The effects of algae pre-treatment on the biomethane potential of swine wastewater

Anaerobic digestion is a common method of waste treatment in the agro-industrial and municipal sectors, which utilizes microbial metabolisms that take place in an environment closed to the atmosphere to convert the organic content of wastewater into gas composed of approximately 65% methane and 35% carbon dioxide. This gas can be used as a combustible fuel for the production of heat and/or electricity. Anaerobic digestion is not typically used to treat swine waste because of its low carbon to nitrogen ratio being below the ideal range of 20-30:1. This high nitrogen content of swine waste results in ammonia inhibition of the methanogen microbial consortia, which are responsible for the production of methane. A periphytic algae cultivator (PAC) is a system in which high nutrient wastewaters; such as swine waste, can be circulated over a bed of algae. In this process, all ammonia nitrogen is taken out of solution through volatilization into the atmosphere and uptake by the algae. Also, the algae facilitate the conversion of carbon dioxide into organic compounds, increasing the carbon to nitrogen ratio of wastewater. The goal of the project was to test the hypothesis that treating swine wastewaters with a PAC results in a significant increase in biomethane potential of the waste by increasing its carbon to nitrogen ratio and overall organic content, making it a more suitable feedstock for anaerobic digestion. This is significant because, if successful, the research could contribute to the development of a more economically feasible method of utilizing and recycling nutrients in agro-industrial and municipal wastewaters for the cultivation of algae to be used as a renewable energy source. It was found in the project that algae pre-treatment of swine wastewater results in a lower ammonia concentration and higher VS and COD contents, which leads to a better conversion of the substrate into methane and a larger reductions of VS and COD contents of the wastewater resulting from anaerobic digestion

From Learning Comes Meaning: Informal Comentorship and the Second-Career Academic in Education

Informal mentoring relationships develop out of mutual identification and the fulfillment of career needs. As new faculty, we struggled to balance and decipher all the various facets inherent in the research, service, and teaching responsibilities in our new roles. This paper chronicles an informal comentorship collaboration we struck up to support our efforts as second-career academics in the field of education, seeking to navigate our way through institutional resocialization at a mid-sized Canadian university. Using a collaborative autoethnographic approach, we collected data comprising handwritten notes, tape-recorded coversations, e-mail reflections, and metareflections crafted after scheduled meetings over the course of a single academic school year. We sought to link theory with practice while using our own stories, narratives, and lived experiences as a basis for understanding our respective journeys toward social health and well-being in the academy, as well as our proficiency and competence as new scholars. From our analysis, we were able to interpret more clearly our roles, responsibilities, and needs, as well as institutional and departmental culture and norms. We offer practical implications and five lessons we have learned regarding the use of informal comentorships as an approach to managing the institutional resocialization of second-career academics

A Laboratory-Scale Study on the Production of High-Value Products from Broiler Litter Involving Solid-State Anaerobic Digestion and Mushroom Cultivation

There is a need to investigate alternate uses and treatments of broiler litter that lessen environmental impacts and decrease costs associated with its disposal. Anaerobic digestion is a biological process in which organic material is converted to a renewable fuel source. However, the substrate for anaerobic digestion often requires some form or pretreatment. Certain types of fungus have been investigated as a pretreatment for anaerobic digestion, one of which is Pleurotis ostreatus or the oyster mushroom, which also produces an edible fruiting body. Thus, this study was performed to investigate the use of broiler litter for oyster mushroom cultivation and anaerobic digestion in terms of effects their effects on broiler litter characteristics, effects of mushroom cultivation on anaerobic digestion, and the yields associated with the two treatments. It was found that the addition of 75% wheat straw was required to culture edible oyster mushrooms using broiler litter and that mushroom yields were larger than those for 100% wheat straw. Mushroom cultivation had either negative to no impacts on subsequent methane yields from anaerobic digestion. However, it was also found that lignin and soluble phosphorus contents could be reduced by mushroom cultivation while soluble nitrogen and extractives contents were increased. It was also found that nitrate concentrations were increased by mushroom cultivation, which could explain the decrease in yields from subsequent anaerobic digestion. Although methane yields were not increased by fungal pretreatment, it was concluded that the cultivation of oyster mushrooms on broiler litter could have significant impacts by adding more value to the waste material through the production of edible mushrooms and the improvement of fertilizer value. It was also concluded that there is a need for further research to explain the decrease in methane production following the fungal pretreatment, and to possibly find an additional pretreatment to account for this. Several questions were answered as to the general concept of utilizing broiler litter for both oyster mushroom cultivation and anaerobic digestion, but many other question must be answered before the findings discussed can be used to make recommendations to those involved in the poultry and mushroom industries

Peak Wind Tool for General Forecasting

The expected peak wind speed of the day is an important forecast element in the 45th Weather Squadron's (45 WS) daily 24-Hour and Weekly Planning Forecasts. The forecasts are used for ground and space launch operations at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45 WS also issues wind advisories for KSC/CCAFS when they expect wind gusts to meet or exceed 25 kt, 35 kt and 50 kt thresholds at any level from the surface to 300 ft. The 45 WS forecasters have indicated peak wind speeds are challenging to forecast, particularly in the cool season months of October - April. In Phase I of this task, the Applied Meteorology Unit (AMU) developed a tool to help the 45 WS forecast non-convective winds at KSC/CCAFS for the 24-hour period of 0800 to 0800 local time. The tool was delivered as a Microsoft Excel graphical user interface (GUI). The GUI displayed the forecast of peak wind speed, 5-minute average wind speed at the time of the peak wind, timing of the peak wind and probability the peak speed would meet or exceed 25 kt, 35 kt and 50 kt. For the current task (Phase II ), the 45 WS requested additional observations be used for the creation of the forecast equations by expanding the period of record (POR). Additional parameters were evaluated as predictors, including wind speeds between 500 ft and 3000 ft, static stability classification, Bulk Richardson Number, mixing depth, vertical wind shear, temperature inversion strength and depth and wind direction. Using a verification data set, the AMU compared the performance of the Phase I and II prediction methods. Just as in Phase I, the tool was delivered as a Microsoft Excel GUI. The 45 WS requested the tool also be available in the Meteorological Interactive Data Display System (MIDDS). The AMU first expanded the POR by two years by adding tower observations, surface observations and CCAFS (XMR) soundings for the cool season months of March 2007 to April 2009. The POR was expanded again by six years, from October 1996 to April 2002, by interpolating 1000-ft sounding data to 100-ft increments. The Phase II developmental data set included observations for the cool season months of October 1996 to February 2007. The AMU calculated 68 candidate predictors from the XMR soundings, to include 19 stability parameters, 48 wind speed parameters and one wind shear parameter. Each day in the data set was stratified by synoptic weather pattern, low-level wind direction, precipitation and Richardson Number, for a total of 60 stratification methods. Linear regression equations, using the 68 predictors and 60 stratification methods, were created for the tool's three forecast parameters: the highest peak wind speed of the day (PWSD), 5-minute average speed at the same time (A WSD), and timing of the PWSD. For PWSD and A WSD, 30 Phase II methods were selected for evaluation in the verification data set. For timing of the PWSD, 12 Phase\I methods were selected for evaluation. The verification data set contained observations for the cool season months of March 2007 to April 2009. The data set was used to compare the Phase I and II forecast methods to climatology, model forecast winds and wind advisories issued by the 45 WS. The model forecast winds were derived from the 0000 and 1200 UTC runs of the 12-km North American Mesoscale (MesoNAM) model. The forecast methods that performed the best in the verification data set were selected for the Phase II version of the tool. For PWSD and A WSD, linear regression equations based on MesoNAM forecasts performed significantly better than the Phase I and II methods. For timing of the PWSD, none of the methods performed significantly bener than climatology. The AMU then developed the Microsoft Excel and MIDDS GUls. The GUIs display the forecasts for PWSD, AWSD and the probability the PWSD will meet or exceed 25 kt, 35 kt and 50 kt. Since none of the prediction methods for timing of the PWSD performed significantly better thanlimatology, the tool no longer displays this predictand. The Excel and MIDDS GUIs display forecasts for Day-I to Day-3 and Day-I to Day-5, respectively. The Excel GUI uses MesoNAM forecasts as input, while the MIDDS GUI uses input from the MesoNAM and Global Forecast System model. Based on feedback from the 45 WS, the AMU added the daily average wind speed from 30 ft to 60 ft to the tool, which is one of the parameters in the 24-Hour and Weekly Planning Forecasts issued by the 45 WS. In addition, the AMU expanded the MIDDS GUI to include forecasts out to Day-7

Situational Lightning Climatologies for Central Florida: Phase III

This report describes work done by the Applied Meteorology Unit (AMU) to add composite soundings to the Advanced Weather Interactive Processing System (AWIPS). This allows National Weather Service (NWS) forecasters to compare the current atmospheric state with climatology. In a previous phase, the AMU created composite soundings for four rawinsonde observation stations in Florida, for each of eight flow regimes. The composite soundings were delivered to the NWS Melbourne (MLB) office for display using the NSHARP software program. NWS MLB requested that the AMU make the composite soundings available for display in AWIPS. The AMU first created a procedure to customize AWIPS so composite soundings could be displayed. A unique four-character identifier was created for each of the 32 composite soundings. The AMU wrote a Tool Command Language/Tool Kit (TcVTk) software program to convert the composite soundings from NSHARP to Network Common Data Form (NetCDF) format. The NetCDF files were then displayable by AWIPS

Anvil Forecast Tool in the Advanced Weather Interactive Processing System (AWIPS)

Launch Weather Officers (LWOs) from the 45th Weather Squadron (45 WS) and forecasters from the National Weather Service (NWS) Spaceflight Meteorology Group (SMG) have identified anvil forecasting as one of their most challenging tasks when predicting the probability of violating the Lightning Launch Commit Criteria (LLCC) (Krider et al. 2006; Space Shuttle Flight Rules (FR), NASA/JSC 2004)). As a result, the Applied Meteorology Unit (AMU) developed a tool that creates an anvil threat corridor graphic that can be overlaid on satellite imagery using the Meteorological Interactive Data Display System (MIDDS, Short and Wheeler, 2002). The tool helps forecasters estimate the locations of thunderstorm anvils at one, two, and three hours into the future. It has been used extensively in launch and landing operations by both the 45 WS and SMG. The Advanced Weather Interactive Processing System (AWIPS) is now used along with MIDDS for weather analysis and display at SMG. In Phase I of this task, SMG tasked the AMU to transition the tool from MIDDS to AWIPS (Barrett et aI., 2007). For Phase II, SMG requested the AMU make the Anvil Forecast Tool in AWIPS more configurable by creating the capability to read model gridded data from user-defined model files instead of hard-coded files. An NWS local AWIPS application called AGRID was used to accomplish this. In addition, SMG needed to be able to define the pressure levels for the model data, instead of hard-coding the bottom level as 300 mb and the top level as 150 mb. This paper describes the initial development of the Anvil Forecast Tool for MIDDS, followed by the migration of the tool to AWIPS in Phase I. It then gives a detailed presentation of the Phase II improvements to the AWIPS tool

The Effect of Step Frequency Training on a Male Runner with Patellofemoral Pain

Abstract Running is a very popular form of exercise. The most common site of injury for runners is the knee with patellofemoral pain being the most common complaint. Patellofemoral pain is described as pain around the patella that is worse with activities such as running, squatting, ascending or descending stairs, or sitting for long periods. Much of the recent work with the treatment of patellofemoral pain has involved strengthening of the hip musculature to reduce pain about the knee. However, the ability of these strengthening programs to change lower extremity mechanics or sustain long-term pain reduction has been unproven. More recently, researchers have started to examine the impact of step frequency modification on the forces encountered in the lower extremity, and specifically about the patellofemoral joint. The purpose of this study was to examine the short term effects of step frequency training in a recreational runner with PFP. Methods: This was a single-subject case study design. The subject completed a pre- and post-training assessment to determine the preferred step frequency. The subject also completed a Visual Analog Scale (VAS) and a Lower Extremity Functional Scale (LEFS). Results: After the initial evaluation, the subject completed training 2 times per week for 4 weeks using auditory feedback to increase their step frequency by 5% above their preferred step frequency. The subject experienced a decrease in pain as measured by the VAS and an increase in function as measured by the LEFS across the 4 week training. Discussion: Although the results of this case study may not be generalized, the positive findings support additional research to determine both the short and long-term effects of step frequency training on PFP

Tool for Forecasting Cool-Season Peak Winds Across Kennedy Space Center and Cape Canaveral Air Force Station (CCAFS)

Peak wind speed is important element in 24-Hour and Weekly Planning Forecasts issued by 45th Weather Squadron (45 WS). Forecasts issued for planning operations at KSC/CCAFS. 45 WS wind advisories issued for wind gusts greater than or equal to 25 kt. 35 kt and 50 kt from surface to 300 ft. AMU developed cool-season (Oct - Apr) tool to help 45 WS forecast: daily peak wind speed, 5-minute average speed at time of peak wind, and probability peak speed greater than or equal to 25 kt, 35 kt, 50 kt. AMU tool also forecasts daily average wind speed from 30 ft to 60 ft. Phase I and II tools delivered as a Microsoft Excel graphical user interface (GUI). Phase II tool also delivered as Meteorological Interactive Data Display System (MIDDS) GUI. Phase I and II forecast methods were compared to climatology, 45 WS wind advisories and North American Mesoscale model (MesoNAM) forecasts in a verification data set

Tool for Forecasting Cool-Season Peak Winds Across Kennedy Space Center and Cape Canaveral Air Force Station

The expected peak wind speed for the day is an important element in the daily morning forecast for ground and space launch operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45th Weather Squadron (45 WS) must issue forecast advisories for KSC/CCAFS when they expect peak gusts for >= 25, >= 35, and >= 50 kt thresholds at any level from the surface to 300 ft. In Phase I of this task, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a cool-season (October - April) tool to help forecast the non-convective peak wind from the surface to 300 ft at KSC/CCAFS. During the warm season, these wind speeds are rarely exceeded except during convective winds or under the influence of tropical cyclones, for which other techniques are already in use. The tool used single and multiple linear regression equations to predict the peak wind from the morning sounding. The forecaster manually entered several observed sounding parameters into a Microsoft Excel graphical user interface (GUI), and then the tool displayed the forecast peak wind speed, average wind speed at the time of the peak wind, the timing of the peak wind and the probability the peak wind will meet or exceed 35, 50 and 60 kt. The 45 WS customers later dropped the requirement for >= 60 kt wind warnings. During Phase II of this task, the AMU expanded the period of record (POR) by six years to increase the number of observations used to create the forecast equations. A large number of possible predictors were evaluated from archived soundings, including inversion depth and strength, low-level wind shear, mixing height, temperature lapse rate and winds from the surface to 3000 ft. Each day in the POR was stratified in a number of ways, such as by low-level wind direction, synoptic weather pattern, precipitation and Bulk Richardson number. The most accurate Phase II equations were then selected for an independent verification. The Phase I and II forecast methods were compared using an independent verification data set. The two methods were compared to climatology, wind warnings and advisories issued by the 45 WS, and North American Mesoscale (NAM) model (MesoNAM) forecast winds. The performance of the Phase I and II methods were similar with respect to mean absolute error. Since the Phase I data were not stratified by precipitation, this method's peak wind forecasts had a large negative bias on days with precipitation and a small positive bias on days with no precipitation. Overall, the climatology methods performed the worst while the MesoNAM performed the best. Since the MesoNAM winds were the most accurate in the comparison, the final version of the tool was based on the MesoNAM winds. The probability the peak wind will meet or exceed the warning thresholds were based on the one standard deviation error bars from the linear regression. For example, the linear regression might forecast the most likely peak speed to be 35 kt and the error bars used to calculate that the probability of >= 25 kt = 76%, the probability of >= 35 kt = 50%, and the probability of >= 50 kt = 19%. The authors have not seen this application of linear regression error bars in any other meteorological applications. Although probability forecast tools should usually be developed with logistic regression, this technique could be easily generalized to any linear regression forecast tool to estimate the probability of exceeding any desired threshold . This could be useful for previously developed linear regression forecast tools or new forecast applications where statistical analysis software to perform logistic regression is not available. The tool was delivered in two formats - a Microsoft Excel GUI and a Tool Command Language/Tool Kit (Tcl/Tk) GUI in the Meteorological Interactive Data Display System (MIDDS). The Microsoft Excel GUI reads a MesoNAM text file containing hourly forecasts from 0 to 84 hours, from one model run (00 or 12 UTC). The GUI then displays e peak wind speed, average wind speed, and the probability the peak wind will meet or exceed the 25-, 35- and 50-kt thresholds. The user can display the Day-1 through Day-3 peak wind forecasts, and separate forecasts are made for precipitation and non-precipitation days. The MIDDS GUI uses data from the NAM and Global Forecast System (GFS), instead of the MesoNAM. It can display Day-1 and Day-2 forecasts using NAM data, and Day-1 through Day-5 forecasts using GFS data. The timing of the peak wind is not displayed, since the independent verification showed that none of the forecast methods performed significantly better than climatology. The forecaster should use the climatological timing of the peak wind (2248 UTC) as a first guess and then adjust it based on the movement of weather features