Monitoring of Microbial Loads During Long Duration Missions as a Risk Reduction Tool

Humans have been exploring space for more than 40 years. For all those years microorganisms have accompanied, first un-manned spacecraft/cargo and later manned vessels. Microorganisms are everywhere on Earth, could easily adapt to new environments and/or can rapidly mutate to survive in very harsh conditions. Their presence in spacecraft and cargo have caused a few inconveniences over the years of humans spaceflight, ranging from crew health, life support systems challenges and material degradation. The sterilization of spacecraft that will host humans in long duration mission would be a costly operation that will not provide a long-term solution to the microbial colonization of the vessels. As soon as a human is exposed to the spacecraft, during the mission, microorganisms will start to populate the new environment. As the hum an presence in space increases in length, the risk from the microbial load, to hardware and crew will also increase. Mitigation of this risk includes several different strategies that will include minimizing the microbial load (in numbers and diversity) and monitoring. This presentation will provide a list of the risk mitigation strategies that should be implemented during ground processing, and during the mission. It will also discuss the areas that should be discussed before an effective in-flight microbial monitoring regimen is implemented. Microbial monitoring technologies will also be presented

Explore Humans in Space

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Daring You to Ask, What If?

No abstract availabl

Interval symmetric single-step procedure ISS2-5D for polynomial zeros

We analyzed the rate of convergence of a new modified interval symmetric single-step procedure ISS2-5D which is an extension from the previous procedure ISS2. The algorithm of ISS2-5D includes the introduction of reusable correctors δi(k) (i = 1, …, n) for k ≥ 0. Furthermore, this procedure was tested on five test polynomials and the results were obtained using MATLAB 2007 software in association with IntLab V5.5 toolbox to record the CPU times and the number of iterations

Atmosphere Resource Recovery and Environmental Monitoring

Atmosphere Resource Recovery and Environmental Monitoring (ARREM) is a project focused on evolving existing and maturing emerging 'closed loop' atmosphere revitalization (AR) life support systems that produce clean, breathable air for crewmembers, and developing a suite of low mass, low power environmental monitors to detect and measure air- and waterborne constituents and contaminants. The objective is to improve reliability and efficiency, reduce mass and volume, and increase recovery of oxygen from carbon dioxide created by human metabolism from 43% to greater than 90%. The technology developments under ARREM are vital to extending human space missions from low-Earth orbit like the International Space Station to destinations deeper into space such as Mars where dependency on Earth for resupply of maintenance items and critical life support elements such as water and oxygen is not possible. The primary goal of the ARREM project is to demonstrate that systems meet the more stringent performance parameters for deep space exploration and are compatible with other systems within closed loop life support through a series of integrated tests performed in an environmental test chamber capable of simulating human metabolic activities and measuring systems outputs

Microbiological Tests Performed During the Design of the International Space Station Environmental Control and Life Support Systems. Part 1, Bulk Phase

The design and manufacturing of the main Environmental Control and Life Support Systems (ECLSS) for the United States segments of the International Space Station (ISS) was an involved process that started in the mid 1980s, with the assessment and testing of competing technologies that could be used to clean the air and recycle water. It culminated in 2009 with the delivery and successful activation of the Water Recovery System (WRS) water processor (WP). The ECLSS required the work of a team of engineers and scientist working together to develop systems that could clean and/or recycle human metabolic loads to maintain a clean atmosphere and provide the crew clean water. One of the main goals of the ECLSS is to minimize the time spent by the crew worrying about vital resources not available in the vacuum of space, which allows them to spend most of their time learning to live in a microgravity environment many miles from the comforts of Earth and working on science experiments. Microorganisms are a significant part of the human body as well as part of the environment that we live in. Therefore, the ISS ECLSS design had to take into account the effect microorganisms have on the quality of stored water and wastewater, as well as that of the air systems. Hardware performance issues impacted by the accumulation of biofilm and/or microbiologically influenced corrosion were also studied during the ECLSS development stages. Many of the tests that were performed had to take into account the unique aspects of a microgravity environment as well as the challenge of understanding how to design systems that could not be sterilized or maintained in a sterile state. This paper will summarize the work of several studies that were performed to assess the impacts and/or to minimize the effects of microorganisms in open, semi-closed and closed loop life support system. The biofilm and biodeterioration studies that were performed during the design and test periods will be presented in a future publication

On the interval zoro symmetric single step procedure IZSS2-5D for simultaneous bounding of simple polynomial zeros

A new method called the interval zoro symmetric single-step procedure IZSS2-5D which is an extension of the previous procedure IZSS2 is described. The numerical results using five test polynomials contributed to shorter CPU times and reduced number of iterations

A fast and reliable method for the delineation of tree crown outlines for the computation of crown openness values and other crown parameters

Numerous crown parameters (e.g., leaf area index, diameter, height, volume) can be obtained via the analysis of tree crown photographs. In all cases, parameter values are functions of the position of the crown outline. However, no standardized method to delineate crowns exists. To explore the effect of different outlines on tree crown descriptors, in this case crown openness (CO), and facilitate the adoption of a standard method free of user bias, we developed the program Crown Delineator that automatically delineates any outline around tree crowns following predetermined sensibility settings. We used different outlines to analyze tree CO in contrasting settings: using saplings from four species in young boreal mixedwood forests and medium-sized hybrid poplar trees from a low-density plantation. In both cases, the estimated CO increases when calculated from a looser outline, which had a strong influence on understory available light simulations using a forest simulator. These results demonstrate that the method used to trace crown outlines is an important step in the determination of CO values. We provide a much-needed computer-assisted solution to help standardize this procedure, which can also be used in many other situations in which the delineation of tree crowns is needed (e.g., competition and crown shyness)

Setting targets with interval data envelopment analysis models via wang method

Data envelopment analysis (DEA) is a mathematical programming for evaluating the relative efficiency of decision making units (DMUs). The first DEA model (CCR model) assumed for exact data, later some authors introduced the applications of DEA which the data was imprecise. In imprecise data envelopment analysis (IDEA) the data can be ordinal, interval and fuzzy. Data envelopment analysis also can be used for the future programming of organizations and the response of the different policies, which is related to the target setting and resource allocation. The existing target model that conveys performance based targets in line with the policy making scenarios was defined for exact data. In this paper we improved the model for imprecise data such as fuzzy, ordinal and interval data. To deal with imprecise data we first established an interval DEA model. We used one of the methods to convert fuzzy and ordinal data into the interval data. A numerical experiment is used to illustrate the application to our interval model