Double-row planetary gear set (PGS) is a common form of the PGS, which is relatively more complex than the regular PGSs. It consists of one sun gear, several long planets, several short planets, two ring gears, and one carrier. Due to the significantly wider tooth width of the long planet compared to the sun gear, the axial meshing position between the sun gear and the long planet can be adjusted. The vibrations of PGS should vary with different axial meshing positions. If the axial position of the sun gear is optimized, the vibrations of PGS can be reduced. This work establishes a dynamic model of a double-row PGS. The dynamic model considers the mesh forces of the gear pairs and the supporting forces of the bearing. The effect of the sun gear axial position on the sun gear and ring gear #2 vibrations are investigated. Finally, the recommended axial position for the sun gear is provided.

OBJECTIVE: We aimed to validate and, if performance was unsatisfactory, update the previously published prognostic model to predict clinical deterioration in patients hospitalized for COVID-19, using data following vaccine availability.
METHODS: Using electronic health records of patients ≥18 years, with laboratory-confirmed COVID-19, from a large care-delivery network in Massachusetts, USA, from March 2020 to November 2021, we tested the performance of the previously developed prediction model and updated the prediction model by incorporating data after availability of COVID-19 vaccines. We randomly divided data into development (70%) and validation (30%) cohorts. We built a model predicting worsening in a published severity scale in 24 h by LASSO regression and evaluated performance by c-statistic and Brier score.
RESULTS: Our study cohort consisted of 8185 patients (Development: 5730 patients [mean age: 62; 44% female] and Validation: 2455 patients [mean age: 62; 45% female]). The previously published model had suboptimal performance using data after November 2020 (N = 4973, c-statistic = 0.60. Brier score = 0.11). After retraining with the new data, the updated model included 38 predictors including 18 changing biomarkers. Patients hospitalized after Jun 1st, 2021 (when COVID-19 vaccines became widely available in Massachusetts) were younger and had fewer comorbidities than those hospitalized before. The c-statistic and Brier score were 0.77 and 0.13 in the development cohort, and 0.73 and 0.14 in the validation cohort.
CONCLUSIONS: The characteristics of patients hospitalized for COVID-19 differed substantially over time. We developed a new dynamic model for rapid progression with satisfactory performance in the validation set.

Cells store triacylglycerol (TAG) within lipid droplets (LDs). A dynamic model describing complete LD formation at the endoplasmic reticulum (ER) membrane does not yet exist. A biochemical-biophysical model of LD synthesis is proposed. It describes the time-dependent accumulation of TAG in the ER membrane as the formation of a potential LD (pLD) bounded by spherical caps of the inner and outer monolayers of the membrane. The expansion rate of the pLD depends on the TAG supply, the elastic properties of the ER membrane, and the recruitment of phospholipids (PLs) to the cap-covering monolayers. Model simulations provided the following insights: (a) Marginal differences in the surface tension of the cap monolayers are sufficient to fully drive the expansion of the pLD towards the cytosol or lumen. (b) Selective reduction of PL supply to the luminal monolayer ensures stable formation of cytosolic LDs, irrespective of variations in the elasto-mechanical properties of the ER membrane. (c) The rate of TAG supply to the cytosolic monolayer has a major effect on the size and maturation time of LDs but has no significant effect on the TAG export per individual LD. The recruitment of additional PLs to the cap monolayers of pLDs critically controls the budding direction, size, and maturation time of LDs. The ability of cells to acquire additional LD initiation sites appears to be key to coping with acutely high levels of potentially toxic free fatty acids.

Hydrocarbon fuels contain approximately 50 times more energy per unit mass than commercial batteries, thus converting even 10% of the energy contained in hydrocarbon fuels to electrical energy could present a more mass-efficient electrical energy source than batteries. Considering the storability of hydrocarbon fuels compared to hydrogen, the viability of direct hydrocarbon polymer electrolyte membrane fuel cells was examined. With extremely pure (> 99.99%) propane, the cell Open-Circuit Voltage (OCV) was only 0.05 V and produced negligible power. However, with addition of trace quantities of unsaturated hydrocarbons, the cell had an OCV of 0.85 V and produced power, even after the unsaturated hydrocarbon addition was discontinued. At sufficiently high current densities, power output gradually decreased then the cell rapidly \"extinguished\" but by periodically shutting off the current for short time intervals the average power density could be increased significantly. Chemical analysis revealed that no significant amounts of hydrocarbon intermediates or CO were present in the effluent and that conversion of the hydrocarbon fuel to CO2 and H2O was nearly complete. An analytical model incorporating the relative rates of conversion of active anode catalyst sites to inactive sites and vice versa was developed to interpret this behavior. The model predictions were consistent with the experimental observations; possible physical mechanisms are discussed.

BACKGROUND: This study aimed to investigate quality of life (QoL) in middle-aged adults living alone and identify comprehensive biological, psychological, interpersonal, and contextual factors related to QoL using the dynamic biopsychosocial model. As a secondary analysis, this study used data from the 2017 Korea Community Health Survey conducted by the Korea Disease Control and Prevention Agency.
METHODS: Among the total 228,381 respondents, 10,639 middle-aged individuals aged 40-64 years from single-person households (5,036 men and 5,603 women) were included in the analysis. QoL was measured using the EuroQoL-5 Dimension (EQ-5D). The EQ-5D descriptive statistics were provided according to biological, psychological, interpersonal, and contextual factors. Considering the data structure of the multistage stratified cluster sampling method, a complex samples general linear model statistic was used to identify the predictors of QoL.
RESULTS: QoL was lower in those who had undesirable psychological status (e.g., more depressive symptoms, poor subjective health, and higher perceived stress), less engagement in social networking (less frequent contact with friends and less frequent participation in social activities such as religious activities, friendship gathering, and leisure), and lower physical, behavioral, and socioeconomic factors.
CONCLUSIONS: This study\'s findings indicate that psychological and interpersonal factors should be addressed and prioritized to improve the QoL of middle-aged adults living alone. By providing many opportunities for easily accessible social activities that meet the needs and interests of this demographic, their QoL can be improved through strengthening social support.

The global spread of COVID-19 has profoundly affected health and economies, highlighting the need for precise epidemic trend predictions for effective interventions. In this study, we used infectious disease models to simulate and predict the trajectory of COVID-19. An SEIR (susceptible, exposed, infected, removed) model was established using Wuhan data to reflect the pandemic. We then trained a genetic algorithm-based SEIR (GA-SEIR) model using data from a specific U.S. region and focused on individual susceptibility and infection dynamics. By integrating socio-psychological factors, we achieved a significant enhancement to the GA-SEIR model, leading to the development of an optimized version. This refined GA-SEIR model significantly improved our ability to simulate the spread and control of the epidemic and to effectively track trends. Remarkably, it successfully predicted the resurgence of COVID-19 in mainland China in April 2023, demonstrating its robustness and reliability. The refined GA-SEIR model provides crucial insights for public health authorities, enabling them to design and implement proactive strategies for outbreak containment and mitigation. Its substantial contributions to epidemic modelling and public health planning are invaluable, particularly in managing and controlling respiratory infectious diseases such as COVID-19.

Influenza A has two hemagglutinin groups, with stronger cross-immunity to reinfection within than between groups. Here, we explore the implications of this heterogeneity for proposed cross-protective influenza vaccines that may offer broad, but not universal, protection. While the development goal for the breadth of human influenza A vaccine is to provide cross-group protection, vaccines in current development stages may provide better protection against target groups than non-target groups. To evaluate vaccine formulation and strategies, we propose a novel perspective: a vaccine population-level target product profile (PTPP). Under this perspective, we use dynamical models to quantify the epidemiological impacts of future influenza A vaccines as a function of their properties. Our results show that the interplay of natural and vaccine-induced immunity could strongly affect seasonal subtype dynamics. A broadly protective bivalent vaccine could lower the incidence of both groups and achieve elimination with sufficient vaccination coverage. However, a univalent vaccine at low vaccination rates could permit a resurgence of the non-target group when the vaccine provides weaker immunity than natural infection. Moreover, as a proxy for pandemic simulation, we analyze the invasion of a variant that evades natural immunity. We find that a future vaccine providing sufficiently broad and long-lived cross-group protection at a sufficiently high vaccination rate, could prevent pandemic emergence and lower the pandemic burden. This study highlights that as well as effectiveness, breadth and duration should be considered in epidemiologically informed TPPs for future human influenza A vaccines.

BACKGROUND: In France, influenza accounts for an average of over one million consultations with GPs, 20,000 hospitalizations, and 9000 deaths per year, particularly among the over-65s. This study evaluates the cost-effectiveness of the adjuvanted quadrivalent influenza vaccine (aQIV) compared to standard (SD-QIV) and high-dose (HD-QIV) quadrivalent influenza vaccines for individuals aged 65 and older in France.
METHODS: The age-structured SEIR transmission model, calibrated to simulate a mean influenza season, incorporates a contact matrix to estimate intergroup contact rates. Epidemiological, economic, and utility outcomes are evaluated. Vaccine effectiveness and costs are derived from literature and national insurance data. Quality of life adjustments for influenza attack rates and hospitalizations are applied. Deterministic and probabilistic analyses are also conducted.
RESULTS: Compared to SD-QIV, aQIV demonstrates substantial reductions in healthcare utilization and mortality, avoiding 89,485 GP consultations, 2144 hospitalizations, and preventing 1611 deaths. Despite an investment of EUR 110 million, aQIV yields a net saving of EUR 14 million in healthcare spending. Compared to HD-QIV, aQIV saves 62 million euros on vaccination costs. Cost-effectiveness analysis reveals an incremental cost-effectiveness ratio of EUR 7062 per QALY.
CONCLUSIONS: This study highlights the cost-effectiveness of aQIV versus SD-QIV and HD-QIV, preventing influenza cases, hospitalizations, and deaths.

Clarifying the occurrence and morphological characteristics of petroleum hydrocarbons (PHs) in soil can facilitate a comprehensive understanding of their migration and transformation patterns in soil/sediment. Additionally, by establishing the dynamic transformation process of each occurrence state, the ecological impact and environmental risk associated with PHs in soil/sediment can be assessed more precisely. The adsorption experiments and closed static incubation experiments was carried out to explore the PHs degradation and fraction distribution in aged contaminated soil under two remediation scenarios of natural attenuation (NA) and bioaugmentation (BA) by exogenous bacteria through a new sequential extraction method based on Tenax-TA, Hydroxypropyl-β-cyclodextrin and Rhamnolipid (HPCD/RL), accelerated solvent extractor (ASE) unit and alkaline hydrolysis extraction. The adsorption experiment results illustrated that bioaugmentation could promote the desorption of PHs in the adsorption phase, and the soil-water partition coefficient Kd decreased from 0.153 L/g to 0.092 L/g. The incubation experiment results showed that compared with natural attenuation, bioaugmentation could improve the utilization of PHs in aged soil and promote the generation of non-extractable hydrocarbons. On the 90th day of the experiment, the concentrations of weakly adsorbed hydrocarbons in the natural attenuation and bioaugmentation experimental groups decreased by 46.44% and 87.07%, respectively, while the concentrations of strongly adsorbed hydrocarbons and non-extractable hydrocarbons increased by 77.93%, 182.14%, and 80.91%, and 501.19%, respectively, compared their initial values. We developed a novel dynamic model and inverted the kinetic parameters of the model by the parameter scanning function and the Markov Chain Monte Carlo (MCMC) method based on the Bayesian approach in COMSOL Multiphysics® finite element software combined with experimental data. There was a good linear relationship between experimental interpolation data and model prediction data. The R2 for the concentrations of weakly adsorbed hydrocarbons ranged from 0.9953 to 0.9974, for strongly adsorbed hydrocarbons from 0.9063 to 0.9756, and for non-extractable hydrocarbons from 0.9931 to 0.9982. These extremely high correlation coefficients demonstrate the high accuracy of the parameters calculated using the Bayesian inversion method.

Ventilation is paramount in sanitary and stormwater sewer systems to mitigate odor problems and avert pressure surges. Existing numerical models have constraints in practical applications in actual sewer systems due to insufficient airflow modeling or suitability only for steady-state conditions. This research endeavors to formulate a mathematical model capable of accurately simulating various operational conditions of sewer systems under the natural ventilation condition. The dynamic water flow is modeled using a shock-capturing MacCormack scheme. The dynamic airflow model amalgamates energy and momentum equations, circumventing laborious pressure iteration computations. This model utilizes friction coefficients at interfaces to enhance the description of the momentum exchange in the airflow and provide a logical explanation for air pressure. A systematic analysis indicates that this model can be easily adapted to include complex boundary conditions, facilitating its use for modeling airflow in real sewer networks. Furthermore, this research uncovers a direct correlation between the air-to-water flow rate ratio and the filling ratio under natural ventilation conditions, and an empirical formula encapsulating this relationship is derived. This finding offers insights for practical engineering applications.