Observer-Based Control of Tilting-Pad Thrust Bearings

The active control of hydrodynamic bearings is beginning to receive more attention in the pursuit of lower power losses and reduced maintenance. This paper presents a method by which, from simple measurements, rich information can be deduced from a running bearing that can used to modify the operating parameters of the unit. The bearing is a line-pivot, unidirectional, steadily loaded, directly lubricated tilting pad thrust bearing. This control is achieved by designing an Observer whose inputs include the output measurement(s) from the bearing. The Observer is, in some ways, an inverse model of the bearing (or Plant) that runs in parallel to the bearing and estimates the states of the bearing, such as the applied load, pivot height, minimum film thickness, maximum temperature, effective temperature and power loss. These estimated parameters can then be used in a control algorithm to modify bearing parameters such as inlet temperature or pivot location. It is demonstrated that disturbances in the load on the bearing can be detected simply by measuring a representative temperature in the bearing or changes in pivot height. Appropriate corrective action can then be employed. Whilst only steady-state operation is considered, the method could be developed to study time-varying situations.

Patients with Alzheimer's disease have increased cellular amyloid uptake

Amyloid plaques are the main signature of Alzheimer's disease (AD). Beta-amyloid (Aβ) concentration in cerebrospinal fluid (CSF-Aβ) and the density of amyloid depositions have a strong negative correlation. However, AD patients have lower CSF-Aβ levels compared to cognitively normal people even after accounting for this correlation. The goal of this study was to infer variations of parameters in Aβ metabolism of AD patients that underlie this difference using data from the Alzheimer's Disease Neuroimaging Initiative cohort. We found that AD patients had dramatically increased rates of cellular amyloid uptake compared to individuals with normal cognition (NC). A group with late-onset mild cognitive impairment (LMCI) also exhibited stronger amyloid uptake, however this was less pronounced than in the AD group. Estimated parameters in the early-onset MCI group did not differ significantly from those in the NC group. Aβ cytotoxicity depends on both the amount of peptide internalized by cells and its intracellular degradation into toxic products. Based on our results, we speculate that AD and LMCI are associated with increased cellular amyloid uptake which leads to faster disease progression, whereas the early-onset MCI may be mediated by the increased production of toxic amyloid metabolites.

Identification and Control of Game-Based Epidemic Models

The effectiveness of control measures against the diffusion of the COVID-19 pandemic is grounded on the assumption that people are prepared and disposed to cooperate. From a strategic decision point of view, cooperation is the unreachable strategy of the Prisoner’s Dilemma game, where the temptation to exploit the others and the fear of being betrayed by them drives the people’s behavior, which eventually results in a fully defective outcome. In this work, we integrate a standard epidemic model with the replicator equation of evolutionary games in order to study the interplay between the infection spreading and the propensity of people to be cooperative under the pressure of the epidemic. The developed model shows high performance in fitting real measurements of infected, recovered and dead people during the whole period of COVID-19 epidemic spread, from March 2020 to September 2021 in Italy. The estimated parameters related to cooperation result to be significantly correlated with vaccination and screening data, thus validating the model. The stability analysis of the multiple steady states present in the proposed model highlights the possibility to tune fundamental control parameters to dramatically reduce the number of potential dead people with respect to the non-controlled case.

Estimating Pan evolutionary history from nucleotide site patterns

Introgression appears increasingly ubiquitous in the evolutionary history of various taxa, including humans. However, accurately estimating introgression is difficult, particularly when 1) there are many parameters, 2) multiple models fit the data well, and 3) parameters are not simultaneously estimated. Here, we use the software Legofit to investigate the evolutionary history of bonobos (Pan paniscus) and chimpanzees (P. troglodytes) using whole genome sequences. This approach 1) ignores within-population variation, reducing the number of parameters requiring estimation, 2) allows for model selection, and 3) simultaneously estimates all parameters. We tabulated site patterns from the autosomes of 71 bonobos and chimpanzees representing all five extant Pan lineages. We then compared previously proposed demographic models and estimated parameters using a deterministic approach. We further considered sex bias in Pan evolutionary history by analyzing the site patterns from the X chromosome. Introgression from bonobos into the ancestor of eastern and central chimpanzees and from western into eastern chimpanzees best explained the autosomal site patterns. This second event was substantial with an estimated 0.21 admixture proportion. Estimates of effective population size and most divergence dates are consistent with previous findings; however, we observe a deeper divergence within chimpanzees at 987 ka. Finally, we identify male-biased reproduction in Pan evolutionary history and suggest that western to eastern chimpanzee introgression was driven by western males mating with eastern females.

Response of the Earth’s Lower Ionosphere to Solar Flares and Lightning-Induced Electron Precipitation Events by Analysis of VLF Signals: Similarities and Differences

The lower ionosphere influences the propagation of electromagnetic (EM) waves, satellite and also terrestrial (anthropic) signals at the time of intense perturbations and disturbances. Therefore, data and modelling of the perturbed lower ionosphere are crucial in various technological areas. An analysis of the lower ionospheric response induced by sudden events during daytime-solar flares and during night-time-lightning-induced electron precipitation was carried out. A case study of the solar flare event recorded on 7 September 2017 and lightning-induced electron precipitation event recorded on 16 November 2004 were used in this work. Sudden events induced changes in the ionosphere and, consequently, the electron density height profile. All data are recorded by Belgrade (BEL) radio station system and the model computation is used to obtain the ionospheric parameters induced by these sudden events. According to perturbed conditions, variation of estimated parameters, sharpness and reflection height differ for analysed cases. Data and results are useful for Earth observation, telecommunication and other applications in modern society.

Estimation the state of the Covid-19 epidemic curve in Mayotte

We study in this work some statistical methods to estimate the parameters resulting from the use of an age-structured contact mathematical epidemic model in order to analyze the evolution of the epidemic curve of Covid-19 in the French overseas department Mayotte from march 13, 2020 to february 26,2021. Using several statistic methods based on time dependent method, maximum likelihood, mixture method, we fit the probability distribution which underlines the serial interval distribution and we give an adapted version of the generation time distribution from Package R0. The best-fit model of the serial interval was given by a mixture of Weibull distribution. Furthermore this estimation allows to obtain the evolution of the time varying effective reproduction number and hence the temporal transmission rates. Finally based on others known estimates parameters we incorporate the estimated parameters in the model in order to give an approximation of the epidemic curve in Mayotte under the conditions of the model. We also discuss the limit of our study and the conclusion concerned a probable impact of non pharmacological interventions of the Covid-19 in Mayotte such us the re-infection cases and the introduction of the variants which probably affect the estimates.

Effect of Hydrogen Coverage on Elastic and Optical Properties of Silicene: A First-Principle Study

The structural, electronic, and optical properties of hydrogenated silicene have been investigated using first-principles DFT calculations. In comparison to pristine silicene, the hydrogenated silicene exhibits high stability, reduced anisotropy, and less birefringence. In the visible range, hydrogenated silicene exhibits a constant refractive index than silicene. The elastic and optical parameters: Young’s modulus (Y), poisson’s ratio (ν), bulk modulus (B), shear modulus (G), dielectric constant ε(0), refractive index n(0), conductivity threshold (Eth), birefringence Δn(0), and plasmon energy (ħωp) were calculated for the first time for various hydrogen occupancy levels. The estimated parameters are agree well with the experimental and reported values that are available.

Integrated reporting as a determinant of changing the targets of economic analysis of sustainable development in the face of challenges

Subject. The article deals with the revision of targets in the economic analysis, enabling timely identification of factors of value creation, and considering the influence of the interests of stakeholders. Objectives. The purpose is to identify targets of economic analysis in connection with changes in information requests of stakeholders and requirements for corporate reporting, concerning the disclosure of opportunities for sustainable development in the context of challenges. Methods. We performed a content analysis of changes in information requests of stakeholders and requirements for the composition and content of types of corporate reporting. The study employs methods of systems, comparative, structural, and logical analysis. Results. The demonstration of excellence by management and investors in understanding the values and the best ways to achieve goals creates threats, and, by definition, is a challenge that should be reflected in integrated reporting. The system of indicators and methods of analysis should be aimed at identifying conflicts and take into account the interests of stakeholders, which will ensure the balance of resources used in creating value. Conclusions. The determinant of the development of corporate reporting is integration, in which a significant amount of information should contain estimated parameters of economic, social and environmental problems and threats specific to major challenges. It will ensure the most effective interaction of stakeholders in managing corporate risks associated with all types of capital. Such disclosure will lead to a synergistic effect in making strategic decisions on sustainable development.

Online Estimation of Terminal Airspace Sector Capacity from ATC Workload

Neural Partial Differentiation (NPD) approach is applied to estimate terminal airspace sector capacity in real-time from the ATC (Air Traffic Controller) dynamical neural model with permissible safe separation and affordable workload. A neural model of a multi-input-single-output (MISO) ATC dynamical system is primarily established and used to estimate parameters from the experimental data using NPD. Since the relative standard deviations of these estimated parameters are lesser, the predicted neural model response is well matched with the intervention of ATC workload. Moreover, the proposed neural network-based approach works well with the experimental data online as it does not require the initial values of model parameters that are unknown in practice.