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Multisystemic Resilience and Anxious-Depressed Symptoms in Black Youth Exposed to Maternal Syndemics: A Mixed-Method Study
No full textInternalizing symptoms of anxiety and depression are common mental health concerns for youth. Research suggests that maternal SAVA (i.e., Substance Abuse, Violence, and AIDS/HIV) syndemics impact family systems and are associated with youth internalizing symptoms. Scholars have also found that resilience factors may have a buffering effect on the association between stressors and anxiety and depression among Black youth. Drawing on resilience and adapted socio-ecological theories, this study aimed to increase understanding of associations among resilience, maternal SAVA syndemics, and anxious-depressed symptoms in Black youth. Using data from the PaTH Kids Study, a sequential explanatory mixed-methods design was used with 171 Black youth aged 8 to 17 (57% girls; Mage=12.13, SD=2.90) who were exposed to maternal adversities in the U.S. Midsouth. Quantitative data was first analyzed using a hierarchical regression to determine factors associated with fewer anxious-depressive symptoms. Covariates of age, gender, and SAVA were entered first, then entered next were resilience factors across three levels: 1) Individual (inter/intrapersonal skills, strong ethnic identity); 2) Caregiver (physical/psychological caregiving, open family communication); 3) Community (community assets, community cohesion, and school assets). Qualitative data included transcripts of a subset of 10 youth and their maternal caregivers recruited from quantitative study participants with high resilience scores that were examined using a thematic approach. The final step of the quantitative regression model, F(10, 149) = 6.89, p <.001, Adj R2= 27.0%, showed that girls (�� = -.17, p = .02), youth with more inter/intrapersonal skills (�� = -.28, p =.003) and youth with more open family communication (�� = -.40, p<.001) reported less anxious-depressive symptoms. Qualitatively, four themes emerged related to inter/intrapersonal skills: (a) emotion regulation strategies; (b) goal setting; (c) personal characteristics; and (d) problem-solving skills. Five themes emerged related to open communication: (a) providing a comfortable environment to talk; (b) solving problems; (c) processing feelings; (d) showing affection; (e) benefiting from open communication. Across quantitative and qualitative findings, results suggested that individual and caregiver level variables are key multisystemic resilience factors related to less anxious-depressed symptoms. Findings provide a deeper understanding of how resilience at the individual and caregiver level may be enhanced in the context of maternal adversity for Black youth
Decentralized Learning for Wireless Video Streaming with Delayed Feedback
No full textWe study the optimal control of multiple video streams over a wireless downlink from a base-station (BS)/access point to N end-devices. The BS sends video packets to each end-device under a joint transmission power constraint, the end-devices choose how to play out the received packets, and the collective goal is to provide a high Quality-of-Experience (QoE) to the end-users. All the end-devices send feedback about their states and actions to the BS which is assumed to reach it with a fixed deterministic delay. We analyze this team problem with delayed information sharing by casting it as a cooperative Multi-Agent Constrained Partially Observed Markov Decision Process (MA-C-POMDP). First, the original team problem is decomposed into N independent unconstrained team problems, using recent theoretical developments for MA-C-POMDPs. Thereafter, the common information approach and the formalism of approximate information states (AISs) are used to develop approximately optimal solutions. Computationally feasible data-driven implementations using neural networks are then employed to obtain such solutions. Numerical simulations using AISs demonstrate vastly improved performance when compared to a scheme without AISs. We compare performance, power costs, QoE and robustness to channel variations
Distributed Filtering Solutions for Addressing Power Quality Concerns in Low-Voltage Distribution Systems with High EV Penetration Levels
Get PDFWith the ever-increasing popularity of EVs and the addition of dynamic distributed generators, such as solar panels and wind generators, the conventionally designed utility grid faces issues like stability concerns, overloading, and power quality issues, including harmonics and voltage sag/swell throughout the grid. These power quality issues impact the operation and lifetime of other linear loads connected to the grid. With EVs being mobile and random in nature, an extra layer of complexity is added to the already dynamic system. Conventional compensation strategies are designed for fixed node loads, which may result in over/under-compensation in the case of EVs, due to their randomness and mobility. In this research, We focus on addressing the power quality issues (harmonics) while attempting to accurately model the randomness and mobility of EVs in a low-voltage distribution system. Active filters are the most popular solution for addressing power quality concerns in conventional grids. Load-Point Filtering is a solution that places a filter on each harmonic load and tries to supply harmonics locally instead of them being drawn from the grid. However, these filters become impossible to implement and expensive when there are many harmonic loads in a distribution line. Thus, there is an emerging need to develop a novel filtering solution capable of restricting the voltage harmonics below 5% (as per IEEE 519-2014), while staying cost-competitive. To address these concerns, my research will explore this issue and develop a novel distributed filtering solution that will optimally place the active filters throughout the electric grid to address the power quality issues. To benchmark, the problem statement and the defined proposed algorithm are presented in detail using a standard IEEE 33-node system (consisting of different sectors, including industrial, commercial, and residential) attempting to mimic a Texas grid. This modeled system is initially analyzed for 24-hours without EVs to establish the benchmarking data and obtain the available power on each node. In the next step, EV loads are added to different sectors based on the available power, thereby avoiding any overloading. This includes fast charging stations added to the industrial sector, parking lot with EV chargers added to the commercial sector, and random/mobile EV loads added to the residential sector. To account for the randomness, a PMF (probability mass function), based on the maximum power allowed in each node, is used. With these EVs added to the utility grid, the impact on grid voltage and harmonics is obtained. To meet the IEEE harmonic mandate, an optimization-based distributed filtering solution is developed and validated that will strategically place filters throughout the system. The proposed philosophy that is being defined as the research progress will have the capability to be repeated with any grid system to fit a variety of needs
Host Genetic Factors Underlying the Differential Response to Bacterial Infections
No full textThe Collaborative Cross (CC) mouse population is an ideal tool for systems genetics. We have used this tool to examine several aspects of host-pathogen biology: (1) Defining diversity in disease outcome to S. aureus infection, (2) Identifying regions in the mouse genome responsible for some of these differences, and (3) Defining differences in the microbiome across host genetics and determining how this may influence disease outcome after gastrointestinal infection with Salmonella.
To identify host genes involved in the S. aureus host-pathogen interaction, we infected Collaborative Cross strains with methicillin-resistant S. aureus (USA300) and monitored disease progression. We identified eight ���susceptible,��� six ���tolerant,��� and six ���resistant��� CC strains. We identified four CC strains with sex differences: females of these strains survived longer than males. We also identified strains for modeling endocarditis, myocarditis, and pneumonia. QTL analysis identified two significant genomic loci involved in survival after infection. We shortlisted Npc1 and Ifi44l genes using variant analysis and mRNA expression in these intervals. To specifically identify host genes involved in tolerance after S. aureus infections, we crossed a susceptible (CC061) and a tolerant (CC024) CC strain. Colonization in F2 animals was more extreme than in their parents, showing successful segregation of genetic factors. We identified a QTL peak for survival after infection in the F2 population. We shortlisted two genes, C5ar1 and C5ar2, with high-impact variants that could lead to tolerance against MRSA infection. Finally, we studied the effect of host genetics on gut microbial composition in the CC population. We observed a large variance in the bacterial composition across CC strains starting at the phylum level. We identified 17 significant QTL peaks linked to 14 genera. Multiple host genes involved in obesity, glucose homeostasis, and immunity in this region determine the gut microbial composition. Salmonella Typhimurium (STm) typically causes self-limiting gastroenteritis, but in some individuals, it spreads systemically, causing severe disease. A subset of these CC strains was infected with S. Typhimurium. Using infection outcome data and a machine learning algorithm, an increase in abundance of Genus Lachnospiraceae and a decrease in Genus Parasutterella correlated with positive health outcomes after infection
Modified Decline Curve Analysis Workflow Aids Forecast Certainty
No full textIn this project, I propose the use of a three-segment Arps model, with segment length corresponding to the beginning and end of each flow regime, to construct representative type well profile distributions for horizontal multi-fractured wells in unconventional reservoirs. These flow regimes are ramp-up, transient, transition, and boundary-dominated flow. Arps parameters used in forecasting should be different for each of the observed flow regimes; therefore, a multi-segment model can be used. Current operator practice in the oil and gas industry generally ignores the need for flow regime identification and therefore includes transient flow data in long-term forecasting. This can lead to gross overestimation of reserves, even with a minimum exponential decline rate imposed. Using decline curve analysis and Monte Carlo simulation, probabilistic distributions of EUR, including ramp-up production can be determined. However, unique type well profiles cannot be determined based solely on EUR and input distributions. I show that a range of possible production profile outcomes can be determined, if fixed percentiles of input distributions are used. Rather than obtaining a singular type well profile, this methodology can be used to report ranges of uncertainty in Arps inputs and corresponding production profiles and economics
Palynostratigraphic Constraints on the Upper Tanezzuft and Akakus Formations in the Ghadamis Basin of Libya
No full textThe Ghadamis Basin in northwest Libya has generated a tremendous amount of oil and gas, sourced primarily from the lower Silurian anoxic black shales (aka ���hot shales���) at the base of the Tanezzuft Formation. These dark grey, fissile shales contain substantial amounts of organic matter, as well as radioactive minerals. The Silurian System in the Ghadamis Basin consists of both the Tanezzuft and the overlying Akakus formations. Cores and outcrops are difficult to correlate across the basin but can be improved using chitinozoans biostratigraphy. Eighty samples from three wells that collectively cover the entire Silurian in the northeastern Ghadamis Basin yielded a diverse group of marine chitinozoans. Identified species include Ancyrochitina ancyrea, A. fragilis, Sphaerochitin concava, S. sphaerocephala, Fungochitina spinifera, Pseudoclathrochitina carmenchui, and Eisenackitina cylindrica. These species along with others could allow for robust age determination and enhanced stratigraphic correlation between the three wells, which can increase our understanding of the Ghadamis Basin���s paleogeography and paleoenvironments