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COMPARISONS OF MAJOR HEALTHCARE SYSTEMS IN EUROPE AND THE UNITED STATES THROUGH THE 20TH AND 21ST CENTURY
No full textThis paper examines how healthcare systems have been created in four countries, the USSR (and then Russia post 1991), Poland, Germany and the United States, how they changed throughout the decades, their efficacy, as well as focusing on aspects such as funding, budget allocation, care quality, and the overall structure of the system. These cases were chosen to give a contrast between the development and subsequent abandonment of the Soviet Semashko system which proposed an entirely state ran and centralized program that was imposed on other Soviet Bloc Countries and the United States’ decentralized employer led health insurance system. Germany was chosen both due to it having one of the oldest health insurance programs, but also because it was split during the cold war and the system that was imposed on East Germany was not the same as the system used by the USSR. Findings reveal that the Soviet Semashko system often had major core contradicting flaws between their ideological rhetoric surrounding healthcare and the actual allocation of resources it received, while Germany’s Bismarkian model achieved a high rate of successful outcomes while being able to minimize costs
THE USE OF ARTIFICIAL INTELLIGENCE IN RADAR DATA PROCESSING
No full textAccurate retrieval and classification of precipitation are essential for advancing hydrologic modeling, weather forecasting, and climate monitoring. This dissertation presents two methodologies that integrate artificial intelligence with multi-frequency and polarimetric radar observations to enhance radar-based precipitation processing.The first component focuses on retrieving drop size distribution (DSD) parameters using dual-polarization radar at S- and C-band frequencies. An optimization framework combining particle swarm optimization (PSO) and T-Matrix scattering simulations is developed to estimate DSD parameters from radar observations. Validation with a network of OTT PARSIVEL disdrometers and radar data from a unique observational configuration in Taiwan shows a 30% improvement in quantitative precipitation estimation (QPE) accuracy over traditional techniques.The second component introduces a deep learning classification system using vertical profiles of reflectivity from the Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR). A deep neural network (DNN) classifies hydrometeors into stratiform, convective, hail, and snow classes. Compared to the GPM DPR Version 07 data product, the DNN improves precision from 0.70 to 0.87 and recall from 0.67 to 0.88.These results demonstrate that artificial intelligence can significantly improve both ground-based and satellite-based radar data processing, enabling more accurate and efficient precipitation retrieval and classification
WHEN CLOSENESS BACKFIRES: INCLUSION OF OTHER IN THE SELF AND BIDIRECTIONAL UNETHICAL BEHAVIOR IN SUPERVISOR-TEAM RELATIONSHIPS
No full textThis dissertation examines how psychological closeness between supervisors and teams influences bidirectional unethical behavior in South Korean police organizations. Drawing on self-expansion theory and social identity theory, I investigate the relationship between “Inclusion of Other in the Self” (IOS) congruence, affective commitment, and unethical behavior benefiting relationship counterparts. Using polynomial regression and response surface methodology with data from 275 police officers in 92 teams, I found results that both support and challenge theoretical expectations. Contrary to predictions, certain forms of perceptual misalignment enhanced rather than undermined affective commitment, particularly when team members perceived greater inclusion than supervisors reciprocated. As hypothesized, the association between IOS congruence and affective commitment was stronger at higher levels of mutual inclusion, and affective commitment mediated the relationship between IOS patterns and unethical behavior. The multi-perspective measurement approach revealed significant differences across rating perspectives, highlighting complex perceptual dynamics in ethical decision-making. These findings demonstrate that close supervisor-team relationships can redefine ethical boundaries through expanded self-interest, while challenging conventional assumptions about perceptual congruence in hierarchical relationships. This research contributes to organizational ethics literature by integrating self-expansion and social identity theories, introducing a bidirectional ethical framework, establishing IOS congruence as an antecedent of unethical behavior, and identifying affective commitment as a key mediating mechanism. These findings suggest organizations should implement targeted interventions based on relationship patterns to maintain benefits while mitigating ethical risks
SELECTIVE RECOVERY OF RARE EARTH ELEMENTS FROM ACID MINE DRAINAGE USING INDIGENOUS BACTERIA IN BIOELECTROCHEMICAL SYSTEMS
No full textRare earth elements (REEs) are essential components in many modern technologies. The heterogeneous global REE reserves, increasing demand, and environmental concerns associated with traditional methods from primary resources have driven researchers to strive for sustainable REE extraction techniques from secondary and low-grade non-conventional sources. This study aims to sustainably extract REEs from acid mine drainage (AMD)—a low-grade secondary source—through the attached growth of indigenous species in a two-chamber bioelectrochemical system (BES) under aerobic and anaerobic conditions. In the first study, AMD was used as a seed to cultivate an indigenous bacterial consortium under aerobic conditions. A two-chamber BES was employed to treat the AMD, where PAN-based carbon fiber brushes (CFBs) served as biocathodes, graphite rods as anodes, synthetic wastewater as the anolyte, and raw AMD as the catholyte. A 300 Ω external resistor and an anion exchange membrane (AEM) were used to facilitate electrical connection and ionic separation between the two chambers, respectively. Nitric acid treatment followed by coating with lab-synthesized Fe3O4 nanoparticles increased surface roughness and enhanced the biofilm-holding capacity of the CFBs. Lysinibacillus fusiformis and Bacillus spp. were the dominant bacterial species on the biocathodes before and after BES operation. A 5-day BES treatment significantly increased the pH of AMD in the cathode chamber, resulting in the selective bioprecipitation of REEs over other critical metals. The use of surface-modified CFBs, a greater number of biocathodes, an initial pH increase of the raw AMD, and multiple stripping cycles were all positively correlated with REE extraction efficiency. A three-electrode setup with three stripping cycles achieved REE extraction efficiencies of 68.06 ± 2.44% for total REEs, 69.31 ± 2.30% for light REEs, and 66.16 ± 2.64% for heavy REEs. Active attached growth and electrical connection between the two chambers were essential for REE recovery under aerobic conditions, as control tests showed minimal extraction when either factor was missing. Approximately 15% of the other major metals were extracted by the system, while ~ 60% remained in the catholyte after the BES operation, encompassing considerable selectivity towards REEs. Increasing the solution pH led to a higher precipitation percentage but reduced the overall purity of the final REE product, as indicated in precipitation studies using 10% (w/v) oxalic acid. A solution pH of 4.0 precipitated ~ 55% of REEs from the REE-loaded liquor but also co-precipitated large amounts of Fe and Cu, suggesting the need for further purification steps. In contrast, a lower pH range (1.0-2.0), combined with a higher initial REE concentration, may lead to improved recovery and product purity. In the second study, indigenous anaerobic and sulfate-reducing bacterial species were cultivated in liquid culture media from AMD. Both a sequential extraction technique—employing initial pH enhancement and REE fractionation in an aerobic BES, followed by REE recovery in anaerobic bioreactors—and a completely anaerobic BES were used for REE extraction. Improved attached growth formation was observed in SEM analysis following nitric acid treatment of the hydrophobic, non-polar CFB surface. The presence of Desulfosporosinus auripigmenti and Clostridium subterminale in the attached growth before and after treatment confirmed the establishment of anaerobic conditions and active sulfate-reducing metabolism. A 5-day treatment in the aerobic BES resulted in the extraction of ~ 33% of TREEs from AMD with excellent selectivity. Subsequent treatment of the catholyte with anaerobic biofilm in the bioreactors resulted in an additional ~ 47% of TREEs extraction, leading to a combined efficiency of 80.67 ± 5.88% for TREEs, 79.95 ± 5.98% for LREEs, and 81.79 ± 5.72% for HREEs. Initial pH adjustment to 3.0 helped reduce interference from other metals, and the completely anaerobic BES achieved nearly 100% removal of REEs from raw AMD with excellent selectivity. A single stripping step recovered only ~ 40% of TREEs from the attached biomass, suggesting the need for multiple stripping cycles and extended contact time to improve recovery. Subsequent precipitation using 10% (w/v) oxalic acid at an optimized pH range of 1.0-2.0 can further enhance the separation of REEs from the REE-enriched liquor. Based on the findings from both aerobic and anaerobic systems, this study demonstrates the technical feasibility and selectivity of using indigenous microbial consortia and surface-modified biocathodes for sustainable REE recovery from AMD. The integration of sequential extraction and optimized pH control significantly enhances REE fractionation while minimizing the co-extraction of competing metals. These results underscore the potential for scaling up bioelectrochemical approaches using flow-through reactor designs and advanced electrode modifications to support environmentally responsible REE recovery technologies
Surface-Stabilized Laser-induced Breakdown Spectroscopy (SS-LIBS) for Sensitive Biomarker Detection Using a Particle-based Assay Technique
No full textLaser-Induced Breakdown Spectroscopy is a powerful analytical technique for elemental analysis that uses a high-energy laser pulse to ablate a sample surface, creating a plasma plume. As the plasma cools, excited atoms and ions emit characteristic photons, producing emission spectra that are unique for each element. However, LIBS analysis of powdered samples, especially those composed of micro- and nano-sized particles, often suffers from poor reproducibility due to particle loss during the ablation process. This study investigates how thin epoxy coating can enhance particle adhesion and improve the LIBS reproducibility. By varying the epoxy-to-ethanol ratio, we evaluated thicknesses of coating to produce a stable sample matrix while minimizing LIBS signal attenuation. Our results demonstrate that applying a 1:750 (v/v) epoxy-to-ethanol solution applied in a 1 µL significantly improved the sensitivity and reproducibility of LIBS for both micron- and submicron-sized particles. This SS-LIBS method offers a simple yet effective approach to improving the reproducibility of LIBS-based analysis of particles containing samples, with potential application in materials characterization and biomedical diagnostics, particularly biomarker detections
Reduced-rank spatio-temporal models
No full textTime and space are two of the most significant and complex dimensions underlying real-world phenomena. Although we often overlook them in daily reasoning, they are crucial for understanding real-world circumstances such as crime rate patterns in neighborhoods, climate shifts, disease outbreaks, and urban traffic. To model these processes accurately, it is essential to consider their spatial and temporal dependencies simultaneously. Spatio-temporal models provide this framework by incorporating spatial structure with temporal evolution. allowing for a more comprehensive understanding of how processes evolve across both dimensions. Unlike time series and spatial models, spatio-temporal models capture both cross-sectional dependencies and dynamic trends over time.Many existing models use spatial weight matrices to parameterize the coefficient matrices. But construction of these matrices requires more information about different locations/ units, can be challenging in high-dimensional settings, and may not reflect true underlying relationships. To address these limitations, a novel approach that directly captures spatial and temporal dependencies through a low-rank structure on coefficient matrices is proposed here.In comparison to vector autoregressive (VAR) models, spatio-temporal models allow the number of cross-sectional units (locations) to diverge. This flexibility leads to the curse of dimensionality and the failure of standard estimation techniques due to the complex, nonlinear structure in the coefficients. To estimate model parameters, a quasi-likelihood estimation method is developed, and a ridge-type ratio estimator is introduced for selecting the appropriate rank. Reduced-rank spatio-temporal models effectively reduce dimensionality, facilitate interpretation, and enhance estimation performance in high-dimensional environments
INVESTIGATION OF CHARGE TRANSFER OF MOS2 MODIFIED ELECTRODE IN THE ABSENCE AND PRESENCE OF MONOVALENT (Na⁺) AND DIVALENT (Mg²⁺) CATIONS
No full textThe kinetics of charge transfer at modified electrode surfaces must be understood to develop electrochemical biosensing platforms. The charge transfer behavior at indium tin oxide (ITO) electrodes modified with molybdenum disulfide (MoS₂) is investigated in this work for applications employing nucleic acid-based biosensing. Two-dimensional (2D) MoS₂ nanoparticles are a suitable choice for electrochemical sensing due to their exceptional electrical properties, strong biomolecular adsorption ability, and large surface area. We investigate the charge transport and electrostatic interactions at the MoS₂/ITO interface using [Ru(NH₃)₆]³⁺/²⁺ as a redox probe. We investigate the charge transport and electrostatic interactions at the MoS₂/ITO interface. To further understand biomolecular interactions and their consequences on the electrical double layer, we investigate the adsorption of DNA (ss-DNA, ds-DNA) and locked nucleic acids LNA, ss-LNA, and ds-LNA onto MoS₂ with and without monovalent and divalent ions. Chronocoulometry measures surface charge fluctuations and distinguishes between double-layer capacitance (Qdl) and adsorbed charge (Qads) using the Cottrell and Anson equations, while cyclic voltammetry gives information on electron transport kinetics. The insertion of monovalent and divalent ions permits charge screening, which permits the calculation of charge transfer kinetics at the probe because MoS₂ has an intrinsic negative charge, and DNA and LNA have negatively charged phosphate backbones. Additionally, atomic force microscopy (AFM) is used to investigate charge fluctuations on the MoS₂ surface. Better electrochemical sensing technologies for environmental monitoring and disease diagnosis are made possible by the findings of this work, which significantly contribute to the development of label-free, MoS₂-based biosensors
Evaluating the Accuracy of Traction Force Estimations in Traction Microscopy via Deep Learning
No full textThis research introduces a deep learning-based framework for evaluating the structural consistency of traction force estimations in microscopy. The proposed approach identifies deviations in predicted traction maps by comparing their boundary structures to those from a chosen baseline method, without requiring ground truth labels.A UNET-based model is trained using both clean and synthetically distorted data, incorporating a set of noise models that simulate biologically relevant perturbations. This training strategy improves the model\u27s ability to flag potentially unreliable traction patterns across varying distortion levels.To quantify these deviations, we introduce a metric ranging from 0 to 1, allowing for threshold-based identification of inconsistent traction outputs. The framework generalizes across multiple cell samples cultured on the same substrate and supports automated, scalable evaluation without manual inspection. Results demonstrate the model’s robustness under diverse scenarios and its practical value in replacing time-consuming manual evaluation with an automated and scalable assessment framework
THE PETROLOGICAL AND GEOCHEMICAL ANALYSIS OF THE GRANT INTRUSIVE BRECCIA AND VAUGHN INTRUSIVE WITHIN HICKS DOME, HARDIN COUNTY, ILLINOIS
No full textHicks Dome is a crypto-volcanic feature found in the southeastern corner of Hardin County, Illinois. The dome formed around 270 Ma (late Permian), as part of the Permian Wauboukigou Igneous Province (PWIP), through a series of explosive igneous intrusions that caused uplift and clear structural deformation to the area. There was not enough magma feeding the intrusions to breach the surface, but due to the unique geochemistries of the magma(s), these intrusions formed amalgamations of alkaline, carbonatitic, and ultramafic gabbros. The overall geochemistry of these intrusions have high amounts of iron (Fe) and calcium (Ca), with relatively low amounts of silicon (Si). A previous characterization of the Grant Intrusive revealed the potential for economic concentrations of barium (Ba), titanium (Ti), and thorium (Th), as well has Heavy Rare Earth Elements(HREEs) including scandium (Sc) and yttrium (Y). Not all of the intrusions found at Hicks Dome have been studied, and new intrusions are still being discovered as the topsoil erodes away revealing the crystallized dikes that have been preserved for the past 270 million years. Of these intrusions the Grant Intrusive has been cited in several studies Bradbury and Baxter, (1992); Reynolds et. al. (1997); and Trela et. al. (2024). However the Vaughn Intrusive, has not been previously studied or cited in any publications or papers until now. The composition and mineralogy of the Vaughn Intrusive has been unknown, but it still leaves the question of whether or not this intrusion is possibly connected to the Grant Intrusive, due to its close vicinity, or were these intrusions formed from different magmatic episodes? Initial samples for the Grant Intrusive were provided by the Illinois State Geological Survey (ISGS), and additional samples for the Grant Intrusive and initial samples for the Vaughn Intrusive were collected during a field expedition on October 19th 2024. X-Ray Diffraction (XRD), Scanning Electron Microscope (SEM-EDS), and an optical petrographic analysis were all utilized to analyze potential ore and gangue minerals. X-Ray Fluorescence (XRF) was used to determine bulk geochemistry and make inferences on element partitioning and economic viability, Electron Dispersive Spectroscopy (EDS) was used in conjunction to confirm the presence of critical elements such as titanium and niobium. A magnetic anomaly model of the intrusion was also constructed using a dual sensor cesium vapor magnetometer, and Surfer Pro Modeling Software. By mapping magnetic anomaly localities, igneous bodies within the subsurface have been located and inferred. Results show extensive emplacement of ultramafic material throughout the Hicks Dome region, and strong potential for economic HREE ores in breccias proximal to Grant Intrusive. Geochemical and mineralogical data also show many differences between the Grant Intrusive and Vaughn Intrusive magmas, indicating that multiple magma sources, or episodes of magmatic differentiation have taken place
Assessing Place-Based Water Recommendations: A Case Study for University Experiential Learning Programs
No full textThe ability of small to medium-sized manufacturing, processing, and agricultural industries to become more sustainable revolves around dedicated technical and financial resources to investigate opportunities for increased efficiency and implementation. With extension-based funding, university experiential learning programs provide no-cost sustainability assessments utilizing students and faculty to promote more sustainable practices, cost savings, and expansion for industrial partners. These place-based initiatives allow students in these programs to enhance their communication skills, design practical solutions to solve persistent problems, and expand their network for future workforce opportunities. The assessments focus on short-term solutions that can build large capital projects. Assessment teams work with partnering industries to identify persistent issues in water usage including reclamation, conservation, treatment, and disposal, while providing pathways for implementation through educating stakeholders about target federal grant programs. By working with the university, industrial partners have a wealth of knowledge and means for analysis on a variety of projects. This leads to increased resources for projects tailored directly to everyday needs at individual sites. Thus, university experiential learning programs play a critical role in increasing the resources available for small to medium-sized industrial facilities and promoting sustainable practices in industrial settings