The University of Texas at Tyler

Many advances in enhanced oil recovery (EOR) take advantage of the unique properties of nanomaterials to improve characterization of formation properties, achieve conformance control during flood operations, and extend the controlled release time of polymers. Magnetite nanoparticles (nMag) have been employed in these processes due to their low cost, low toxicity, and ability to be engineered to meet desired needs, especially with the application of a magnetic field. Similarly, silica dioxide (SiO2) and aluminum oxide (Al2O3) nanoparticles have been evaluated for the delivery of scale and asphaltene inhibitors. However, the injection of nanoparticles into porous media comes with the risk of formation damage due to particle deposition, which can lead to increased injection pressures and reductions in permeability. The goal of this study was to develop a method to evaluate and assess nanoparticle formulations for their potential to cause formation damage. A screening apparatus was constructed to hold small sandstone discs (~2 mm) or cores (~2.5 cm) for rapid testing with minimal material use and the capability to be used with either aqueous brine solutions or non-polar solvents as the mobile phase. Image analysis of the disc and pressure measurements demonstrated increasing deposition of nMag and face-caking when the salinity was increased from 500 mg/L NaCl (8.56 mM) to API brine (2.0 M). Similarly, when the injected concentration of silica nanoparticles in 500 mg/L NaCl was increased from 1 to 10 wt%, the back pressure increased by 55 psi, and face-caking was observed. The screening test results were consistent with traditional core-flood tests and was able to be modified to accommodate organic liquid mobile phases. The screening test results closely matched nanoparticle transport and retention measured in sandstone cores, confirming the ability of the system to rapidly screen nanoparticle formulations for potential formation damage.

The transition to sustainable energy sources has heightened interest in perovskite solar cells (PSCs), yet commercialization remains challenged by the toxicity of lead-based compounds and their vulnerability to environmental degradation. In response, this study presents a comprehensive computational framework for designing and optimizing a lead-free, inorganic PSC that employs Ba3SbI3 as the absorber material. Implementing SCAPS-1D simulations, we systematically evaluate the influence of device architecture, carrier transport layers (CTLs), defect densities, doping concentrations, and operational conditions on key photovoltaic metrics. When different device layouts were compared, the Al/FTO/SnS2/Ba3SbI3/CBTS/Au structure stood out as the most promising. It yielded a simulated power conversion efficiency (PCE) of 33.31%, accompanied by an open-circuit voltage (Voc) of 1.2068 V, short-circuit current density (Jsc) of 32.17 mA/cm2 and fill factor (FF) of 85.81%, outperforming the reference model without a hole transport layer (HTL) achieved PCE = 21.55%, Voc = 0.9089 V, Jsc = 27.83 mA/cm2, FF = 85.19%. Beyond parametric optimization, we incorporate machine learning (ML) via Random Forest Regression (RFR) to enhance predictive modeling capabilities. The model demonstrates high fidelity (R² > 0.97) and offers insight into variable importance, identifying absorber defect density, doping level, and operational temperature as primary performance drivers. Our hybrid approach not only accelerates the design of high-efficiency Ba3SbI3-based PSCs but also underscores the viability of environmentally benign materials for next-generation photovoltaics. The integration of physics-based simulation with data-driven analysis provides a scalable methodology for future studies in sustainable solar energy technology.

ABSTRACT Using recently developed proxies for firm‐level political risk and earnings manipulation, we test the limited attention theory. Contrary to Hirshleifer and Teoh's core prediction that investor attention is associated with less managerial manipulation, we find that firm‐level political risk, serving as a proxy for investor attention, is positively associated with manipulative earnings management, using both accruals and real activities. The results are robust to alternative proxies for political risk and earnings manipulation, various techniques addressing endogeneity concerns, and subsamples of firms with different earnings manipulation incentives. Moreover, we find that the negative relation between earnings manipulation and subsequent operating performance is more pronounced among firms exposed to more firm‐level political risk, suggesting that firm‐level political risk is associated with managerial incentives for manipulation more than its association with the monitoring that comes with greater attention.

Teacher preparation is an emotional as well as a cognitive process in which pre-service teachers must develop both reflective judgment and the emotional resilience needed for demanding instructional contexts. This study examined how university-based supervisors enacted the relational spaces of the University-Based Coaching Framework (UBCF) and how these enactments shaped pre-service teachers' emotional and reflective development. Drawing on qualitative analysis of coaching discourse among three supervisor-pre-service teacher pairs, the comparative case study identifies distinct coaching identities that emerged from supervisors' patterned relational moves. These identities corresponded to varying intensities of UBCF space enactment and produced differential pathways through a reflective-motional cycle connecting appraisal, coping, and reappraisal. Findings demonstrate that supervisors' relational stance functions as both cognitive scaffolding and as an emotional regulator. By conceptualizing UBCF-based coaching as an interactional process that integrates relational attunement with reflective challenge, this study contributes new insight into how emotional and cognitive dimensions of supervision jointly support teacher knowledge development and early professional resilience.

<sec><title>OBJECTIVE</title>Poor sustained sputum culture conversion with guidelines-based therapy for Mycobacterium avium complex lung disease highlights the need for new and improved multidrug combinations.</sec><sec><title>DESIGN</title>We tested eight drugs by performing minimum inhibitory concentration (MIC) experiments with the ATCC#700898 strain and 49 clinical isolates, followed by single and multidrug combination studies.</sec><sec><title>RESULTS</title>MIC90 of rifabutin, rifampin, azithromycin, and ethambutol were 4, 16, 256, and 128 mg/L, respectively. Among other drugs, MIC90 (mg/L) in lowest to highest rank order were for bedaquiline (0.25), tedizolid (16), tebipenem (64), and minocycline (128). As monotherapy, none of the drugs had better MAC kill compared to rifampin. While minocycline alone killed 1.76 ± 0.33 log10 CFU/mL MAC, replacement of rifabutin in the standard therapy resulted in 6.27 ± 0.28 log10 CFU/mL MAC kill, showing minocycline's synergistic effect with azithromycin and ethambutol. An example of a macrolide-rifamycin-ethambutol-free oral regimen, the azithromycin-minocycline-tedizolid combination killed 4.35 ± 0.42 log10 CFU/mL MAC. The tebipenem-tedizolid-minocycline combination killed 4.82 ± 0.42 log10 CFU/mL; however, addition of bedaquiline resulted in a lower kill of 2.71 ± 0.22 log10 CFU/mL, suggesting a likely antagonism.</sec><sec><title>CONCLUSION</title>We tested eight different drugs to identify several rifamycin-, macrolide-, and ethambutol-free oral multidrug combinations. The minocycline-based regimens warrant further preclinical and clinical testing.</sec>.