Inference for cumulative risk model under step-stress experiments and its application in nanocrystalline data

With the popularity of step-stress accelerated life testing, researchers are exploring more possibilities for models that relate the life distributions under different stress levels. Cumulative risk model assumes that the effects of stress changes have a lag period before they are fully observed, which guarantees the continuity of the hazard rate function. This paper studies the cumulative risk model for Lomax distribution with step-stress experiments. For maximum likelihood estimation, Newton-Rapson method is adopted to get point estimates. Meanwhile, the asymptotic normality of the maximum likelihood estimator is used to obtain asymptotic confidence intervals. For Bayesian estimation, point estimates and highest posterior density credible intervals under squared error loss function with informative prior and non-informative prior are derived using Metropolis-Hastings method and Metropolis-Hastings within Gibbs algorithm. To evaluate the effects of stress change time and the length of lag period, as well as the performance of different methods, numerical simulations are conducted. Then a real nanocrystalline data set is analyzed.

Competing Risks Step-Stress Model with Lagged Effect under Gompertz Distribution

In many survival analysis studies, the failure of a product may be attributed to one of several competing risks. In addition, if survival time is long, researchers can adopt accelerated life tests, causing devices to fail more quickly. One popular type of accelerated life tests is the step-stress test, and in this test, the stress level changes at a predetermined point time. The manner that stress levels change abruptly and increase discontinuously has been studied extensively. This paper considers a more realistic situation where the effect of stress increases cannot be achieved all at once, but with a lag time, and we propose a step-stress model consisting of two independent competing risks with a lag period in which the failure time caused by different risks at different stress levels obey Gompertz distribution, and the range of lag period is predetermined. The unknown parameters are estimated by maximum likelihood estimation and least squares estimation. For comparison, asymptotic confidence intervals and percentile bootstrap confidence intervals are constructed. By using Monte-Carlo simulations, we obtain the means and mean square errors of the maximum likelihood estimates and the least squares estimates, as well as the mean lengths and coverage rates of the two confidence intervals, which show the performance of various methods. Finally, in order to illustrate the model and proposed methods, we analyze a dataset from a solar energy experiment.

Cell cycle-dependent recruitment of FtsN to the divisome in Escherichia coli

Cell division in Escherichia coli starts with the formation of an FtsZ protofilament network in the middle of the cell, the Z ring. However, only after a considerable lag period do the cells start to form a midcell constriction. The basis of this cell cycle checkpoint is yet unclear. The onset of constriction is dependent upon the arrival of so-called late divisome proteins, among which, FtsN is the last arriving essential one. The timing and dependency of FtsN arrival to the divisome, along with genetic evidence, suggests it triggers cell division. In this study, we used high throughput fluorescence microscopy to quantitatively determine the arrival of FtsN and the early divisome protein ZapA to midcell at a single-cell level during the cell cycle. Our data show that recruitment of FtsN coincides with the initiation of constriction within experimental uncertainties and that the relative fraction of ZapA/FtsZ reaches its highest value at this event. We also find that FtsN is recruited to midcell in two distinct temporal stages with septal peptidoglycan synthesis starting in the first stage and accelerating in the second stage, during which the amount of ZapA/FtsZ in the midcell decreases. In the presence of FtsA*, recruitment of FtsN becomes concurrent with the formation of the Z-ring, but constriction is still delayed indicating FtsN recruitment is not rate limiting, at least under these conditions. Finally, our data support the recently proposed idea that ZapA/FtsZ and FtsN are part of physically separate complexes in midcell throughout the whole septation process.

Growth Modeling Kinetics of Aspergillus flavus in Dried Jujube at Different Temperatures

Dried jujube is a characteristic fruit of Xinjiang. Aspergillus is one of the main pathogens that causes mold on dried jujube, and A. flavus is a toxin-producing species, the aflatoxin produced by A. flavus is extremely toxic and carcinogenic. In this study, the growth kinetic models of A. flavus isolated from red jujube at different temperatures and times were fitted to Huang model and linear equation respectively, the Cardinal model was used to describe the growth rate and lag time of A. flavus on dried jujube agar. It turned out that 30–35 °C was the optimal temperature for growing A. flavus, so dried jujube should avoid storing in this temperature range. The kinetic model established in this study will help to understand the growth characteristics of A. flavus, and lay a foundation for evaluating the quality of stored dried jujube and predictions of shelf life, which are conducive to optimizing storage methods for dried jujube. It can be judged according to the value of Af and Bf, the Huang model had a better fitting effect than the Baranyi model, The two models all had the highest growth rate at 35 °C, and A. flavus grew more vigorously and the lag period shortened as the temperature was increased. The secondary Cardinal model had a good fitting effect on the growth rate and lag time, and the secondary Ratkowsky model had a good fitting effect on the growth rate. This study may have theoretical and application value to strengthen the safety of jujube storage in the future.

Kinetics of alpha-synuclein depletion in three brain regions following conditional pan-neuronal inactivation of the encoding gene (Snca) by tamoxifen-induced Cre-recombination in adult mice

Conditional pan-neuronal inactivation of the Snca gene in 2-month old male and female mice causes dramatic decrease in the level of the encoded protein, alpha-synuclein, in three studied brain regions, namely cerebral cortex, midbrain and striatum, 12 weeks after the last injection of tamoxifen. Kinetics of alpha-synuclein depletion is different in these brain regions with a longer lag period in the cerebral cortex where this protein is normally most abundant. Our results suggest that efficient post-developmental pan-neuronal knockout of alpha-synuclein in adult, i.e. 5- to 6-month old, animals, could be achieved by tamoxifen treatment of 2-month old mice carrying loxP-flanked Snca gene and expressing inducible Cre-ERT2 recombinase under control of the promoter of neuron-specific enolase (NSE) gene.

Production Risk and the Early Adoption of Alternatives to Antibiotics: Evidence From Poultry Farmers in China

Excessive or unreasonable use of agricultural chemicals has caused a wide range of negative effects on the environment and residents' health. It is urgent to promote the reduction of the use of agricultural chemicals. Taking the use of veterinary antibiotics (hereafter antibiotics) in broiler breeding as an example, based on the data of 380 contract farmers, this paper first investigated the effects of production risk on farmers' decision-making on the use of alternatives to antibiotics and the amount of antibiotics in the initial stage of alternatives entering into the market. The results show that: (1) the fluctuation of mortality in the lag period has no significant influence on the adoption of alternatives, and farmers are concerned about the absolute or average level of mortality in the lag period. (2) The mortality rate lagged three phases had a significant positive impact on the adoption of alternatives. On average, the mortality rate lagged three phases increased by 0.01, and the likelihood of farmers adopting substitutes in the early stage increased by 0.670%. (3) The production risk plays an important role in regulating the effects of alternatives. When using alternatives, the mortality rate of lagging three phases is higher, the higher the dosage of antibiotics and the lower the mortality rate in the early stage, suggesting that higher production risk would result in using alternatives for the purpose of reducing the production risk rather than reducing the use of antibiotics. Thus, to realize the effect of alternatives in reducing agricultural chemicals, the prerequisite is to improve the production risk management ability of farmers.

Photochemical changes during rehydration of an intertidal cyanobacterial mat exposed to variations in salinity and light intensity

This study focuses on a Lyngbya cf. aestuarii dominated mat community from the intertidal zone of the Laguna Ojo de Liebre, Baja California Sur. In this environment, the mat is desiccated for several days between spring tides. While the mats were desiccated, photosynthetic activity was absent but recovered rapidly (~3 h) upon rehydration. It has been shown previously that the rate of photosynthetic recovery is dependent on both light intensity and salinity. In the current study, photosynthetic recovery was measured based on chlorophyll a fluorescence using pulse amplitude modulated (PAM) fluorometry. Upon the addition of water, photosystem II (PSII) complexes recovered the capacity for reaction centre excitation. However, these functional centres were initially closed. Respiratory activity early in recovery probably reduced the plastoquinone pool through the shared use of part of the photosynthetic transport chain, thus temporarily blocking electron transport downstream of PSII. The time that PSII complexes remained closed increased with light intensities above saturation. This condition is potentially damaging to the cyanobacteria since the exposure of closed PSII centres to high light intensities can lead to the production of singlet oxygen. After this initial lag period, PSII centres opened rapidly indicating an increase in the flow of electrons from PSII to PSI. The rate of photosynthetic recovery appeared to be limited primarily by the relatively slow return of functional PSII. Photosynthetic recovery rates were slower in salinities greater than those that naturally occur in the intertidal zone.

Applying Quantile Regression to Assess the Relationship between R&D, Technology Import and Patent Performance in Taiwan

Electronics companies are facing global economic and trade competition. As patents can form an endowment shield that protects the development of corporate capabilities, companies are actively increasing their number of patents and attaching importance to technological research and development and patent management to achieve differentiated strategic effects. As such, patent layout and research and development (R&D) investment have become important strategic weapons for Taiwanese manufacturers, with which to enter the international market or compete among enterprises. This study first utilized the principal components analysis method to define patents in terms of the number of patents and the times patents are cited, with R&D defined in terms of expenditure and intensity. Furthermore, this study used a quantile regression model to visualize the relationship between R&D, technological imports, and patent performance in Taiwanese listed electronics companies. The empirical results show that technological imports in the second time-lag period require patents, while the effect on patents varies alongside industry characteristics. In addition, the empirical results found that the total assets, number of employees, and number of patent inventors are also factors that significantly affect patents. This research proposes that Taiwan’s listed electronics companies should expand their scale, increase their economic efficiency, maximize their resources, increase their patents, enhance their corporate value, boost their investor confidence, and improve their industry competitiveness.

Monetary Policy And Economic Stabilisation In Nigeria; 1986 – 2019; (Distributional Koyck Lag Model Approach)

This study examined the relevance of Monetary Policy in stabilizing the Nigerian Economy for the period (1986-2019); using the Koyck Model, regression. The results obtained reveal that the rate of growth in the money stock has significant impact on output, contrary to its impact on inflation. Changes in money supply did not exert significant influence on the lending interest rate; however operating lag period of money stock on interest rate was instantaneous. The lending interest rates were exogenously determined by lending institutions. Lending interest rates influenced investment significantly, though with a very long operating lag period. The immediate past value of Money supply significantly influenced the succeeding inflation rate and investment. Likewise, inflation caused growth in the gross domestic output. The joint influences of money stock and national output impacted significantly on the general price level. Consequently, monetary policy measures through adjustments in money stock were better in stabilizing growth than Inflation. Measures that make cash directly available to economic units stimulated investment.Based on the results of this study,we recommend that; the growth of Money Supply cannot be used to influence the general price level and the lending Interest Rate especially in the short run. Changes in the stock of Money Supply can be used to stimulate Economic Growth. Inflation can better be managed with proportionate growths in Money Supply and the Gross Domestic Product. Investment can be tracked by manipulating the lending interest rate. Preview