An exploration of fractal-based prognostic model and comparative analysis for second wave of COVID-19 diffusion.

The coronavirus disease 2019 (COVID-19) pandemic has fatalized 216 countries across the world and has claimed the lives of millions of people globally. Researches are being carried out worldwide by scientists to understand the nature of this catastrophic virus and find a potential vaccine for it. The most possible efforts have been taken to present this paper as a form of contribution to the understanding of this lethal virus in the first and second wave. This paper presents a unique technique for the methodical comparison of disastrous virus dissemination in two waves amid five most infested countries and the death rate of the virus in order to attain a clear view on the behaviour of the spread of the disease. For this study, the data set of the number of deaths per day and the number of infected cases per day of the most affected countries, the USA, Brazil, Russia, India, and the UK, have been considered in the first and second waves. The correlation fractal dimension has been estimated for the prescribed data sets of COVID-19, and the rate of death has been compared based on the correlation fractal dimension estimate curve. The statistical tool, analysis of variance, has also been used to support the performance of the proposed method. Further, the prediction of the daily death rate has been demonstrated through the autoregressive moving average model. In addition, this study also emphasis a feasible reconstruction of the death rate based on the fractal interpolation function. Subsequently, the normal probability plot is portrayed for the original data and the predicted data, derived through the fractal interpolation function to estimate the accuracy of the prediction. Finally, this paper neatly summarized with the comparison and prediction of epidemic curve of the first and second waves of COVID-19 pandemic to visualize the transmission rate in the both times.

A Study on the Estimation of Postmortem Interval Based on Environmental Temperature and Concentrations of Substance in Vitreous Humor.

A method to determine postmortem interval (PMI) based on environmental temperature and the concentrations of vitreous humor (VH) molecules were explored. Rabbit carcasses were placed in a chamber at 5, 15, 25, or 35°C, and 80-100 µL of VH was collected with the double-eye alternating micro-sampling method every 12 h. A Roche DPPI biochemical analyzer was used to measure the concentrations of six substances in VH samples. The interpolation function model and mixed-effect model were employed for data fitting to establish equations for PMI estimation. The concentrations of K+ , P, Mg2+ , creatinine (CRE), and urea nitrogen (UN) exhibited an upward trend with increasing PMI in all temperature groups, while the concentration of Ca2+ showed a downward trend. Validation results using K+ and Mg2+ ions revealed that the mixed-effect model provided a better estimation than the interpolation function model using the data from our experiment. However, both models were able to estimate PMI using temperature and VH molecule concentrations.

Correlation between postmortem intervals and the changes of K+ concentration in rabbit vitreous humor after death under different temperature / 中国法医学杂志

Objective To investigate the relationship between K+ concentration in rabbit vitreous humor and postmortem interval (PMI) under different ambient temperature. Methods Rabbit corpses were stored at 5℃ , 15℃ , 25℃ , and 35℃ after execution, and 80~100μL vitreous humor was extracted from each eye of the rabbit in turn every 12 hours. The concentrations of K+ were examined by Modular DPPI automatic biochemistry analyzer. The Interpolation Functions were used to analyze the statistical relationship between PMI and K+ concentration under different temperature. Results In each animal group, K+ concentration increased with PMI. Equation was obtained after interpolation analysis on range of temperature 5℃ ~30℃ . The three-variable quintic surface equation was f(x,y)=-1.998e14+1.345e12x+5.902e13y+0.005585x2-4.509e11xy-3.876e12y2-0.0002868x3+0.003545x2y+4.406e10xy2-1.746e10y3+2.669e-6x4-1.568e-5x3y-0.0001771x2y2-1.64e9xy3+6.669e9y4-8.672e-9x5+4.467e-8x4y+2.354e-7x3y2+2.459e-6x2y3+2.05e7xy4-1.214e8y5(R2=0.9956), x stands for temperature, y stands for K+ concentration, f(x,y) stands for PMI. Conclusion The rule of K+ concentration changes at ambient temperature complied with three-variable quintic surface equation distribution. Measurement of interpolation function may be used for PMI estimation at different ambient temperature.

Correlation between postmortem intervals and the changes of 18s rRNA degradation in liver after death under the ;condition of different temperature( / 中国法医学杂志

Objective To investigate the relationship between Ct value of mice liver and postmortem interval (PMI) under various ambient temperatures. Methods mice were stored at 10℃, 15℃, 20℃, 25℃ and 30℃ after execution, and total RNA was extracted from mice liver every 6 hours (PMI 6h to 72h). The levels of 18s rRNA were examined using real-time PCR. The results were expressed by cycle threshold (Ct) value to explore relationship between PMI and Ct value, and the interpolation functions were established to estimate PMI. Results In each group, Ct value increased with PMI increased. Surface equation was obtained after interpolation analysis on temperature range 10℃~30℃. The three-variable quintic surface equation was f(x, y)=-426.9+30.82x+44.48y-1.297x2-1.837xy-1.388y2+0.034 38x3+0.038 17x2y+0.038 67xy2+0.028 77y3-0.000 612 9x4-3.897e-7x3y-0.001 223x2y2+0.000 256 6xy3-0.000 537 4y4+3.606e-6x5-2.846e-6x4y+1.009e-5x3y2-3.439e-6x2y3-2.556e-7xy4+2.664e-6y5(r2=0.999 4). Conclusion The rule of Ct value changes at ambient temperature complied with three-variable quintic surface equation distribution. Measurement of interpolation function may be used for PMI estimation at ambient temperature.

Interpolation function estimates post mortem interval under ambient temperature correlating with blood ATP level.

OBJECTIVE: We developed a mathematical model using interpolation function, to characterize the correlation between blood ATP levels in the right ventricle of rabbit and post mortem interval (PMI) at different ambient temperatures. METHODS: Forty-eight healthy rabbits were randomly divided into 6 groups of 8 each. The sacrificed rabbits were maintained in calorstats at 10°C, 15°C, 20°C, 25°C, 30°C and 35°C, respectively. Blood from the right ventricle was sampled every 4h until 72h after death. At different time points, ATP concentrations in the blood samples were measured using an ATP fluorescence rapid detector, and then displayed on the detector screen in the form of relative light units (RLU). Relationship between PMI and ATP degradation levels was investigated statistically by SPSS 17.0 and MATLAB 10.0 software. RESULTS: We obtained six regression equations (Ra(2)=0.887-0.929) with RLU values at PMIs of 72h (10°C), 60h (15°C), 56h (20°C), 52h (25°C), 40h (30°C) and 32h (35°C), and an interpolation function (Ra(2)=0.930) was established with PMI as the dependent variable (z), RLU value as independent variable (x) and temperature as independent variable (y). CONCLUSION: Interpolation function is an appropriate choice for PMI estimation by weakening influence of ambient temperature.

Correlation between the Changes of Oxidation Reduction Potential Values and Post-mortem Interval of Heart Blood in Rabbits after Death / 法医学杂志

Objective To investigate correlation between the changes of oxidation reduction potential (ORP ) values of heart blood in rabbits after death and postm ortem interval (PMI) at different temperatures. Meth-ods Forty-eight rabbits were random ly divided into 6 groups and sacrificed by air em bolism . Blood sam-ples were taken from the right ventricle of each rabbit and stored at different temperatures of 10, 15, 20, 25, 30and 35℃, respectively. Every 4 hours from 0h to 132 hpostm ortem , the ORP values of the blood samples were measured at different intervals by PB-21 electrochem ical analyzer. The curvilinear regres-sion equation was established by SPSS 17.0software. The surface equation and 3D surface diagram were established by MATL A B7.10.0software. Results The ORP values at different temperatures of heart blood in rabbits were highly correlated with the PMI. The ORP values rised obviously when the temper-ature was high and rised slowly when the temperature was low. The surface equation and 3D surface diagram were obtained. Conclusion The surface equation and 3D surface diagram of ORP values and PMI may be used for PMI estimation at different temperatures.