A framework of effective debris management for a resilient community

Natural disasters have an enormous physical impact on communities and generate a huge volume of debris. The amount of debris is almost five to ten times higher than the annual solid waste volume in a community, and slow debris removal can hinder both emergency response and proceeding with the tasks of recovery. The cost of debris management also can reach more than 27% of the total disaster recovery costs. Therefore, debris management teams have considerable challenges in removing disaster debris. ^ This thesis introduces a framework for an effective debris management plan based on the interrelationship between critical infrastructure systems for debris management and providing resources that would enable a community to effectively remove debris from disaster-affected areas. This research also focuses on the impact of the capacity of infrastructure systems and the resources required for debris management with respect to the general debris removal procedures of generation, collection, transportation, processing, and disposal. ^ A debris management team could benefit from this research by being able to evaluate the existing debris management system in a community at pre- or post-disaster levels and assess its current resilience and total duration for debris removal in order to set up a short- and long-term strategy. The framework also suggests the feasible capacities of debris handling facilities and the resources required to improve the resilience of a community with respect to debris management

Selecting a Temporary Debris Management Site for Effective Debris Removal

The overall debris removal after disasters is often prolonged due to the huge amount of debris and lack of capacities such as a Temporary Debris Management Site (TDMS) in the community. This results in a delay of overall recovery and increases the total recovery cost. Strategic planning and building a TDMS will help in providing extra time for proper disposal of debris and clearing a disaster-impacted site that will facilitate the reconstruction process. This paper presents a unique approach for identifying and selecting TDMS locations for expediting debris removal from the community. A hypothetical example of a community impacted by a natural hazard is presented to explain how the the proposed model works. The research integrates data from a loss assessment report obtained from HAZUS-MH, Post Disaster Needs Assessment (PDNA), and Geographical Information System (GIS) in a dynamic simulation model. Various TDMS locations could be evaluated based on the existing capacity and infrastructure services and considering factors such as overall debris removal time, associated cost, productivity, and availability of resources. Debris management teams would greatly benefit from the research for strategically siting TDMS for accelerating the debris removal process

Draft genome of methanol-oxidizing Methylobacterium fujisawaense strain LAC1

We report the draft genome of Methylobacterium fujisawaense LAC1 isolated from an acidic aquifer in Indian Head, MD, USA. The genome contains 5,883,000 bp and has a GC content of 70% with 5,434 protein-encoding genes with functional assignments. This strain can grow on methanol with lanthanum, a rare earth element

Active Citizen E-Participation in Local Governance: Do Individual Social Capital and E-Participation Management Matter?

Abstract While a growing body of literature has touted e-participation as a means of facilitating greater citizen participation in policy decision-making processes, little is known about the driving forces of active citizen e-participation. Active e-participation is defined as the extent to which citizens make inputs via e-participation programs. Based on a literature review of social capital and citizen participation, the study develops a model of active e-participation and tests it in the context of local governance. Three dimensions of social capital -trust in government, strength of social ties, and volunteering activitiesare classified to explore the association of individual social capital and active e-participation. The model addresses that three dimensions of citizen participation management -fairness, access to information, and government responsiveness -are positively associated with active e-participation. To test several hypotheses, the study uses the 2009 E-Participation Survey data collected from 1,076 participants of the Cheon Man Sang Sang Oasis, which is an e-participation program administered by the Seoul Metropolitan Government in South Korea since 2006. Using ordered logistic regression analysis, the study found that citizens' trust in government and their volunteer experiences are positively related to active e-participation. The results demonstrate that citizens embedded in weak offline social ties are likely to use e-participation actively. The study also found that citizens' perception of quality responsiveness during the e-participation process is positively related to active e-participation. Based on the study's findings, the paper discusses the managerial and policy implications for fostering citizens' eparticipation through effective e-participation programs in the context of local governance

Dispersion retrieval from multi-level ultra-deep reactive-ion-etched microstructures for terahertz slow-wave circuits

A multi-level microstructure is proposed for terahertz slow-wave circuits, with dispersion relation retrieved by scattering parameter measurements. The measured return loss shows strong resonances above the cutoff with negligible phase shifts compared with finite element analysis. Splitting the circuit into multi levels enables a low aspect ratio configuration that alleviates the loading effect of deep-reactive-ion etching on silicon wafers. This makes it easier to achieve flat-etched bottom and smooth sidewall profiles. The dispersion retrieved from the measurement, therefore, corresponds well to the theoretical estimation. The result provides a straightforward way to the precise determination of dispersions in terahertz vacuum electronics.</jats:p

Vitamin D and Exercise Are Major Determinants of Natural Killer Cell Activity, Which Is Age- and Gender-Specific

BackgroundThe coronavirus-19 disease (COVID-19) pandemic reminds us of the importance of immune function, even in immunologically normal individuals. Multiple lifestyle factors are known to influence the immune function.ObjectiveThe aim was to investigate the association between NK cell activity (NKA) and multiple factors including vitamin D, physical exercise, age, and gender.MethodsThis was a cross-sectional association study using health check-up and NKA data of 2,095 subjects collected from 2016 to 2018 in a health check-up center in the Republic of Korea. NKA was measured using the interferon-γ (IFN-γ) stimulation method. The association of NKA with 25-(OH)-vitamin D (25(OH)D) and other factors was investigated by multiple logistic regression analysis.ResultsThe average age of subjects was 48.8 ± 11.6 years (52.9% of subjects were female). Among 2,095 subjects, 1,427 had normal NKA (NKA ≥ 500 pg IFN-γ/mL), while 506 had low NKA (100 ≤ NKA &lt; 500 pg/mL), and 162 subjects had very low NKA (NKA &lt; 100 pg/mL). Compared to men with low 25(OH)D serum level (&lt; 20 ng/mL), vitamin D replete men (30–39.9 ng/mL) had significantly lower risk of very low NKA (OR: 0.358; 95% CI: 0.138, 0.929; P = 0.035). In women, both low exercise (OR: 0.529; 95% CI: 0.299, 0.939; P = 0.030) and medium to high exercise (OR: 0.522; 95% CI: 0.277, 0.981; P = 0.043) decreased the risk compared to lack of physical exercise. Interestingly, in men and women older than 60 years, physical exercise significantly decreased the risk. Older-age was associated with increased risk of very low NKA in men, but not in women.ConclusionPhysical exercise and vitamin D were associated with NKA in a gender- and age-dependent manner. Age was a major risk factor of very low NKA in men but not in women

Adaptive Decision Support System to Navigate the Complexity of Post-Disaster Debris Management

Disaster debris management is critical to the success of disaster recovery systems. While there are multiple disaster mitigation strategies and post-disaster debris management plans, it is hard to implement because of: (i) the uniqueness of disaster incidents and randomness of its impacts; (ii) complexity of disaster debris removal operations, policy and regulations and (iii) interdependency of multiple infrastructure networks. Also, delayed debris removal operation affects following emergency response activities. Furthermore, uncontrolled debris removal activities can result in significant environmental and public health consequences. Therefore, there is a need for a systematic approach to optimizing post-disaster debris management systems. This research is aimed to understand the complexity of debris management and associated emergent dynamics through the lens of an adaptive system-of-systems (SoS). To develop the adaptive decision support system, this research (a) identifies the interdependent infrastructure network within a community and its relative importance; (b) develops real-time GIS database to integrate the data associated with critical infrastructure and geographical characteristics in the community map; (c) designs and selects a TDMS network to analyze the required number, capacity and resources, based on engineering-technical, managerial, and social-political dynamics; (d) simulate the productivity of debris-management SoS based on the real-time GIS database to gain insight into the impact of the dynamical nature of a disaster-affected area; and (e) develop a visualized interactive GIS-based platform for debris management to communicate real-time debris clearance strategies and operations among different agencies and organizations. To evaluate the proposed framework and decision support system, this research conducted a case study, debris removal operation in the city of Baton Rouge, after the 2016 Louisiana flood. The results demonstrated the influence of sub-systems such as TDMS locations and capacity, road network condition, available resources, existing regulations and policies, characteristics of community on the behavior of the entire disaster debris removal management as a whole. The proposed decision support system for effective disaster debris management will be beneficial for emergency agencies and disaster-prone communities to evaluate and optimize their disaster debris management system. Also, the system can be systematically integrated with other emergency response systems to maximize the efficiency of the entire disaster responses during post-disaster situations

Examining consumers\u27 risky food consumption behavior in restaurants

The popularity of raw or undercooked foods has continued to grow even though FDA defines them as risky foods. As consumers’ demand for raw or undercooked foods has increased, many restaurants have started to offer these foods as part of their menu. Thus, it is important to understand the reasons and behaviors behind risky food consumption. This dissertation examined risky food consumption behavior from the standpoint of a based on social behavior scale, personality traits, and consumers’ perceptions. The first study showed direct relationships from two social behavioral variables (sensation seeking and emotional brand attachment) to intention to consume risky foods. Consumers who had a higher sensation seeking level (high risk takers) tended to have more intention to consume risky foods in restaurants. When consumers were more emotionally attached to the restaurants, they were more likely to consume risky foods in restaurants. In the second study, consumers’ risky food perception was examined with ten risky food items. The likelihood of eating risky foods was explained by the risky food perception, and the perceived riskiness of foods was affected by three variables: cultural norm, experience, and knowledge. The moderating role of risk taking level was also proved in the relationship between the perceived riskiness of foods and likelihood of eating risky foods. Lastly, personality variables (sense of power and optimism) were adopted to understand consumers’ intention to consume risky foods. The sense of power affected optimism in general and food safety optimism, but only food safety optimism affected the intention to consume risky foods. Thus, an indirect relationship between sense of power and intention to consume risky foods via food safety optimism was proved