Emerging Digital Technologies to Combat Future Crises: Learnings From COVID-19 to be Prepared for the Future

In 2020, the world has witnessed an unprecedented global pandemic with COVID-19. It has led nations to take measures that have an enormous impact on individuals, society, and the economy. Researchers and practitioners responded rapidly, evaluating the opportunities to capitalize on technology for tackling the associated challenges. We investigate the innovative potentials of three emerging digital technologies — namely, the Internet of Things, artificial intelligence, and distributed ledgers — to tackle pandemic-related challenges. We present our findings on the most effective means of leveraging each technology’s potential, the implications for use in crises, and the convergence of the three technologies.

Reflected fractional Brownian motion in one and higher dimensions

Fractional Brownian motion (FBM), a non-Markovian self-similar Gaussian stochastic process with long-ranged correlations, represents a widely applied, paradigmatic mathematical model of anomalous diffusion. We report the results of large-scale computer simulations of FBM in one, two, and three dimensions in the presence of reflecting boundaries that confine the motion to finite regions in space. Generalizing earlier results for finite and semi-infinite one-dimensional intervals, we observe that the interplay between the long-time correlations of FBM and the reflecting boundaries leads to striking deviations of the stationary probability density from the uniform density found for normal diffusion. Particles accumulate at the boundaries for superdiffusive FBM while their density is depleted at the boundaries for subdiffusion. Specifically, the probability density P develops a power-law singularity, P∼r^{κ}, as a function of the distance r from the wall. We determine the exponent κ as a function of the dimensionality, the confining geometry, and the anomalous diffusion exponent α of the FBM. We also discuss implications of our results, including an application to modeling serotonergic fiber density patterns in vertebrate brains.

Continuous and Long-Term Measurement of Reticuloruminal pH in Grazing Dairy Cows by an Indwelling and Wireless Data Transmitting Unit

The aim of the present study was the continuous measurement of ruminal pH in grazing dairy cows to monitor the diets effects on ruminal pH value. A novel indwelling pH-measurement and data transmitting system was given to 6 multiparous cows orally. Ruminal pH was measured every 600 sec over a 40 d period. After barn feeding and changeover to pasture, the following 3 treatments (2 cows/treatment) were included in the measurement period: continuous grazing (G), continuous grazing plus 4 kg/d of hay fed twice daily (GH), and continuous grazing plus 4 kg/d of concentrate (GC). Ruminal pH decreased significantly (P < 0.05) from 6.58 ± 0.15 to pH 6.19 ± 0.19 during feed changeover to pasture. Mean ruminal pH for G, GH, and GC was 6.36, 6.56, and 6.01. Mean 24-h minimum pH was 5.95, 6.20 and, 5.58. The time pH was below 6.3, 6.0, 5.8, and 5.5, for G it was 583, 91, 26, and 3 min/d, for GH it was 97, 12, 0, and 0 min/d and for GC it was 1126, 621, 347, and 101 min/d, respectively. Results were significantly influenced by the diet. The indwelling pH-measurement and data transmitting system is a very useful and proper tool for long-term measurement of ruminal pH in cows.