UTSA Runner Research Press (Univ. of Texas at San Antonio)
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SLO-Aware Resource Management for Edge Computing Applications
No full textThe advent of Internet of Things (IoTs) promise significant data growth as devices continue to proliferate, requiring robust solutions for data management and analysis. Edge Computing and the Cloud play vital roles in processing and analyzing data generated by IoT devices. Edge Computing strategically deploys computing resources near data sources for rapid processing, while the Cloud provides centralized storage and computational power for complex analytics. Effective resource management is crucial across IoT, Edge, and Cloud environments to optimize system performance, ensure efficient utilization, and enhance reliability. This involves dynamically allocating resources to meet diverse demands, minimizing tail latency, and deploying computing resources effectively. However, poor resource management can lead to service-level objective (SLO) violations and latency issues, underscoring the importance of a cohesive strategy to orchestrate interactions and maximize the potential of distributed computing architectures.
To address this challenge, we explored three research directions. Firstly, we advocate the utilization of machine learning
and statistical inference to optimize resource allocation and reallocation within the Edge and Cloud environments, aiming
to mitigate SLO violations in applications spanning both domains. This approach encompasses horizontal and vertical scaling of resources, leveraging predictive models to accurately forecast workload demands and adapt resource allocation accordingly, thereby enhancing resource utilization and overall performance. Secondly, we introduce an algorithm leveraging spectral partitioning of application topologies and a topology-aware resource matching technique for efficient stream operator placement across distributed edge nodes. This algorithm addresses the complexities of minimizing network bottlenecks and computational resource constraints at the edge, with additional exploration into the benefits of priority-scheduling for streaming data to mitigate SLO violations. Thirdly, our collaborative research efforts concentrate on crafting lightweight deep neural network models tailored for edge devices. These endeavors contribute significantly to optimizing resource management and enhancing model efficiency within the Edge and Cloud environments, thereby facilitating the advancement of IoT applications.Computer Scienc
Painting the Picture: Using Various Perspectives to Evaluate the Effects of Active Learning on Students in Math Courses
No full textActive learning has been studied in mathematics education because of its potential effects on student learning and outcomes. Many studies have shown benefits on student learning, with some studies showing how active learning can help level the playing field for historically underrepresented student populations. However, some of the literature on active learning shows mixed results on student effects, including inequitable student outcomes. Therefore, it is important for any course implementing active learning strategies to evaluate the effects it has on students. In this thesis, several datapoints were leveraged to study the impact of active learning on student outcomes, including institutional data, pretest scores (at the beginning of the semester) and posttest scores (at the end of the semester), and student responses to a survey. These data represented different perspectives that were considered in the analyses on student outcomes. These analyses included descriptive analytics, identifying trends in the data, and performing statistical significance tests. Specifically, I looked at students’ final grades, changes in students’ majors, student performance in subsequent courses, and student attitudes on mathematics. Together, the results showed a positive trend in student outcomes as active learning strategies have been implemented in a college algebra course at a Hispanic serving institution.Mathematic
SeTe nano-alloy for the regulation of redox reaction in cancer cells
No full textNanomaterials are one of the most promising technologies of the 21st century. They are widely used in fields of science, health care, agriculture, technology, and industries. Their physical and chemical properties, such as magnetic, electrical, and optical, differentiate them from their bulk counterparts. These physical characteristics make them the focus of different scientific studies. The synthesis of nanomaterials is currently being studied due to the restrictions relevant to the translation of these materials from laboratory to fabrication. Pulse Laser Ablation in Liquids (PLAL) has been shown to be optimal. It is a versatile technique that allows the production of most nanomaterials, is low-cost and is environmentally friendly. To overcome the challenges of the oxidative effects of traditional liquid phases (water, acetone), we synthesized SeTe nanoalloys utilizing deep eutectic solvents with Ch-Cl as the hydrogen bond donor. The hydrogen bond acceptor is sugar-based to increase biocompatibility. We analyzed the size, shape, and charge of the nanomaterials to characterize the properties of SeTe. Our goal is to regulate redox activity in cancer cells by reducing the toxicity of SeTe by using Deep Eutectic Solvents. The use of this solvent as a liquid environment for pulse laser ablation was explored for the first time. Another key factor to consider ahead for the scalability of the system is the low cost of production of these deep eutectic solvents.Physics and Astronom
Assistant Principal Balancing Act: Making Sense of Social Justice Leadership in a High-Stakes Testing and Accountability Environment
No full textThis is a dataset that was originally created as a part of this author's dissertation. The dissertation is available at the following link: https://rrpress.utsa.edu/items/0d297e13-3c45-403f-bf53-1c0196e57a44The purpose of this study was to examine variation in assistant principal (AP) social justice beliefs and high-stakes accountability perceptions and explore how APs balance accountability policies while addressing social justice issues in their schools. 79 assistant principals participated in a phase 1 survey with 10 APs selected to participate in phase 2 interviews. Findings revealed divergent AP views across social justice and accountability beliefs. Findings drove recommendations for policy, practice, and future research by connecting what APs shared regarding leadership balancing actions that support social justice goals and mitigate impacts of high-stakes testing. Policy recommendations include reducing frequency of testing, developing of alternative authentic assessments, and redesigning more robust measures of school-based accountability. Recommendations for practice include continued support for APs beyond initial certification, democratic leadership practices by APs, and more professional development that address issues of marginalization. Recommendations for future research include research to investigate relationships between schools with more students with disabilities and APs’ social justice beliefs, and AP mentoring and rotational assignments. The study highlighted the complexity and ambiguity of the assistant principal position, the complicated, nuanced, and ongoing sensemaking of assistant principals, their importance at the forefront of campus leadership, and the impact these often-unnoticed school leaders have onEducational Leadership and Policy Studie
Experimental Thermal Conductivity Studies of Agar-Based Aqueous Suspensions with Lignin Magnetic Nanocomposites
No full textNanoparticle additives increase the thermal conductivity of conventional heat transfer fluids at low concentrations, which leads to improved heat transfer fluids and processes. This study investigates lignin-coated magnetic nanocomposites (lignin@Fe<sub>3</sub>O<sub>4</sub>) as a novel bio-based magnetic nanoparticle additive to enhance the thermal conductivity of aqueous-based fluids. Kraft lignin was used to encapsulate the Fe<sub>3</sub>O<sub>4</sub> nanoparticles to prevent agglomeration and oxidation of the magnetic nanoparticles. Lignin@Fe<sub>3</sub>O<sub>4</sub> nanoparticles were prepared using a pH-driven co-precipitation method with a 3:1 lignin to magnetite ratio and characterized by X-ray diffraction, FT-IR, thermogravimetric analysis, and transmission electron microscopy. The magnetic properties were characterized using a vibrating sample magnetometer. Once fully characterized, lignin@Fe<sub>3</sub>O<sub>4</sub> nanoparticles were dispersed in aqueous 0.1% <i>w</i>/<i>v</i> agar&ndash;water solutions at five different concentrations, from 0.001% <i>w</i>/<i>v</i> to 0.005% <i>w</i>/<i>v</i>. Thermal conductivity measurements were performed using the transient line heat source method at various temperatures. A maximum enhancement of 10% in thermal conductivity was achieved after adding 0.005% <i>w</i>/<i>v</i> lignin@Fe<sub>3</sub>O<sub>4</sub> to the agar-based aqueous suspension at 45 &deg;C. At room temperature (25 &deg;C), the thermal conductivity of lignin@Fe<sub>3</sub>O<sub>4</sub> and uncoated Fe<sub>3</sub>O<sub>4</sub> agar-based suspensions was characterized at varying magnetic fields from 0 to 0.04 T, which were generated using a permanent magnet. For this analysis, the thermal conductivity of lignin magnetic nanosuspensions initially increased, showing a 5% maximum peak increase after applying a 0.02 T magnetic field, followed by a decreasing thermal conductivity at higher magnetic fields up to 0.04 T. This result is attributed to induced magnetic nanoparticle aggregation under external applied magnetic fields. Overall, this work demonstrates that lignin-coated Fe<sub>3</sub>O<sub>4</sub> nanosuspension at low concentrations slightly increases the thermal conductivity of agar aqueous-based solutions, using a simple permanent magnet at room temperature or by adjusting temperature without any externally applied magnetic field.Biomedical Engineering and Chemical Engineerin
Structured Segment Rescaling with Gaussian Processes for Parameter Efficient ConvNets
No full textWe study methods to transform exiting Neural Networks (NNs) into more parameter efficient variants using a novel mechanism for structured pruning. The pruning method Structured Segment Rescaling (SSR) functions as downsampler on model dimensions and utilizes rescaling modifiers. These modifiers act on a segment, which is a logical group of identically dimensioned blocks. We study the behavior of SSR in Convolutional Neural Networks (ConvNets) and its generalization from heuristics into a well-defined framework.
Our novel structured pruning starts at model instantiation where we begin with heuristics that explore radical segment rescales. The rescales construct ConvNets with varied segments that can have new dimensions where some or most blocks and channels may be pruned away. In contrast to iterative unstructured pruning, SSR is significantly more aggressive, requires a single train cycle, and purposefully targets parameter banks to completely avoid tensor sparsity. Since sparse ten- sors require similar compute to dense tensors, our circumvention of sparsity uniquely places SSR amongst the prior work. SSR significantly reduces computation as measured in General Matrix Multiplications (GeMMs); we show that optimized SSR modifiers can achieve up to a 5X lower GeMM compute load.
The modifiers that rescale model segments in SSR are also augmented with an optimization step using a low cost Gaussian Process (GP). The GP serves to approximate the optimal modifiers using an initial set of depth and width modifiers that enumerate only extreme rescales. ConvNets constructed from these initial modifiers are named the sentinels. The sentinels coarsely explore the modifier space and provide the data bedrock for training GPs.
We utilize the CIFAR datasets and ResNets to validate our findings. SSR only requires 10<sup>1</sup> GPU hours to yield efficient new ConvNets that can facilitate edge inference. Over 10<sup>5</sup> ConvNets may be derived from any typical ConvNet and these ConvNets need only be trained if their GP predicted accuracies show that they are viable candidates for power limited devices.
Our sentinel models drop parameter count by over 65% and improve latency by 3X. We then further optimize for better modifiers with GP modeling, and show that up to 80% structured parameter reduction is possible. We observe that both depth and width modifiers can significantly reduce parameters. We also note that only depth modification decreases latency because fewer blocks means less serial computation. Lastly, applying depth and width modifiers simultaneously to segments significantly increases ConvNet compression. We demonstrate that <1% accuracy degradation and >90% parameter reduction is possible when modifiers are jointly optimized.Computer Scienc
Tuning the Superspin Dynamics in Inverse Spinel Ferrite Nanoparticle Ensembles via Indirect Cation Substitution
No full textWe used magnetic and synchrotron X-ray diffraction measurements to investigate the possibility of tuning the strength of magnetic interparticle interactions in nanoparticle ensembles via chemical manipulation. Our main result comes from temperature-resolved in-phase ac-susceptibility data collected on 8 nm average-diameter Ni<sub>0.25</sub>Zn<sub>0.75</sub>Fe<sub>2</sub>O<sub>4</sub> (Ni25) and Ni<sub>0.5</sub>Zn<sub>0.5</sub>Fe<sub>2</sub>O<sub>4</sub> (Ni50) nanoparticles at different frequencies, &chi;&prime; vs. T|<sub>f</sub>. We found that the relative peak temperature variation per frequency decade, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="sans-serif">&#981;</mi><mo>=</mo><mfrac><mrow><mo>&#8710;</mo><mi mathvariant="normal">T</mi></mrow><mrow><mi mathvariant="normal">T</mi><mo>&middot;</mo><mo>&#8710;</mo><mi mathvariant="normal">l</mi><mi mathvariant="normal">o</mi><mi mathvariant="normal">g</mi><mo>(</mo><mi mathvariant="normal">f</mi><mo>)</mo></mrow></mfrac></mrow></semantics></math></inline-formula>&mdash;a known measure of interparticle interaction strength&mdash;exhibits a four-fold increase, from &#981; = 0.04 in Ni50 to &#981; = 0.16 in Ni25. This corresponds to a fundamental change in the nanoparticles&rsquo; superspin dynamics, as proven by the fit of phenomenological models to magnetic relaxation data. Indeed, the Ni25 ensemble exhibits superparamagnetic behavior, where the temperature dependence of the superspin relaxation time, &tau;, is described in the Dorman&ndash;Bessais&ndash;Fiorani (DBF) model: <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>&tau;</mo><mfenced separators="|"><mrow><mi mathvariant="normal">T</mi></mrow></mfenced><mo>=</mo><msub><mrow><mo>&tau;</mo></mrow><mrow><mi mathvariant="normal">r</mi></mrow></msub><mrow><mrow><mi mathvariant="normal">exp</mi></mrow><mo>&#8289;</mo><mrow><mfenced separators="|"><mrow><mfrac><mrow><msub><mrow><mi mathvariant="normal">E</mi></mrow><mrow><mi mathvariant="normal">B</mi></mrow></msub><mo>+</mo><msub><mrow><mi mathvariant="normal">E</mi></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">d</mi></mrow></msub></mrow><mrow><msub><mrow><mi mathvariant="normal">k</mi></mrow><mrow><mi mathvariant="normal">B</mi></mrow></msub><mi mathvariant="normal">T</mi></mrow></mfrac></mrow></mfenced><mo>,</mo><mtext>&nbsp;</mtext></mrow></mrow></mrow></semantics></math></inline-formula> with parameters &tau;<sub>r</sub> = 4 &times; 10<sup>&minus;12</sup> s, and (E<sub>B</sub> + E<sub>ad</sub>)/k<sub>B</sub> = 1473 K. On the other hand, the nanoparticles in the Ni50 ensemble freeze collectively upon cooling in a spin-glass fashion according to a critical dynamics law: <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>&tau;</mo><mo stretchy="false">(</mo><mi mathvariant="normal">T</mi><mo stretchy="false">)</mo><mo>=</mo><mfrac><mrow><msub><mrow><mo>&tau;</mo></mrow><mrow><mn>0</mn></mrow></msub></mrow><mrow><msup><mrow><mfenced open="[" close="]" separators="|"><mrow><mfrac><mrow><mi mathvariant="normal">T</mi></mrow><mrow><msub><mrow><mi mathvariant="normal">T</mi></mrow><mrow><mi mathvariant="normal">g</mi></mrow></msub></mrow></mfrac><mo>&minus;</mo><mn>1</mn></mrow></mfenced></mrow><mrow><mi mathvariant="normal">z</mi><mi mathvariant="sans-serif">&nu;</mi></mrow></msup></mrow></mfrac></mrow></semantics></math></inline-formula>, with &tau;<sub>0</sub> = 4 &times; 10<sup>&minus;8</sup> s, T<sub>g</sub> = 145 K, and z&nu; = 7.2. Rietveld refinements against powder X-ray diffraction data reveal the structural details that underlie the observed magnetic behavior: an indirect cation replacement mechanism by which non-magnetic Zn ions are incorporated in the tetrahedral sites of the inverse spinel.Physics and Astronom
Defining the Connectivity and Dynamics of Peripheral Taste Synapses
No full textThe turnover and re-establishment of peripheral taste synapses is vital to maintain connectivity between the primary taste receptor cells (TRCs) and the gustatory neurons which relay taste information from the tongue to the brain. Despite the importance of neuron-TRC reconnection, mechanisms governing synapse assembly and the specificity of synaptic connections are largely unknown. This gap in knowledge is partially due to the lack of tools to observe these processes. Here we use ex-vivo histology methods and re-designed a novel in-vivo synapse detection technique to characterize synapse formation and maintenance in the highly dynamic taste bud environment. To accomplish this, initiating factors for the recruitment of presynaptic machinery in different populations of TRCs were probed using presynaptic markers, Bassoon and CALHM1, and gustatory neuron marker, P2X2, in normal, denervated, and re-innervated taste buds. We found that gustatory neuron proximity, rather than direct contact, drives TRCs to express and aggregate presynaptic proteins at the cell membrane. Additionally, we redesigned and employed genetically encoded GRASP (GFP Reconstitution Across Synaptic Partners) in the peripheral taste system to visualize the synaptic connections between gustatory neurons and TRCs in-vivo. Characterization of GRASP in the taste system confirmed that synapses between TRCs and gustatory neurons are marked by GRASP signal in-vivo and ex-vivo, providing a new method to track taste synapses over time. Together, these findings reveal new insights into the mechanisms driving synaptogenesis and provide a reliable method to study synapse dynamics in the highly plastic taste bud environment.Neuroscience, Developmental and Regenerative Biolog
Non-Debye Behavior of the Néel and Brown Relaxation in Interacting Magnetic Nanoparticle Ensembles
Get PDFWe used ac-susceptibility measurements to study the superspin relaxation in Fe<sub>3</sub>O<sub>4</sub>/Isopar M nanomagnetic fluids of different concentrations. Temperature-resolved data collected at different frequencies, &chi;&Prime; vs. T|<sub>f</sub>, reveal magnetic events both below and above the freezing point of the carrier fluid (T<sub>F</sub> = 197 K): &chi;&Prime; shows peaks at temperatures T<sub>p1</sub> and T<sub>p2</sub> around 75 K and 225 K, respectively. Below T<sub>F</sub>, the N&eacute;el mechanism is entirely responsible for the superspin relaxation (as the carrier fluid is frozen), and we found that the temperature dependence of the relaxation time, &tau;<sub>N</sub>(T<sub>p1</sub>), is well described by the Dorman–Bessais–Fiorani (DBF) model: <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi mathvariant="sans-serif">&tau;</mi></mrow><mrow><mi>N</mi></mrow></msub><mfenced separators="|"><mrow><mi mathvariant="normal">T</mi></mrow></mfenced><mo>=</mo><msub><mrow><mi mathvariant="sans-serif">&tau;</mi></mrow><mrow><mi mathvariant="normal">r</mi></mrow></msub><mrow><mrow><mi mathvariant="normal">exp</mi></mrow><mo>&#8289;</mo><mrow><mfenced separators="|"><mrow><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><msub><mrow><mi mathvariant="normal">E</mi></mrow><mrow><mi mathvariant="normal">B</mi></mrow></msub><mo>+</mo><msub><mrow><mi mathvariant="normal">E</mi></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">d</mi></mrow></msub></mrow><mrow><msub><mrow><mi mathvariant="normal">k</mi></mrow><mrow><mi mathvariant="normal">B</mi></mrow></msub><mo>&nbsp;</mo><mi mathvariant="normal">T</mi></mrow></mfrac></mstyle></mrow></mfenced></mrow></mrow></mrow></semantics></math></inline-formula>. Above T<sub>F</sub>, both the internal (Néel) and the Brownian superspin relaxation mechanisms are active. Yet, we found evidence that the effective relaxation times, &tau;<sub>eff</sub>, corresponding to the T<sub>p2</sub> peaks observed in the denser samples <i>do not</i> follow the typical Debye behavior described by the Rosensweig formula <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><mn>1</mn></mrow><mrow><msub><mrow><mi>&tau;</mi></mrow><mrow><mi>e</mi><mi>f</mi><mi>f</mi></mrow></msub></mrow></mfrac></mstyle><mo>=</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><mn>1</mn></mrow><mrow><msub><mrow><mi>&tau;</mi></mrow><mrow><mi>N</mi></mrow></msub></mrow></mfrac></mstyle><mo>+</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><mn>1</mn></mrow><mrow><msub><mrow><mi>&tau;</mi></mrow><mrow><mi>B</mi></mrow></msub></mrow></mfrac></mstyle></mrow></semantics></math></inline-formula>. First, &tau;<sub>eff</sub> is 5 &times; 10<sup>&minus;5</sup> s at 225 K, almost three orders of magnitude more that its Néel counterpart, &tau;<sub>N</sub>~8 &times; 10<sup>&minus;8</sup> s, estimated by extrapolating the above-mentioned DBF analysis. Thus, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><mn>1</mn></mrow><mrow><msub><mrow><mi>&tau;</mi></mrow><mrow><mi>N</mi></mrow></msub></mrow></mfrac></mstyle><mo>&#8811;</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><mn>1</mn></mrow><mrow><msub><mrow><mi>&tau;</mi></mrow><mrow><mi>e</mi><mi>f</mi><mi>f</mi></mrow></msub></mrow></mfrac></mstyle></mrow></semantics></math></inline-formula>, which is clearly not consistent with the Rosensweig formula. Second, the observed temperature dependence of the effective relaxation time, &tau;<sub>eff</sub>(T<sub>p2</sub>), is excellently described by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi>&tau;</mi></mrow><mrow><mi>B</mi></mrow><mrow><mo>&minus;</mo><mn>1</mn></mrow></msubsup><mfenced separators="|"><mrow><mi mathvariant="normal">T</mi></mrow></mfenced><mo>=</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><mi>T</mi></mrow><mrow><msub><mrow><mi>&gamma;</mi></mrow><mrow><mn>0</mn></mrow></msub></mrow></mfrac></mstyle><mrow><mrow><mi mathvariant="normal">exp</mi></mrow><mo>&#8289;</mo><mrow><mfenced open="[" close="]" separators="|"><mrow><mo>&minus;</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><msup><mi mathvariant="normal">E</mi><mo>&prime;</mo></msup></mrow><mrow><msub><mrow><mi mathvariant="normal">k</mi></mrow><mrow><mi mathvariant="normal">B</mi></mrow></msub><mfenced separators="|"><mrow><mi mathvariant="normal">T</mi><mo>&minus;</mo><msup><mrow><msub><mrow><mi>T</mi></mrow><mrow><mn>0</mn></mrow></msub></mrow><mo>&prime;</mo></msup></mrow></mfenced></mrow></mfrac></mstyle></mrow></mfenced></mrow></mrow></mrow></semantics></math></inline-formula>, a model solely based on the hydrodynamic Brown relaxation, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi mathvariant="sans-serif">&tau;</mi></mrow><mrow><mi>B</mi></mrow></msub><mo stretchy="false">(</mo><mi mathvariant="normal">T</mi><mo stretchy="false">)</mo><mo>=</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><mn>3</mn><mi>&eta;</mi><mfenced separators="|"><mrow><mi>T</mi></mrow></mfenced><msub><mrow><mi>V</mi></mrow><mrow><mi>H</mi></mrow></msub></mrow><mrow><msub><mrow><mi>k</mi></mrow><mrow><mi>B</mi></mrow></msub><mi>T</mi></mrow></mfrac></mstyle></mrow></semantics></math></inline-formula>, combined with an activation law for the temperature variation of the viscosity, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi mathvariant="sans-serif">&eta;</mi><mfenced separators="|"><mrow><mi mathvariant="normal">T</mi></mrow></mfenced><mo>=</mo><msub><mrow><mi mathvariant="sans-serif">&eta;</mi></mrow><mrow><mn>0</mn></mrow></msub><mrow><mrow><mi mathvariant="normal">exp</mi></mrow><mo>&#8289;</mo><mrow><mfenced open="[" close="]" separators="|"><mrow><msup><mrow><mi>E</mi></mrow><mrow><mo>&prime;</mo></mrow></msup><mo>/</mo><msub><mrow><mi>k</mi></mrow><mrow><mi>B</mi></mrow></msub><mo>(</mo><mi>T</mi><mo>&minus;</mo><msup><mrow><msub><mrow><mi>T</mi></mrow><mrow><mn>0</mn></mrow></msub></mrow><mo>&prime;</mo></msup></mrow></mfenced></mrow></mrow></mrow></semantics></math></inline-formula>. The best fit yields <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>&gamma;</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>=</mo><mstyle scriptlevel="0" displaystyle="true"><mfrac><mrow><mn>3</mn><mi>&eta;</mi><msub><mrow><mi>V</mi></mrow><mrow><mi>H</mi></mrow></msub></mrow><mrow><msub><mrow><mi>k</mi></mrow><mrow><mi>B</mi></mrow></msub></mrow></mfrac></mstyle></mrow></semantics></math></inline-formula> = 1.6 &times; 10<sup>&minus;5</sup> s&middot;K, E&prime;/k<sub>B</sub> = 312 K, and T<sub>0</sub>&prime; = 178 K. Finally, the higher temperature T<sub>p2</sub> peaks vanish in the more diluted samples (&delta; &le; 0.02). This indicates that the formation of larger hydrodynamic particles via aggregation, which is responsible for the observed Brownian relaxation in dense samples, is inhibited by dilution. Our findings, corroborating previous results from Monte Carlo calculations, are important because they might lead to new strategies to synthesize functional magnetic ferrofluids for biomedical applications.Physics and Astronom
My Mind Turns Your Life Into Folklore: A Rhetorical Analysis of Identification in Taylor Swift's folklore Album
No full textOver the course of her career, Taylor Swift has moved effortlessly across genres and continues to innovate the music industry. She recently became the only artist in history to win Album of the Year at the Grammy Awards four times, and she shows no signs of slowing down. Through all her accomplishments, there is one group of people she never forgets to acknowledge: her fans. Musicians are a unique type of celebrity when it comes to connecting with their fans due to their vulnerability and media presence as purely themselves. The rhetoric of identification plays a crucial role in creating a strong fandom culture and in strengthening parasocial relationships between fans and musicians. Through generative rhetorical criticism, this project sought to understand how identification is accomplished in the lyrics of Taylor Swift's <i>folklore</i> album. Major themes found within the album are fear, sorrow, innocence, reflection, and perseverance. For each theme I provide my interpretation of lyrics that best exemplify the theme, consider how the interpretations might resonate with other listeners, and how they resonate with me as a means to understand how identification is woven into the lyrics. Through this analysis, I found that Taylor's use of narrative as a rhetorical device is the driving force in <i>folklore</i>'s lyrics that fosters identification.Communicatio