Comparison and estimation of different linear and nonlinear lactation curve submodels in random regression analyses on dairy cattle

In the random regression model (RRM) for milk yield, by replacing empirical lactation curves with the five-order Legendre polynomial to fit fixed groups, the RRM can be transformed to a hierarchical model that consisted of a RRM in the first hierarchy with Legendre polynomials as individuals’ lactation curves resolved by restricted maximum likelihood (REML) software, and a multivariate animal model for phenotypic regression coefficients in the second hierarchy resolved by DMU software. Some empirical lactation functions can be embedded into the RRM at the first hierarchy to well fit phenotypic lactation curve of the average observations across all animals. The functional relationship between each parameter and time can be described by a Legendre polynomial or an empirical curve usually called submodel, and according to three commonly used criteria, the optimal submodels were picked from linear and nonlinear submodels except for polynomials. The so-called hierarchical estimation for the RRMs in dairy cattle indicated that more biologically meaningful models were available to fit the lactation curves; moreover, with the same number of parameters, the empirical lactation curves (MIL1, MIL5, and MK1 for 3, 4, and 5 parameters, respectively) performed higher goodness of fit than Legendre polynomial when modelling individuals’ phenotypic lactation curves.

Characteristics of Typhoon “Fung-Wong” Near Earth Pulsation

To study the wind field characteristics near the ground pulsation in typhoon conditions, wind field conditions in the area affected by Typhoon “Fung-Wong” were monitored using wind field instruments installed in the construction building of Wenzhou University, China. Real-time wind field data were collected during typhoons. Wind characteristic parameters such as mean wind speed, wind direction angle, turbulence intensity, gust factor, peak factor, coherence function, and autocorrelation were analyzed, and the wind field characteristics during the typhoon were summarized. The results indicated that the longitudinal and lateral turbulence intensities decreased with an increase in the mean wind speed, and there was an obvious linear relationship between them. The vertical and horizontal gust factor and peak factor decreased with an increase in mean wind speed, and the trend was more obvious in the horizontal direction. There was a significant correlation between the gust factor and the peak factor. The turbulence intensity and gust factor decreased with time, and the turbulence intensity attenuation speed increased with time. The empirical curve presented by Davenport (1961) can simulate the correlation characteristics of the fluctuating wind speed components of Typhoon Fung-Wong at some measuring points. With an increase in the time difference, the dependence of the instantaneous values at the two time points gradually decreased.

Flattening the curve is flattening the complexity of covid-19

Since the February 2020 publication of the article ‘Flattening the curve’ in The Economist, political leaders worldwide have used this expression to legitimize the introduction of social distancing measures in fighting Covid-19. In fact, this expression represents a complex combination of three components: the shape of the epidemic curve, the social distancing measures and the reproduction number $$ \mathscr{R}_{0}$$ R 0 . Each component has its own history, each with a different history of control. Presenting the control of the epidemic as flattening the curve is in fact flattening the underlying natural-social complexity. The curve that needs to be flattened is presented as a bell-shaped curve, implicitly suggesting that the pathogen’s spread is subject only to natural laws. The $$ \mathscr{R}$$ R value, however, is, fundamentally, a metric of how a pathogen behaves within a social context, namely its numerical value is affected by sociopolitical influences. The jagged and erratic empirical curve of Covid-19 illustrates this. Although the virus has most likely infected only a small portion of the total susceptible population, it is clear its shape has changed drastically. This changing shape is largely due to sociopolitical factors. These include shifting formal laws and policies, shifting individual behaviors as well as shifting various other social norms and practices. This makes the course of Covid-19 curve both erratic and unpredictable.

The Dissolution Rate of CaCO3 in the Ocean

The dissolution of CaCO3 minerals in the ocean is a fundamental part of the marine alkalinity and carbon cycles. While there have been decades of work aimed at deriving the relationship between dissolution rate and mineral saturation state (a so-called rate law), no real consensus has been reached. There are disagreements between laboratory- and field-based studies and differences in rates for inorganic and biogenic materials. Rates based on measurements on suspended particles do not always agree with rates inferred from measurements made near the sediment–water interface of the actual ocean. By contrast, the freshwater dissolution rate of calcite has been well described by bulk rate measurements from a number of different laboratories, fit by basic kinetic theory, and well studied by atomic force microscopy and vertical scanning interferometry to document the processes at the atomic scale. In this review, we try to better unify our understanding of carbonate dissolution in the ocean via a relatively new, highly sensitive method we have developed combined with a theoretical framework guided by the success of the freshwater studies. We show that empirical curve fits of seawater data as a function of saturation state do not agree, largely because the curvature is itself a function of the thermodynamics. Instead, we show that models that consider both surface energetic theory and the complicated speciation of seawater and calcite surfaces in seawater are able to explain most of the most recent data.This new framework can also explain features of the historical data that have not been previously explained. The existence of a kink in the relationship between rate and saturation state, reflecting a change in dissolution mechanism, may be playing an important role in accelerating CaCO3 dissolution in key sedimentary environments.

A new regression model for the forecasting of COVID-19 outbreak evolution: an application to Italian data

The novel coronavirus SARS-CoV-2 was first identified in China in December 2019. In just over five months, the virus affected over 4 million people and caused about 300,000 deaths. This study aimed to model new COVID-19 cases in Italy using a new curve. A new empirical curve is proposed to model the number of new cases of COVID-19. It resembles a known exponential growth curve which has a straight line as an exponent, but in the growth curve proposed, the exponent is a logistic curve multiplied for a straight line. This curve shows an initial phase, the expected exponential growth; then rises to the maximum value and finally reaches zero. We characterized the epidemic growth patterns for the entire Italian nation and for each of the 20 Italian regions. The estimated growth curve has been used to calculate the expected time of the beginning, the time related to peak, and the end of the epidemics. Our analysis explores the development of the epidemics in Italy and the impact of the containment measures. Data obtained are useful to forecast future scenario and the possible end of the outbreak.

Application of the Minor Destructive Test (MDT) method for determination of AAC masonry compressive strength

Non-destructive methods (NDT) in masonry made of autoclaved aerated concrete (AAC) are not used as commonly as in concrete or reinforced concrete constructions. The porous structure and sensitivity to atmospheric factors, especially humidity, makes it necessary to determine the compressive strength of the wall in existing and used objects. The article presents a proposal of a semi-non-destructive method for determining the compressive strength of AAC, and then a wall made with thin-layer joints. An empirical curve developed for cellularconcrete with nominal density classes 400, 500, 600 and 700 in an air-dry condition was used for calibration.In addition, an empirical relationship was developed to take into account the impact of ABK moisture.

Vehicle–bridge coupling dynamic response of sea-crossing railway bridge under correlated wind and wave conditions

The sea-crossing railway bridge is exposed to a high risk of wind and wave, which threatens the safety of the bridge and railway. A wind–wave–vehicle–bridge dynamic analysis model for sea-crossing railway bridge under wind and wave loadings is developed by extending the previous wind–vehicle–bridge model. The developed wind–wave–vehicle–bridge model involves multipoint fluctuating wind field, irregular wave field, finite element model of the bridge, and mass–spring–damper model of the vehicle. The correlation between wind and wave is considered by an empirical curve derived based on field measurement. Static, buffeting, and self-excited wind forces on the bridge and vehicle are considered with coefficients obtained from wind tunnel tests. The wave forces on the bridge are calculated by Morison equation including stretching modification. The governing equations of the wind–wave–vehicle–bridge model are solved in time domain by Newmark-β method to compute the dynamic response of bridge and vehicle. The dynamic response of bridge and vehicle is compared and discussed in both wind–wave–vehicle–bridge and wind–vehicle–bridge model. The performance of bridge and vehicle are finally evaluated. Studies of dynamic response under correlated wind and wave are found to be imperative for assessment of structural and vehicle safety and driving comfort of sea-crossing railway bridge.

An alternative method for estimating hygroscopic growth factor of aerosol light-scattering coefficient: a case study in an urban area of Guangzhou, South China

A method was developed to estimate hygroscopic growth factor (f(RH)) of aerosol light-scattering coefficient (bsp), making use of the measured size- and chemically resolved aerosol samples. In this method, chemical composition of the measured aerosol samples were first reconstructed using the equilibrium model ISORROPIA II. The reconstructed chemical composition, which varies with relative humidity (RH), was then employed to calculate bsp and hygroscopic growth factor of bsp (fsp(RH)) using the Mie model. Furthermore, the calculated fsp(RH) was fitted with an empirical curve. To evaluate the applicability of fsp(RH), the curve of fsp(RH) was used to correct the long-term records of the measured bsp from the values under comparative dry conditions to the ones under ambient RH conditions. Compared with the original bsp data, the fsp(RH)-corrected bsp had a higher linear correlation with, and a smaller discrepancy from, the bsp derived directly from visibility and absorption measurements. The fsp(RH) determined here was further compared with that reported in previous studies. The method described in this manuscript provides an alternative approach to derive credible fsp(RH) with high accuracy and has many potential applications in aerosol-related research.

Quantifying correlations between galaxy emission lines and stellar continua using a PCA-based technique

We analyse the correlations between continuum properties and emission line equivalent widths of star-forming and narrow-line active galaxies from SDSS. We show that emission line strengths can be predicted reasonably well from PCA coefficients of the stellar continuum using local multiple linear regression. Since upcoming sky surveys will make broadband observations only, theoretical modelling of spectra will be essential to estimate physical properties of galaxies. Combined with stellar population synthesis models, our technique will help generate more accurate model spectra and mock catalogues of galaxies to be used to fit data from new surveys. We also show that, by combining PCA coefficients from the pure continuum and the emission lines, a plausible distinction can be made between weak AGNs and quiescent star-forming galaxies. Our method uses a support vector machine, and allows a more refined separation of active and star-forming galaxies than the empirical curve of Kauffmann et al. (2003).