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Dynamical analysis of a stochastic epidemic model with vaccination and log-normal Ornstein-Uhlenbeck process
Full text linkIn this study, we develop and investigate a stochastic (Susceptible-Exposed-Undetected infected-Detected infected-Recovered-Susceptible) epidemic model with vaccination of newborns and the disease transmission rate driven by a log-normal Ornstein-Uhlenbeck process. By establishing a series of Lyapunov functions, we derive sufficient conditions for persistence in the mean of the disease in the long term under the condition and these criteria are applied to guarantee the existence of an invariant probability measure of the stochastic system. Subsequently, we also derive sufficient conditions for eradication of the disease when the parameters and . Finally, two numerical examples are given to confirm the theoretical results. This work can help us implement interventions to regulate the disease dynamics
Persistent chemicals in particulate matter (PM) near a hazardous waste thermal treatment facility
No full textColfax, an overburdened community in central Louisiana, hosts the last commercially-operated open-burn/open-detonation (OB/OD) hazardous waste thermal treatment facility in the United States. Until December 2023 when their permit disallowed OB/OD, the facility processed military waste, fireworks, propellants, soils excavated from Superfund sites, and other hazardous materials. This community-engaged study measured ambient fine particulate matter (PM2.5), environmentally persistent free radicals (EPFRs), polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), and metals using two high-volume PM2.5 samplers deployed 1.2 mi and 9.0 mi from the facility from April, 2022 through February, 2023. Elevated PM2.5 concentrations were recorded at both sites during spring and summer 2022. EPFR concentrations increased during fall and winter, coinciding with increases in PCDD/F but in contrast to PM2.5. Similarities between the 1.2 mi and 9.0 mi sites for both PM2.5 and EPFRs suggest a common emission source influencing concentrations at both sites. Regularized linear regression analyses indicated that EPFRs were significant predictors of PM2.5 at both sites, with a markedly stronger effect at the 9.0 mi site than at 1.2 mi. Among the metals, Zn was consistently the strongest and most significant predictor of EPFRs and PM2.5 across both sites and seasons, supported by both moderately high Pearson correlations and Elastic Net coefficients. Through this study, we aim to provide crucial information on exposure risks from an OB/OD facility with the goal of empowering exposed community members for mitigating their risks
ARBITRAGE-FREE PRICING WITH DIFFUSION-DEPENDENT JUMPS
No full textStandard jump-diffusion models assume independence between jumps and diffusion components. We develop a multi-type jump-diffusion model where jump occurrence and magnitude depend on contemporaneous diffusion movements. Unlike previous one-sided models that create arbitrage opportunities, our framework includes upward and downward jumps triggered by both large upward and large downward diffusion increments. We derive the explicit no-arbitrage condition linking the physical drift to model pa- rameters and market risk premia by constructing an Equivalent Martingale Measure using Girsanov’s theorem and a normalized Esscher transform. This condition provides a rigorous foundation for arbitrage-free pricing in models with diffusion-dependent jumps
Driving mechanisms of distinct seasonal phytoplankton dynamics in a low-latitude basin revealed by multi-platform observations
No full textPhytoplankton forms the foundation of marine food webs, and their seasonal dynamics shape ocean ecosystem functioning and carbon cycling. In low-latitude basins such as the South China Sea (SCS), these dynamics have traditionally been regarded as stable and primarily controlled by warm-cold seasonal oscillations, often evaluated using single metrics such as chlorophyll-a concentration. However, this paradigm fails to capture the significant regional heterogeneity within a single basin and the complex, sometimes contradictory, responses of different phytoplankton community parameters. To address this, we conducted a comprehensive analysis of a 20-year multi-platform dataset (remote sensing, ship-based, and Biogeochemical-Argo) to reveal how regional physical processes drive the seasonal dynamics of phytoplankton chlorophyll-a, community composition, and primary production in the basin of SCS. In the northern basin, winter monsoon coupling with strong Kuroshio intrusion elevated surface chlorophyll-a by 200 % compared to summer, yet contributed only 31.2 % to the annual primary production, revealing a significant decoupling driven by light limitation and low-temperature suppression of photosynthesis. In the southwestern basin, summer upwelling stimulated diatom blooms and sustained primary production comparable to its winter levels. Niche models confirmed that regional physical processes (Kuroshio intrusion vs. upwelling) select for distinct phytoplankton assemblages within the basin. We conclude that regional physical forcing, rather than basin-wide monsoon seasonality alone, is the primary driver of phytoplankton dynamics and carbon cycling in this low-latitude basin, supplementing the traditional seasonal oscillation paradigm for such systems
Metacommunity Coupled Epidemiological and Biophysical Modeling of an Emergent Coral Disease
No full textEmerging infectious diseases pose imminent risk to the marine realm and coral reefs in particular. Since its emergence in 2014, stony coral tissue loss disease (SCTLD) has dramatically reduced living coral cover in Florida and charted a similar course in the Caribbean. SCTLD is by far the most severe coral disease in history and has driven highly susceptible species to local extinction, yet the mechanisms driving the regional epizootic are not well understood. Here, we developed reef-scale parameterizations of disease spread using model sites in the lower Florida Keys, developed extensive metacommunity habitat maps for the US Caribbean, and then combined the two as inputs to a multi-scale epidemiological-biophysical model of SCTLD in the US, Spanish, and British Virgin Islands. Our goals included investigating the roles of host density, host identity, depth-structured habitat, and spatiotemporally explicit ocean currents in driving outbreaks. Findings identify the species compositions, habitat niches, and oceanographic features that render a marine metacommunities vulnerable to uniquely devastating multi-host contagion. Managers and policymakers who are tasked with allocating resources toward conservation may find our modeling useful in identifying spatially explicit risk factors, as the model framework can ideally be applied to future multi-species marine mass mortalities caused by emerging infectious diseases
XOOD: A Self-supervised Algorithm for Detecting Out-of-Distribution Data for Image Classification
No full textNeural Networks are known to be opaque in their decision-making process. In particular, it is known that, when encountering out-of-distribution (OOD) data, they can confidently provide an erroneous output without warning the user. It is well known that the “class probabilities” output by the softmax layer of a neural network are only weakly correlated with how confident the model should be about the prediction. Therefore, identifying out-of-distribution input data at inference time is critical for many applications of machine learning. We present XOOD: a self-supervised extreme value-based OOD detection framework for image classification. The algorithm relies on the signals captured by the extreme values of the data in the activation layers of the neural network in order to distinguish between in-distribution and OOD instances. We show experimentally that XOOD outperforms state-of-the-art OOD detection methods on many benchmark data sets in both efficiency and accuracy, reducing false-positive rate (FPR95) by 50%, while improving the inferencing time by an order of magnitude. The source code is available at https://github.com/MdSaifulIslamSajol/xood-icann/
Thermal performance of additively manufactured alloys
No full textAdditive manufacturing (AM) has created new opportunities for high-performance alloys for use in complex components across the aerospace, industrial, automotive, and energy industries. Among AM techniques, laser powder bed fusion (L-PBF) is widely used for alloy parts fabrication. However, L-PBF parameters optimized in laboratory do not always translate into a production environment. This dissertation first investigates the effects of various L-PBF systems and parameters on the thermal properties of GRCop-84 and GRCop-42 parts fabricated via L-PBF. Subsequently, thermal properties of L-PBF prepared nickel alloys, including GRX-810 and Inconel 718, were investigated. GRX-810 is a novel oxide-dispersion-strengthened NiCoCr-based alloy recently developed by NASA. GRX-810 has been fabricated using L-PBF to facilitate the homogeneous dispersion of nanoscale yttria particles throughout the material\u27s intricate microstructure. However, Yttria ratio of the alloy could significantly impact its performance which is still lack of knowledge. This dissertation explored the relationship between the Yttria content and mechanical properties and thermal properties of GRX-810. Finally, thermal properties of Inconel 718 prepared by different L-PBF systems were investigated to evaluate the variability due to the use of different fabrication systems
The Influence of Global Value Chains on the Design of Preferential Trade Agreements
No full textAbstract
This dissertation examines how Global Value Chain (GVC) integration influences the regulatory depth of Preferential Trade Agreements (PTAs) across 154 countries from 1990-2015. As global production networks have transformed international trade, with approximately 50% of world trade consisting of intermediate inputs by 2015, PTAs have simultaneously evolved from simple tariff-reduction instruments to comprehensive regulatory frameworks governing intellectual property, investment, technical standards, and beyond-the-border policies. This study investigates whether and how countries\u27 positions in global supply chains shape their demand for deeper regulatory commitments in trade agreements.
Drawing on transaction cost economics, credible commitment theory, and institutional learning frameworks, I test three interconnected hypotheses using fixed-effects panel regression analysis. First, I hypothesize that GVC integration drives deeper PTA commitments through transaction cost reduction and credible commitment mechanisms. Second, I predict this relationship is systematically stronger for lower-income countries facing greater institutional constraints. Third, I expect the effect weakens as countries accumulate PTA experience through institutional learning and strategic sophistication.
The empirical findings reveal substantial heterogeneity that uniform models mask. While baseline unconditional models show no significant average effect, conditional analyses demonstrate that lower-income countries exhibit positive relationships between GVC integration and PTA depth, whereas high-income countries show statistically significant negative relationships. Similarly, countries with extensive PTA portfolios exhibit strong negative relationships, while those with fewer agreements show near-zero effects. Temporal subsample analysis reveals a dramatic reversal: during 1990-2002, GVC integration strongly predicted deeper PTAs, but during 2003-2015, the relationship reversed significantly.
These patterns challenge both classical trade theory\u27s uniform preference predictions and liberal institutionalist convergence arguments. The findings support conditional frameworks recognizing that domestic institutional capacity, strategic choices, and accumulated experience mediate how international economic pressures translate into institutional outcomes. This research contributes to international political economy scholarship by empirically demonstrating that GVC integration creates distinct political coalitions around trade agreement design, that globalization\u27s effects vary systematically across institutional contexts, and that institutional preferences evolve through policy experience
Student Perceptions of Historically Black Colleges and Universities (HBCUs) and Its Influence on College Choice
No full textABSTRACT
Student Perceptions of the HBCU and its Influence on College Choice.
Historically Black Colleges and Universities (HBCUs) continue to represent a great legacy in the history of education for African Americans; however, these institutions are faced with current challenges that include: declining African -American enrollment, financial issues, and questions concerning the value that a degree from an HBCU may hold. Research illustrates how HBCUs are academically and culturally accommodating for Black students (Albritton, 2012; Fountaine, 2012; Fries-Britt & Turner, 2002; Outcalt & Skewes-Cox, 2002; Thompson, 2008), but when deciding on which college to attend, high schoolers give more consideration to financial access and prestige, and less to the development or affirmation of racial identities (Braddock & Hua, 2006; Fleming, 1984; Freeman & Thomas, 2002; Tobolowsky, Outcalt, & McDonough, 2005). The current scope of literature fails to recognize Black high school students’ perspectives on electing to attend an HBCU (Dancy & Brown, 2008; Davis, 2004; Dillon, 1999; Freeman, 1999). Critical Race Afrocentricity provides a lens to examine how HBCUs serve as a historical, as well as current option for educational opportunity among African-American college students in a time where the concept of race appears not to be a determinant in selecting a college.
This study examines the perceptions of 13 African-American college-bound high school students regarding attending an HBCU. It is necessary to examine the current role HBCUs will serve for future generations of African-American students. Findings of the study indicate that although African-American teens recognize the intellectual, cultural, and social value in attending an HBCU, they feel that factors such as financial affordability and academic reputation are more pertinent factors in selecting a college. Furthermore, there is a need for future research to examine the participants’ perspectives to their actual collegiate experiences
Health-Related Social Needs and Fear of Death: Moderating Effect of Advance Care Planning
No full textFear of death is a phenomenon affecting individuals of all ages, and its presence continues well into older adulthood. This study explores the associations between health-related social needs and fear of death within the theoretical framework of social determinants of health in the late stages of psychosocial stages of development. The health-related social needs of particular focus in this study match those of focus by the Centers for Medicare and Medicaid Services, which are food insecurity, housing problems, trouble paying bills, transportation problems, and safety. This study further sought to analyze the moderating effect of advance care planning on those relationships, to ascertain whether discussing or completing advance care plans may moderate the direct effects of health-related social needs on fear of death. Using the longitudinal panel study results made public by the Health and Retirement Study, waves 2020 and 2022, this study narrowed the results to include adults aged 65 and older living in the community. Results found low occurrence of worrying about food, difficulty paying bills, and fear of death in the week prior to survey. Some older adults reported having housing problems and not owning transportation. There was moderate concern about neighborhood safety after dark. Housing problems was shown to be positively associated with fear of death for the 2022 wave. Additionally, perceived neighborhood safety was inversely associated with fear of death for the 2022 wave. Both the 2020 and 2022 waves showed a positive association between trouble paying bills and fear of death. With discussion and completion of advance care planning ranging from two-fifths to nearly three-fifths of older adults, a moderating effect was found for discussion of advance care planning on the relationship between problems with housing and fear of death in the 2020 wave. The 2020 wave also showed a moderating effect for having a living will on the relationship between transportation and fear of death. The effects and implications for social work practice and research are discussed