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Title: The copper-manganese relationship in the growth of oats, spring wheat, and alfalfa
Creator: Sparks, Lloyd Lester
Date: 1947
Collection: Electronic Theses & Dissertations

Title: Internal surface structure of human placental villi using the scanning electron microscope
Creator: Caetano, Jussara Maria
Date: 1979
Collection: Electronic Theses & Dissertations

Title: A comparison of swine marketing methods in Michigan
Creator: Sloan, Paul Marshall
Date: 1996
Collection: Electronic Theses & Dissertations

Title: The effect of supplementing a rachitogenic diet with desiccate thyroid, iodinated casein, and casein
Creator: Schechet, Isidor Arthur
Date: 1949
Collection: Electronic Theses & Dissertations

Title: Study of the variable /t/ in the English dialect of Indian immigrants in the United States
Creator: Gogate, Lakshmi Jagadish
Date: 1989
Collection: Electronic Theses & Dissertations

Title: Experimental measurements of the flow field inside of an automotive torque converter
Creator: Dalimonte, Lawrence Joseph
Date: 1998
Collection: Electronic Theses & Dissertations

Title: In vitro enzymatic digestion of milk proteins
Creator: Dimler, Steven Robert
Date: 1975
Collection: Electronic Theses & Dissertations

Title: Development of a method for deriving the correlation between free fall and shock machine drop height based on equivalent velocity change
Creator: Li, Fanfu
Date: 1988
Collection: Electronic Theses & Dissertations

Title: Equity or equality : a question of relevant inputs and norms
Creator: Fullerton, Terrence David
Date: 1978
Collection: Electronic Theses & Dissertations

Title: Inhibition of intercellular communication in rat leydig cells in vitro by xenobiotic chemicals
Creator: Hsu, Hong
Date: 1991
Collection: Electronic Theses & Dissertations

Title: A study of the potential effectiveness of ITV at the college level
Creator: Vanoy, Gabriel Robayo
Date: 1972
Collection: Electronic Theses & Dissertations

Title: Assessment of uncertainty management approaches in construction organizations
Creator: Jayaraman, Venkataramanan
Date: 2006
Collection: Electronic Theses & Dissertations

Title: Black reaction to "Bird of the Iron Feather"
Creator: Hardy, Thomas Andrew
Date: 1972
Collection: Electronic Theses & Dissertations

Title: Electrical Weed Control in Integrated Weed Management : Impacts on Vegetable Production, Weed Seed Germination, and Soil Microbial Communities
Creator: Galbraith, Christopher G.
Date: 2023
Collection: Electronic Theses & Dissertations
Description: Electrical weeding is an emerging practice for late-season weed control that is being adopted in numerous cropping systems and agricultural industries, including Michigan vegetable production. However, little scientific research has been conducted directly evaluating the performance of electrical weeding and its effects on the agroecosystem. The objectives of the research program were to investigate electrical weeding in terms of 1) weed control, 2) crop injury, 3) economic viability, as well...
Show moreElectrical weeding is an emerging practice for late-season weed control that is being adopted in numerous cropping systems and agricultural industries, including Michigan vegetable production. However, little scientific research has been conducted directly evaluating the performance of electrical weeding and its effects on the agroecosystem. The objectives of the research program were to investigate electrical weeding in terms of 1) weed control, 2) crop injury, 3) economic viability, as well as its effects on 4) weed seed germinability and 5) rhizosphere microbial communities. Field trials at Hart, MI in 2021 and 2022 investigated these research objectives in conventional carrot and organic green bean production systems. Late-season weed control methods including one hand-weeding event (HW), one electrical weeder pass (1P), two electrical weeder passes performed consecutively [2P(ST)], one pass followed by one pass after a 14-day interval [2P(14d)], two passes followed by one pass after a 14-day interval (3P), and no late-season control (NLC) were evaluated in both carrot and green beans. Early-season weed control methods [low, medium, and intensive herbicide programs, weed-free, and no early-season control (NEC)] were also included in the carrot trials in order to produce different weed densities within which to assess the performance of the late-season weed control methods. In carrot, use of the intensive herbicide program typically led to lower densities of above-canopy redroot pigweed compared to NEC or the low herbicide program. There was no difference reported in redroot pigweed control with respect to early-season weed control methods after performing the various late-season weed control methods in 2021. However, in 2022, redroot pigweed control tended to be higher for treatments that caused initially lower weed densities (weed-free and intensive herbicide program). Increasing passes above 2P(ST) did not provide any higher control of redroot pigweed in carrot, while 3P did have higher weed control in green beans. Foliar injury did not exceed 10% in carrot and 20% for green beans. Electrical weeding did not cause any internal damage to carrot root tissue or have any effect on carrot root length. Hand weeding was correlated with a yield increase in 2022, whereas none of the electrical treatments led to any difference in yield in either year that was not related to natural variation in weed pressure. For green beans, neither electrical weeding nor hand weeding led to a yield difference in both years. Hand weeding had a significantly higher cost acre-1 than all electrical treatments in both years (19.6 and 28.4 times higher than 1P in carrot and green bean, respectively) due to the greater amount of time required. The range of time and cost acre-1 observed relates to the differences in weed pressure, where fields with higher weed competition requiring longer hand and electrical weeding times. Electrical weed control was found to significantly reduce redroot pigweed seed germination in 2021 (10 to 14%) but not in 2022. However, germination did not differ between early- or late season weed control methods in either year. Electrical weeding did not generally lead to differences in NH4+ or NO3- that would indicate changes in N mineralization in the rhizosphere. Microbial biomass C was higher after 1P than NLC in 2021. Apart from this, there were no differences in microbial biomass C or N reported with respect to early-season or late-season weed control methods in either year. Informed by the experimental results, growers can make more pragmatic decisions around investing in electrical weeding equipment based on its weed control performance, risk of crop injury, and economic feasibility compared with alternative late-season control practices. As well, electrical weeding has the potential to be an effective integrated weed management solution in vegetable production for control of the weed seedbank with little to no significant impacts on rhizosphere microbial communities.
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Title: The Construct Development and Measurement of Contributive Justice
Creator: Scott, William Campbell
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Organizational justice has long since been considered multi-dimensional. However, the dimensionality of organizational justice has been stagnant in recent years, consisting primarily of distributive, procedural, interpersonal, and informational justice. When further examining the meaning of justice and fairness in organizations, it becomes apparent that these organizational justice dimensions are not capturing an important element of justice, that being the equality of opportunity. This is an...
Show moreOrganizational justice has long since been considered multi-dimensional. However, the dimensionality of organizational justice has been stagnant in recent years, consisting primarily of distributive, procedural, interpersonal, and informational justice. When further examining the meaning of justice and fairness in organizations, it becomes apparent that these organizational justice dimensions are not capturing an important element of justice, that being the equality of opportunity. This is an important absence because the opportunity to contribute in organizations will likely affect both organizational outcomes and personal outcomes outside of work. Therefore, building upon previous work, the construct of contributive justice in organizations was introduced and defined as the fairness of opportunities to contribute to core work processes. Contributive justice consists of two dimensions, the equal opportunity to engage in complex labor, and the equal opportunity to participate in decision-making processes. A measure was constructed to capture these dimensions, along with specific subdimensions. In a sample of 534 full-time employees, the results suggested that the contributive justice measure was a reliable two-factor measure that was discriminable from the other organizational justice dimensions and was positively correlated with other variables such as meaningful work, instrumental voice, inclusion, empowerment, and self-esteem. Contributive justice was also found to have incremental validity over the other organizational justice dimensions. These results suggest the importance of contributive justice as an aspect of organizational fairness and employee well-being.
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Title: Depression Detection in Social Media via Differential Text Embedding
Creator: alfadhli, Norah
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Deep learning models have shown promising results for depression detection using social media data (i.e., Twitter), but the difficulties of maintaining explainability and few-shot adaptation of models for new problems remain an open challenge. Another challenging aspect of the problem of depression detection in social media is the fact that the number of instances belonging to the depressed class are in a minority when compared to the number of instances belonging to the non-depressed class....
Show moreDeep learning models have shown promising results for depression detection using social media data (i.e., Twitter), but the difficulties of maintaining explainability and few-shot adaptation of models for new problems remain an open challenge. Another challenging aspect of the problem of depression detection in social media is the fact that the number of instances belonging to the depressed class are in a minority when compared to the number of instances belonging to the non-depressed class. This, especially, makes it harder for supervised machine learning algorithms to learn and predict depressed class instances.In this study, we proposed a simple solution to this problem by generating \textit{differential embeddings} using the Sentence BERT transformer architecture. More specifically, we proposed a few-shot model that can leverage state-of-the-art (SOTA) representation learning techniques and used it in supervised and unsupervised tasks. We constructed a small set of dysfunctional thought patterns in the embedding space, i.e., a set of clinically-backed depression symptoms. We then used SBERT embedding vectors to measure the similarities between different tweets and anchor points as a distance in the vector space, or fed them directly into the machine learning model. We assessed the capability of our approach on two different datasets. We trained supervised and unsupervised models using different approaches that were derived from Sentence-BERT and the anchor points. Results show that the proposed solution improved SBERT in both supervised and unsupervised tasks.
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Title: Filling in the Gaps : Modeling the Role of Groundwater in Lake Erie’s Nutrient Budget
Creator: Lanier, Alexis Ann
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Lake Erie is a hotspot for large harmful algal blooms, which damage human health, degrade natural habitats, and impair industries reliant on the lake. The Maumee River watershed, the largest in the Great Lakes, often acts as a major driver for these blooms, as it is the largest contributor of nutrients to the lake, mainly attributed to intense agricultural activity. Consequently, surficial transport of phosphorus and nitrogen within the Maumee River watershed has been extensively studied....
Show moreLake Erie is a hotspot for large harmful algal blooms, which damage human health, degrade natural habitats, and impair industries reliant on the lake. The Maumee River watershed, the largest in the Great Lakes, often acts as a major driver for these blooms, as it is the largest contributor of nutrients to the lake, mainly attributed to intense agricultural activity. Consequently, surficial transport of phosphorus and nitrogen within the Maumee River watershed has been extensively studied. However, there has been very little research into the role of groundwater here, especially groundwater modeling studies. Here, I evaluate the literature that has explored nutrient transport to Lake Erie, with a focus on the Maumee River watershed, and examine groundwater nutrient transport. This knowledge will inform nutrient management decisions, especially those regarding future and legacy nutrient loads. In Chapter 1, I review the current state of literature on hydrologic nutrient modeling in the Lake Erie Basin. I highlight common themes in the literature and detail prominent gaps. Specifically, I focus on the role of groundwater in nutrient modeling studies within the Maumee River watershed and recommend future directions for research. In Chapter 2, I create a spatially explicit, process-based groundwater model of the Maumee River watershed. This model allows me to quantify the contributions of groundwater in the context of total basin loading. I then quantify the role of legacy nutrient accumulation by reducing input loads in a projected future scenario. This research completes the nutrient budget by highlighting ‘hidden’ groundwater nutrient loads and informs the timescale of subsurface nutrient management.
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Title: PRECISION DIAGNOSTICS AND INNOVATIONS FOR PLANT BREEDING RESEARCH
Creator: Hugghis, Eli
Date: 2021
Collection: Electronic Theses & Dissertations
Description: Major technological advances are necessary to reach the goal of feeding our world’s growing population. To do this, there is an increasing demand within the agricultural field for rapid diagnostic tools to improve the efficiency of current methods in plant disease and DNA identification. The use of gold nanoparticles has emerged as a promising technology for a range of applications from smart agrochemical delivery systems to pathogen detection. In addition to this, advances in image...
Show moreMajor technological advances are necessary to reach the goal of feeding our world’s growing population. To do this, there is an increasing demand within the agricultural field for rapid diagnostic tools to improve the efficiency of current methods in plant disease and DNA identification. The use of gold nanoparticles has emerged as a promising technology for a range of applications from smart agrochemical delivery systems to pathogen detection. In addition to this, advances in image classification analyses have allowed machine learning approaches to become more accessible to the agricultural field. Here we present the use of gold nanoparticles (AuNPs) for the detection of transgenic gene sequences in maize and the use of machine learning algorithms for the identification and classification of Fusarium spp. infected wheat seed. AuNPs show promise in their ability to diagnose the presence of transgenic insertions in DNA samples within 10 minutes through colorimetric response. Image-based analysis with the utilization of logistic regression, support vector machines, and k-nearest neighbors were able to accurately identify and differentiate healthy and diseased wheat kernels within the testing set at an accuracy of 95-98.8%. These technologies act as rapid tools to be used by plant breeders and pathologists to improve their ability to make selection decisions efficiently and objectively.
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Title: Detection and Characterization of Rolling Contact Fatigue types of defects using Surface Acoustic Waves
Creator: Vu, Alex Tian
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Rolling Contact Fatigue or Damage (RCF/RCD) is the surface and near-surface damage thatoccurs on the rail head and wheel treads of rail cars. The damage in the rail head due to progressive cyclic loading from the contact between the wheel and the rail head can lead to formations of small cracks that can ultimately grow and join up to form a flake that falls loose, leaving behind a cavity in the running surface of the rail or turn downward to a limited depth forming a fatigue crack commonly...
Show moreRolling Contact Fatigue or Damage (RCF/RCD) is the surface and near-surface damage thatoccurs on the rail head and wheel treads of rail cars. The damage in the rail head due to progressive cyclic loading from the contact between the wheel and the rail head can lead to formations of small cracks that can ultimately grow and join up to form a flake that falls loose, leaving behind a cavity in the running surface of the rail or turn downward to a limited depth forming a fatigue crack commonly referred to as head checks and gauge corner cracks. Quantifying RCF/RCD crack depths and density in rails is important for all the railroad authority and industries to manage their grinding programs effectively and efficiently. Detecting RCF/RCD can be challenging due to the size of the cracks, which typically starts out at 2 −10μm and progressively can grow up to depths of 3mm to 5mm. It becomes impossible to characterize these early stage RCF cracks without physically destroying the sample to get to the area of interest. To gain a better understanding, the cracks that are formed from RCF/RCD can be simplified into four different types: (I) vertical/normal, (II) oblique, (III) branched, and (IV ) clustered cracks. Methods that can accurately detect and characterize these cracks non-destructively have been of high interest for the rail community. This work focuses on utilizing Surface Acoustic Waves (SAWs) for detection and characterization of RCF/RCD defects through numerical simulations the using finite element method (FEM). A transient, elastodynamics wave propagation model was used to simulate SAW propagation. Parameters such as the transmission (Tc), reflection (Rc), scattered (Ps), and time of flight(TOF) were extracted from the model and quantified to build relationships for understanding the mode conversion and interaction phenomena. The different type of defects that were modeled in FE included vertical, oblique, and branched defects. First, SAW interaction with a set of vertical, oblique and branched RCF defects were studied by quantifying Tc. The Tc values exhibit duality at certain crack angles, which makes it challenging to accurately characterize oblique RCF/RCD type of defects. Experiments have been done to validate vertical and oblique defects: the results also exhibit a duality in Tc for the oblique defects. To understand branched crack morphology, the complex crack geometry can be simplified into a series of varying angled elastic wedges, which is part of a classical problem within elastodynamics. Finally, SAW interaction with clustered cracks for two sets of densely packed RCF/RCD type of defects: a uniform cluster and a non-uniform cluster to further develop characterization techniques using Tc/Rc relationships and through signal processing methods. The impact of this work is to provide a proof of concept that the presented numerical results can be validated through experiments and become field implemented.
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Title: COMPARING WATER QUALITY VALUATION ACROSS PROBABILITY AND NON-PROBABILITY SAMPLES
Creator: Sandstrom, Kaitlynn
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This thesis compares the results of a stated preference survey administered to three samples: one non-probability sample and two non-probability samples. The probability sample is an address-based sample from the USPS postal delivery file, while the two non-probability samples are from the opt-in panels, MTurk and Qualtrics. The survey used a single binary referendum contingent valuation question with respondents voting on a water quality change at a cost to their household. To understand...
Show moreThis thesis compares the results of a stated preference survey administered to three samples: one non-probability sample and two non-probability samples. The probability sample is an address-based sample from the USPS postal delivery file, while the two non-probability samples are from the opt-in panels, MTurk and Qualtrics. The survey used a single binary referendum contingent valuation question with respondents voting on a water quality change at a cost to their household. To understand differences in economic values across samples, we compared results of logit models that relate the referendum vote to cost and each water quality index. Several tests reveal differences across samples. First, almost all parameters were significantly different across samples except for water clarity. Second, we compared marginal willingness to pay (MWTP). However, many of the MWTP estimates for individual water quality indices were not significantly different across the three sources. Third, we calculated total WTP (TWTP) for a range of non-marginal changes. The MTurk values were always significantly greater than the address sample at the 1% level, and the Qualtrics values were significantly greater than the address sample for changes up to about a 20% improvement. In summary, we find that the non-probability methods generate different valuation results than the probability-based sample, especially in terms of TWTP.
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