Effect of Temperature on the Daily Increment Deposition in the Otoliths of European Sardine Sardina pilchardus (Walbaum, 1792) Larvae

Otolith microstructure analysis is a valuable tool to evaluate the relationship between larval age and growth and how it relates to environmental variability. Otolith growth and daily increment deposition were analyzed in sardine (Sardina pilchardus) larvae reared in the laboratory under different temperatures (13, 15, and 17 °C), with a diet rich in microalgae, rotifers, and copepods Acartia grani. The number and width of growth increments, first-check and otolith diameter were determined in the otoliths and then related to larval age and total length. At hatching, the sagittal otoliths consisted of a lenticular core with a diameter of 10.56 μm (±1.07 μm SD). Somatic growth increased with the increasing temperature and the growth rate of larvae reared at 13 and 15 °C was significantly lower than for larvae reared at 17 °C. At 17 °C, otoliths exhibited a higher diameter with wider increments than at 13 °C. There was a high variability of increment counts-at-age for larvae reared within the same temperature treatment. The increase of growth increments with larval size was higher for larvae reared at 17 °C until 35 days post-hatching than those growing at 15 °C. Scanning electronic microscopy confirmed that increments are deposited daily, with an average width smaller than 1 µm and as low as 0.33 μm, therefore impossible to distinguish using light microscopy. At colder temperatures, larval otoliths had thinner and less marked increments and lower growth rates, which can lead to incorrect age determinations. The effect of temperature on the otolith microstructure can help in identifying strong temperature gradients experienced by wild sardine larvae.

Infradian rhythms of increment dynamics of shoots in clones of almond willow (Salix triandra, Salicaceae)

Purpose of research – harmonic analysis of the structure of seasonal dynamics of daily increment of shoots in almond willow (Salix triandra) clones. Research methodology and methods. Object is a model population created by cuttings of sibs-seedlings from the same family obtained by regular inbreeding over three generations. Material – growing long shoots. Experimental group: seven clones of one-year saplings from cuttings; 6-fold repetition. Control group – seedlings from the same family on their own roots of the fourth year of life. Methods: comparative morphological, chronobiological, numerical analysis of time series. Observations were made during the growing season of 2020. Results. The beginning of the growth of shoots – the end of the first decade of May. The maximum daily increase is in early summer (06.06…14.06). Further, the daily growth decreased unevenly until the end of August. Seasonal dynamics of daily increment is determined by the interaction of linear and nonlinear components. Linear components determine the seasonal trend of daily increment dynamics. They are approximated by the corresponding regression equations with different reliability. Nonlinear components determine the cyclical nature of the seasonal dynamics of daily increment. They are approximated by sums of harmonics with an oscillation period of 9–144 days with very high reliability. Scientific novelty. The cyclical nature of the seasonal dynamics of daily increment is determined by the interaction of biorhythms with different periods. Subannual biorhythms with a period of more than 48 days correct seasonal trends of daily increment. Infradian biorhythms with a period of 9...36 days determine the alternation of peaks and dips in the seasonal dynamics of daily increment. Biorhythms with a period of 29...36 days were synchronized in the experimental and control groups, but shifted in phase when comparing the experiment and control. Biorhythms with a period of 21...24 days are synchronized on all the researched shoots. Biorhythms with a period of 9…18 days are not synchronized, but their resulting fluctuations affect the dynamics of daily increment at the beginning and end of the growing season.

The prediction for development of COVID-19 in global major epidemic areas through empirical trends in China by utilizing state transition matrix model

Background Since pneumonia caused by coronavirus disease 2019 (COVID-19) broke out in Wuhan, Hubei province, China, tremendous infected cases has risen all over the world attributed to its high transmissibility. We aimed to mathematically forecast the inflection point (IFP) of new cases in South Korea, Italy, and Iran, utilizing the transcendental model from China. Methods Data from reports released by the National Health Commission of the People’s Republic of China (Dec 31, 2019 to Mar 5, 2020) and the World Health Organization (Jan 20, 2020 to Mar 5, 2020) were extracted as the training set and the data from Mar 6 to 9 as the validation set. New close contacts, newly confirmed cases, cumulative confirmed cases, non-severe cases, severe cases, critical cases, cured cases, and death were collected and analyzed. We analyzed the data above through the State Transition Matrix model. Results The optimistic scenario (non-Hubei model, daily increment rate of − 3.87%), the cautiously optimistic scenario (Hubei model, daily increment rate of − 2.20%), and the relatively pessimistic scenario (adjustment, daily increment rate of − 1.50%) were inferred and modeling from data in China. The IFP of time in South Korea would be Mar 6 to 12, Italy Mar 10 to 24, and Iran Mar 10 to 24. The numbers of cumulative confirmed patients will reach approximately 20 k in South Korea, 209 k in Italy, and 226 k in Iran under fitting scenarios, respectively. However, with the adoption of different diagnosis criteria, the variation of new cases could impose various influences in the predictive model. If that happens, the IFP of increment will be earlier than predicted above. Conclusion The end of the pandemic is still inapproachable, and the number of confirmed cases is still escalating. With the augment of data, the world epidemic trend could be further predicted, and it is imperative to consummate the assignment of global medical resources to curb the development of COVID-19.

The Prediction for Development of COVID-19 in Global Major Epidemic Areas Through Empirical Trends in China by Utilizing State Transition Matrix Model

Background: Since pneumonia caused by coronavirus disease 2019 (COVID-19) broke out in Wuhan, Hubei province, China, tremendous infected cases has risen all over the world attributed to its high transmissibility. We aimed to mathematically forecast the inflection point (IFP) of new cases in South Korea, Italy, and Iran, utilizing the transcendental model from China. Methods: Data from reports released by the National Health Commission of the People’s Republic of China (Dec 31, 2019 to Mar 5, 2020) and the World Health Organization (Jan 20, 2020 to Mar 5, 2020) were extracted as the training set and the data from Mar 6 to 9 as the validation set. New close contacts, newly confirmed cases, cumulative confirmed cases, non-severe cases, severe cases, critical cases, cured cases, and death were collected and analyzed. We analyzed the data above through the State Transition Matrix model. Results: The optimistic scenario (non-Hubei model, daily increment rate of -3.87%), the cautiously optimistic scenario (Hubei model, daily increment rate of -2.20%), and the relatively pessimistic scenario (adjustment, daily increment rate of -1.50%) were inferred and modeling from data in China. The IFP of time in South Korea would be Mar 6 to 12, Italy Mar 10 to 24, and Iran Mar 10 to 24. The numbers of cumulative confirmed patients will reach approximately 20k in South Korea, 209k in Italy, and 226k in Iran under fitting scenarios, respectively. However, with the adoption of different diagnosis criteria, the variation of new cases could impose various influences in the predictive model. If that happens, the IFP of increment will be earlier than predicted above. Conclusion: The end of the pandemic is still inapproachable, and the number of confirmed cases is still escalating. With the augment of data, the world epidemic trend could be further predicted, and it is imperative to consummate the assignment of global medical resources to curb the development of COVID-19.

The Prediction for Development of COVID-19 in Global Major Epidemic Areas Through Empirical Trends in China by Utilizing State Transition Matrix Model

Background: Since pneumonia caused by coronavirus disease 2019 (COVID-19) broke out in Wuhan, Hubei province, China, tremendous infected cases has risen all over the world attributed to high transmissibility. We managed to mathematically forecast the inflection point (IFP) of new cases in South Korea, Italy, and Iran, utilizing the transcendental model from China. Methods: Data from reports released by the National Health Commission of the People’s Republic of China (Dec 31, 2019 to Mar 5, 2020) and the World Health Organization (Jan 20, 2020 to Mar 5, 2020) were extracted as the training set and the data from Mar 6 to 9 as validation set. New close contacts, newly confirmed cases, cumulative confirmed cases, non-severe cases, severe cases, critical cases, cured cases, and death were collected and analyzed. All data were analyzed through the State Transition Matrix model. Results: the optimistic scenario (non-Hubei model, daily increment rate of -3.87%), the cautiously optimistic scenario (Hubei model, daily increment rate of -2.20%), and the relatively pessimistic scenario (adjustment, daily increment rate of -1.50%) were inferred and modeling from data in China. The IFP of time in South Korea would be Mar 6 to 12, Italy Mar 10 to 24, and Iran Mar 10 to 24. The numbers of cumulative confirmed patients will reach approximately 20k in South Korea, 209k in Italy, and 226k in Iran under fitting scenarios, respectively. However, with the adoption of different diagnosis criteria, the variation of new cases could impose various influences in the predictive model. If that happens, the IFP of increment will be earlier than predicted above. Conclusion: The end of the pandemic is still inapproachable, and the number of confirmed cases is still escalating. With the augment of data, the world epidemic trend could be further predicted, and it is imperative to consummate the assignment of global medical resources to curb the development of COVID-19.

Estimation of the period of permanence of Cordia americana seedlings in protected environment

The use of new tools as the technical criterion of interception of the curves of average daily increment and current daily are useful for indicating the optimal period of permanence of the plants in the protected environment. The objective of this study was to determine the length of stay of the Cordia americana (Linnaeus) Gottshling & JE Mill seedlings in protected environment based on the morphological parameters height, base diameter and total dry mass of the seedlings and in the intercept between daily increment curves and increment daily average. The experiment was conducted in a randomized complete block design, with subdivided plots with a 2 x 2 factorial scheme. The criteria were defined based on the growth curves and intercept between curves of daily increment and average daily increment. The volume of substrate that could be explored by the root system and the density of seedlings per tray influenced the growth, in general larger seedlings were obtained in larger tubes. The period of stay of the seedlings in the nursery varies from 150 to 250 days depending on the treatment used using the dry mass as a quality parameter. The technical criterion used to intercept the curves of daily increment and average daily increment is useful in decision making, with a view to the evaluation of the quality standard of the seedlings.

The Prediction for Development of COVID-19 in Global Major Epidemic Areas Through Empirical Trends in China by Utilizing State Transition Matrix Model

Background: Since pneumonia caused by coronavirus disease 2019 (COVID-19) broke out in Wuhan, Hubei province, China, tremendous infected cases has risen all over the world attributed to high transmissibility. We managed to mathematically forecast the inflection point (IFP) of new cases in South Korea, Italy, and Iran, utilizing the transcendental model from China. Methods: Data from reports released by the National Health Commission of the People’s Republic of China (Dec 31, 2019 to Mar 5, 2020) and the World Health Organization (Jan 20, 2020 to Mar 5, 2020) were extracted as the training set and the data from Mar 6 to Mar 9 as validation set. New close contacts, newly confirmed cases, cumulative confirmed cases, non-severe cases, severe cases, critical cases, cured cases, and death were collected and analyzed. All data were analyzed through the State Transition Matrix model. Results: the optimistic scenario (non-Hubei model, daily increment rate of -3.87%), the cautiously optimistic scenario (Hubei model, daily increment rate of -2.20%), and the relatively pessimistic scenario (adjustment, daily increment rate of -1.50%) were inferred and modeling from data in China. The IFP of time in South Korea would be Mar 6-Mar 12, Italy Mar 10-Mar 24, and Iran is Mar 10-Mar 24. The numbers of cumulative confirmed patients will reach approximately 20k in South Korea, 209k in Italy, and 226k in Iran under fitting scenarios, respectively. There should be room for improvement if these metrics continue to improve. In that case, the IFP will arrive earlier than our estimation. However, with the adoption of different diagnosis criteria, the variation of new cases could impose various influences in the predictive model. If that happens, the IFP of increment will be higher than predicted above. Conclusion: The end of the pandemic is still inapproachable, and the number of confirmed cases is still escalating. With the augment of data, the world epidemic trend could be further predicted, and it is imperative to consummate the assignment of global medical resources to curb the development of COVID-19.

The Prediction for Development of COVID-19 in Global Major Epidemic Areas Through Empirical Trends in China by Utilizing State Transition Matrix Model

BackgroundSince pneumonia caused by coronavirus disease 2019 (COVID-19) broke out in Wuhan, Hubei province, China, tremendous infected cases has risen all over the world attributed to high transmissibility. We managed to mathematically forecast the inflection point (IFP) of new cases in South Korea, Italy, and Iran, utilizing the transcendental model from Hubei and non-Hubei in China.MethodsWe extracted data from reports released by the National Health Commission of the People’s Republic of China (Dec 31, 2019 to Mar 5, 2020) and the World Health Organization (Jan 20, 2020 to Mar 5, 2020) as the training set to deduce the arrival of the IFP of new cases in Hubei and non-Hubei on subsequent days and the data from Mar 6 to Mar 9 as validation set. New close contacts, newly confirmed cases, cumulative confirmed cases, non-severe cases, severe cases, critical cases, cured cases, and death data were collected and analyzed. Using this state transition matrix model, the horizon of the IFP of time (the rate of new increment reaches zero) could be predicted in South Korean, Italy, and Iran. Also, through this model, the global trend of the epidemic will be decoded to allocate international medical resources better and instruct the strategy for quarantine.Resultsthe optimistic scenario (non-Hubei model, daily increment rate of −3.87%), the relative pessimistic scenario (Hubei model, daily increment rate of −2.20%), and the relatively pessimistic scenario (adjustment, daily increment rate of −1.50%) were inferred and modeling from data in China. Matching and fitting with these scenarios, the IFP of time in South Korea would be Mar 6-Mar 12, Italy Mar 10-Mar 24, and Iran is Mar 10-Mar 24. The numbers of cumulative confirmed patients will reach approximately 20k in South Korea, 209k in Italy, and 226k in Iran under fitting scenarios, respectively. There should be room for improvement if these metrics continue to improve. In that case, the IFP will arrive earlier than our estimation. However, with the adoption of different diagnosis criteria, the variation of new cases could impose various influences in the predictive model. If that happens, the IFP of increment will be higher than predicted above.ConclusionWe can affirm that the end of the burst of the epidemic is still inapproachable, and the number of confirmed cases is still escalating. With the augment of data, the world epidemic trend could be further predicted, and it is imperative to consummate the assignment of global medical resources to manipulate the development of COVID-19.

CHRONOBIOLOGICAL ASPECTS OF PESTICIDE LOAD OPTIMIZATION IN SALIX VIMINALIS L. PLANTINGS OF INTENSIVE TYPE

The article considers common osier from the utilitarian perspective and addresses the necessity to applyprolonged-action pesticides in the plantings of intensive type. To reduce the pesticide load, it is proposed to schedule agroforestry activities taking into account the seasonal dynamics of annual shoot growth. The study aims to identify patterns of seasonal dynamics of daily increment of annual shoots of common osier, using such methods as selection, structural-morphological methods, and harmonic analysis. The object of the study is a model inbred population of common osier. It was found that the seasonal dynamics of daily shoot growth ΔL(t) is cyclic. A three-level structure of seasonal biorhythms of daily shoot growth wasdiscovered. The contribution of lower harmonics with the oscillation period of 32 to 96 days to the total cyclicity ΔL(t) was 65%. The contribution of the medium harmonics with the oscillation period of 16 to 24daysto the total cyclicity ΔL(t) was 23%. The contribution of higher harmonics with the oscillation period of less than 14 days to the total cyclicity ΔL(t) was 6%. To optimize the pesticide load in the plantings of common osier, it is recommended to take into account the biorhythms of shoot growth with a frequency of fluctuations from 16 to 24 days.