<p>Adoption of conservation tillage systems is known to result in increased soil K stratification. Yet, there have been few investigations into the optimization of K management in these tillage systems, particularly regarding the placement and timing of K-based fertilizer applications. Additionally, there are many unknowns regarding the influence of tillage timing with/ without K fertilizer application. Increased availability of fertilizers containing both macro- and micro-nutrients, such as Aspire™ (which includes both K and B), has coincided with new questions about potential micronutrient deficiencies in maize (<i>Zea mays</i> L.) production. Previous research has investigated the influence of K and B individually; however, few university studies utilize multi-nutrient fertilizer sources. These knowledge gaps prompted a series of field investigations into the impacts of alternative tillage/ placement of Aspire™ on maize growth and development. Because K stratification is thought to potentially limit K availability to maize, tillage/fertilizer placement treatments involving no till (NT), fall strip-till (FST), spring strip-till (SST), and fall chisel (FC) were compared with at least two application rates of Aspire™ (ranging from 0 to 108 kg K ha^-1) from 2016 to 2019 on Indiana soils with moderate exchangeable K concentrations. Maize was grown in rotation with unfertilized soybean (<i>Glycine max </i>L) planted after strip-till.</p><p>Although tillage systems, other than no-till, were intended to decrease stratification, little change in vertical stratification for in-row samples was observed in the strip-till systems when Aspire™ was band applied at the time of strip-till (indicating fertilizer application was limited to the top several centimeters of soil). Few interactions were evident in maize response between tillage/placement and Aspire™ applications; however, superior V6-stage growth/nutrition responses to Aspire™ application occurred in fall tillage systems (FST or FC). The latter was especially true when comparing the two strip-till timings (FST and SST) at three rates. In addition to early season plant nutritional benefits, plant stature also benefited from Aspire™ across tillage/ placement systems (e.g., ~20% increase in height at V8, plus a leaf area index (LAI) gain at V14 of ~10%) reflecting on the potential to increase the source capacity of fertilized maize plants. By R1, there was little synergism between treatments in the tested parameters, indicating little difference among the tillage/ placement methods (and strip-till timing), and few immediate consequences from 50% rate reduction for Aspire™ in the strip-till systems. Although grain yield increases of 4-8% were common when Aspire™ was applied, yield component analysis showed little interaction between tillage/placement and Aspire™. Grain yields were shown to be more highly correlated and had significant relationships to earleaf K at R1, and less so with minor changes in B concentrations at R1.</p><p>Aspire™ application at the full and 50% rate commonly benefited plant nutrition and grain yield, but little synergism between Aspire™ application and tillage/ placement system was evident. Although rate reduction did not show immediate consequences to plant nutrition in either strip-till timing, longer-term research is necessary to better understand future consequences from this management practice. The lack of differences in response to strip-till timing (fall vs. spring) shows the potential for flexible timing when optimum tillage conditions are present. This research confirmed the importance of K fertilization to maize performance, but the efficient management of K requires further inquiry.</p>

This master's thesis summarizes theory on how to perform data load onto on-board computers of aircrafts. Specifically, how automated data load of Honeywell's Aspire 400 satellite data unit is done. First part of the text describes requirements and possible ways of the data load process, including standards that are applicable to this topic in the aeronautical industry. The second part describes the implementation of the data load process on the aforementioned unit.

BACKGROUND: The Aspire program is an eight-week program for troubled youths around the Canberra, Australia community that is run by former Canberran of the year and Canberra Raiders Captain Alan Tongue. The program aims to build self-esteem, develop social skills, help teach the effects actions have on others, understand how practice and hard work provide support, give purpose in life, and teach other practical, lifelong skills. During the program, Alan uses a combination of various activities including fitness, teamwork, discussion, writing, and self-reflection to help youth see their potential. PURPOSE: The purpose of this study was to examine the lasting effects of the Aspire program. METHODS: Twenty-six of last year’s participants across six schools were interviewed ten months after the program had taken place. Qualitative data was taken via group discussion, while quantitative data was taken via an eleven-question survey. RESULTS: Overall, the program received positive feedback from both the students and the youth workers in both qualitative and quantitative responses. CONCLUSION: The Aspire program had a positive effect on the participant’s behaviors, confidence, and outlook on life after ten months post-program.

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This thesis presents the development of a Sensor Tower Platform (STP) comprised of an array of Passive Infra-Red (PIR) sensors along with a classification algorithm that enables the STP to distinguish between human intrusion, animal intrusion and clutter arising from wind-blown vegetative movement in an outdoor environment. The research was motivated by the aim of exploring the potential use of wireless sensor networks (WSNs) as an early-warning system to help mitigate human-wildlife conflicts occurring at the edge of a forest. While PIR sensors are in commonplace use in indoor settings, their use in an outdoor environment is hampered by the fact that they are prone to false alarms arising from wind-blown vegetation. Every PIR sensor is made up of one or more pairs of pyroelectric pixels arranged in a plane, and the orientation of interest in this thesis is one in which this plane is a vertical plane, i.e., a plane perpendicular to the ground plane. The intersection of the Field Of View (FOV) of the PIR sensor with a second vertical plane that lies within the FOV of the PIR sensor, is called the virtual pixel array (VPA). The structure of the VPA corresponding to the plane along which intruder motion takes place determines the form of the signal generated by the PIR sensor. The STP developed in this thesis employs an array of PIR sensors designed so as to result in a VPA that makes it easier to discriminate between human and animal intrusion while keeping to a small level false alarms arising from vegetative motion. The design was carried out in iterative fashion, with each successive iteration separated by a lengthy testing phase. There were a total of 5 design iterations spanning a total period of 14 months. Given the inherent challenges involved in gathering data corresponding to animal intrusion, the testing of the SP was carried out both using real-world data and through simulation. Simulation was carried out by developing a tool that employed animation software to simulate intruder and animal motion as well as some limited models of wind-blown vegetation. More specifically, the simulation tool employed 3-dimensional models of intruder and shrub motion that were developed using the popular animation software Blender. The simulated output signal of the PIR sensor was then generated by calculating the area of the 3-dimensional intruder when projected onto the VPA of the STP. An algorithm for efficiently calculating this to a good degree of approximation was implemented in Open Graphics Library (OpenGL). The simulation tool was useful both for evaluating various competing design alternatives as well as for developing an intuition for the kind of signals the SP would generate without the need for time-consuming and challenging animal-motion data collection. Real-world data corresponding to human motion was gathered on the campus of the Indian Institute of Science (IISc), while animal data was recorded at a dog-trainer facility in Kengeri as well as the Bannerghatta Biological Park, both located in the outskirts of Bengaluru. The array of PIR sensors was designed so as to result in a VPA that had good spatial resolution. The spatial resolution capabilities of the STP permitted distinguishing between human and animal motion with good accuracy based on low-complexity, signal-energy computations. Rejecting false alarms arising from vegetative movement proved to be more challenging. While the inherent spatial resolution of the STP was very helpful, an alternative approach turned out to have much higher accuracy, although it is computationally more intensive. Under this approach, the intruder signal, either human or animal, was modelled as a chirp waveform. When the intruder moves along a circular arc surrounding the STP, the resulting signal is periodic with constant frequency. However, when the intruder moves along a more likely straight-line path, the resultant signal has a strong chirp component. Clutter signals arising from vegetative motion does not exhibit this chirp behavior and an algorithm that exploited this difference turned in a classification accuracy in excess of 97%.