Here: dynamic loading (libraries/functions) meaning: at run time

This is such a strong remark, and I assume that it’s intentional and purposeful as we learn more about Betteredge’s role (beyond his butler role?) in this story. On another note, this also brings up the social norms in the Victorian era, especially the power dynamic between servants and their employers.

Karl Friston: Up to 80% not even susceptible to Covid-19. (2020, June 4). UnHerd. https://unherd.com/2020/06/karl-friston-up-to-80-not-even-susceptible-to-covid-19/

Chari, Varadarajan V, Rishabh Kirpalani, and Christopher Phelan. ‘The Hammer and the Scalpel: On the Economics of Indiscriminate versus Targeted Isolation Policies during Pandemics’. Working Paper. Working Paper Series. National Bureau of Economic Research, May 2020. https://doi.org/10.3386/w27232.

Alstadsæter, A., Bratsberg, B., Eielsen, G., Kopczuk, W., Markussen, S., Raaum, O., & Røed, K. (2020). The First Weeks of the Coronavirus Crisis: Who Got Hit, When and Why? Evidence from Norway (Working Paper No. 27131; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27131

A dynamic language (Lisp, Perl, Python, Ruby) is designed to optimize programmer efficiency, so you can implement functionality with less code. A static language (C, C++, etc) is designed to optimize hardware efficiency, so that the code you write executes as quickly as possible. https://stackoverflow.com/questions/20563433/difference-between-static-and-dynamic-programming-languages#:~:text=A%20dynamic%20language%20(Lisp%2C%20Perl,executes%20as%20quickly%20as%20possible.

Friston KJ, Parr T, Zeidman P et al. Dynamic causal modelling of COVID-19 [version 1; peer review: awaiting peer review]. Wellcome Open Res 2020, 5:89 (https://doi.org/10.12688/wellcomeopenres.15881.1)

Della Rossa, F., & DeLellis, P. (2020). Stochastic master stability function for noisy complex networks. Physical Review E, 101(5), 052211. https://doi.org/10.1103/PhysRevE.101.052211

Cai, L., Chen, Z., Luo, C., Gui, J., Ni, J., Li, D., & Chen, H. (2020). Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs. ArXiv:2005.07427 [Cs, Stat]. http://arxiv.org/abs/2005.07427

Zhou, B., Lu, X., & Holme, P. (2020). Universal evolution patterns of degree assortativity in social networks. Social Networks, 63, 47–55. https://doi.org/10.1016/j.socnet.2020.04.004

Gou, W., Huang, S., Chen, J., Li, X., & Chen, Q. (2020). Structural and Dynamic of Global Population Migration Network. ArXiv:2006.02208 [Physics]. http://arxiv.org/abs/2006.02208

Coronavirus won’t be the end of big cities. (n.d.). Retrieved June 4, 2020, from https://www.centreforlondon.org/blog/the-city-isnt-dead/

Mancastroppa, M., Burioni, R., Colizza, V., & Vezzani, A. (2020). Active and inactive quarantine in epidemic spreading on adaptive activity-driven networks. ArXiv:2004.07902 [Cond-Mat, Physics:Physics]. http://arxiv.org/abs/2004.07902

sharing function

Sun, K., & Viboud, C. (2020). Impact of contact tracing on SARS-CoV-2 transmission. The Lancet Infectious Diseases, 0(0). https://doi.org/10.1016/S1473-3099(20)30357-1

Jiang, C., Gao, J., & Magdon-Ismail, M. (2020). Inferring Degrees from Incomplete Networks and Nonlinear Dynamics. ArXiv:2004.10546 [Physics]. http://arxiv.org/abs/2004.10546

Cowling, B. J., Ali, S. T., Ng, T. W. Y., Tsang, T. K., Li, J. C. M., Fong, M. W., Liao, Q., Kwan, M. Y., Lee, S. L., Chiu, S. S., Wu, J. T., Wu, P., & Leung, G. M. (2020). Impact assessment of non-pharmaceutical interventions against coronavirus disease 2019 and influenza in Hong Kong: An observational study. The Lancet Public Health, 0(0). https://doi.org/10.1016/S2468-2667(20)30090-6

Crutchfield, J. P. (2020). The Hidden Fragility of Complex Systems—Consequences of Change, Changing Consequences. ArXiv:2003.11153 [Cond-Mat, Physics:Nlin, Physics:Physics]. http://arxiv.org/abs/2003.11153

National Academies of Sciences, E. (2017). Building Communication Capacity to Counter Infectious Disease Threats: Proceedings of a Workshop. https://doi.org/10.17226/24738

The mention here of "innate capabilities" and the importance to yielding motor actions toward complex challenges, is noted. A question arises, regarding "basic cognitive capabilities" and their role in the process?

Celie talks to Sophia about their difference in handling their husbands. Celie is obedient and oppressed, while Sophia is rebellious and oppressed. The way it sounds to me, is that Sophia was also subjected to sexual abuse, but she stood up for herself and didn't allow the men to take her power from her. Sophia, it seems, not to be afraid of killing someone or of death itself. While Celie has been forced to live after all of her babies got killed or thought to be killed. I don't believe Sophia has every been pregnant, therefore she still feels powerful. Does power come with not having children? You don't need to nurture a child and you can focus on yourself when you don't have a child. Shug Avery never had kids (or nurtured them for that matter) and she rose to fame and fortune

Use these questions to drive what article you bring in to annotate. Or bring them into the reflection. The questions you are asking focus on dynamic network analysis. We will not do any of that in this class but you can find a lot of work on this way of doing SNA via Google.

Here's another article, with a different point-of-view on this subject.

A more detailed expansion on which approach to pick (and the reasons thereof) can be found here.

Some other problems can be found in the quoted works section, for this paper/web page. For example, have a look here.

So, from the whole thing I take it that the problem has actually two parts: i.) a pre-processing part in which all paths have been explored (via memoization), and, ii). discover the optimal path to take, given the memoization table.

This approach is a (sort of) memoization approach.

The most shocking thing about this 1977 article is we used to have tech people who knew who Durrell was.