Beacon Success Rate versus Gateway Density in Sub-GHz Sensor Networks.

Multiple Gateways (GWs) provide network connectivity to Internet of Things (IoT) sensors in a Wide Area Network (WAN). The End Nodes (ENs) can connect to any GW by discovering and acquiring its periodic beacons. This provides GW diversity, improving coverage area. However, simultaneous periodic beacon transmissions among nearby GWs lead to interference and collisions. In this study, the impact of such intra-network interference is analyzed to determine the maximum number of GWs that can coexist. The paper presents a new collision model that considers the combined effects of the Medium Access Control (MAC) and Physical (PHY) layers. The model takes into account the partial overlap durations and relative power of all colliding events. It also illustrates the relationship between the collisions and the resulting packet loss rates. A performance evaluation is presented using a combination of analytical and simulation methods, with the former validating the simulation results. The system models are developed from experimental data obtained from field measurements. Numerical results are provided with Gaussian Frequency Shift Keying (GFSK) modulation. This paper provides guidance on selecting GFSK modulation parameters for low bit-rate and narrow-bandwidth IoT applications. The analysis and simulation results show that larger beacon intervals and frequency hopping help in reducing beacon loss rates, at the cost of larger beacon acquisition latency. On the flip side, the gateway discovery latency reduces with increasing GW density, thanks to an abundance of beacons.

Performance of Narrow Band Wide Area Networks with Gateway Diversity.

This paper quantifies the coverage area of Low-Power Wide-Area Networks (LPWAN) for Packet Success Rates (PSR) above 85%, where acceptable Quality of Service (QoS) can be achieved. The network consists of battery-operated end-nodes (ENs) and multiple stationary gateways (GWs). We consider asynchronous communication that uses ALOHA-based random channel access. Each transmission from the ENs can be received by multiple GWs. Such spatial diversity results in favorable Signal-to-Noise ratios (SNR). The LoRa modulation is assumed and its specific features, such as IQ inversion, further contribute to decreasing the impact of interference. An increase in the GW density improves network performance, which allows support for a larger density of end-nodes as well as increasing the coverage area. Our simulation results show that a suburban area of up to 1.44 km2 can be covered with five GWs with up to fifty end-nodes with a PSR greater than 86%.

Recurrent neural networks for partially observed dynamical systems.

Complex nonlinear dynamics are ubiquitous in many fields. Moreover, we rarely have access to all of the relevant state variables governing the dynamics. Delay embedding allows us, in principle, to account for unobserved state variables. Here we provide an algebraic approach to delay embedding that permits explicit approximation of error. We also provide the asymptotic dependence of the first-order approximation error on the system size. More importantly, this formulation of delay embedding can be directly implemented using a recurrent neural network (RNN). This observation expands the interpretability of both delay embedding and the RNN and facilitates principled incorporation of structure and other constraints into these approaches.

Caching in or Falling Back at the Sevilleta: The Effects of Body Size and Seasonal Uncertainty on Desert Rodent Foraging.

Foraging in uncertain environments requires balancing the risks associated with finding alternative resources against potential gains. In arid-land environments characterized by extreme variation in the amount and seasonal timing of primary production, consumers must weigh the risks associated with foraging for preferred seeds that can be cached against fallback foods of low nutritional quality (e.g., leaves) that must be consumed immediately. Here, we explore the influence of resource scarcity, body size, and seasonal uncertainty on the expected foraging behaviors of caching rodents in the northern Chihuahaun Desert by integrating these elements with a stochastic dynamic program to determine fitness-maximizing foraging strategies. We demonstrate that resource-limited environments promote dependence on fallback foods, reducing the likelihood of starvation while increasing future risk exposure. Our results point to a qualitative difference in the use of fallback foods and the fitness benefits of caching at the threshold body size of 50 g. Above this 50-g body size threshold, we observe large fitness gains associated with the maintenance of even a modest-sized cache, whereas similar gains for smaller consumers require maintenance of unrealistically large caches. This suggests that larger-bodied consumers that cache may be less sensitive to the future uncertainties in monsoonal onset predicted by global climate scenarios, whereas smaller consumers, regardless of caching behavior, may be at greater risk.

Scaling the risk landscape drives optimal life-history strategies and the evolution of grazing.

Consumers face numerous risks that can be minimized by incorporating different life-history strategies. How much and when a consumer adds to its energetic reserves or invests in reproduction are key behavioral and physiological adaptations that structure communities. Here we develop a theoretical framework that explicitly accounts for stochastic fluctuations of an individual consumer's energetic reserves while foraging and reproducing on a landscape with resources that range from uniformly distributed to highly clustered. First, we show that the selection of alternative life histories depends on both the mean and variance of resource availability, where depleted and more stochastic environments promote investment in each reproductive event at the expense of future fitness as well as more investment per offspring. We then show that if resource variance scales with body size due to landscape clustering, consumers that forage for clustered foods are susceptible to strong Allee effects, increasing extinction risk. Finally, we show that the proposed relationship between resource distributions, consumer body size, and emergent demographic risk offers key ecological insights into the evolution of large-bodied grazing herbivores from small-bodied browsing ancestors.

Edge fires drive the shape and stability of tropical forests.

In tropical regions, fires propagate readily in grasslands but typically consume only edges of forest patches. Thus, forest patches grow due to tree propagation and shrink by fires in surrounding grasslands. The interplay between these competing edge effects is unknown, but critical in determining the shape and stability of individual forest patches, as well the landscape-level spatial distribution and stability of forests. We analyze high-resolution remote-sensing data from protected Brazilian Cerrado areas and find that forest shapes obey a robust perimeter-area scaling relation across climatic zones. We explain this scaling by introducing a heterogeneous fire propagation model of tropical forest-grassland ecotones. Deviations from this perimeter-area relation determine the stability of individual forest patches. At a larger scale, our model predicts that the relative rates of tree growth due to propagative expansion and long-distance seed dispersal determine whether collapse of regional-scale tree cover is continuous or discontinuous as fire frequency changes.

Exotic phase transitions of k-cores in clustered networks.

The giant k-core-maximal connected subgraph of a network where each node has at least k neighbors-is important in the study of phase transitions and in applications of network theory. Unlike Erdos-Rényi graphs and other random networks where k-cores emerge discontinuously for k≥3, we show that transitive linking (or triadic closure) leads to 3-cores emerging through single or double phase transitions of both discontinuous and continuous nature. We also develop a k-core calculation that includes clustering and provides insights into how high-level connectivity emerges.

How chimpanzees integrate sensory information to select figs.

Figs are keystone resources that sustain chimpanzees when preferred fruits are scarce. Many figs retain a green(ish) colour throughout development, a pattern that causes chimpanzees to evaluate edibility on the basis of achromatic accessory cues. Such behaviour is conspicuous because it entails a succession of discrete sensory assessments, including the deliberate palpation of individual figs, a task that requires advanced visuomotor control. These actions are strongly suggestive of domain-specific information processing and decision-making, and they call attention to a potential selective force on the origin of advanced manual prehension and digital dexterity during primate evolution. To explore this concept, we report on the foraging behaviours of chimpanzees and the spectral, chemical and mechanical properties of figs, with cutting tests revealing ease of fracture in the mouth. By integrating the ability of different sensory cues to predict fructose content in a Bayesian updating framework, we quantified the amount of information gained when a chimpanzee successively observes, palpates and bites the green figs of Ficus sansibarica. We found that the cue eliciting ingestion was not colour or size, but fig mechanics (including toughness estimates from wedge tests), which relays higher-quality information on fructose concentrations than colour vision. This result explains why chimpanzees evaluate green figs by palpation and dental incision, actions that could explain the adaptive origins of advanced manual prehension.

Exclusion processes with avalanches.

In an exclusion process with avalanches, when a particle hops to a neighboring empty site which is adjacent to an island the particle on the other end of the island immediately hops, and if it joins another island this triggers another hop. There are no restrictions on the length of the islands and the duration of the avalanche. This process is well defined in the low-density region ρ < 1/2. We describe the nature of steady states (on a ring) and determine all correlation functions. For the asymmetric version of the process, we compute the steady state current, and we describe shock and rarefaction waves which arise in the evolution of the step-function initial profile. For the symmetric version, we determine the diffusion coefficient and examine the evolution of a tagged particle.