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RAS Ratio Impacts to Biological Phosphorus Removal and Secondary Clarifier Denitrification
No full textReturn Activated Sludge (RAS) is the cornerstone of activated sludge treatment and research presented herein demonstrates the considerable impact it has on BPR process stability. Data collected at Moscow’s full-scale and scale model Water Resource Recovery Facilities (WRRFs), as well as a process model demonstrate that increasing the RAS ratio, in turn increases the RAS nitrate load through decreased secondary clarifier denitrification and increased RAS flow containing nitrate. Impacts of the increased nitrate load are apparent within the anaerobic basins in terms of decreased phosphorus release and PHA synthesis. The results indicate that RAS rate is an important process control parameter that can be used to increase BPR process stability and success. Additionally, the BPR Operator Survey responses gathered as part of this research indicate many highly regarded WRRFs practicing BPR are beginning to use novel RAS control techniques to enhance their systems. Further discussion with the operators of these WRRFs would undoubtedly lead to valuable insight that could then be analyzed and disseminated to benefit the BPR community as a whole. The findings from this research will hopefully shine light on an otherwise largely neglected process control parameter, the RAS rate.masters, M.S., Civil Engineering -- University of Idaho - College of Graduate Studies, 2021-0
Targeted Application of Biochar in the Palouse: Modeling Hydrologic Processes in Undulating Topographies
No full textThe use of biochar as a soil amendment has gained great interest among academics, researchers, and private industry over the recent years. Biochar is a carbon rich substance that is made from thermochemical conversion of biomass. It is rich in carbon and nitrogen, two components of soil organic matter, that when introduced into the soil has shown to be beneficial to soil fertility, water retention, and crop yields. Currently biochar is cost prohibitive for large scale amendment to Palouse farmland. In this thesis, we first hypothesize the use of biochar as a precision agriculture technique. Targeted application of biochar to eroded Palouse soils would potentially allow for restoration of the soils by increasing soil health, water retention, and crop yield. To determine if biochar has potential as a precision agriculture technique, a combination of laboratory experimentation and hydrologic modeling was employed. A finite element analysis model was developed in MATLAB to simulate how moisture is redistributed in an undulating topography. Two types of biochar were amended to a standard Palouse silt loam soil, at two different concentrations, to measure how biochar affects the matric potential, hydraulic conductivity, and diffusivity of a silt loam soil. The developed model utilizes the measured soil hydraulic properties to simulate the effects of biochar on water redistribution. This model is driven by evaporation off the simulated soil profile. A novel equation for modeling evaporation/evapotranspiration was developed based on the theory of convective heat transfer, which is utilized in the model. This work then proceeded to validate the model output by comparing simulated and measured soil moisture data. The developed evaporation equation was then refined through linear regression analysis to provide a more comprehensive equation that better simulates evaporation and evapotranspiration. This model, prior to the linear regression analysis, yielded positive results. Amending Palouse silt loam soil with biochar showed an increase retention across both amendment types and concentrations. The simulation showed that more moisture was retained in and around the amendment area. This is likely due to biochar increasing the water retention of the soil in both wet and dry conditions and apparent reduction in hydraulic conductivity in saturated conditions. Finally, this work culminated in the exploration of biochar amendment on the greater hydrologic processes in the region. In the Palouse, argillic and fragipan horizons form restrictive layers in the soil profile that drive subsurface hydrology. A soil moisture routing (SMR) model, based on water balance principles, was developed to explore biochar amendment in a more complex soil profile. This model showed biochar was able to increase the ET from the profile while reducing runoff.masters, M.S., Biological & Agricultural Engineering -- University of Idaho - College of Graduate Studies, 2021-0
Rhizoctonia in Idaho Wheat, Barley and Common Bean Crops: Isolate Characterization and Potential Chemical Control
No full textRhizoctonia and associated fungi are an important group of soil-borne pathogens. Three groups of Rhizoctonia fungi are important for plant diseases, these are the multinucleate Rhizoctonia solani and Waitea circinata, as well as binucleate Rhizoctonia species (BNR). The Rhizoctonia species complex is characterized through the affinity for hyphal fusion and isolates can be assigned to anastomosis groups (AGs) based on the specific hyphal fusion affinity. The Rhizoctonia solani complex is comprised currently of thirteen known AGs, with twenty-nine subgroups. The BNR complex consist of twenty AGs with eight subgroups, including the most recently found AG W, found in China on potatoes (Solanum tuberosum) in 2015. There are five varieties that are known within Waitea circinata in the newly placed Corticacaeae family. AGs can differ in, means of dispersal, host range, fungicide sensitivity (Kataria and Gisi 1999) and aggressiveness, even to certain plant parts, such as R. solani AG 8 almost exclusively infecting the roots of potatoes (Woodhall et al. 2008). Multiple AGs have been implicated causing disease in wheat, barley and common beans. Optimum disease management based on the knowledge of the AG, or even AG subgroup present, is essential for correct diagnosis. Presently there is limited knowledge of the AGs present on wheat, barley and common bean crops in Idaho. Furthermore, there is very limited knowledge of the AGs present in Idaho and the specific diseases they cause, particularly for Southern Idaho where there is a diverse range of crops grown. Therefore, this study aimed to determine which species, AGs or subgroups are associated with Rhizoctonia diseases were present in wheat, barley and common bean crops in Idaho. 118 commercial wheat and barley fields and 102 commercial common bean fields were sampled in 2018, 2019 and 2020 resulting in 238 wheat and barley isolates and 188 common bean isolates of Rhizoctonia and related groups. Isolate identity was determined using rDNA ITS sequencing and phylogenetic analysis with known reference strains. Of the isolates collected, Waitea circinata varieties were most prevalent in wheat and barley, while AG 4 HG-II was the most prevalent in common beans. Phylogenetic placement showed three unidentified BNR isolates and five unidentified Waitea circinata varieties for wheat and barley. Phylogenetic placement for beans showed two unidentified AG 11 clades. For cereal fields, the relative incidence of Rhizoctonia solani AGs 2-1, 4 HG-II, 5, 8 and BNR AG D (I) was also determined using real-time PCR on directly extracted soil DNA samples. This determined that AG2-1 was widely present in cereal fields prior to planting. With 62 wheat and barley isolates and 61 common bean isolates, replicated glasshouse experiments were undertaken to determine their relative aggressiveness to each host. For cereals BNR AG D was the most aggressive, whilst AG 4 HG-I was most aggressive for beans. Finally, the effectiveness of various fungicides to control Rhizoctonia was evaluated in a laboratory based EC50 assay to 23 isolates, whilst for AG 11, which was determined to significantly reduce bean yields in preliminary experiments, a field and glasshouse experiment was undertaken to determine the effectiveness of serval fungicides to control the pathogen in pinto beans. These experiments indicate that inpyrfluxam and prothioconazole showed most potential to manage the pathogen.masters, M.S., Plant, Soil and Entomological Sciences -- University of Idaho - College of Graduate Studies, 2021-0
Delayed Parturition Determined by Body Condition: A State-Dependent Life History Model for Elk
No full textThe long-lived iteroparous animals are known to favor their own survival over current reproduction. Indeed, the tradeoff between future survival and investment in reproduction is central to life history theory. One means of managing this tradeoff involves the adjustment of reproductive investment post conception. We modeled one such strategy, using a series of life stage-specific equations (both deterministic and stochastic) derived either from our own empirical data or from previously published data for elk, in which a simulated population of female elk adjust the parturition date of their calves based on their body condition. We predicted that due to the reduced energetic costs of gestation relative to lactation, females would be able to enter winter in a better state and thus more likely to survive to attempt reproduction the following season. In addition, calves would be born larger and thus better able to survive through the summer. These two factors would lead to the simulated elk populations employing this state-dependent “bet-hedging” strategy to increase at a faster rate than populations for which timing of reproduction is independent of maternal condition. Our result supported the prediction that elk simulated using the bet-hedging strategy would have a higher rate of population increase. However, this was driven mostly by female over-winter survival rates. These results help provide a better understanding of the evolution of life-history traits and how they affect population dynamics.masters, M.S., Mathematics -- University of Idaho - College of Graduate Studies, 2021-1
Increasing the Mobility of a Small Modular Molten Salt Nuclear Battery
No full textThe concept of Small Modular Mobile Reactors (SMMR) has been around since thebeginning of the atomic age. In remote locations, electrical power and heat provided byconventional power systems require constant resupply of bulky fuel such as coal or diesel.These shipments often constitute the major expense of keeping a remote location operational.A small nuclear reactor eliminates the need for these shipments.However, the intense radiological source term at the end of life associated with all nuclearreactors makes mobility challenging, and makes decontamination and decommissioning veryexpensive, difficult, and time consuming. As a result, the deployment of these reactors hasbeen very limited, and many of the experimental SMMRs constructed in the 1950s and 1960shave yet to be decommissioned.For SMMRs to be practical, they must be capable of being moved relatively easily andquickly, and when they reach the end of use, they must be able to be disposed of quickly.This thesis will present a transportation and disposal analysis of an SMMR referred to asthe Molten Salt Nuclear Battery (MSnB), based on natural circulation of a molten fluoridesalt (FLiNaK), operating at 400 kW thermal for a period of 10 years. Further, it will presentthe design changes necessary to allow the reactor to be recovered from the deploymentlocation within weeks of reactor shutdown, using only over-the-road and currently availabletransportation equipment, transport the spent fuel to a location for either reprocessing orlong term storage, and dispose of all other reactor components immediately as low levelwaste.masters, M.S., Nuclear Engineering -- University of Idaho - College of Graduate Studies, 2021-1
Mobile Computer-Aided Diagnosis (CAD) for Breast Cancer Detection
No full textDeep learning-based computer-aided diagnosis systems have achieved unprecedented performance in breast cancer detection. However, most approaches are computationally intensive, and impede their broad dissemination. In this study, we propose an efficient and light-weighted multitask learning framework to simultaneously classify and segment breast tumor. Pretrained MobileNetV1 is employed as the multitask network backbone, followed by 2 branches for classification and segmentation respectively. The segmentation branch utilizes the Link-Net as decoder. The proposed approaches are evaluated using a dataset with 864 B-model breast ultrasound images. Extensive experiments demonstrate that the proposed multitask learning network not only improves the classification and segmentation accuracy, but also keeps the low latency and efficiency properties. The network achieves 86.6% Dice’s coefficient and 79% Intersection Over Union for segmentation, while 93.85 % Accuracy, 94.44% Sensitivity and 93.42 Specificity for classification. The trained network has the size of around 60 MB in Keras H5 format, and 20 MB after converting to Tensorflow Lite format. Lastly, we develop and build a mobile application in Android Studio. It launches the trained multitask learning network to do real-time breast tumor detection, with average inference time cost for classification and segmentation together being around 300 milliseconds.masters, M.S., Computer Science -- University of Idaho - College of Graduate Studies, 2021-0