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Plant Blindness Represents the Loss of Generational Knowledge and Cultural Identity
Get PDFElders from the Turtle Mountain Band of Chippewa Indians (TMBCI) who have gathered plants within the region have seen the plant numbers reduced and species of plants disappear. Their statements of concern for the plants and their hope for increased plant diversity led to the development of the current research study. Increasing plant knowledge is vital to rebuilding and maintaining the diversity of vegetation within the forest, grassland, and wetland habitats. The present study used an online survey to assess citizens? ability to identify plants that belong in wetland, grassland, and forest habitats in the area; names of plants; learn how citizens use plant features to find and identify plants; and where citizens gained their knowledge. The survey also gathered demographic data, which allowed authors to determine trends across different demographic groups including age and ethnicity. In total, 212 participants took the survey, the majority were female and 91% classified themselves as Native American or Alaska Native. Participants were readily able to identify forest and wetland plants correctly, but struggled distinguishing grassland plants from the other habitat types. Participants in this study demonstrated a preference for natural areas maintained for humans for recreation purposes. Although more wild habitats may not be in the top three choices for the average citizen to spend time in, forest did have the fourth highest selection. Building on the knowledge that can be learned in familiar and comfortable environments as well as moving into new and wild areas will be important in helping citizens understand the value of biodiversity and conservation in the future. Beyond the local area, this information is useful to researchers and scientists working with plant blindness and seeking to understand how people see and identify plants and how this may change across demographic groups
A Biomechanical and Electromyographic Analysis of Elite Shot Putters at a Division I University
Get PDFIn effort to understand the most optimal technique for shot put throwing, researchers have investigated the individual factors of the throw that may contribute to elite level performances. Two techniques are commonly utilized by shot put throwers, known as the glide and rotational techniques. Within research studies, electromyography (EMG) and kinematic motion capture (MOCAP) analysis technologies are common data collection tools utilized by the authors. Within the dynamic shot put throwing movement, muscle activations and kinematic positions demonstrated by a thrower in motion will vary throughout the four phases of the throw, which are commonly referred to as: initiation, flight, landing, and completion phase In the current analysis of shot putters (n = 12, Males = 6, Females = 6), EMG analysis was conducted on seven muscles throughout the four phases of the throw: Rectus Femoris (RF), Biceps Femoris (BF), Gastrocnemius (GAS), Triceps (TRI), Latissimus Dorsi (LAT), External Oblique (EO), and Gluteus Medius (GM). The majority of MOCAP data variables within the current study were analyzed in the landing phase: Shoulder-Hip (S-H) Separation and Trunk Angle in the X, Y, and Z planes. Additionally, the maximum height which the thrower achieves during the flight phase, referred to as Peak Height of Center of Mass (PCOM), was analyzed using MOCAP. Significant relationships were found between thrown distance and activation of RF, EO, LAT, and GAS, with some differences existing between technique groups. For MOCAP data, significant relationships were found between thrown distance and angles of trunk inclination and trunk lateral flexion, with some differences existing between groups of technique and sex. The findings of this study are practical to track and field coaches in their understanding of the muscle activations in various phases of the throw as well as kinematic positions exhibited by athletes in the landing phase
Kisspeptins: Airway Remodeling in Asthma
Get PDFAsthma is a chronic respiratory disorder that affects people of all ages. Sex and gender disparity in asthma is recognized and suggests a modulatory role for sex steroids, particularly estrogen. However, there is a dichotomous role of estrogen in airway remodeling, making it unclear whether sex hormones are protective or detrimental in asthma and suggesting a need to explore mechanisms upstream or independent of estrogen. Kisspeptins (Kp) are a novel peptide existing upstream of sex steroids and function as a crucial regulator of puberty. Kp via KISS1R are further implicated in the sex steroid biogenesis via action on the gonadotrophins. Therefore, this research hypothesizes that kisspeptin (Kp)/KISS1R signaling serves this role, thereby regulating airway remodeling and airway hyperresponsiveness (AHR).Airway smooth muscle (ASM) is a key structural cell type that contributes to remodeling in asthma. In the first aim, I report novel data indicating that Kp and KISS1R are expressed in human airways, especially ASM, with lower expression in ASM from women compared with men and lower in patients with asthma compared with people without asthma.
My second aim discusses the functional mechanisms of Kp/KISS1R signaling on majorly proliferation, and in part ECM deposition studies. Proliferation studies show that Kp-10, mitigates PDGF-induced ASM proliferation. Pharmacological inhibition and shRNA knockdown of KISS1R increased basal ASM proliferation, which was further amplified by PDGF. The anti-proliferative effect of Kp-10 in ASM was mediated by inhibition of MAPK/ERK/Akt pathways, with altered expression of PCNA, C/EBP-?, Ki-67, cyclin D1, and cyclin E leading to cell cycle arrest at G0/G1 phase. ECM studies show that administration of Kp-10 can mitigate PDGF- and TGF?- induced increase in ECM remodeling gene and protein expression, such as collagens and fibronectins.
To corroborate my in vitro findings, I have further performed in vivo studies utilizing Kp-10 (a cleaved peptide of parent kisspeptin) in mixed allergen-induced mouse models of asthma. I found that Kp-10 was able to mitigate asthma by significantly improving airway structural, morphological and lung function parameters. Overall, I demonstrate the importance of Kp/KISS1R signaling in the ASM as a potential therapeutic avenue to blunt remodeling in asthma
Advanced Numerical Modeling in Manufacturing Processes
Get PDFIn manufacturing applications, a large number of data can be collected by experimental studies and/or sensors. This collected data is vital to improving process efficiency, scheduling maintenance activities, and predicting target variables. This dissertation explores a wide range of numerical modeling techniques that use data for manufacturing applications. Ignorance of uncertainty and the physical principle of a system are shortcomings of the existing methods. Besides, different methods are proposed to overcome the shortcomings by incorporating uncertainty and physics-based knowledge.
In the first part of this dissertation, artificial neural networks (ANNs) are applied to develop a functional relationship between input and target variables and process parameter optimization. The second part evaluates the robust response surface optimization (RRSO) to quantify different sources of uncertainty in numerical analysis. Additionally, a framework based on the Bayesian network (BN) approach is proposed to support decision-making. Due to various uncertainties, estimating interval and probability distribution are often more helpful than deterministic point value estimation. Thus, the Monte Carlo (MC) dropout-based interval prediction technique is explored in the third part of this dissertation. A conservative interval prediction technique for the linear and polynomial regression model is also developed using linear optimization.
Applications of different data-driven methods in manufacturing are useful to analyze situations, gain insights, and make essential decisions. But, the prediction by data-driven methods may be physically inconsistent. Thus, in the fourth part of this dissertation, a physics-informed machine learning (PIML) technique is proposed to incorporate physics-based knowledge with collected data for improving prediction accuracy and generating physically consistent outcomes. Each numerical analysis section is presented with case studies that involve conventional or additive manufacturing applications.
Based on various case studies carried out, it can be concluded that advanced numerical modeling methods are essential to be incorporated in manufacturing applications to gain advantages in the era of Industry 4.0 and Industry 5.0. Although the case study for the advanced numerical modeling proposed in this dissertation is only presented in manufacturing-related applications, the methods presented in this dissertation is not exhaustive to manufacturing application and can also be expanded to other data-driven engineering and system applications
Fracture Initiating Mechanism in Additively Manufactured 17-4 Stainless Steel
Get PDFAdditive manufacturing provides exceptional geometrical freedom to the designers and enables the production of parts that cannot be made through subtractive processes. Defects in additively manufactured (AM) metals are detrimental to the manufactured components. This study aims to understand the fracture initiation mechanism in as-built AM 17-4 stainless steel. Micro-computed tomography (micro-CT) analysis was conducted on the undeformed and fractured unnotched and notched specimens to characterize the defects in the as-printed specimens before and after deformation. The micro-CT analysis showed that the initial void count and volume fraction increased after the deformation indicating new void nucleation and dilation of voids. Furthermore, coalesced void colonies were noticed in the fractured specimens in the vicinity of the fracture surface. Evidence for void nucleation, dilation, and coalescence indicates ductile fracture to be the fracture initiation mechanism in AM 17-4 steel
A Meta-Analysis of Studies Addressing the Impact of GBH on Human, Animal Health and the Environment
Get PDFThe herbicide glyphosate has been tested and approved by both the FDA and the USDA, as evidenced by many published research papers, i.e., they are deemed safe for humans, animals, and the environment. However, evidence is mounting that glyphosate interferes with many metabolic processes in plants and animals, and glyphosate residues have been detected in both. The factors that influence the outcomes of previous scientific research on the potential adverse effects of GBH on human and animal health and the environment were investigated.
Using DAGs and Granger causality tests, the study found that while private and public organizations were more likely to generate research indicating that GBH was not harmful, public funding and universities were more likely to produce research indicating that GBH was hazardous. Policy actions should be guided by independent research comprised of actors from major stakeholders and research organizations
Vehicle Axle Detection from Under-Sampled Signal through Compressed-Sensing-Based Signal Recovery
Get PDFRaj Bridgelall is the program director for the Upper Great Plains Transportation Institute (UGPTI) Center for Surface Mobility Applications & Real-time Simulation environments (SMARTSeSM).In traffic data collection, sampling design should satisfy the requirements of identifying prominent pulses corresponding to vehicle axle passage. Insufficient measurement leads to signal distortion and attenuation, reducing the quality of signal pulses. This study exploits the value of under-sampled data by applying compressed sensing (CS) methods to recover signal components that are critical for vehicle axle detection. Two CS methods are investigated in this study to recover the strain signal pulses from inside-pavement instrumented sensors at high-speed traversals. The CS methods successfully recovered the signal pulses from all axles of the truck used for testing. A comparison of the measured axle distances with the reference measurements validated the effectiveness of signal recovery methods. Therefore, the CS methods have the potential of reducing the cost, energy consumption, and data storage space, and improving the data transmission efficiency in practical implementations by enabling sampling devices designed for static measurements to achieve dynamic measurements.https://www.ugpti.org/about/staff/viewbio.php?id=7
Detecting Sources of Ride Roughness by Ensemble Connected Vehicle Signals
Get PDFRaj Bridgelall is the program director for the Upper Great Plains Transportation Institute (UGPTI) Center for Surface Mobility Applications & Real-time Simulation environments (SMARTSeSM).It is expensive and impractical to scale existing methods of road condition monitoring for more frequent and network-wide coverage. Consequently, defects that increase ride roughness or can cause accidents will go undetected. This paper presents a method to enable network-wide, continuous monitoring by using low-cost GPS receivers and accelerometers on board regular vehicles. The technique leverages the large volume of sensor signals from multiple traversals of a road segment to enhance the signal quality by ensemble averaging. However, ensemble averaging requires position-repeatable signals which is not possible because of the low resolution and low accuracy of GPS receivers and the non-uniform sampling of accelerometers. This research overcame those challenges by integrating methods of interpolation, signal resampling, and correlation alignment. The experiments showed that the approach doubled the peak of the composite signal by decreasing signal misalignment by a factor of 67. The signal-to-noise ratio increased by 10 dBs after combining the signals from only 6 traversals. A probabilistic model developed to estimate a dynamic signal-detection threshold demonstrated that both the false-positive and false-negative rates approached zero after combining the signals from 15 traversals. The method will augment the efficiency of follow-up inspections by focusing resources to locations that consistently produce rough rides.North Dakota State UniversityMountain-Plains Consortium (MPC)https://www.ugpti.org/about/staff/viewbio.php?id=7
Healthcare Provider Education for Recognizing and Assisting Victims of Human Trafficking
Get PDFHuman trafficking has increasing prevalence in the United States (U.S.) with an estimated 1.6 million people trafficked at any time. Healthcare systems are one of the most critical access points for identifying and recognizing victims of human trafficking. Unfortunately, a majority of healthcare providers have never received training on human trafficking. There are approximately 835 nurse practitioners (NPs) within North Dakota (ND). With increasing prevalence of human trafficking in the U.S., education for healthcare providers must be provided to aid in the fight against human trafficking.
The purpose of this practice improvement project (PIP) was to increase NP perceived knowledge and confidence regarding human trafficking prevalence, identification, and resource utilization within ND by providing online education and resources for use within the clinical setting. This PIP consisted of two, one and a half hour educational sessions that were electronically deployed to NPs throughout ND through email, the North Dakota Nurse Practitioner annual pharmacology conference, and word of mouth. Pre- and post-surveys helped evaluate if the educational sessions improved NP perceived knowledge and confidence levels regarding human trafficking. The surveys also helped determine if NPs would utilize an online toolkit in practice.
Ten NPs completed the pre- and post-surveys. The co-investigator found that nine respondents (N=10) had increased levels of perceived knowledge regarding identifying potential human trafficking victims and eight respondents showed an increase in perceived level of confidence in managing a potential or identified victim of human trafficking. Nine participants indicated that the toolkit was comprehensive and fit the needs of their practice and a majority of respondents indicated that they would use the toolkit in the clinical setting.
Although results supported the purpose of the PIP, the co-investigator would advocate for further research to determine best modalities to increase provider human trafficking education participation in ND. Developing connections with healthcare facilities and the North Dakota Human Trafficking Task Force (NDHTTF) will also allow for continued dissemination of this education for healthcare providers. Although limitations from this PIP exist, the comprehensive education and delivery method met the needs of the NPs who participated
Technology Developments and Impacts of Connected and Autonomous Vehicles: An Overview
Get PDFRaj Bridgelall is the program director for the Upper Great Plains Transportation Institute (UGPTI) Center for Surface Mobility Applications & Real-time Simulation environments (SMARTSeSM).The scientific advancements in the vehicle and infrastructure automation industry are progressively improving nowadays to provide benefits for the end-users in terms of traffic congestion reduction, safety enhancements, stress-free travels, fuel cost savings, and smart parking, etc. The advances in connected, autonomous, and connected autonomous vehicles (CV, AV, and CAV) depend on the continuous technology developments in the advanced driving assistance systems (ADAS). A clear view of the technology developments related to the AVs will give the users insights on the evolution of the technology and predict future research needs. In this paper, firstly, a review is performed on the available ADAS technologies, their functions, and the expected benefits in the context of CVs, AVs, and CAVs such as the sensors deployed on the partial or fully automated vehicles (Radar, LiDAR, etc.), the communication systems for vehicle-to-vehicle and vehicle-to-infrastructure networking, and the adaptive and cooperative adaptive cruise control technology (ACC/CACC). Secondly, for any technologies to be applied in practical AVs related applications, this study also includes a detailed review in the state/federal guidance, legislation, and regulations toward AVs related applications. Last but not least, the impacts of CVs, AVs, and CAVs on traffic are also reviewed to evaluate the potential benefits as the AV related technologies penetrating in the market. Based on the extensive reviews in this paper, the future related research gaps in technology development and impact analysis are also discussed.U.S. Department of Transportation under the agreement of No. 69A3551747108 through MPC project No.685.https://www.ugpti.org/about/staff/viewbio.php?id=7