2063 research outputs found
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The effects of public health measures on severe dengue cases: An optimal control approach
Get PDFDengue fever is the most important viral mosquito-borne disease worldwide, with approximately 3.9 billion people at risk of acquiring dengue infection. Measures against mosquito bite combined with vector control programs to reduce mosquito population have been used in endemic countries for several years. Most recently, vaccines have become an important ally to prevent and control disease transmission. Economic costs of dengue control programs vary from region to region and therefore designing an optimal control strategy must be evaluated at different epidemiological contexts. Using a multi-strain vector-host mathematical model, we investigate the impact of different control measures to reduce dengue prevalence. A detailed sensitivity analysis to identify the key parameters influencing disease transmission is followed by an exploratory analysis of the possible solutions for the optimal control problem considering preventive measures to avoid mosquito bites, reduce mosquito population and vaccinate human hosts. The proposed cost functional includes a weighted sum of several efforts (not necessarily quantified as economic costs) for the controls which are evaluated alone and combined. The control system is analyzed using the Pontryagin`s Principle for optimal control where different strategies are compared. Our results have shown that the simultaneous use of intervention measures are highly effective to reduce disease cases, however, the use of a single control measure can be as effective as the use of two or more controls combined. A careful evaluation of the epidemiological scenario is advised before designing strategies for disease prevention and control, allowing an optimal allocation of the public health resources
Impact of outdoor air pollution on severity and mortality in COVID-19 pneumonia
Get PDFThe relationship between exposure to air pollution and the severity of coronavirus disease 2019 (COVID-19) pneumonia and other outcomes is poorly understood. Beyond age and comorbidity, risk factors for adverse outcomes including death have been poorly studied. The main objective of our study was to examine the relationship between exposure to outdoor air pollution and the risk of death in patients with COVID-19 pneumonia using individual-level data. The secondary objective was to investigate the impact of air pollutants on gas exchange and systemic inflammation in this disease. This cohort study included 1548 patients hospitalised for COVID-19 pneumonia between February and May 2020 in one of four hospitals. Local agencies supplied daily data on environmental air pollutants (, , , , and ) and meteorological conditions (temperature and humidity) in the year before hospital admission (from January 2019 to December 2019). Daily exposure to pollution and meteorological conditions by individual postcode of residence was estimated using geospatial Bayesian generalised additive models. The influence of air pollution on pneumonia severity was studied using generalised additive models which included: age, sex, Charlson comorbidity index, hospital, average income, air temperature and humidity, and exposure to each pollutant. Additionally, generalised additive models were generated for exploring the effect of air pollution on C-reactive protein (CRP) level and Sp/Fi at admission. According to our results, both risk of COVID-19 death and CRP level increased significantly with median exposure to , , and , while higher exposure to , and was associated with lower Sp/Fi ratios. In conclusion, after controlling for socioeconomic, demographic and health-related variables, we found evidence of a significant positive relationship between air pollution and mortality in patients hospitalised for COVID-19 pneumonia. Additionally, inflammation (CRP) and gas exchange (Sp/Fi) in these patients were significantly related to exposure to air pollution
Nektar++: Development of the Compressible Flow Solver for Large Scale Aeroacoustic Applications
Get PDFA recently developed computational framework for jet noise predictions
is presented. The framework consists of two main components, focusing on
source prediction and noise propagation. To compute the noise sources, the
turbulent jet is simulated using the compressible flow solver implemented
in the open-source spectral/hp element framework Nektar++, which solves
the unfiltered Navier-Stokes equations on unstructured grids using the high-
order discontinuous Galerkin method. This allows high-order accuracy to be
achieved on unstructured grids, which in turn is important in order to accu-
rately simulate industrially relevant geometries. For noise propagation, the
Ffowcs Williams - Hawkings method is used to propagate the noise between
the jet and the far-field. The paper provides a detailed description of the com-
putational framework, including how the different components fit together
and how to use them. To demonstrate the framework, two configurations of a
single stream subsonic jet are considered. In the first configuration, the jet is treated in isolation, whereas in the second configuration, it is installed under
a wing. The aerodynamic results for these two jets show strong agreement
with experimental data, while some discrepancies are observed in the acous-
tic results, which are discussed. In addition to this, we demonstrate close to
linear scaling beyond 100, 000 processors on the ARCHER2 supercomputer
Statistical Modelling for Recurrent Events in Sports Injury Research with Applications to Football Injury Data
Get PDFSports injuries stand as undesirable side effects of athletic participation, carrying serious consequences for athletes' health, their professional careers, and overall team performance. With the growing availability of data, there has been an increasing reliance on statistical models to monitor athletes' health and mitigate the risks of injuries.
In this dissertation, we present advanced statistical modelling approaches and software tools for sports injury data. Our focus is on the time-varying and recurrent nature of injury occurrences, and we pursue three primary objectives: (a) identifying biomechanical risk factors using variable selection methods and shared frailty Cox models, (b) developing a flexible recurrent time-to-event approach to model the effects of training load on subsequent injuries, and (c) creating dedicated statistical tools through the statistical open-source software \textbf{R}. These objectives are driven by interdisciplinary research, conducted in close collaboration with the Medical Services of Athletic Club, and are motivated by real-world applications. Specifically, the work is based on three distinct data sets: functional screening tests data, external training load data, and web-scraped football injury data. The statistical advancements developed contribute to ongoing efforts in sports injury prevention, providing insights, methodologies, and accessible software implementations for sports medicine practitioners
The crystal chemistry and reactivity of ternary Na2Fe3Cl8 from the NaCl-FeCl2 system and its potential application as coating layer for cathode in sodium ion batteries
Get PDFThis report explores theoretical and experimental methods to characterize the ternary phases arising from the NaCl + FeCl2 system at both low (150 °C) and high temperatures (550 °C), through milling and evaporation processing techniques. We found that Na2Fe3Cl8 is the only metastable ternary compound produced in either case and only at high temperatures, which is in good qualitative agreement with density functional theory calculations performed with the recent r2SCAN metaGGA functional. The elementary, crystallographic, and grain structure information on Na2Fe3Cl8 collected using a combination of x-ray diffraction, scanning electron microscopy, energy dispersive, and Mössbauer spectroscopy is described and discussed in detail. Na2Fe3Cl8 is determined to have a layered trigonal structure in the R3m space group. Other ternary stable or metastable ternary phases such as Na6FeCl8 and Na2FeCl4 were not observed, which is likely the result of decomposition occurring beyond 400 °C. While the structure of Na2Fe3Cl8 makes it inadequate as a potential cathode in Na-ion batteries, Na2Fe3Cl8 may operate as a suitable coating layer to regulate the passage of ions from electrolytes to active electrode materials without interfacial degradation
Challenging test problems for multi- and many-objective optimization
Get PDFIn spite of the extensive studies that have been conducted regarding the construction of multi-objective test problems, researchers have mainly focused their interests on designing complicated search spaces, disregarding, in many cases, the design of the Pareto optimal fronts of the problems. In this regard, the work related to scalable multi-objective test problems – i.e., problems that can be formulated for an arbitrary number of objectives – has been much less studied. This paper introduces a new set of continuous and box-constrained multi-objective test problems which are scalable in both the number of objectives and in the number of decision variables. Each test problem included in the proposed test suite has a peculiar Pareto front different from those observed in the existing scalable multi-objective test suites. In addition to different Pareto fronts, the proposed test suite introduces features related to the search space that place obstacles that complicate exploring Pareto optimal solutions. Such features can be easily switched on and off by the user to analyze specific mechanisms of multi-objective evolutionary algorithms (MOEAs). The components used in the proposed test suite can be used as a toolkit to construct new test instances not included in this set of problems. To illustrate the use and difficulties of the proposed test suite, some experiments are presented adopting three MOEAs using selection mechanisms based on Pareto optimality, decomposition, and a performance indicator (hypervolume)
Dirac operators with infinite mass boundary conditions on unbounded domains with infinite corners
No full textWell-posedness of the Kolmogorov two-equation model of turbulence in optimal Sobolev spaces
Get PDFIn this paper, we study the well-posedness of the Kolmogorov two-equation model of turbulence in a periodic domain Td, for space dimensions d = 2,3. We admit the average turbulent kinetic energy k to vanish in part of the domain, i.e. we consider the case k ≥ 0; in this situation, the parabolic structure of the equations becomes degenerate.
For this system, we prove a local well-posedness result in Sobolev spaces Hs, for any s > 1+d/2. We expect this regularity to be optimal, due to the degeneracy of the system when k ≈ 0. We also prove a continuation criterion and provide a lower bound for the lifespan of the solutions. The proof of the results is based on Littlewood- Paley analysis and paradifferential calculus on the torus, together with a precise commutator decomposition of the non-linear terms involved in the computations
On the Use of Second Order Neighbors to Escape from Local Optima
Get PDFDesigning efficient local search based algorithms requires to consider the specific properties of the problems. We introduce a simple and effi- cient strategy, the Extended Reach, that escapes from local optima ob- tained from a best improvement local search and apply it to the linear ordering problem (LOP), the traveling salesperson problem (TSP) and the quadratic assignment problem (QAP). This strategy is based on two landscape properties observed in the literature. First, it considers that a local optimum is usually located in the frontier of its own attraction basin, and thus, it is enough to inspect the second order neighbors to reach a (better) solution inside an attraction basin of a better local optimum. Second, taking into account that for the LOP and specific neighborhoods it is possible to discard solutions without the need of being evaluated, we extend this result to the TSP with the 2-opt neighborhood to avoid the unnecessary evaluation of solutions. Efficient ways of evaluating the second order neighbors are also presented, based on the cost differences, reducing significantly the computation cost. Experimental results on ran- dom and benchmark instances show that our strategy, indeed, escapes from local optima despite its simplicity.PID2019-104966GB-I00
AXA Research Fun
Sharp constants in inequalities admitting the Calderón transference principle
Get PDFThe aim of this note is twofold. First, we prove an abstract version of the Calderón transference principle for inequalities of admissible type in the general commutative multilinear and multiparameter setting. Such an operation does not increase the constants in the transferred inequalities. Second, we use the last information to study a certain dichotomy arising in problems of finding the best constants in the weak type and strong type inequalities for one-parameter ergodic maximal operators.Basque Government (BERC 2022-2025),
Spanish State Research Agency (CEX2021-001142-S and RYC2021-031981-I),
Foundation for Polish Science (START 032.2022)