three Solanaceae crops. Our transcriptome, RT-qPCR, and antioxidant enzyme activity data showed that NtCLE3 increased antioxidant capacity and ABA synthesis in tobacco. Moreover, the recombinant protein RPNtCLE3, composed of 6*NtCLE3, preserved the capacity to foster drought resilience and proved to be a promising drought resistance regulator, which presents a more favorable alternative for field applications compared to ABA which degrades rapidly under sunlight exposure. This research unveils the prospective utility of NtCLE3 in enhancing drought tolerance in Solanaceae crops and provides new ideas for the development of novel bioregulators aimed at mitigating drought stress.

Functional screening of the Arabidopsis 2C protein phosphatases family identifies PP2C15 as a negative regulator of plant immunity by targeting BRI1-associated receptor kinase 1.

Genetic engineering using negative regulators of plant immunity has the potential to provide a huge impetus in agricultural biotechnology to achieve a higher degree of disease resistance without reducing yield. Type 2C protein phosphatases (PP2Cs) represent the largest group of protein phosphatases in plants, with a high potential for negative regulatory functions by blocking the transmission of defence signals through dephosphorylation. Here, we established a PP2C functional protoplast screen using pFRK1::luciferase as a reporter and found that 14 of 56 PP2Cs significantly inhibited the immune response induced by flg22. To verify the reliability of the system, a previously reported MAPK3/4/6-interacting protein phosphatase, PP2C5, was used; it was confirmed to be a negative regulator of PAMP-triggered immunity (PTI). We further identified PP2C15 as an interacting partner of BRI1-associated receptor kinase 1 (BAK1), which is the most well-known co-receptor of plasma membrane-localized pattern recognition receptors (PRRs), and a central component of PTI. PP2C15 dephosphorylates BAK1 and negatively regulates BAK1-mediated PTI responses such as MAPK3/4/6 activation, defence gene expression, reactive oxygen species bursts, stomatal immunity, callose deposition, and pathogen resistance. Although plant growth and 1000-seed weight of pp2c15 mutants were reduced compared to those of wild-type plants, pp2c5 mutants did not show any adverse effects. Thus, our findings strengthen the understanding of the mechanism by which PP2C family members negatively regulate plant immunity at multiple levels and indicate a possible approach to enhance plant resistance by eliminating specific PP2Cs without affecting plant growth and yield.

Experimental demonstration of OpenFlow-based control plane for elastic lightpath provisioning in Flexi-Grid optical networks.

Due to the prominent performance on networking virtualization and programmability, OpenFlow is widely regarded as a promising control plane technology in packet-switched IP networks as well as wavelength-switched optical networks. For the purpose of applying software programmable feature to future optical networks, we propose an OpenFlow-based control plane in Flexi-Grid optical networks. Experimental results demonstrate its feasibility of dynamic lightpath establishment and adjustment via extended OpenFlow protocol. Wireshark captures of the signaling procedure are printed out. Additionally, the overall latency including signaling and hardware for lightpath setup and adjustment is also reported.