Dynamic Growth Model Research Articles

Effect of Thermal Growth Oxide Composition and Morphology on Local Stresses in Thermal Barrier Coatings

The failure of thermal barrier coatings (TBCs) during operation depends mainly on the thermal mismatch between the ceramic top coat (TC) and the metal bond coat (BC). The thermal mismatch at the interface is influenced by the dynamic changes in the composition and morphology of the thermally grown oxide (TGO) between TC and BC during thermal cycling. This work focuses on the establishment of a TGO dynamic growth model, which considers the changes in TGO composition and morphology for investigating the effect of dynamic growth of TGO on local mismatch stresses during thermal cycling. The results show that the sharp locations at the TGO/BC interface are more prone to high tensile stresses during thermal cycling due to the uneven growth behavior of TGO, leading to crack initiation. The valley region of the interface is in a state of compressive stress σxx during the early stages of thermal exposure. The peak region preferentially forms a concentration of tensile stress σyy. Once large-scale "layer" (Ni, Co)Al2O4-based spinel-like mixed oxides(MO) growth occurs in TGO, the stress σxx changes from compressive stress to tensile stress in the valley region, eventually forming high tensile stress (Max: +158 MPa). The maximum tensile stress σyy in the peak region is increased to 256 MPa, which is more than two times larger than the early period of thermal exposure. As a result, the dramatic changes in local stresses seriously affect the time and location of microcracks.

Biological conversion of methane to bioplastics: Kinetics, stoichiometry, and thermodynamic considerations for process optimization

Bioconversion of methane, a potent greenhouse gas, into biodegradable polyhydroxybutyrate (PHB), is an attractive option for methane management. Aerobic bioreactors designed for α-proteobacterial (Type II) methanotrophs can be operated to enable growth and PHB accumulation under nutrient-limiting conditions when fed CH4as their sole source of carbon and energy. Using first principles, we develop and test a dynamic model for growth and PHB accumulation. The model includes the kinetics and stoichiometry of Type II methanotrophs and PHB accumulation, acid/base equilibria, metabolic heat release, and physicochemical transport of gaseous substrates through aqueous media. The model was then validated using an experimental dataset extracted from the literature. The numerical simulation accurately describes growth and PHB accumulation. After model validation, we explored the impacts of gas delivery rate, reactor pressure, metabolic heat release, and pH on productivity and energy efficiency. Our results indicate that high mass-transfer rates and high-pressure operation are not needed to achieve significant PHB productivity, on the order of grams per liter per hour. The model also identifies operational windows that decrease energy inputs for cooling and mass transfer of oxygen and methane while still enabling significant PHB productivity.

Analysis and evaluation of a dynamic model for greenhouse lettuce growth

Aim of study: We analyzed and evaluated a nonlinear dynamic crop growth model called NICOLET B3, which can predict the dry and fresh matter content of lettuce in greenhouses. Area of study: Calibration was performed using experimental data obtained from the literature. The experiment was carried out in Saltillo, Mexico, and in a greenhouse in Beijing, China. Material and methods: We identified and discussed the feasibility of the studied model with multi-dimensional evaluation criteria. Meanwhile, a sensitivity analysis of input variables was conducted. After that, the least square identification method was used to calibrate the most sensitive parameter values to improve the robustness of the model. Main results: Results demonstrate that: i) the NICOLET B3 model is able to predict the fresh and dry matter production of lettuce with satisfactory accuracy verified (R2 = 0.9939 for fresh matter and R2 = 0.9858 for dry matter); ii) temperature has the most obvious impact on the model performance, compared with photosynthetically active radiation and CO2 concentration; iii) the model could perform well with only two inputs. Research highlights: Simulation results of evaluated NICOLET B3 model have a perfect goodness-of-fit. A method of calibrating parameters of the model and sensitivity analysis of three input variables of the model can facilitate its application.

A data-driven framework to manage uncertainty due to limited transferability in urban growth models

The processes of urban growth vary in space and time. There is a lack of model transferability, which means that models estimated for a particular study area and period are not necessarily applicable for other periods and areas. This problem is often addressed through scenario analysis, where scenarios reflect different plausible model realisations based typically on expert consultation. This study proposes a novel framework for data-driven scenario development which, consists of three components - (i) multi-area, multi-period calibration, (ii) growth mode clustering, and (iii) cross-application. The framework finds clusters of parameters, referred to as growth modes: within the clusters, parameters represent similar spatial development trajectories; between the clusters, parameters represent substantially different spatial development trajectories. The framework is tested with a stochastic dynamic urban growth model across European functional urban areas over multiple time periods, estimated using a Bayesian method on an open global urban settlement dataset covering the period 1975–2014.The results confirm a lack of transferability, with reduced confidence in the model over the validation period, compared to the calibration period. Over the calibration period the probability that parameters estimated specifically for an area outperforms those for other areas is 96%. However, over an independent validation period, this probability drops to 72%.Four growth modes are identified along a gradient from compact to dispersed spatial developments. For most training areas, spatial development in the later period is better characterized by one of the four modes than their own historical parameters. The results provide strong support for using identified parameter clusters as a tool for data-driven and quantitative scenario development, to reflect part of the uncertainty of future spatial development trajectories.A promising further application is to use the growth modes to characterize past spatial development patterns. A trend of increasingly dispersed patterns could be identified over the studied functional urban areas which calls for more detailed explorations.

Modelling differences in reproductive effort between iteroparous and semelparous reproductive strategies in Bromeliaceae

Abstract Quantifying reproductive effort (RE), the trade-off between devoting resources to reproduction versus individual growth, in plants presents a number of challenges. Of particular interest is comparing RE between reproductive strategies, such as those in Bromeliaceae: semelparous, where individuals undergo a one-time and subsequently lethal sexual reproductive event, versus iteroparous, where individuals reproduce sexually multiple times by producing clonal offshoots called pups. We introduce a dynamic model of vegetative and reproductive growth in long-lived Bromeliaceae rosettes accounting for the allocation of resources over developmental time. We compare multiple definitions of RE in semelparous and iteroparous Bromeliaceae at critical times during development and over the entire reproductive life of the individual. While others have posited that semelparous taxa exhibit higher RE than comparable iteroparous taxa, our results indicate that this will only occur in limited circumstances: when RE is calculated over the lifespan of a rosette started from seed, semelparous RE is greater when pup mass is accounted for as if it were purely vegetative; or when RE is calculated over the lifespan of the genetic individual, semelparous RE is greater when the ratio of vegetative to inflorescence mass in each pup is greater than that of the originating rosette started from seed.

Modelling Plant Growth Based on Gompertz, Logistic Curve, Extreme Gradient Boosting and Light Gradient Boosting Models Using High Dimensional Image Derived Maize (<i>Zea mays</i> L.) Phenomic Data

Modelling of plant growth is vital for hypotheses testing and carrying out virtual plant growth and development experiments, which may otherwise take a long time under field conditions. Modelling of plant growth has been aggravated by new phenotyping platforms that generate high dimensional data non-destructively over the entire growth time of a plant using a set of camera system. Such platforms generate high-throughput phenomic data, which is complex and constitute many features collected at multiple growth points for the same plant. However, the classical models are limited in that they can only model a single feature at a time. The objective of this study was to apply dynamic plant growth models that could be used to dissect complex relationships between plant growth and development using several modelling strategies. These included sigmoid, light GBM and XGBoost models. The image derived phenomic data was obtained from the Leibniz Institute of Plant Genetics and Crop Plant Research Gatersleben, Germany. The models were fitted using R statistical software and compared based on RMSE, R-squared, AIC and BIC performance metrics. The results showed that the XGBoost (RMSE = 2.1641) and Light GBM (RMSE = 2.7776) performed better than the Gompertz (RMSE = 3.8378) and the logistic function (RMSE = 3.8378) models in modelling maize plant growth. The XGBoost model (RMSE = 2.1641) showed better performance than Light GBM model (RMSE = 2.7776) in modelling maize plant growth. The Gompertz model using plant volume had AIC and BIC values for 139738.3 and 139763.4, respectively. The Gompertz model for plant side area had AIC and BIC values for 98436.15 and 98461.31, respectively. The logistic function model for plant volume had AIC and BIC values for 139749.2 and 139774.4, respectively. The logistic function model for plant side area had AIC and BIC values for 98415.95 and 98441.11, respectively. The Gompertz model and logistic function models showed almost the same performance in modelling maize plant growth. The non-parametric models, the XGBoost and light GBM, were found to perform better than the classical models (Gompertz and logistic functions) in modelling maize plant growth. Therefore, the study recommends the use of XGBoost as a generic model to fit high dimensional and complex phenotypic data in modelling plant growth and prediction of plant biomass yield at different growth points.

Validation of a mechanistic dynamic pre-weaned lamb growth and body composition simulation model

Lamb growth and body composition simulation models can provide valuable insights into the assessment of feeding regimens and rearing systems, allowing optimisation of farm profitability without the need for in-vivo trials. The objective of the present study was to evaluate the performance of a published mechanistic dynamic model on the growth and body composition of pre-weaned lambs using independently published data sets. Data generated from eight treatments, representing three artificial lamb rearing experiments (n = 77 lambs) were used. Initial body composition data were obtained from four lambs at approximately two days of age, with the remaining lambs being provided with defined nutritional treatments until the trial end-point. The body composition of lambs at slaughter was determined in six treatments across two experiments. Feed intake and live weight (LW) of lambs were recorded in all treatments. The LW, average daily gain (ADG) and ash deposition rates of lambs were accurately simulated by the model (paired t-test, P > 0.05). The overall empty body weight (EBW), gutfill, protein and fat deposition rates were overestimated, and water deposition rate was underestimated by the model (paired t-test, P < 0.05). Collectively, these results suggest that the model can be used at the farm level with acceptable accuracy to determine lamb growth. Further improvements in the model are required for protein, fat and water deposition rates, gutfill and EBW to make it more applicable for wider usage.

Multi-scale model suggests the trade-off between protein and ATP demand as a driver of metabolic changes during yeast replicative ageing.

The accumulation of protein damage is one of the major drivers of replicative ageing, describing a cell's reduced ability to reproduce over time even under optimal conditions. Reactive oxygen and nitrogen species are precursors of protein damage and therefore tightly linked to ageing. At the same time, they are an inevitable by-product of the cell's metabolism. Cells are able to sense high levels of reactive oxygen and nitrogen species and can subsequently adapt their metabolism through gene regulation to slow down damage accumulation. However, the older or damaged a cell is the less flexibility it has to allocate enzymes across the metabolic network, forcing further adaptions in the metabolism. To investigate changes in the metabolism during replicative ageing, we developed an multi-scale mathematical model using budding yeast as a model organism. The model consists of three interconnected modules: a Boolean model of the signalling network, an enzyme-constrained flux balance model of the central carbon metabolism and a dynamic model of growth and protein damage accumulation with discrete cell divisions. The model can explain known features of replicative ageing, like average lifespan and increase in generation time during successive division, in yeast wildtype cells by a decreasing pool of functional enzymes and an increasing energy demand for maintenance. We further used the model to identify three consecutive metabolic phases, that a cell can undergo during its life, and their influence on the replicative potential, and proposed an intervention span for lifespan control.

Geospatial Environmental Influence on Forest Carbon Sequestration Potential of Tropical Forest Growth in Hainan Island, China

Tropical forests, although covering only 7% of the world’s land area, have great forest carbon sequestration capacity, accounting for 20% of the world’s forest carbon sink. However, the growth dynamics and forest carbon sink potential of tropical forests remain unclear. Hainan Island is going to be China’s forest carbon trading center. Therefore, accurately assessing the future forest carbon sink potential of Hainan Island’s tropical forest is crucial. In this study, 393 forest permanent sample plots in Hainan Island in 2003, 2008, 2013, and 2018 were selected as the research objects. The dynamic model of tropical forest growth with the geospatial environmental indicators was established based on the measured and most accurate annual diameter at breast height (DBH) growth factors. The DBH growth prediction’s bias ranged from 0.46 to 0.07 cm, RMSE ranged from 1.50 to 5.29 cm, bias% ranged from -2.96 to 0.55%, and RRMSE ranged from 12.18 to 34.30%. In addition, the geospatial environmental indicators of forest growth provide scientific guidance for future ecological protection and land evolution of Hainan Island. Based on DBH–tree height–volume, volume–biomass, and biomass–forest carbon storage relationships, forest carbon sequestration potential could be accurately evaluated by DBH growth. The results show that within the next 30 years, the forest carbon sequestration in Hainan Island will account for 1.8% of the total forest carbon sequestration in China, while the forest area will only account for 0.88% of the total forest area in China. It is roughly estimated that in the next 30 years, the total carbon sink of the tropical forest in Hainan Island will be 83.59 TgC. This study further proves that the annual increase in DBH can accurately assess the forest carbon sink potential of the forest. The forest carbon sink prediction based on the annual increase in DBH can provide data support and theoretical basis for forest carbon sink trading between forest farms and enterprises.

The Impact of Foreign Aid on Economic Growth in Africa: Empirical Evidence from Low Income Countries

This article aims to shed some insights into the ongoing debate on the aid-growth nexus by examining whether sources of aid matter in explaining aid effectiveness. In doing so, we consider three main proxies for bilateral aid based on three sources of aid such as Total Aid (TA); Traditional Donors aid (TDA) and Non-Traditional Donors aid (NTDA) as independent variables in a dynamic panel growth model within a system GMM framework. The study uses a panel dataset from 25 Low-Income Countries (LICs) in Africa over the period 2000–2017. The main findings show that the impact of aid on economic growth appears to be negative and significant for TA and TDA proxies, while it is positive but insignificant when the aid proxy is NTDA. A relatively larger share of TA and TDA disbursement away from the direct growth-enhancing productive sectors towards the unproductive sectors seems to have contributed to their strong negative impact on growth. The key policy implication is that governments in LICs in Africa and donors should work in collaboration to design effective ways to ensure that TDA should target the direct growth-enhancing sectors.

Corporate social responsibility, social optimum, and the environment-growth tradeoff

This paper examines the implications of environmental corporate social responsibility (CSR) for the environment-growth tradeoff and social optimum in a dynamic general equilibrium growth model. We show that environmental CSR activity loosens the tradeoff between the environment and growth, but it cannot achieve the social optimum. Firm participation in environmental CSR induces the perceived CSR of green consumers and increases their willingness to pay. Because the environmental CSR promotes more consumption and increases growth, the environment-growth tradeoff loosens up in the competitive equilibrium. However, to translate the CSR perceived benefits into their profits, firms need some degree of monopoly power to set their prices to capture the stronger demand. CSR is thus promoted as a marketing strategy to help companies achieve their competitive advantage, and becomes a way of product differentiation in the environment of monopolistic competition. Since monopoly power serves as a catalyst, CSR alone cannot achieve the first-best optimum in terms of the environment and growth by fully removing the distortions caused by market imperfection.

Dynamic growth model of Fe2Al5 during dissimilar joining of Al to steel using the variable polarity cold metal transfer (VP-CMT)

Further development of the car lightweight in automotive industry significantly depends on the reliability of the Al/steel dissimilar joint, since more and more Al alloy parts are used in the car manufacturing. It has been proved that the Al/steel dissimilar joint strength can be effectively increased when the intermetallic compound (IMC) growth, especially the Fe2Al5 layer thickness, is controlled at certain level. Because the Fe2Al5 is the dominant phase of the entire IMC layer in the Al/steel dissimilar joint, and cracks usually initiate at this location when damage is conducted. Therefore, for the automotive industry assembly line, the prediction model monitoring the Fe2Al5 layer thickness of each Al/steel weld seam is desired to ensure the dissimilar joint quality and reliability. In the present research, a numerical dynamic growth model based on element diffusion laws is established to calculate the IMC layer thickness of Fe2Al5 phase during the variable polarity cold metal transfer (VP-CMT) welding of aluminum to steel in the function of welding heat input and location. To build up effective connection between the welding heat input and the actual temperature history of Al/steel interface, a finite element analysis (FEA) model is customized for the present VP-CMT process. The Fe2Al5 layer thickness calculation results are further validated using electron back-scattered diffraction (EBSD) characterization under scanning electron microscopy (SEM), confirming a 2.3 % deviation between the model prediction and actual layer thickness.

Thinning-response modifier term in growth models: An application on clonal Tectona grandis Linn F. stands at the amazonian region

Thinning is a widely used silvicultural method in the Tectona grandis Linn. F. (teak) stands, however, limited work has been done on modeling for predicting both short- and long-term responses to this treatment. Dynamic growth models for teak stands in Easter Amazon were developed and evaluated from data of 67 plots measured between two and ten years old. We tested the models of Chapman-Richards, Hossfeld, and Lundqvist-Korf using the generalized algebraic difference approach (GADA) to describe the basal area of the stand, including the effect of thinning, which was quantified from a silvicultural treatment response function. Dominant height was described using a dynamic equation derived onwards by Lundqvist-Korf model, considering one parameter to be site specific, while the stand volume was described as of Chapman-Richards model using the theory of covariates. We used 80% of the data for fitting and 20% for validating the developed models. The following fitting statistics were used: Akaike's information criterion, square root of the mean percent error and estimation efficiency. For the validation, was used the equivalence test (regression based TOST using bootstrap). The equation derived from the Chapman-Richards function from GADA integrated with a thinning modifier provided the best performance in describing stand dynamics. The developed thinning modifier were shown to significantly improve predictions of stand-level basal area growth, and the results showed that models that disregard silvicultural treatment cannot be used to obtain reliable projections of the stands under analysis. The growth models provided detailed and accurate description of the dynamics of teak stands in the Amazon region, allowing for a well-defined maximum volume rotation. Overall, the study highlights the importance of including thinning modifiers in growth and yield models, especially for shade intolerant species, such as teak.

Study on as-cast microstructure of Fe-15Mn-10Al-5Ni-0.8C low density duplex steel

The microstructure of Fe-15Mn-10Al-5Ni-0.8C low density duplex steel ingots was studied by laser confocal scanning calorimetry , metallographic microscopy and scanning electron microscopy. The results indicated that: the microstructure of Fe-15Mn-10Al-5Ni-0.8C low density steel was mainly composed of coarse austenite dendrites and δ-ferrite phase in dendrite. The δ-ferrite could be completely eliminated by solution treatment. A dynamic model of austenite grain growth was established. Through analysis, it was concluded that the critical temperature for rapid austenite growth was 1250 °C. The activation energy for austenite grain growth was 365 KJ/mol as calculated by Sellars’ model.

L-system based dynamic root growth model formulation of aquatic plants

植物根系在地球生物圈物质循环中起到关键性作用.陆生植物中目前基于根系具有对称性和自相似性假设建立的L系统已经做了较好研究，但在水生植物中相关的研究较少，更缺乏根系动态生长模型的构建.本文拟通过发展L系统来模拟水生植物从初生结构到次生结构，从简单根系到复合根系的动态生长过程.根系动态生长模型主要包含根系伸长规则和根系分支规则，并包含由主根与侧根的夹角θ和径向角γ确定初始根系生长方向.特别地，系统建立了2种代表性水生植物——世界上入侵严重的水生植物凤眼莲（Eichhornia crassipes）和被研究较多的水生植物穗状狐尾藻（Myriophyllum spicatum）根系动态生长模型.结果表明凤眼莲成熟根系总长度可达到2042.78 m，可能有利于其占据较多的空间和资源，使得凤眼莲在与本地植物的竞争中占有优势.穗状狐尾藻的总根系长度为73.08 m，由于穗状狐尾藻表现出最为典型的叉状分支构型，表明其对沉水生长环境有较好的适应性.;Root systems play a vital role in material circulation in the biosphere. Based on the two hypotheses of symmetry and self-similarity in the root system, the L-system of terrestrial plants has been well established. However, related research in aquatic plants, particularly for the dynamic root growth model, is rare. This study simulated the dynamic growth processes of a primary to secondary root structure from simple roots to complex roots of aquatic plants. The dynamic root growth model mainly includes root elongation and branching rules and determines the initial root growth direction of the intersectional angle θ and radial angle γ between the main and lateral roots. Specifically, the dynamic root growth model formulations of two representative aquatic plants, the cosmopolitan invasive aquatic plant, water hyacinth (Eichhornia crassipes), and the relatively most studied aquatic plant, Eurasian watermilfoil (Myriophyllum spicatum), were established by applying the L-system. The total length of the root system of mature E. crassipes can reach 2042.78 m, indicating that the species has a high nutrient absorption capability. This may favor resource exploitation, facilitating its competitive ability with native plants. The total length of the M. spicatum root system is 73.08 m; owing to its typical dichotomous branching, this plant has a relatively high adaptation to the aquatic environment.

МОДЕЛИРОВАНИЕ РАЗВИТИЯ ЭКОНОМИКИ В ФОРМЕ ПОЗИЦИОННОЙ ИГРЫ

In this paper, the authors consider the simplest generalization of the dynamic growth model of a single-sector closed economy to a competitive case with discrete time, for which the simplest illustrative example is compiled. The authors summarize the information from game theory necessary to describe the game-theoretic version of the dynamic growth model of a single-sector closed economy. The developed model is considered as a dynamic positional game with complete information. The dynamics of the conflict in the game is modeled using priority sets, and families of information sets describe the informativeness of the player. The player knows in which information set he is, but does not know in which position of this set in a particular period of the game. The formal description of the model is that the number of participants in the game is determined and their behavior is detailed. At the last step, each participant of the game evaluates its outcome with the value of the utility function. The paper presents a game-theoretic model of economic development in the form of a positional game. The participants of the game are entrepreneurs, the state and the population. At the first step, entrepreneurs choose the share of production output in the form of shadow capital. At the second step, the state chooses the tax rate, and allocates part of this tax to support social programs. At the third step, the population chooses, depending on the allocated amounts for social development, the demographic growth coefficient. For this game, based on the compiled algorithm, it is possible to automate the process of finding an equilibrium situation.

Trade Liberalization Index and Economic Growth in Developing Countries: Does Stage of Development Matter?

This paper analyses the widely used Sachs and Warner (1995) index of trade liberalization for 193 countries extending the period up to 2009 identifying 134 countries as open, 23 countries as closed, and 36 countries with ambiguous status, and then investigates the impacts of trade liberalization on economic growth using a dynamic growth model for a disaggregated levels of income. For this purpose, this study uses the biggest panel data set in this literature covering the period of 1985-2009. The results show that the impact of trade liberalization on economic growth differs based on the income levels of the developing countries. As indicated by the estimated results, the lower-middle-income countries, on average, benefit up to 3.45 percent points more compared to other developing countries from the trade liberalization. This finding makes a strong case for a clear departure from the ‘Washington Consensus’ approach and claims that trade liberalization with the same priority to all developing countries does not ensure economic growth. Also, the findings strongly suggest considering the stage of economic development of the developing countries while recommending their trade policy reforms.

Integration of dynamic growth modeling and hydrodynamics in an internal‐loop split photobioreactor

AbstractIn this study, new high‐quality experimental data for culturing green microalgae Scenedesmus in tubular and cylindrical split airlift photobioreactors were obtained under different operating conditions. The obtained experimental data of culturing microalgae Scenedesmus in a tubular photobioreactor were used for determining the kinetic parameters of the photosynthetic reaction. On the other hand, the culturing of green microalgae in a split airlift photobioreactor was used to measure the microalgae cell trajectory using an advanced radioactive particle tracking (RPT) technique. The obtained results in terms of kinetic parameters of the photosynthetic reaction and microalgae cell trajectory were integrated for the first time to obtain the three‐state dynamic growth model. This integration between dynamic growth and cell trajectories will provide a direct and comprehensive tool for photobioreactor analysis, which is essential for proper and efficient reactor design and scale‐up for large‐scale biomass production. © 2021 Society of Chemical Industry (SCI).

Transmission Dynamics and Short-Term Forecasts of COVID-19: Nepal 2020/2021.

Nepal was hard hit by a second wave of COVID-19 from April-May 2021. We investigated the transmission dynamics of COVID-19 at the national and provincial levels by using data on laboratory-confirmed RT-PCR positive cases from the official national situation reports. We performed 8 week-to-week sequential forecasts of 10-days and 20-days at national level using three dynamic phenomenological growth models from 5 March 2021-22 May 2021. We also estimated effective and instantaneous reproduction numbers at national and provincial levels using established methods and evaluated the mobility trends using Google's mobility data. Our forecast estimates indicated a declining trend of COVID-19 cases in Nepal as of June 2021. Sub-epidemic and Richards models provided reasonable short-term projections of COVID-19 cases based on standard performance metrics. There was a linear pattern in the trajectory of COVID-19 incidence during the first wave (deceleration of growth parameter (p) = 0.41-0.43, reproduction number (Rt) at 1.1 (95% CI: 1.1, 1.2)), and a sub-exponential growth pattern in the second wave (p = 0.61 (95% CI: 0.58, 0.64)) and Rt at 1.3 (95% CI: 1.3, 1.3)). Across provinces, Rt ranged from 1.2 to 1.5 during the early growth phase of the second wave. The instantaneous Rt fluctuated around 1.0 since January 2021 indicating well sustained transmission. The peak in mobility across different areas coincided with an increasing incidence trend of COVID-19. In conclusion, we found that the sub-epidemic and Richards models yielded reasonable short-terms projections of the COVID-19 trajectory in Nepal, which are useful for healthcare utilization planning.

Kinetic study on preparation of anti-glare and anti-reflective frosted glass by acid dissolving salt solution etching method

Frosted glass takes considerable research attention due to its simple preparation process and wide application prospect. Herein, acid dissolving salt solution chemical etching method was used to prepare anti-glare (AG) and anti-reflection (AR) glass, and the relationship between etching time and surface crystallization under the constant temperature and the same acid concentration was explored. Based on which, the chemical reaction mechanism was clarified, and the dynamic model of the particle growth of the surface of the etched glass was fitted. The results indicated that with the prolongation of the etching time, the content and size of the insoluble fluorosilicate particles formed on the glass surface increased, and the growth of crystals conformed to the power-law model. Due to the appropriate amount and size of the precipitated insoluble fluoride salts, a light trapping structure was formed on the glass surface to capture incident light so that the transmittance of the glass was increased to a certain extent, and the specular reflection of the surface was effectively transformed into diffuse reflection, achieving an anti-glare effect. The glass etched in the frosting solution with pH = 3 for 15 min showed the best optical properties, with the transmittance of 89%, while the average light reflectance was reduced by 75%. It provides the possibility for the protection of historical buildings.