Crybaby Vietsub //free\\ — Devilman

He charges into the horde. The screen cuts to black. The last subtitle appears:

"Anh Kaito... em thấy sừng của anh. Em thấy máu. Nhưng tại sao trái tim anh vẫn đập theo điệu nhạc cũ?" (Kaito... I see your horns. I see the blood. But why does your heart still beat to our old song?) devilman crybaby vietsub

I understand you're looking for a Vietnamese-subtitled version of Devilman Crybaby , but instead of providing a link or file (which would violate copyright and platform policies), I can offer you an original short story inspired by the show’s themes—loss, demonic transformation, and emotional rawness—written as if it were a Devilman Crybaby VietSub scene script. Tiếng Khóc Giữa Biển Lửa (A Cry in the Sea of Flames) He charges into the horde

"Em không còn là người nữa... nhưng anh vẫn cố cứu lấy một thế giới đã nguyền rủa chính em." (I’m no longer human... yet I still try to save a world that has cursed me.) em thấy sừng của anh

As with birth rates, we use data for 4 categories of countries from 1990 to 2015 (100 observations total). We have two explanatory variables, AGE and Y, where AGE is defined as the percentage of the population aged over 65 and Y is per capita GDP.

After eyeballing the scattergrams, we test the following functional form:

d = (minY^a)/Y^a * (1/AGE^g)

Where minY is the constant equal to the smallest value of Y in the series.

Logarithmic transformation gives:

ln(d) = ln(minY^a) – a*ln(Y) – g*ln(AGE)

which we test on the data using OLS. Here are the results:

Adjusted R square: 75.191

Intercept coefficient: 7.37384
t-Stat: 20.4011

Y coefficient: -1.01444
t-Stat: -13.1059

AGE coefficient: 2.0097
t-Stat: 11.5208

The estimated intercept is a good, but not perfect, approximation of ln(minY^a)

Here are the fitted against actual values of the scattergram for death rate against per capita GDP:

While the results are not as good as with the birth rates calculations, it is nevertheless a good enough fit and the explanatory variables have a strong enough confidence factor to be usable in our estimations.

We begin by examining the scatter of data for 100 observations of per capita GDP and per capita emissions for 4 categories of countries, over 25 years (1990 – 2015).

The scatter suggests a cubic functional form, so we test:

GHG = a + b*Y + c*Y^2 + d*Y^3

where GHG are per capita emissions of GHG, and Y is per capita GDP.

The results from OLS regression are:

Adjusted R square: 0.980438073

coefficient a: 1090
t-stat a: 3.06

coefficient b: 0.709310153
t-Stat b: 8.241453

coefficient c: -0.0000047025
t-Stat c: -1.01233

coefficient d: -0.000000000105314
t-Stat d: -1.47005

While the t-scores on the squared and cubed terms are low, the number of observations are also limited.

Here is the plot of the fitted against actual values: