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New Directions in Indirect Detections: Gamma-Ray Observations of Globular Clusters and Dwarf Galaxies
No full textOne of the most elusive unknowns in particle physics and astrophysics today is the fundamental nature of dark matter. It is theoretically well-motivated that dark matter is a weakly interacting massive particle (WIMP) ��� a particle lying within the GeV to TeV energy ranges that interacts very weakly with Standard Model particles. Such behavior makes dark matter extremely difficult to detect with terrestrial detectors. However, there are still many ways to probe the fundamental nature of dark matter. One such way is by searching for astrophysical signatures of dark matter annihilation. Supposing that dark matter is a WIMP which self-annihilates, we can look for inexplicable excesses of Standard Model particles from astrophysical sources. In particular, we can look for high-energy gamma-rays with energies in the range of GeV to TeV. In this thesis, I will discuss recent results on both the dark matter distributions and gamma-ray emissions of a selection of Milky Way satellites and globular clusters with an emphasis on the Sagittarius dwarf galaxy system and the Omega Centauri globular cluster. In Chapter Two, I discuss an updated dynamical analysis of the Omega Centauri globular cluster. In Chapter Three, I discuss an in-depth analysis of the gamma-ray source associated with M54, the globular cluster at the center of the Sagittarius dwarf galaxy. In Chapter Four, I discuss a follow-up paper in which we use cosmological simulations to further test the physical origins of the M54/Sagittarius source. I conclude in Chapter Five by describing several unique ways in which it may be possible to differentiate between the signal of annihilating DM and that of astrophysical background sources
Effects of Horizontal Resolution on Precipitation Simulations
No full textPrecipitation simulated by climate models in different resolutions, including the mean state of global precipitation, regional precipitation response to mesoscale SST variability, global extreme precipitation in present-day and its future projections, are investigated using both observational (reanalysis) data and global climate model simulations.
The hydrological cycle and its anticipated alterations in the face of global warming are analyzed and compared based on observations, reanalysis datasets, and climate models with different horizontal resolution. Notably, CESM-HR demonstrates a remarkably more robust oceanic water cycle than CESM-LR, a difference possibly stemming from the warmer SSTs in CESM-HR in contrast to CESM-LR. Under global warming, the impact of increased horizontal resolution on future projected changes in the hydrological cycle becomes apparent. Specifically, CESM-HR exhibits a slightly higher percentage increase in ocean-to-land water vapor transport. Therefore, it plays a role in the amplified increase in precipitation over land under climate change.
Precipitation and associated atmospheric response to mesoscale SST forcing is explored. By filtering out mesoscale SST variability, CESM-HR produces a realistic precipitation response as observed, while CESM-LR fails to capture such a response because of absent mesoscale SST variability. Further analyses in CESM-HR and ERA5 reveal a similar vertical velocity response extending up to 500hPa, suggesting a possible free-atmosphere response to mesoscale SST anomalies. Composite analysis further validates this local deep response. The poor representation of mesoscale SST variability in CESM-LR hampers model���s ability to simulate precipitation and associated circulation response.
A comprehensive overview of the impact of horizontal resolution on presenting extreme precipitation shows that, CESM-HR not only replicates the observed spatial distribution of extreme precipitation but also accurately captures the intensity across the global land. Significantly, the discernible influence of horizontal resolution on precipitation extremes predominantly manifests itself through its effect on the representation of resolved large-scale precipitation. Under global warming, extreme precipitation over most of the global land is shown to be intensified. After decomposing projected changes of extreme precipitation by moisture budget analysis in CESM-HR, we find that across most of the global land area, the projected changes are predominantly attributed to shifts in atmospheric circulation features, rather than contributions from thermodynamics
Sequence Stratigraphy and Chemostratigraphy of the Middle Cretaceous Woodbine and Eagle Ford Groups on the Southeastern Margin of the East Texas Basin and East Texas Submarine Plateau
No full textWithin the East Texas Basin (ETB), the Woodbine and Eagle Ford groups are important hydrocarbon reservoirs. However, little work was done within the southeast margin of the ETB, and adjacent East Texas Submarine Plateau (ETSP) region, to properly differentiate these units. In fact, the entire succession between the Buda Formation and Austin Groups often is referred to as the ���Eaglebine���. When defined, sandstone beds, as well as underlying mudstone beds, within it, are simply lithologically assigned to the Woodbine Group. This study takes a surface-based, or sequence stratigraphic, approach using: 1) a grid of well log cross sections, 2) x-ray fluorescence (XRF) data from cuttings and cores, and 3) previously published seismic data, to chronostratigraphically define and differentiate the Woodbine and Eagle Ford Groups across the study area.
Across much of the western portions of the study area, in Grimes and Madison Counties, a regional unconformity at the base of the Lower Eagle Ford Formation (K630sb) separates the Woodbine Group below from the Eagle Ford Group above. In this area, TOC- and Ca-rich, high-resistivity mudstone of the Lower Eagle Ford Formation unconformably overlie Al-rich, moderate resistivity mudstones of the Pepper Shale, which represent the distal downdip (basinal) equivalents of the Woodbine Group Freestone Delta.
In the western portions of the study area, in Houston and Walker Counties, a regional unconformity at the base of the Upper Eagle Ford Formation (K650sb), truncates the Lower Eagle Ford Formation near the interpreted K630 depositional shelf break. In this area, Al-rich, low-resistivity mudstone, and overlying sandstone, of the Upper Eagle Ford Formation Harris Delta, unconformably overlie Al-rich, low-resistivity mudstones, and overlying sandstones, of the Woodbine Group Freestone Delta. Fortunately, a low-resistivity marker, interpreted as regional flooding surface (K650mfs), near the base of the Upper Eagle Ford Formation can be defined, mapped, and used to differentiate strata of the Upper Eagle Ford Formation Harris Delta from the underlying Woodbine Group Freestone Delta in this area.
Finally, in the southeastern portions of the study area in Polk County, a regional unconformity at the base of the Austin Group (K720sb) truncates most, or all, of the Eagle Ford Group, and the Austin Group, or the lowermost portion of the Upper Eagle Ford Formation unconformably overlie the Woodbine Group Freestone Delta. A thick succession of the Eagle Ford Group was deposited downdip of the interpreted K630sb depositional shelf break in this region
The Development of Texneut and Spectroscopy of 10Li Using Isobaric Analog States
No full textFor at least two decades there has been uncertainty in the description of the low-level structure of 10Li, including the J �� and energy of the ground state. The properties of the system are crucial for the understanding of the evolution of nuclear structure out beyond the drip line. The 9Li + n dynamics also play an important role in the 11Li system. 11Li has been experimentally shown to be a di-neutron halo nucleus whose structure, in part, is determined by the interaction of the 9Li + n system. Reliable experimental results on 10Li are also important to benchmark predictions of contemporary nuclear structure models.
Various experiments and calculations have been conducted that target the low-lying structure of 10Li. Many of the calculations, including ab initio, were performed. Past experiments have used different reactions to populate the 10Li nucleus. Yet, no clear understanding on the J �� of 10Li has been achieved. We propose a new way to study 10Li.
With the TexAT time-projection chamber, we measured the excitation function for 9Li + p elastic scattering populating T = 2 isobaric analog states (IAS) in 10Be. The presence of the T = 2 IAS is expected in 10Be just above the 9Li+p threshold. These resonances lead to enhancements in the elastic scattering cross section at the resonance energies. Comparing the experimental data for 9Li + p elastic scattering to R-matrix calculations we hoped to assess the spin-parity assignment for the T = 2 states in 10Be, and infer the low-lying level spin-parity of 10Li
Furthermore, we have developed a neutron detector array, TexNeut. The spectroscopy of fast neutrons opens up a wide range of experiments that can be performed with rare isotope beams (RIBs) at Texas A&M University. These experiments complement those performed using charged particles. TexNeut is comprised of small modular detector bars which fit compactly together to form a thick array. TexNeut has been characterized and shown to give excellent n/�� pulse shape discrimination (PSD), fast timing, and gives a discrete position spectrum with a resolution fixed to 2 �� 2 �� 2 cm3 . The commissioning experiment of TexNeut is a measurement of 9Li(p, n) 9Be reaction to study the same IASs in 10Be as previously mentioned. The development of the detector modules, construction of the array, and detector commissioning will be discussed in this work
Advancing Iron Catalyzed Three-Component Cross-Coupling Reactions
No full textTransition metal���catalyzed cross-coupling reactions are some of the most widely used methods in chemical synthesis. Notable advantages of iron as a potentially cheaper, more abundant, and a less toxic transition metal catalyst have drawn the interest of our lab, in particular to explore the mechanism of action in three-component radical cross-couplings. In the first project, we explored the difunctionalization of unactivated olefins with alkyl halides and Grignard reagents. The reaction tolerates a wide range of sp^2 hybridized nucleophiles, alkyl halides, and unactivated olefins bearing a diverse range of functional groups.
Our second work highlights iron���s practical application in more elaborate multicomponent cross-couplings including formation and trapping of ��-boryl radicals and allyl alkyl halides for practical synthesis of cyclic fluorous compounds. Incorporating fluorine into drug scaffolds remains of utmost importance in medicinal chemistry since it generally increases lipophilicity, stability, and overall lifetime, and ~20% of drugs on the market contain at least one C-F bond. In that vein, pinacol boronate esters and boronic acids are excellent building blocks due to their reaction efficiency, low cost, and ability to be transformed into many other desired functional groups.
The final research focus is on using a mechanistic-driven approach towards designing new chiral organoiron catalytic species capable of controlling the C-C bond formation with diverse C-centered radicals. To date, there are only three examples of enantioselective iron-catalyzed cross-coupling reactions, and all are limited to the union of only two components. We reported a practical and simple protocol that uses commercially available and inexpensive iron salts in combination with chiral bisphosphine ligands to enable the regio- and enantioselective (up to 91:9) multicomponent cross-coupling of vinyl boronates, (fluoro)alkyl halides, and Grignard reagents. Preliminary mechanistic studies are consistent with rapid formation of ��-boryl radical followed by reversible radical addition to mono-aryl bisphosphine-Fe(II) and subsequent enantioselective inner-sphere reductive elimination. Overall, my research is expected to expand the field of asymmetric iron cross-couplings and have broad implications towards the synthesis of bioactive compounds via the use of alkenes to translocate alkyl radicals, modify their steric and electronic properties, and induce stereocontrol
Reinforcement Learning Model to Demystify the Limited Human Motor Learning Efficacy Due to the Sensory Mismatch
No full textVision and proprioception have fundamental sensory mismatches in delivering locational information, and such mismatches are critical factors limiting the efficacy of motor learning. However, it is still not clear how and to what extent this mismatch limits motor learning outcomes. To further the understanding of the effect of sensory mismatch on motor learning outcomes, a reinforcement learning algorithm and the simplified biomechanical elbow joint model were employed to mimic the motor learning process in a computational environment. By applying a reinforcement learning algorithm to the motor learning of elbow joint flexion task, simulation results successfully explained how visual-proprioceptive mismatch limits motor learning outcomes in terms of motor control accuracy and task completion speed. The larger the perceived angular offset between the two sensory modalities, the lower the motor control accuracy. Also, the more similar the peak reward amplitude of the two sensory modalities, the lower the motor control accuracy. In addition, simulation results suggest that insufficient exploration rate limits task completion speed, and excessive exploration rate limits motor control accuracy. Such a speed-accuracy trade-off shows that a moderate exploration rate could serve as another important factor in motor learning
Image-Based PV Soiling Quantification and Defect Detection Using Machine Learning
No full textSolar energy, a rapidly growing renewable energy source, has garnered significant global attention in recent years. Achieving high efficiency and maintaining the optimal performance of PV panels is crucial. In addition to the material properties and design of the solar cells, PV efficiency is also significantly affected by system losses and degradation.
Soiling loss, an important system loss, cannot be improved solely through design modifications and requires periodic inspection and cleaning. In this thesis study, a novel image-based method for estimating soiling loss has been proposed, utilizing key feature extraction and linear regression techniques. Two datasets were collected for this purpose: an in-lab simulation dataset and a dataset obtained from an outdoor PV testing field. The proposed method was tested with both datasets using measured soiling loss/power loss as a gold standard. The method achieved an r-squared value of 0.98 and the root mean squared error of 0.01, which showed its significant potential for cost-effective soiling monitoring purposes.
In addition to soiling loss, this study also addresses the problem of PV cell defects, which can come from degradation. A computer vision-based method is developed for detecting PV defects. The method utilized the State-of-the-Art (SOTA) object detection algorithm You Look Only Once V8 (YOLOV8), with U-net architecture and feature pyramid network to improve the accuracy. In addition, the model is compressed with Layer-Adaptive Magnitude-based Pruning to improve the computational efficiency, Additional improvement including the adoption of a better loss function inner-CIoU and the activation function MiSH. To test the proposed method, an open-source Electroluminescent PV defect dataset PVEL-AD was used. The method is compared with several existing algorithms in terms of accuracy and efficiency. The proposed method outperformed all reported work in accuracy and ranked No.2 only in efficiency. It reached mean Average Precision under IoU of 50% (mAP50) of 93.1%, and mean Average Precision under IoU from 50% to 95% (mAP50:95) of 68.7%, which improved about 8-15% comparing to the best existing algorithm. The model���s detection speed is 85.3 Frame per Second (FPS) which ranked in 2nd place among all the existing works. In addition, the model is trained on multiclass detection, the fastest method with FPS of 94.34 only trained on selected classes.
In summary, the novel methods developed in this thesis provide effective tools for estimating soiling loss and detecting defects in PV panels. With improved efficiency and accuracy, these developments have the potential to significantly improve the overall efficiency and maintenance of solar energy systems
Exploring the Career Aspirations of China���s Generation Z (Gen Z): A Basic Qualitative Study
No full textThe topic of career aspirations has attracted increasing attention from scholars and practitioners given its crucial role as one of the most useful predictors of eventual career. While ample studies were conducted to explore the career aspirations of Gen Z living in the West, few were situated in the context of the non-Western world. This critical group outnumbers Gen Z in the West. However, we have limited understanding of attracting, engaging, and retaining the emerging workforce in the non-Western world. For human resource development (HRD) field, whose core mission is developing people, limited research attention has been given to Gen Z in the non-Western world. With jobs changing and the workforce shrinking, talent competition will be fierce, employers need to prepare differently to win the global talent market. Therefore, this study aimed to explore the career aspirations of China's Gen Z members. Specifically, three research questions guided this inquiry: First, what are the career aspirations of China's Gen Z? Second, what influences the career aspirations of China's Gen Z? Third, what do China's Gen Z expect from their prospective employers?
To address these questions, I used a basic qualitative research approach. Informed by this design, I recruited 27 Gen Z participants from a comprehensive university in Eastern China. I conducted in-depth, face-to-face interviews. I analyzed 520 pages of interview data using the thematic analysis (TA) method.
This study revealed three major findings. First, the career aspirations of China's Gen Z participants could be categorized into three types: talent-based, needs-based, and value-based. Second, the shaping factors include contextual factors and personal factors. Lastly, China's Gen Z expects to work with tolerant leaders who are tolerant of mistakes in a positive environment. They favor face-to-face communication and individual tasks.
This study provided significant implications for HRD practice and research. For organizational leaders and HRD professionals, this study proposed actionable strategies that can effectively attract, engage, and retain China's Gen Z. For HRD scholars, this study opened the door to an almost uncharted territory (China's Gen Z) and outlined a new research agenda
The Role of the Science Teacher: Examination of Science Education Research and Science Teacher Education
No full textScience education has repeatedly identified the teacher as the greatest classroom level factor on student learning. Given the known variance in instructor ability and quality, a failure to consider how an instructor effect may be impacting study results draws into question the validity of study analyses and conclusions that fail to adequately conduct meaningful comparisons. The first investigation of this dissertation examined 79 studies from three leading science education journals to determine the frequency and quality of attention towards instructor differences in sampling efforts. Our findings indicate that instructor difference is rarely considered to a sufficient level within science education research, even in studies with exceedingly small sample sizes. These results are concerning for research practitioners who may be neglecting a key factor in research outcomes.
Though literature surrounding science teacher preparation programs is limited, current evidence suggests that methods courses frequently foreground instructional strategies and activities rather than a more comprehensive framework for science teaching. Potential consequences for this emphasis for preservice educators include a rejection of research-based instructional strategies, weakened instructional effectiveness, and an inability to conduct effective classroom decision-making. Study two in this dissertation analyzed 30 science methods syllabi from varying institutions and education programs to provide preliminary insight into science methods emphases. Our findings support prior claims that science methods courses are highlighting instructional strategies while neglecting the crucial role of the science teacher and teacher behaviors.
The science teacher must clearly understand their role in scaffolding student thinking away from misconceptions and towards accurate understanding of scientific ideas. The final study of this dissertation sought to triangulate findings from study two by interviewing methods instructors to understand their conceptualizations of effective science teaching, the instructional role of the science teacher, and the function of teacher behaviors within that role. Our findings suggest that methods instructors often employ vague metaphorical language when describing the instructional role of the science teacher and rarely address teacher behaviors. Syllabi were found to effectively reflect methods instructors��� conceptualizations of effective science teaching and the function of teacher behaviors but were less effective in representing methods instructors��� conceptualizations of the role of the science teacher
High-Dimensional Analysis of the Linear-Quadratic Regulator Problem Using First Order Methods on GPU
No full textThere has been a growing desire to bridge the gap between the fields of machine learning and optimal control theory. While optimal control typically operates on known dynamical systems, machine learning uses large data sets based on sampled data. The differences in input data used have made it difficult to adapt optimal control concepts to machine learning applications. For example, a major challenge in utilizing a linear-quadratic regulator (LQR) is how computationally demanding it can be for high-dimensional systems. Solving the algebraic Riccati equation (ARE)
directly is time-consuming and is typically O(n��) complexity. Posing the problem as a Linear Matrix Inequality (LMI) is even worse, this is typically solved in O(n���) time.
This thesis will examine the discrete-time LQR in the context of first order methods. These gradient-based methods provide an advantage in that they can be parallelized and run on GPUs. Multiple gradient-based algorithms will be proposed, and their performance will be compared with the traditional solutions for optimal LQR gains. The convergence rates of these gradients to the global optimum will be discussed and compared as the dimensionality of the problem increases. The ability to solve the LQR problem faster for high-dimensional systems may be useful for future large-scale optimal control problems in the aerospace field. Additionally, framing the LQR in terms of gradient-dominated policies may allow the LQR to be used in broader fields such as reinforcement learning