Addressing nuclear power plant accidents (NPPAs) overwhelms the capability of single jurisdictional government and spans the boundaries of multiple sectors. NPPAs management requires public sectors affiliating to multiple governments, private and non-profit sectors to interact with each other for sharing responsibilities, capabilities and information. How to leverage network to improve collaboration and coordination among all the involved organizations presents challenges for Chinese public administrators in NPPAs management. From the emergency management practice of the earliest nuclear power plants in China, this research investigates and conceptualizes governance mechanisms and associated interorganizational relationships involving in each jurisdictional governmental level and among multiple governments in this specific field. The intergovernmental and cross-sectoral NPPAs management network is built, visualized and analyzed at the levels of the node, link, subset of the nodes and whole network based on Social Network Analysis, and managerial implications of improving inter-organizational collaboration in this field are discussed. Our research shows that the current NPPAs network in China mainly relies on the resources and capabilities of public sectors, and the private and non-profit sectors should be integrated into the network for providing diversified emergency services. NPPAs management network is a hybrid network in the centralized political-administrative structure of China, and hierarchical, market and network governance mechanism play essential roles together and complement with each other in the multi-organizational environment. This network demonstrates the characteristics of selective integration, and the interorganizational relationships that should be paid more attention to be sustained are identified and emphasized from the network perspectives. Furthermore, the absence of collaborative relationships among the organizations that poses barriers to interorganizational collaboration is also discovered and the improvement approaches are discussed. This research provides guidance for improving collaboration in NPPAs management in China, and contributes literatures on emergency management network and interorganizational collaboration in the centralized political-administrative structure.

To investigate the effect of temperature and relative humidity (RH) on the absorption kinetics of selfactivated and moisture-activated O 2 scavengers for packaged food, kinetic parameters of each O 2 scavenger were evaluated at 43%, 75% or 100% RH and at 10, 25 and 40°C respectively. Absorption kinetics was well described by a first-order reaction with an Arrhenius type behaviour. For moisture-activated O 2 scavengers, a proper high RH was needed to ensure a high O 2 absorption capacity, as average O 2 absorption capacity was 3.82 mL at 43% RH and 43.40 mL at 75% RH. When the temperature increased, O 2 absorption rate constant ascended from 10°C to 40°C on an average of 0.153 and 0.306 h À1 in moisture-activated and self-activated O 2 scavengers respectively. We could take the effect of temperature and RH into account when we chose different types of iron-based O 2 scavengers for packaged food. Absorption kinetics of oxygen scavenger S. Feng et al. 1391 Absorption kinetics of oxygen scavenger S. Feng et al. Absorption kinetics of oxygen scavenger S. Feng et al. Absorption kinetics of oxygen scavenger S. Feng et al. 1394 Absorption kinetics of oxygen scavenger S. Feng et al.

Since the SARS crisis in 2003, institutionalized emergency management systems have been established in each government level for improving inter-organizational collaboration in China. Major accidents require participation of public organizations affiliated with multiple government levels, and the lack of collaboration and coordination among the involved organizations within the critical time constraints during the response process is an existing problem. In this research, a case study of examining the intergovernmental and cross-sectoral collaboration for responding to a well-known oil pipeline explosion accident in China by a complex network method is conducted. The aim is to obtain managerial insights in improving the existing emergency management system in a centralized political-administrative context, such as China. A mixed method of data collection is applied to identify the participating organizations and to determine the interaction spanning organizational boundaries in both hierarchical and horizontal dimensions. An emergency response network is built and visualized for representing intergovernmental and interorganizational collaboration during the response process of the major accident by social network analysis (SNA) tools. The SNA indicators are used to measure quantitatively the network structure at the levels of the whole network, subnetwork, and node. The obstacles of achieving intergovernmental collaboration are found, and managerial suggestions for improving the existing emergency management system are provided. This research indicates that the Chinese government should pay attention to establishing and sustaining partnerships with private and nonprofit organizations and conduct a blend of hierarchical, market, and network principles in fostering collaboration for addressing major accidents. The public organizations in the local government level are shown to be more active than other participators in coordinating their response operations, and their capability should be emphasized for improvement. Additionally, the interactive relationships among specific emergency function groups and between the affected communities and organizations performing emergency command and coordination function should be strengthened.

Due to its simplicity, efficiency, and effectiveness, multinomial naive Bayes (MNB) has been widely used for text classification. As in naive Bayes (NB), its assumption of the conditional independence of features is often violated and, therefore, reduces its classification performance. Of the numerous approaches to alleviating its assumption of the conditional independence of features, structure extension has attracted less attention from researchers. To the best of our knowledge, only structure-extended MNB (SEMNB) has been proposed so far. SEMNB averages all weighted super-parent one-dependence multinomial estimators; therefore, it is an ensemble learning model. In this paper, we propose a single model called hidden MNB (HMNB) by adapting the well-known hidden NB (HNB). HMNB creates a hidden parent for each feature, which synthesizes all the other qualified features’ influences. For HMNB to learn, we propose a simple but effective learning algorithm without incurring a high-computational-complexity structure-learning process. Our improved idea can also be used to improve complement NB (CNB) and the one-versus-all-but-one model (OVA), and the resulting models are simply denoted as HCNB and HOVA, respectively. The extensive experiments on eleven benchmark text classification datasets validate the effectiveness of HMNB, HCNB, and HOVA.

In contemporary China, the rapidly urbanized cities are exposed to a broad range of natural and human-made emergencies, such as COVID-19. Responding to emergencies successfully requires widespread participation of local government sectors that engages in diversified collaboration behaviors across organizational boundaries for achieving sustainability. However, the multi-organizational collaborative process is highly dynamic and complex, as well as its outcomes are uncertain underlying the emergency response network. Examining characteristics of the collaborative process and exploring how collaborative behaviors local governmental sectors engaging in the impact their perceived outcomes is essential to understand how disastrous situations are addressed by collaborative efforts in emergency management. This research investigates diversified collaborative behaviors in emergency response and then examines this using a multi-dimensional model consisting of joint decision making, joint implementation, compromised autonomy, resource sharing, and trust building. We surveyed 148 local governments and their affiliated sectors in China in-depth understanding how collaborative processes contribute to perceived outcomes from perspectives of participating sectors in the context of a centralized political-administrative system. A structural equation model (SEM) is employed to encode multiple dimensions of the collaborative process, perceived outcomes, as well as their relationships. The empirical finding indicates that joint decision making and implementation positively affect the perceived outcomes significantly. The empirical results indicate that joint decision making and joint implementation affect perceived outcomes significantly. Instead, resource sharing and trust building do not affect the outcomes positively as expected. Additionally, compromised autonomy negatively affects the collaborative outcomes. We also discuss the institutional advantages for achieving successful outcomes in emergency management in China by reducing the degree of compromised autonomy. Our findings provide insight that can improve efforts to build and maintain a collaborative process to respond to emergencies.