Geometric parameters optimization of a two-dimensional phoxonic crystal with dual forbidden band characteristics

In this paper, a novel phoxonic crystal (PxC) structure composed of silicon, with optimal dual phononic band gap (PNBG) and photonic band gap (PTBG), is presented. Using the finite element analysis method, both the transmission characteristics and dispersion relation of PNBG and PTBG are calculated, and the existence of dual BGs is demonstrated by the means of the analysis of transmission for the PxC structure. The influences of structural parameters on the dual forbidden band characteristics are further explored, the sensitive structure parameters can be determined: the width of elastic beams, the length of square silicon, and the length of square hole. Using the orthogonal test, 25 experimental runs based on 3-factor and 5-level experiment are performed to finish the numerical experimental design and analysis. Four functional relationships can be acquired between the three sensitive parameters and dual BGs. Finally, the unified objective function method is employed to perform the construction of the single objective optimization model for the purpose of obtaining the optimal dual BGs and the corresponding optimal parameter combinations of the PxC structure. Such scheme can be used as the potential optimization way, which may find wide application in the development and design of PxCs.

Modeling the COVID-19 Epidemic With Multi-Population and Control Strategies in the United States

As of January 19, 2021, the cumulative number of people infected with coronavirus disease-2019 (COVID-19) in the United States has reached 24,433,486, and the number is still rising. The outbreak of the COVID-19 epidemic has not only affected the development of the global economy but also seriously threatened the lives and health of human beings around the world. According to the transmission characteristics of COVID-19 in the population, this study established a theoretical differential equation mathematical model, estimated model parameters through epidemiological data, obtained accurate mathematical models, and adopted global sensitivity analysis methods to screen sensitive parameters that significantly affect the development of the epidemic. Based on the established precise mathematical model, we calculate the basic reproductive number of the epidemic, evaluate the transmission capacity of the COVID-19 epidemic, and predict the development trend of the epidemic. By analyzing the sensitivity of parameters and finding sensitive parameters, we can provide effective control strategies for epidemic prevention and control. After appropriate modifications, the model can also be used for mathematical modeling of epidemics in other countries or other infectious diseases.

Ultrasonic wave propagation in thermally treated concrete up to 400 ºC

The ultrasonic pulse velocity, obtained by ultrasonic non-destructive testing, has been applied to evaluate the concrete integrity. The attenuation parameters have shown more sensitivity to damage detection in the microstructure of concrete since they consider the entire ultrasonic waveform. However, it is still necessary to evaluate the sensitivity of those parameters to thermally damaged concrete. This work aims to assess the behavior and the sensitivity of the following ultrasonic parameters: pulse and group velocities, maximum amplitude, total energy, accumulated energy, and time instants corresponding to 25%, 50%, and 75% of the energy, in detecting changes due to thermal degradation of the concrete. A sample of 39 cylindrical concrete specimens with 100 mm in diameter and 300 mm in length and C25 strength class was used. The sample was distributed into 5 groups heated between 20 and 400 ºC until the internal temperature of the specimens became homogeneous. The groups were cooled inside a muffle furnace until reaching 150 ºC. Subsequently, they were exposed to the ambient temperature and humidity of the laboratory environment for, at least, 24 hours prior to the tests of mass loss, ultrasound, and compressive strength. The results show that the ultrasonic parameters are sensitive to the thermal degradation of the concrete. The pulse velocity, the accumulated energy, and the time instants corresponding to percentages of the energy decrease monotonically as the temperature increases. The group velocity shows significant dispersions, while the maximum amplitude and the total energy increase at 200 ºC. The results led to the conclusion that the pulse velocity is the least sensitive parameter, while the time instants corresponding to 25%, 50%, and 75% of the energy are the most sensitive parameters in detecting changes due to thermal degradation of the concrete.

Fractional order COVID-19 model with transmission rout infected through environment

<abstract><p>In this paper, we study a fractional order COVID-19 model using different techniques and analysis. The sumudu transform is applied with the environment as a route of infection in society to the proposed fractional-order model. It plays a significant part in issues of medical and engineering as well as its analysis in community. Initially, we present the model formation and its sensitivity analysis. Further, the uniqueness and stability analysis has been made for COVID-19 also used the iterative scheme with fixed point theorem. After using the Adams-Moulton rule to support our results, we examine some results using the fractal fractional operator. Demonstrate the numerical simulations to prove the efficiency of the given techniques. We illustrate the visual depiction of sensitive parameters that reveal the decrease and triumph over the virus within the network. We can reduce the virus by the appropriate recognition of the individuals in community of Saudi Arabia.</p></abstract>

Using an Uncertainty Quantification Framework to Calibrate the Runoff Generation Scheme in E3SM Land Model V1

Runoff is a critical component of the terrestrial water cycle and Earth System Models (ESMs) are essential tools to study its spatio-temporal variability. Runoff schemes in ESMs typically include many parameters so model calibration is necessary to improve the accuracy of simulated runoff. However, runoff calibration at global scale is challenging because of the high computational cost and the lack of reliable observational datasets. In this study, we calibrated 11 runoff relevant parameters in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) using an uncertainty quantification framework. First, the Polynomial Chaos Expansion machinery with Bayesian Compressed Sensing is used to construct computationally inexpensive surrogate models for ELM-simulated runoff at 0.5° × 0.5° for 1991–2010. The main methodological advance in this work is the construction of surrogates for the error metric between ELM and the benchmark data, facilitating efficient calibration and avoiding the more conventional, but challenging, construction of high-dimensional surrogates for ELM itself. Second, the Sobol index sensitivity analysis is performed using the surrogate models to identify the most sensitive parameters, and our results show that in most regions ELM-simulated runoff is strongly sensitive to 3 of the 11 uncertain parameters. Third, a Bayesian method is used to infer the optimal values of the most sensitive parameters using an observation-based global runoff dataset as the benchmark. Our results show that model performance is significantly improved with the inferred parameter values. Although the parametric uncertainty of simulated runoff is reduced after the parameter inference, it remains comparable to the multi-model ensemble uncertainty represented by the global hydrological models in ISMIP2a. Additionally, the annual global runoff trend during the simulation period is not well constrained by the inferred parameter values, suggesting the importance of including parametric uncertainty in future runoff projections.

Open-system behaviour of detrital zircon during weathering: an example from the Palaeoproterozoic Pretoria Group, South Africa

Detrital zircon in six surface samples of sandstone and contact metamorphic quartzite of the Magaliesberg and Rayton formations of the Pretoria Group (depositional age c. 2.20–2.06 Ga) show a major age fraction at 2.35–2.20 Ga, and minor early Palaeoproterozoic – Neoarchaean fractions. Trace-element concentrations vary widely, with Ti, Y and light rare earth elements (LREEs) spanning over three orders of magnitude. REE distribution patterns range from typical zircon patterns (LREE depletion, heavy REE enrichment, well-developed positive Ce and negative Eu anomalies) to patterns that are flat to concave downwards, with indistinct Ce and Eu anomalies. The change in REE pattern correlates with increases in alteration-sensitive parameters such as Ti concentration and (Dy/Sm) + (Dy/Nd), U–Pb discordance and content of common lead, and with a gradual washing-out of oscillatory zoning in cathodoluminescence images. U and Th concentrations also increase, but Th/U behaves erratically. Discordant zircon scatters along lead-loss lines to zero-age lower intercepts, suggesting that the isotopic and chemical variations are the results of disturbance long after deposition. The rocks sampled have been in a surface-near position (at least) since Late Cretaceous time, and exposed to deep weathering under intermittently hot and humid conditions. In this environment, even elements commonly considered as relatively insoluble could be mobilized locally, and taken up by radiation-damaged zircon. Such secondary alteration effects on U–Pb and trace elements can be expected in zircon in any ancient sedimentary rock that has been exposed to tropical–subtropical weathering, which needs to be considered when interpreting detrital zircon data.

The Diagnostic Value of Pulsar Perimetry, Optical Coherence Tomography, and Optical Coherence Tomography Angiography in Pre-Perimetric and Perimetric Glaucoma

The purpose of this article is to investigate the diagnostic value of Pulsar perimetry (PP), optical coherence tomography (OCT), and optical coherence tomography angiography (OCTA) in pre-perimetric glaucoma (PPG) and perimetric glaucoma (PG). This retrospective cross-sectional study included 202 eyes (145 eyes in the control group, 40 eyes in the PPG group, and 17 eyes in the PG group) from 105 subjects. The results were analyzed by paired t-tests and Wilcoxon signed-rank test. The area under the curve (AUC), sensitivity, and specificity were used to evaluate the diagnostic accuracy. Pearson correlation was used to investigate the relationships of each parameter. The most sensitive parameters for differentiating the control group from the PPG group by using Pulsar, OCT, and OCTA were square loss variance of PP (AUC = 0.673, p < 0.001), superior ganglion cell complex thickness (AUC = 0.860, p < 0.001), and superior-hemi retina thickness (AUC = 0.817, p < 0.001). In the PG group, the most sensitive parameters were mean defect of PP (AUC = 0.885, p < 0.001), whole image of ganglion cell complex thickness (AUC = 0.847, p < 0.001), and perifoveal retina thickness (AUC = 0.833, p < 0.001). The mean defect of PP was significantly correlated with vascular parameters (radial peripapillary capillary (RPC), p = 0.008; vessel density of macular superficial vascular complex (VDms), p = 0.001; vessel density of macular deep vascular complex (VDmd), p = 0.002). In conclusion, structural measurements using OCT were more sensitive than vascular measurements of OCTA and functional measurements of PP for PPG, while PP was more sensitive than the structural and vascular measurements for PG. The mean defect of PP was also shown to be highly correlated with the reduction of vessel density.

Food and environmental degradation as causative agents of honey bee colonies decline: Mathematical model approach

In this research, a new compartment model of honey bee population is developed to study the effects of gradual change of food availability and environmental degradation on bee population growth and development. The model is proved to be mathematical well posed and a non-trivial equilibrium point is shown to exist and asymptotically stable under certain conditions. The model predicts a critical threshold environmental degradation rate above which the population size of bees decline and subsequently collapse. Low environmental degradation and high food availability leads to stable bee population. Global sensitivity analysis is conducted to determine the most sensitive parameters of the model that can lead to colony collapse disorder. Numerical simulations are conducted to illustrate all the results.

Comparison of Three Daily Rainfall-Runoff Hydrological Models Using Four Evapotranspiration Models in Four Small Forested Watersheds with Different Land Cover in South-Central Chile

We used the lumped rainfall–runoff hydrologic models Génie Rural à 4, 5, 6 paramètres Journalier (GR4J, GR5J and GR6J) to evaluate the most robust model for simulating discharge on four forested small catchments (<40 ha) in south-central Chile. Different evapotranspiration methods were evaluated: Oudin, Hargreaves–Samani and Priestley–Taylor. Oudin’s model allows the achievement of the highest efficiencies in the flow simulation. The more sensitive parameters for each model were identified through a Generalized Probability Uncertainty Estimation (GLUE) model. Our results demonstrate that the three hydrological models were capable of efficiently simulating flow in the four study catchments. However, the GR6J model obtained the most satisfactory results in terms of simulated to measured streamflow closeness. In general, the three models tended to underestimate peak flow, as well as underestimate and overestimate flow events in most of the in situ observations, according to the probability of non-exceedance. We also evaluated the models’ performance in a simulation of summer discharge due to the importance of downstream water supply in the months of greatest scarcity. Again, we found that GR6J obtained the most efficient simulations.