136879 research outputs found
Sort by
Shell Designs for Tailoring Dissolution Rates of Selective Laser Sintered Pharmaceutical Printlets
No full textWith the advent of personalized medicine, 'Just In Time' manufacturing of solid dosage pharmaceutical formulations is necessary, especially for a pediatric population that has a rapidly changing physiology. Solvent-free additive manufacturing is a promising approach that lends geometric and compositional flexibility to the process. The objective of this study is to investigate the behavior of shell-based designs, predominantly in their ability to affect dissolution rates of additively manufactured (AM) pharmaceutical pills/tablets (printlets). The primary motivation for this work lies in being able to leverage the tailorability of the AM process to control the geometric design of printlets and thus ���tune��� the eventual dissolution rates of these pills in a biological medium. For this, Selective Laser Sintering (SLS) was used to manufacture tablets using a powder mixture consisting of Carbamazepine (CBZ) as the active ingredient (drug), Kollidon VA64 as the excipient (polymer), and gold sheen as the agent with high laser absorptivity. A design of experiments was implemented to investigate the influence of compositional variance (% drug fraction) and geometrical differences (shell thickness) on the manufacturability and mechanical/pharmacokinetic performance of the printlets. Results show a general inverse relationship between structural integrity (as measured by pharmaceutical 'hardness' tests) and drug dissolution rates, as expected. Further, certain shell-breakup events were detectable via dissolution tests, as evidenced by sudden increases in dissolution magnitudes. FTIR and XRD analyses confirmed that there was no appreciable drug degradation. Altogether, this effort yielded a viable approach to 'tune' dissolution rates of certain solid dosage formulations
Non-Intrusive Wearable Accelerometry for Early Detection and Monitoring of Chronic Diseases and Mental Health Issues
No full textChronic diseases and mental health issues account for a majority of deaths worldwide. Neuropsychiatric illnesses are a considerable component of this global health burden. Therefore, there is a need for early detection and continuous monitoring of neuropsychiatric illnesses, such as stress, Parkinson's disease, bipolar disorder, and hypoglycemia in patients with diabetes. Traditional monitoring methods, such as medical history, physical examinations, and laboratory tests, have several challenges due to their invasive nature, cost, and continuous monitoring issues.
Wearable technology offers a promising alternative to the traditional methods. Accelerometers, in particular, can provide a non-intrusive, cost-effective, and easy-to-integrate solution suitable for large-scale use. Acceleration data can be combined with machine learning models to provide insights into chronic diseases and mental health issues. Despite the benefits of accelerometer sensors, the use of acceleration data alone has remained unexplored, or it has been used with other physiological data such as heart rate in current literature.
In this dissertation, I study the potential of wearable accelerometer data to detect chronic diseases and mental disorders. In Chapter 1, I review the existing literature that used acceleration data to identify chronic diseases and mental disorders. In Chapter 2, I use wrist-worn acceleration data to detect hypoglycemia in individuals with type 1 diabetes. In Chapter 3, I examine the potential of acceleration data to detect stress in college students. In Chapters 4 and 5, I further extend my findings to stress detection using deep learning models, such as convolutional neural networks (CNNs) and Long Short-Term Memory (LSTM), in two populations: PTSD patients and Intensive Care Unit (ICU) nurses.
My first research (Chapter 2) shows the potential of wearable accelerometers in detecting hand tremors associated with hypoglycemia in diabetic patients. The ensemble of random forest, support vector machines, and K-nearest neighbor models achieved a precision of 81.5% and a recall of 78.6% for hypoglycemia detection. Furthermore, the proposed models for stress detection in college students (Chapter 3) achieved an accuracy of 72.45% for the general population and 78.11% for students with similar movement behaviors. In the PTSD study (Chapter 4), adding power spectral density to raw acceleration data significantly improved the accuracy of hyperarousal detection to 78.45%. Finally, the stress detection models in ICU nurses (Chapter 5) achieved an accuracy of 68.91% using a hybrid CNN-LSTM model.
In conclusion, this Ph.D. research shows the potential of wearable accelerometer data in detecting and monitoring chronic diseases and mental health disorders. The methodologies proposed in this dissertation can be deployed on wearable devices like smartwatches and provide interventions for managing chronic diseases and mental disorders
Alternating Direction Method of Multipliers for Convex Optimization Problems with Tensorflow Using GPU Computing
No full textIn aerospace engineering, there are many high-dimensional optimization problems, including sensor optimization, control variable calculation, structure analysis, and more. Solving these high-dimension optimization problems demands substantial computational resources, leading to high computational costs. Mathematical optimization algorithms and computation methods have long been a focal point of study, aiming to reduce the complexity of high-dimensional problems and minimize computation costs. This research applies the optimization algorithm, alternating direction method of multipliers (ADMM), to multiple convex problems and provides an implementation of these algorithms in Python using TensorFlow for accelerated graphics processing unit (GPU) computing. While an existing public domain implementation of ADMM is available in MATLAB, this research strives to handle high-dimensional problems more effectively than this MATLAB implementation, which relies on central processing unit (CPU) computing. The TensorFlow implementation for GPU computing is then compared to the CPU computing implementation and the performance of the interior point method (IPM) when solving the same problem
The Role of Chondrocyte Transdifferentiation in Midpalatal Sutural Growth in Response to Altered Dietary Load
No full textThe biological mechanism for growth of the midpalatal suture is not fully understood. Chondrocyte transdifferentiation into bone cells has been shown to occur in the condylar cartilage but no study has shown this process to occur in the midpalatal suture.
Twelve Acan-CreErt2; R26RTomato;2.3 Col1a1-GFP (Acan mice) and twelve Col10a1-Cre; R26RTomato; 2.3Col1a1-GFP (Col10a1 mice) were randomly allocated into two groups, respectively; a soft and hard food diet (n=6), fed for 6 weeks and then sacrificed for data collection. One-time tamoxifen injections were given to the Acan mice at 3 weeks. MicroCT, palatal widths, chondrocyte cell proliferation, chondrogenic activity and chondrocyte transdifferentiation were all analyzed and compared between dietary loading groups.
There were no significant differences in palatal widths but a significant decrease in bone quality in the soft diet group. Histologically, there were no significant changes in chondrocyte proliferation, and aggrecan expression. However, soft food diet mice had significantly (p<0.05) lower collagen 10a1 expression, and number of chondrocyte derived bone cells, from the early to late stages of maturation, in the midpalatal suture compared to the control.
Altered dietary loading affects midpalatal sutural bone quality, chondrogenesis and chondrocyte transdifferentiation, which may explain differences in postnatal maxillary transverse development
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
Effects of Prenatal Transportation Stress on Liver Gene Expression in Brahman Calves
No full textThe liver plays an important role in physiological processes necessary for growth and development. Stress can have negative effects on the liver, which may lead to differences in phenotype and gene expression. The objectives of this study were to evaluate phenotypic traits and liver tissue gene expression in Brahman heifer and bull calves from prenatal transportation stress (PNS) and control treatment groups. One group of pregnant Brahman cows were transported for a 2-h period every 20 d (�� 5 d) from 60 to 140 d of gestation. Another group of pregnant Brahman cows were preserved as a control. A total of 32 calves, 8 heifer and 8 bull calves from the PNS and control groups, were utilized. Calves were weighed at approximately 25 d (�� 4 d) of age. The following day, calves were euthanized and liver tissues were harvested.
Phenotypic traits evaluated include birth weight, harvest weight, liver weight, pen score, and liver weight/harvest weight. Interaction of sex and treatment was not significant for any trait (P > 0.28). Sex influenced calf birth weight, harvest weight, and liver weight (P 0.41).
Controlling the false discovery rate at 0.15, there were 4, 0, 5, 42, 15, and 3 differentially expressed genes for 1) male PNS relative to control, 2) female PNS relative to control, 3) PNS male relative to female, 4) control male relative to female, 5) male relative to female, and 6) PNS relative to control comparisons, respectively. A single stress-related gene was differentially expressed across comparisons in the study: heat shock protein family A (Hsp70) member 6 (HSPA6)
Effect of Bone Segementation Data of the Maxilla and Mandible on the Accuracy of Bone-Supported Surgical Guides
No full textPurpose: The purpose of this study was to identify whether the quantity of Cone Beam Computed Tomography Scan (CBCT) image slices included in the jaw segmentation process has a significant effect on the accuracy of bone-supported guides and whether there is a minimum number of slices that can be identified as being needed to produce a surface model of the mandible and the maxilla that will yield an accurate bone-supported guide.
Materials and Methods: Dried human edentulous mandibles and maxillae, three of each, were selected. Each bone model was digitized using an intraoral scanner, and each scan was saved as a Standard Tessellation Language (STL). A bone-supported surgical guide was created on the surface scan of each jaw using a 3D implant planning software program, each serving as a reference guide for each specimen. CBCT images were then acquired once for each bone model, which were then imported into an implant planning software in digital imaging in communication in medicine (DICOM) format. A CBCT image segmentation procedure was then performed for each jaw to create a surface model of each bone with varying numbers of CBCT slices included for each segmentation: 10, 20, 30, 40, 50, 60, 70, 80, 90, and 100 slices. A surgical guide was then created on each surface model rendered from CBCT segmentations and saved as STL. Then the STL of each experimental guide and its corresponding reference guide were imported into an image analysis program and Root Mean Square (RMS) values and heat maps generated to study the internal fit deviation of each guide.
Results: There were statistically significant differences (P<0.001) between the guides created from different numbers of CBCT slices segmented. Additionally, there were statistically significant results between the mandibular and maxillary models, with the mandibular groups having a higher mean deviation (238 ��m) than the maxillary guides (230 ��m). For the mandibles combined, groups below 70 slices produced significant results, while for the maxillae combined, anything below 90 slices was significant.
Conclusions: The internal fit of bone-supported guides is affected by the number of CBCT slices used in the jaw segmentations process for rendering the bone model on which the guide is created. There is a difference in the minimum number of slices needed to create an accurate bone supported guide on the maxilla and mandible. The threshold number of slices is higher for the maxilla compared to the mandible. Although differences between the different guides were observed, the clinical implications are not as clear and should be further studied
Essays on Social Preferences
No full textThis dissertation includes three essays in the field of behavioral economics, with a special focus on social preferences using laboratory experiments. The first essay investigates the influence of patient autonomy on doctors��� performance. Using a theory-driven laboratory experiment, I find that when the patient is not able to assess the doctor���s diagnostic precision, for those patients who are not fully compliant with doctors��� advice, doctors will reduce their investment of effort in the diagnosis. This reduction is the largest among those doctors who prioritize patients��� well-being. The experiment also investigates two institutional changes, communication and reputation, which both effectively improve patients��� well-being. This study contributes to experimental health economics by uncovering the potential detrimental effect of patient autonomy on a doctor���s performance and the patient���s health status.
The second essay explores the effectiveness of two punishment strategies for addressing the free-rider problem in public goods production. By varying the timing of punishment in a public good game, we differentiate between the Post-Punishment rule, expected to induce emotional arousal, and the Pre-Punishment rule, aimed at strategic considerations with minimal emotional impact. Pupil dilation data from eye trackers support our hypotheses, revealing that the Post-Punishment rule���s success relies on negative emotions, while the Pre-Punishment rule does not. This study sheds light on the role of negative emotions in punishment efficacy and introduces a novel punishment rule that operates independently of negative emotional responses within a group.
The third essay examines the trade-offs individuals make between money, honesty, and altruism through a sender-receiver game that allows truth-telling, selfish lies, and altruistic lies. We propose a theoretical model identifying five unique types of senders. Experimental findings show prevalent yet diverse patterns of trade-offs among these three domains of concern. This research adds to the literature on lying behavior by revealing varied preferences across moral domains and a widespread
propensity for costly altruistic lies
Compositional Path Design for Graded Alloys Using Reinforcement Learning
No full textCompositionally Graded Alloys belongs to the category of Functionally Graded Materials (FGMs), distinguished by their varying spatial composition within the structure that results in material alloys of superior properties over traditional alloys. In the recent years, these compositionally graded alloys have gained significant recognition, primarily because of the advancements in the additive manufacturing techniques like Directed Energy Deposition (DED) which make the production of these alloys feasible. However, a linear gradient path of these alloys result in the inclusion of deleterious phases within the alloys micro-structure that can adversely affect the final alloy properties which may result in cracks & in the work done by Kirk et al [1] an innovative gradient path planning algorithm inspired by the state-of-the-art robotic route planning algorithms was adopted and a successful gradient path was designed in Fe-Ni-Cr material system which avoided the deleterious phases that was impacting alloy gradient when printed from 316L stainless steel to pure Cr. One significant drawback of this technique is that it limits the flexibility of material space exploration that could be done by the designer, any new composition exploration can only occur after re-configuring the path planner to compute the feasible gradient throughout the material domain and this limitation leaves designers with few alternatives. Q-Learning is a model-free Reinforcement Learning algorithm was used to solve this design space exploration problem in the ternary materials environment. An innovative method of encoding absolute position of the agent in barycentric coordinates along with the relative heading state to goal was formulated to model the system thus enabling design space exploration. The effectiveness of the proposed method was measured in a holdout dataset which produced a validation accuracy of 97%
Enhancing the Nutritional Quality of Red Leaf Lettuce by Optimizing End-of-Production Supplemental LED Lighting
No full textRed leaf lettuces (Lactuca sativa) are commercially significant leafy vegetables grown both in open fields and controlled-environment facilities such as greenhouses and indoor farms. These plants produce anthocyanins, a group of secondary metabolites that enhance their red coloration and nutritional value. However, low light levels in controlled environments can reduce the biosynthesis of anthocyanins and other key phytochemicals such as phenolics, ascorbic acid, and carotenoids. The light conditions in controlled environments could be optimized by leveraging the light-emitting diodes (LED) technology, potentially improving phytochemical accumulation. This research had two primary objectives: 1) to assess whether a higher intensity, shorter duration blue light would increase anthocyanin production more than a lower intensity, longer duration blue light, given the same total cumulative amount of supplemental blue light applied at the end of production (EOP), and 2) to compare the effectiveness of different light spectra, including red, blue, violet, ultraviolet-A (UVA), and ultraviolet-B (UVB), on enhancing anthocyanins and total phenolics in red lettuce during EOP. Our results indicated that a medium intensity of blue light applied over a medium duration resulted in the highest anthocyanin levels when the same amount of supplemental blue light was applied at varying intensities and durations. In evaluating various monochromatic light treatments, we found that supplemental violet light resulted in the highest leaf expansion and biomass, while UVB radiation (3 ��mol m^- �� s^-1 ), despite its lower intensity compared to other light spectra (60 ��mol m^- �� s^-1 ), was most effective at enhancing the accumulation of phytonutrients such as anthocyanins and phenolics but caused yield reductions. We caution that the tradeoff between enhanced crop nutritional quality and reduced crop yield must be carefully considered in commercial applications