Self-assembly enables nature to build complex forms, from multicellular organisms to complex animal structures such as flocks of birds, through the interaction of vast numbers of limited and unreliable individuals. Creating this ability in engineered systems poses challenges in the design of both algorithms and physical systems that can operate at such scales. We report a system that demonstrates programmable self-assembly of complex two-dimensional shapes with a thousand-robot swarm. This was enabled by creating autonomous robots designed to operate in large groups and to cooperate through local interactions and by developing a collective algorithm for shape formation that is highly robust to the variability and error characteristic of large-scale decentralized systems. This work advances the aim of creating artificial swarms with the capabilities of natural ones.

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We present the discrete beeping communication model, which assumes nodes have minimal knowledge about their environment and severely limited communication capabilities. Specifically, nodes have no information regarding the local or global structure of the network, don't have access to synchronized clocks and are woken up by an adversary. Moreover, instead on communicating through messages they rely solely on carrier sensing to exchange information. This model is interesting from a practical point of view, because it is possible to implement it (or emulate it) even in extremely restricted radio network environments. From a theory point of view, it shows that complex problems (such as vertex coloring) can be solved efficiently even without strong assumptions on properties of the communication model.We study the problem of interval coloring, a variant of vertex coloring specially suited for the studied beeping model. Given a set of resources, the goal of interval coloring is to assign every node a large contiguous fraction of the resources, such that neighboring nodes share no resources.To highlight the importance of the discreteness of the model, we contrast it against a continuous variant described in [17]. We present an O(1) time algorithm that terminates with probability 1 and assigns an interval of size Ω(T /∆) that repeats every T time units to every node of the network. This improves an O(log n) time algorithm with the same guarantees presented in [17], and accentuates the unrealistic assumptions of the continuous model. Under the more realistic discrete model, we present a Las Vegas algorithm that solves Ω(T /∆)-interval coloring in O(log n) time with high probability and describe how to adapt the algorithm for dynamic networks where nodes may join or leave. For constant degree graphs we prove a lower bound of Ω(log n) on the time required to solve interval coloring for this model against randomized algorithms. This lower bound implies that our algorithm is asymptotically optimal for constant degree graphs.

The adhesion ability and adaptability of bacteria, coupled with constant use of the same bactericides, have made the increase in the diversity of treatments against infections necessary. Nanotechnology has played an important role in the search for new ways to prevent and treat infections, including the use of metallic nanoparticles with antibacterial properties. In this study, we worked on the design of a composite of silver nanoparticles (AgNPS) embedded in poly-epsilon-caprolactone nanofibers and evaluated its antimicrobial properties against various Gram-positive and Gram-negative microorganisms associated with drug-resistant infections. Polycaprolactone-silver composites (PCL-AgNPs) were prepared in two steps. The first step consisted in the reduction in situ of Ag+ions using N,N-dimethylformamide (DMF) in tetrahydrofuran (THF) solution, and the second step involved the simple addition of polycaprolactone before electrospinning process. Antibacterial activity of PCL-AgNPs nanofibers againstE. coli,S. mutans,K. pneumoniae,S. aureus,P. aeruginosa, andB. subtiliswas evaluated. Results showed sensibility ofE. coli,K. pneumoniae,S. aureus, andP. aeruginosa, but not forB. subtilisandS. mutans. This antimicrobial activity of PCL-AgNPs showed significant positive correlations associated with the dose-dependent effect. The antibacterial property of the PCL/Ag nanofibers might have high potential medical applications in drug-resistant infections.

We consider the problem of computing a maximal independent set (MIS) in an extremely harsh broadcast model that relies only on carrier sensing. The model consists of an anonymous broadcast network in which nodes have no knowledge about the topology of the network or even an upper bound on its size. Furthermore, it is assumed that an adversary chooses at which time slot each node wakes up. At each time slot a node can either beep, that is, emit a signal, or be silent. At a particular time slot, beeping nodes receive no feedback, while silent nodes can only differentiate between none of its neighbors beeping, or at least one of its neighbors beeping.We start by proving a lower bound that shows that in this model, it is not possible to locally converge to an MIS in sub-polynomial time. We then study four different relaxations of the model which allow us to circumvent the lower bound and find an MIS in polylogarithmic time. First, we show that if a polynomial upper bound on the network size is known, it is possible to find an MIS in O(log 3 n) time. Second, if we assume sleep-ing nodes are awoken by neighboring beeps, then we can also find an MIS in O(log 3 n) time. Third, if in addition to this wakeup assumption we allow sender-side collision detection, that is, beeping nodes can distinguish whether at least one neighboring node is beeping concurrently or not, we can find an MIS in O(log 2 n) time. Finally, if instead we endow nodes with synchronous clocks, it is also possible to find an MIS in O(log 2 n) time.