Digital technology has the potential to eradicate extreme poverty and food insecurity to the majority of smallholder farmers in the world. This paper aims to identify knowledge gaps on digital technology for sustainable agriculture and assess their availability to smallholder farmers worldwide. The particular case of Tanzania receives special attention. We conducted an extensive literature search from relevant databases for review. The advanced digital technology in agriculture, mostly used by large scale farmers, significantly contributes to sustainable agriculture. However, the existing digital services for smallholder farmers lack sustainability in the agriculture context and hardly meet the needs for a comprehensive set of services in a complete farming cycle. In most developing countries, Tanzania case included, digital technology and services respond to a challenge at a particular stage of the farming process or to a specific value chain. Based on this literature review, we identify inequalities among large and small farmers, as well as environmental challenges caused by ICT itself. To conclude we provide suggestions for improvements for smallholder farmers: developing a digital platform that addresses smallholder farmers’ challenges in a complete farming cycle, bringing together the stakeholders at a country level, in order to achieve sustainable agriculture and support adoption of cutting-edge digital technology. These suggestions will be the starting point for future research.

The permanent and presently rising lava lake at Mount Nyiragongo constitutes a major potential geological hazard to the inhabitants of the Virunga volcanic region in the Democratic Republic of Congo (DRC) and Rwanda. Based on two field campaigns in June 2010 and 2011, we estimate the lava lake level from the southeastern crater rim (~400 m diameter) and lava lake area (~46,550 m²), which constrains, respectively, the lava lake volume (~9 × 10⁶ m³) and volume flow rate needed to keep the magma in a molten state (0.6 to 3.5 m³ s⁻¹). A bidirectional magma flow model, which includes the characterization of the conduit diameter and funnel‐shaped lava lake geometry, is developed to constrain the amount of magma intruded/emplaced within the magmatic chamber and rift‐related structures that extend between Mount Nyiragongo's volcanic center and the city of Goma, DRC, since Mount Nyiragongo's last eruption (17 January 2002). Besides matching field data of the lava lake level covering the period 1977 to 2002, numerical solutions of the model indicate that by 2022, 20 years after the January 2002 eruption, between 300 and 1700 × 10⁶ m³ (0.3 to 1.7 km³) of magma could have intruded/emplaced underneath the edifice, and the lava lake volume could exceed 15 × 10⁶ m³.

We develop a theory for the temporal integration of visual motion motivated by psychophysical experiments. The theory proposes that input data are temporally grouped and used to predict and estimate the motion flows in the image sequence. This temporal grouping can be considered a generalization of the data association techniques that engineers use to study motion sequences. Our temporal grouping theory is expressed in terms of the Bayesian generalization of standard Kalman filtering. To implement the theory, we derive a parallel network that shares some properties of cortical networks. Computer simulations of this network demonstrate that our theory qualitatively accounts for psychophysical experiments on motion occlusion and motion outliers. In deriving our theory, we assumed spatial factorizability of the probability distributions and made the approximation of updating the marginal distributions of velocity at each point. This allowed us to perform local computations and simplified our implementation. We argue that these approximations are suitable for the stimuli we are considering (for which spatial coherence effects are negligible).

Spontaneous waves of bursts of action potentials propagate across the ganglion-cell surface of developing retinas. A recent biophysical model postulated that this propagation is mediated by an increase in extracellular K+, following its ejection from ganglion cells during action potentials. Moreover, the model hypothesized that bursts might terminate due to the accumulation of intracellular Ca2+ and the subsequent activation of a Ca(2+)-dependent K+ conductance in the cells' dendrites. Finally, the model proposed that an excitatory synaptic drive causes a neuromodulation of the waves' properties. To test the feasibility of the model, we performed computer simulations of the network of developing ganglion cells under control and pharmacological-manipulation conditions. In particular, we simulated the effects of neostigmine, Cs+ and TEA, low Ca2+ concentrations, and Co2+. A comparison of the simulations with electrophysiological and pharmacological experimental data recently obtained in turtles (Sernagor and Grzywacz, 1993a), and cats and ferrets (Meister et al., 1991; Wong et al., 1993), showed that the model for the most part is consistent with the behavior of developing retinas. Moreover, modifications of the model to allow for GABAergic inputs onto ganglion cells (Sernagor and Grzywacz, 1994) and poor [K+]out buffering (Connors et al., 1982) improved the model's fits. These results lent further support to important roles of extracellular K+ concentration and synaptic drive for the propagation of waves.