Seasonal Variation of the Sea Surface Temperature Growth Rate of ENSO

El Ni?o–Southern Oscillation(ENSO) exhibits a distinctive phase-locking characteristic, first expressed during its onset in boreal spring, developing during summer and autumn, reaching its peak towards winter, and decaying over the next spring. Several studies have demonstrated that this feature arises as a result of seasonal variation in the growth rate of ENSO as expressed by the sea surface temperature(SST). The bias towards simulating the phase locking of ENSO by many state-of-the-art climate models is also attributed to the unrealistic depiction of the growth rate. In this study, the seasonal variation of SST growth rate in the Ni?o-3.4 region(5°S–5°N, 120°–170°W) is estimated in detail based on the mixed layer heat budget equation and recharge oscillator model during 1981–2020. It is suggested that the consideration of a variable mixed layer depth is essential to its diagnostic process. The estimated growth rate has a remarkable seasonal cycle with minimum rates occurring in spring and maximum rates evident in autumn. More specifically, the growth rate derived from the meridional advection(surface heat flux) is positive(negative) throughout the year. Vertical diffusion generally makes a negative contribution to the evolution of growth rate and the magnitude of vertical entrainment represents the smallest contributor. Analysis indicates that the zonal advective feedback is regulated by the meridional immigration of the intertropical convergence zone, which approaches its southernmost extent in February and progresses to its northernmost location in September, and dominates the seasonal variation of the SST growth rate.

Growth rate of CO_(2) hydrate film on water-oil and water-gaseous CO_(2) interface

It is known that injection of carbon dioxide into the petroleum reservoir(CO_(2) flooding) is one of the effective methods for enhanced oil recovery. CO_(2) flooding may be complicated by formation of CO_(2) hydrate plugs. It makes topical investigation of CO_(2) hydrate formation in the system gaseous CO_(2)-oil-water. In this work, the growth rates of carbon dioxide hydrate films at the water-oil as well as the water-gas interface are studied in the pressure range of 2.30-3.04 MPa and at temperatures between -5.4 and 5.0℃. It is found that the growth rate for the water-oil interface is 3.5 times lower than that for the water-gas interface with carbon dioxide. It is hypothesised that the observed decrease in the growth rate is related to the mechanical resistance of the oil components adsorbed on the interface to the growth of the hydrate film. The growth rate of the film has been shown to depend on the experimental procedure,most likely due to the different initial concentrations of carbon dioxide in the aqueous solutions.

Effects of site productivity on individual tree maximum basal area growth rates of Eucalyptus pilularis in subtropical Australia

Inventory data were available from 96 plots of even-aged,monoculture,tall-open forests of Eucalyptus pilularis Smith,aged 2-63 years,growing in sub-tropical regions along the east coast of Australia.A model was developed relating the maximum possible stem basal area growth rate of individual trees to their stem basal area.For any tree size,this maximum increased as site productivity increased.However,the size at which this maximum occurred decreased as productivity increased.Much research has shown that,at any stand age,trees of a particular stem basal area are taller on more productive sites than on less productive ones.Taller trees incur greater respiratory costs to ensure maintenance of the photo synthetic capacity of their canopies;this reduces their growth rates.It was concluded that trees with larger basal areas will have the maximum possible growth rate on a less productive site,whilst trees with smaller basal areas will have the maximum possible on a more productive site.The model developed may constitute the first stage of a complete individual tree growth model system to predict wood yields from these forests.

Crack Growth Rate Model Derived from Domain Knowledge-Guided Symbolic Regression

Machine learning(ML)has powerful nonlinear processing and multivariate learning capabilities,so it has been widely utilised in the fatigue field.However,most ML methods are inexplicable black-box models that are difficult to apply in engineering practice.Symbolic regression(SR)is an interpretable machine learning method for determining the optimal fitting equation for datasets.In this study,domain knowledge-guided SR was used to determine a new fatigue crack growth(FCG)rate model.Three terms of the variable subtree ofΔK,R-ratio,andΔK_(th)were obtained by analysing eight traditional semi-empirical FCG rate models.Based on the FCG rate test data from other literature,the SR model was constructed using Al-7055-T7511.It was subsequently extended to other alloys(Ti-10V-2Fe-3Al,Ti-6Al-4V,Cr-Mo-V,LC9cs,Al-6013-T651,and Al-2324-T3)using multiple linear regression.Compared with the three semi-empirical FCG rate models,the SR model yielded higher prediction accuracy.This result demonstrates the potential of domain knowledge-guided SR for building the FCG rate model.

Aqueous extract of Protaetia brevitarsis larvae increases mTOR-mediated growth rate in zebrafish larvae

Objective:To evaluate the effects of an aqueous extract of Protaetia brevitarsis(AEPB)on the growth of zebrafish and preosteoblast MC3T3-E1 cells.Methods:The effects of AEPB on the linear growth and the expression of growth-related genes in zebrafish and MC3T3-E1 cells were assessed using various molecular techniques.Furthermore,the involvement of the mammalian target of rapamycin(mTOR)pathway in AEPB-induced growth was investigated by employing the mTOR inhibitor rapamycin.Results:AEPB administration led to a significant and dose-dependent increase in zebrafish larvae growth over time.Additionally,AEPB treatment upregulated the expression of growth hormone-1(GH-1),insulin-like growth factor-1(IGF-1),growth hormone receptor-1(GHR-1),and cholecystokinin-a(CCKA)in zebrafish.Similarly,AEPB stimulated the expression and release of IGF-1 and accelerated mTOR expression in MC3T3-E1 cells.In addition,rapamycin hindered AEPB-induced linear growth in zebrafish larvae and suppressed the expression of growth-promoting genes by inhibiting mTOR activation.Conclusions:AEPB shows growth-promoting effects by upregulating growth-related genes and activating the mTOR signaling pathway.Further investigations are warranted to elucidate its mechanisms of action and explore its potential application in the development of growth-enhancing supplements for various purposes.

Relationship of Trace Elements Concentration and Growth Rate in Alsidium triquetrum (Rhodophyta)

Minerals and trace elements content and concentration in marine algae vary depending on species morphology and physiology;as well as growing environmental conditions. Despite this variability, accumulation of magnesium, and especially iron, seems to be common in Chlorophyta;while Rhodophyta and Heterokontophyta show higher affinity to manganese. The red agarophyte Alsidium triquetrum was used to analyze the relationship between metal concentration, environmental conditions and growth rate. Specimens grown in situ showed a large variability of Fe, Mn, Mg, and Al, in thallus tissue concentrations. Further, a compelling relationship between the growth rate and the thallus concentration of Mg and Mn, Zn, and Al was detecte. Manganese, unlike the other trace elements analyzed showed a positive linear relationship between growth rate and tissue content during the period of greatest vegetative growth.

Probability estimation method for fatigue crack growth rate based on a∼t data from service

Purpose–The study aims to provide a basis for the effective use of safety-related information data and a quantitative assessment way for the occurrence probability of the safety risk such as the fatigue fracture of the key components.Design/methodology/approach–The fatigue crack growth rate is of dispersion,which is often used to accurately describe with probability density.In view of the external dispersion caused by the load,a simple and applicable probability expression of fatigue crack growth rate is adopted based on the fatigue growth theory.Considering the isolation among the pairs of crack length a and crack formation time t(a∼t data)obtained from same kind of structural parts,a statistical analysis approach of t distribution is proposed,which divides the crack length in several segments.Furthermore,according to the compatibility criterion of crack growth,that is,there is statistical development correspondence among a∼t data,the probability model of crack growth rate is established.Findings–The results show that the crack growth rate in the stable growth stage can be approximately expressed by the crack growth control curve da/dt=5 Q•a,and the probability density of the crack growth parameter Q represents the external dispersion;t follows two-parameter Weibull distribution in certain a values.Originality/value–The probability density f(Q)can be estimated by using the probability model of crack growth rate,and a calculation example shows that the estimation method is effective and practical.

PROBABILISTIC MODELS FOR LONG FATIGUE CRACK GROWTH RATES OF LZ50 AXLE STEEL

Experimental study is performed on the probabilistic models for the long fatigue crack growth rates (da/dN) of LZ50 axle steel. An equation for crack growth rate was derived to consider the trend of stress intensity factor range going down to the threshold and the average stress effect. The probabilistic models were presented on the equation. They consist of the probabilistic da/dN-ΔK relations, the confidence-based da/dN-ΔK relations, and the probabilistic- and confidence-based da/dN-ΔK relations. Efforts were made respectively to characterize the effects of probabilistic assessments due to the scattering regularity of test data, the number of sampling, and both of them. These relations can provide wide selections for practice. Analysis on the test data of LZ50 steel indicates that the present models are available and feasible.

El Ni?o/Southern Oscillation during the 4.2 ka event recorded by growth rates of corals from the North South China Sea

The 4.2 ka event that occurred during the period from 4 500–3 900 a BP was characterized by cold and dry climates and resulted in the collapse of civilizations around the world. The cause of this climatic event, however, has been under debate. We collected four corals(Porites lutea) from Yongxing Island, Xisha Islands, South China Sea, dated them with the U-series method, and measured the annual coral growth rates using X-ray technology. The dating results showed that the coral growth ages were from 4 500–3 900 a BP, which coincide well with the period of the4.2 ka event. We then reconstructed annual sea surface temperature anomaly(SSTA) variations based on the coral growth rates. The growth rate-based SSTA results showed that the interdecadal SSTA from 4 500–3 900 a BP was lower than that during modern times(1961–2008 AD). A spectral analysis showed that the SSTA variations from4 500–3 900 a BP were under the influence of El Nino-Southern Oscillation(ENSO) activities. From 4 500–4 100 a BP, the climate exhibited La Nina-like conditions with weak ENSO intensity and relatively stable and lower SSTA amplitudes. From 4 100–3 900 a BP, the climate underwent a complicated period of ENSO variability and showed alternating El Nino-or La Nina-like conditions at interdecadal time scales and large SSTA amplitudes. We speculate that during the early and middle stages of the 4.2 ka event, the cold climate caused by weak ENSO activities largely weakened social productivity. Then, during the end stages of the 4.2 ka event, the repeated fluctuations in the ENSO intensity caused frequent extreme weather events, resulting in the collapse of civilizations worldwide. Thus, the new evidence obtained from our coral records suggests that the 4.2 ka event as well as the related collapse of civilizations were very likely driven by ENSO variability.

Spatial diff erence in net growth rate of Yesso scallop Patinopecten yessoensis revealed by an aquaculture ecosystem model

Identifying the main factors on spatial diff erences in net growth rate of Yesso scallop(Patinopecten yessoensis)in culture system is the key to eff ective aquaculture management and development.Coupling a 3D ecosystem model(ROMS-CoSiNE)with a dynamic energy budget model for scallops,a Yesso scallop culture ecosystem(YeSCE)model was established with which scallop growth was simulated with real seeding density and juvenile size from local aquaculture experiments from December 1,2012 to November 30,2013.Results show that the YeSCE model has reasonably simulated the environmental variation and scallop net growth rate in the Changhai sea area.The growth of scallops was slow in winter and midsummer and was limited mainly by temperature.Food availability was a key factor that contributed to the fast growth of the scallops during spring to early summer and in autumn.Generally,the scallops cultured in the north part of the Changhai sea area grew faster than those in the south;and the net growth rate for scallops cultured near the island was signifi cantly higher compare to the others,which is probably correlated to the spatial distribution of food availability.Based on the correlation analysis,the spatial diff erences of the net growth rate were largely aff ected by the length of the match timing of temperatures and food availability.The results of this study provide a scientifi c support for optimizing bottom culture planning and adjusting bottom culture methods.

Plasma assisted molecular beam epitaxial growth of GaN with low growth rates and their properties

A systematic investigation on PA-MBE grown GaN with low growth rates(less than 0.2μm/h)has been conducted in a wide growth temperature range,in order to guide future growth of sophisticated fine structures for quantum device applications.Similar to usual growths with higher growth rates,three growth regions have been revealed,namely,Ga droplets,slightly Ga-rich and N-rich 3D growth regions.The slightly Ga-rich region is preferred,in which GaN epilayers demonstrate optimal crystalline quality,which has been demonstrated by streaky RHEED patterns,atomic smooth surface morphology,and very low defect related yellow and blue luminescence bands.The growth temperature is a critical parameter to obtain high quality materials and the optimal growth temperature window(~700-760℃)has been identified.The growth rate shows a strong dependence on growth temperatures in the optimal temperature window,and attention must be paid when growing fine structures at a low growth rate.Mg and Si doped GaN were also studied,and both p-and n-type materials were obtained.

Transition from Demographic Dividend to Reform Dividend:——Simulation of China's Potential Growth Rate

Due to diminishing demographic dividend characterized by a falling workingage population and rising dependency ratio, China's long-term potential growth rates will keep declining, likely to be a mere 6.6% during the 13 th Five-Year Plan period(2016-2020). China's economic growth sustainability hinges upon its transition from the previous dependence on demographic dividend to the future reform dividend. In the growth accounting equation, we have simulated various reform initiatives and arrived at the following findings. First, although both the labor participation rate and TFP can increase China's potential growth rate, the former will only achieve a short-term growth effect, which will diminish in the long run. By contrast, the growth effect of TFP demonstrates the tendency of continuous increase. This further indicates that China's economic growth will increasingly rely on TFP improvement instead of traditional factor input. Second, different from the diminishing growth effect of enrolment rate, training may play a pivotal role in human capital development to significantly enhance potential growth rates. Third, if all reform initiatives can achieve their expected effects, integrated reform dividends may reach one or two percentage points of China's potential growth rate.

Improvement of uniformity in cultivation environment and crop growth rate by hybrid control of air flow devices

A complete control type plant factory has high efficiency in terms of cultivation area by constructing vertical multiple layered cultivation beds.However,it has a problem of irregular crop growth due to temperature deviation at upper and lower beds and increases in energy consumption by a prolonged cultivation period.In this work,air flow rate inside a facility was improved by a hybrid control of air flow devices like air conditioning and air circulation fan with an established wireless sensor network to minimize temperature deviations between upper and lower beds and to promote crop growth.The performance of proposed system was verified with an experimental environment or Case A wherein air conditioning device was operated without a control algorithm and Case B wherein air conditioning and circulation fans were alternatively operated based on the hybrid control algorithm.After planting leafy vegetables under each experimental condition,crops were cultivated for 21 days.As a result,Case B wherein AC(air conditioning) and ACF(air-circulation fan) were alternatively operated based on the hybrid control algorithm showed that fresh mass,number of leaves,and leaf length for the crops grown were increased by 40.6%,41.1%,and 11.1%,respectively,compared to Case A.

Prostate Volume Growth Rate Changes over Time:Results from Men 18 to 92 Years Old in a Longitudinal Community-based Study

Previous investigations have shown that changes in total prostate volume(TPV) are highly variable among aging men,and a considerable proportion of aging men have a stable or decreasing prostate size.Although there is an abundance of literature describing prostatic enlargement in association with benign prostatic hyperplasia,less is known about the appropriate age cut-off points for TPV growth rate.In this community-based cohort study,TPV was examined once a year in men who had consecutive health checkup,during a follow-up of 4 years.A total of 5058 men(age 18–92 years old) were included.We applied multiple regression analyses to estimate the correlation between TPV growth rate and age.Overall,3232(63.9%) men had prostate growth,and 1826(36.1%) had a stable or decreased TPV during the study period.The TPV growth rate was correlated negatively with baseline TPV(r= –0.32,P<0.001).Among 2620 men with baseline TPV <15 cm3,the TPV growth rate increased with age(β=0.98,95% CI:0.77%–1.18%) only up to 53 years old.Among 2188 men with baseline TPV of 15–33.6 cm3,the TPV growth rate increased with age(β=0.84,95% CI,0.66%–1.01%) only up to 61 years old after adjusting for factors of hypertension,obesity,baseline TPV,diabetes mellitus and dyslipidemia.In this longitudinal study,the TPV growth rate increased negatively with baseline TPV,only extending to a certain age and not beyond.Further research is needed to identify the mechanism underlying such differences in prostate growth.

The growth rate of hepatocellular carcinoma is different with different TNM stages at diagnosis

Background: Hepatocellular carcinoma(HCC) progresses fast and has a poor prognosis, but the growth rate in different TNM stages is not clear. The present study was to estimate the growth rate of HCC with different TNM stages at diagnosis. Methods: Baseline demographics and tumor characteristics were analyzed for 10145 patients in Surveillance, Epidemiology, and End Results(SEER) Program-registered HCC. Multiple linear regression models were used for age adjustment with patient race, sex, marital status, and HCC grade. Results: The age at diagnosis was younger in Caucasians and males. The adjusted average age of patients with stage I HCC was 65.26 years. The adjusted age of patients with stage II, IIIA, IIIB, and IIIC was-0.17,-0.25,-0.29, and-0.55 adjusted-year younger compared with patients with stage I HCC(all P < 0.001). The adjusted average age of patients with T1 was 65.26 years. The age adjustment was-0.17,-0.26, and-0.55 respectively(all P < 0.001) for T2, T3 or T4 tumors without distant metastases. Conclusions: These findings demonstrated that the more advanced the HCC stage at diagnosis, the younger the age at diagnosis and the faster the HCC growth from tumor occurrence.

Carbon biomass,carbon-to-chlorophyll a ratio and the growth rate of phytoplankton in Jiaozhou Bay,China

Carbon biomass,carbon-to-chlorophyll a ratio(C꞉Chl a),and the growth rate of phytoplankton cells were studied during four seasonal cruises in 2017 and 2018 in Jiaozhou Bay,China.Water samples were collected from 12 stations,and phytoplankton carbon biomass(phyto-C)was estimated from microscope-measured cell volumes.The phyto-C ranged from 5.05 to 78.52μg C/L in the bay,and it constituted a mean of 38.16% of the total particulate organic carbon in the bay.High phyto-C values appeared mostly in the northern or northeastern bay.Diatom carbon was predominant during all four cruises.Dinoflagellate carbon contributed much less(<30%)to the total phyto-C,and high values appeared often in the outer bay.The C꞉Chl a of phytoplankton cells varied from 11.50 to 61.45(mean 31.66),and high values appeared in the outer bay during all four seasons.The phyto-C was also used to calculate the intrinsic growth rates of phytoplankton cells in the bay,and phytoplankton growth rates ranged from 0.56 to 1.96/d;the rate was highest in summer(mean 1.79/d),followed by that in fall(mean 1.24/d)and spring(mean 1.17/d),and the rate was lowest in winter(mean 0.77/d).Temperature and silicate concentration were found to be the determining factors of phytoplankton growth rates in the bay.To our knowledge,this study is the first report on phytoplankton carbon biomass and C꞉Chl a based on water samples in Jiaozhou Bay,and it will provide useful information for studies on carbon-based food web calculations and carbon-based ecosystem models in the bay.

Design of real-time feedback control of vertical growth rate on EAST

Real-time feedback control of vertical growth rate,called gamma control,has been successfully applied to experimental advanced superconducting tokamak(EAST).In this paper,a new gamma control method is proposed to regulate the vertical growth rate,which is an estimator of plasma vertical instability.Thus,the gamma controller can be utilized to keep the tokamak plasma away from its unstable boundary.In this work,the main development process includes three steps:(1)real-time implementation of model-based vertical growth rate calculation,taking advantage of GPU parallel computing capability,(2)design of plasma shape response for dynamic shape control using a slight modification to the plasma boundary,and(3)development of a gamma control algorithm integrated into the EAST plasma control system(PCS).The gamma control was experimentally verified in the EAST 2019 experiment campaign.It is shown that the time evolution of the real-time vertical growth rate agrees with the target value,indicating that the real-time vertical growth rate can be regulated by gamma control.

Tests of the real-time vertical growth rate calculation on EAST

In order to measure controllability of vertical instability in EAST,the calculation of model-based vertical growth rate,called rt-gamma,has been successfully carried out in real time.The numerical computing method is adapted from rigid plasma response model in TokSys,which is a widely-used analysis tool for tokamak devices in Matlab environment,but the code is rewritten by taking advantage of GPU parallel computing capability to accelerate the computation.The calculation of rt-gamma is validated by comparing it with the corresponding result generated by TokSys for totally 3508 cases.It is shown that the average absolute value of relative errors is about 0.85%.In addition,the calculation program of rt-gamma has been successfully applied during 2019 EAST campaign.The comparison with experimental results is discussed in this paper.The real-time calculation tool is well able to calculate model-based vertical growth rate,which is convenient for fast and continuous evaluations of EAST control system stability performances.

Prediction of Protein Expression and Growth Rates by Supervised Machine Learning

The DNA sequences of an organism play an important influence on its transcription and translation process, thus affecting its protein production and growth rate. Due to the com-plexity of DNA, it was extremely difficult to predict the macroscopic characteristics of or-ganisms. However, with the rapid development of machine learning in recent years, it be-comes possible to use powerful machine learning algorithms to process and analyze biolog-ical data. Based on the synthetic DNA sequences of a specific microbe, E. coli, I designed a process to predict its protein production and growth rate. By observing the properties of a data set constructed by previous work, I chose to use supervised learning regressors with encoded DNA sequences as input features to perform the predictions. After comparing different encoders and algorithms, I selected three encoders to encode the DNA sequences as inputs and trained seven different regressors to predict the outputs. The hy-per-parameters are optimized for three regressors which have the best potential prediction performance. Finally, I successfully predicted the protein production and growth rates, with the best R2 score 0.55 and 0.77, respectively, by using encoders to catch the potential fea-tures from the DNA sequences.