Renan C. Moioli’s research while affiliated with Heriot-Watt University and other places

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic hit almost all cities in Brazil in early 2020 and lasted for several months. Despite the effort of local state and municipal governments, an inhomogeneous nationwide response resulted in a death toll amongst the highest recorded globally. To evaluate the impact of the nonpharmaceutical governmental interventions applied by different cities—such as the closure of schools and businesses in general—in the evolution and epidemic spread of SARS-CoV-2, we constructed a full-sized agent-based epidemiological model adjusted to the singularities of particular cities. The model incorporates detailed demographic information, mobility networks segregated by economic segments, and restricting bills enacted during the pandemic period. As a case study, we analyzed the early response of the City of Natal—a midsized state capital—to the pandemic. Although our results indicate that the government response could be improved, the restrictive mobility acts saved many lives. The simulations show that a detailed analysis of alternative scenarios can inform policymakers about the most relevant measures for similar pandemic surges and help develop future response protocols.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic hit almost all cities in Brazil in early 2020 and lasted for several months. Despite the effort of local state and municipal governments, an inhomogeneous nationwide response resulted in a death toll amongst the highest recorded globally. To evaluate the impact of the nonpharmaceutical governmental interventions applied by different cities – such as the closure of schools and business in general – in the evolution and epidemic spread of SARS-CoV-2, we constructed a full-sized agent-based epidemiological model adjusted to the singularities of particular cities. The model incorporates detailed demographic information, mobility networks segregated by economic segments, and restricting bills enacted during the pandemic period. As a case study, we analyzed the early response of the City of Natal – a midsized state capital – to the pandemic. Although our results indicate that the governmental response could be improved, the restrictive mobility acts saved many lives. The simulations show that a detailed analysis of alternative scenarios can inform policymakers about the most relevant measures for similar pandemic surges and help developing future response protocols.

Cyborg insects are a major part of the vision of future interactions of the living world and technology, including but not limited to the Internet of Living Things (IoLT). They are crawling or flying insects with additional electronic circuitry allowing remote control of their movement and collection of sensory data. In this critical review, we survey the historical development of cyborg insects engineering, from the first backpacks on insects used for communication and sensing, to different methods of control and actuation of insects’ locomotion. We review the suggested applications of cyborg insects ranging from military use to agriculture, pointing out the problematic connotations of swarms and cyborgs in these contexts. We address the applications and the narratives around engineered insects from the perspective of philosophy, economy, law, and politics. We add perspectives on emancipatory potential of cyborg technology and where the future of it could lie.

Smart meters with automatic meter reading functionalities are becoming popular across the world. As a result, load measurements at various sampling frequencies are now available. Several methods have been proposed to infer device usage characteristics from household load measurements. However, many techniques are based on highly intensive computations that incur heavy computational costs; moreover, they often rely on private household information. In this paper, we propose a technique for the detection of appliance utilization patterns using low-computational-cost algorithms that do not require any information about households. Appliance utilization patterns are identified only from the system status behavior, represented by large system status datasets, by using dimensionality reduction and clustering algorithms. Principal component analysis, k-means, and the elbow method are used to define the clusters, and the minimum spanning tree is used to visualize the results that show the appearance of utilization patterns. Self organizing maps are used to create a system status classifier. We applied our techniques to two public datasets from two different countries, the United Kingdom (UK-DALE) and the US (REDD), with different usage patterns. The proposed clustering techniques enable effective demand-side management, while the system status classifier can detect appliance malfunctions only through system status analyses.

Modeling is widely used in biomedical research to gain insights into pathophysiology and treatment of neurological disorders but existing models, such as animal models and computational models, are limited in generalizability to humans and are restricted in the scope of possible experiments. Robotics offers a potential complementary modeling platform, with advantages such as embodiment and physical environmental interaction yet with easily monitored and adjustable parameters. In this review, we discuss the different types of models used in biomedical research and summarize the existing neurorobotics models of neurological disorders. We detail the pertinent findings of these robot models which would not have been possible through other modeling platforms. We also highlight the existing limitations in a wider uptake of robot models for neurological disorders and suggest future directions for the field.

Extended phenotypes are manifestations of genes that occur outside of the organism that possess those genes. In spite of their widespread occurrence, the role of extended phenotypes in evolutionary biology is still a matter of debate. Here, we explore the indirect effects of extended phenotypes, especially their shared use, in the fitness of simulated individuals and populations. A computer simulation platform was developed in which different populations were compared regarding their ability to produce, use, and share extended phenotypes. Our results show that populations that produce and share extended phenotypes outrun populations that only produce them. A specific parameter in the simulations, a bonus for sharing extended phenotypes among conspecifics, has a more significant impact in defining which population will prevail. All these findings strongly support the view, postulated by the extended fitness hypothesis (EFH) that extended phenotypes play a significant role at the population level and their shared use increases population fitness. Our simulation platform is available at https://github.com/guilherme-araujo/gsop-dist.

Parkinson's disease (PD) is a chronic neurodegenerative disease whose motor symptoms are accompanied by an exaggerated power in the alpha-beta (7-35Hz) band and an increased synchronization of neurons encompassing the cortex-basal ganglia-thalamus network. Currently, deep brain stimulation (DBS) is used as an effective therapy for reducing the excessive power and synchrony observed in brain circuits, thereby ameliorating the PD symptoms. In the present study, we used a biologically plausible computational model of cortex-basal ganglia-thalamus network, which represents both healthy and PD conditions, to systematically investigate the effects of DBS frequency on the model outputs. DBS was applied to the subthalamic nucleus (STN) at different stimulation frequencies (40Hz to 300Hz). Spike train variability and spectral power in the 7-35Hz band were measured from the several nuclei represented in the model. In addition, the magnitude squared coherence between the nuclei was assessed. An increased DBS frequency tended to produce interspike intervals (ISIs) with higher variability as compared to PD condition. Also, DBS significantly reduced the alpha-beta power for almost all brain nuclei. The median of the magnitude-squared coherence matrix (which is a metric of global network synchronization) decreased significantly with the increase of DBS frequency.

Exoskeletons for locomotion, support, or other uses are becoming more common. An increasing number of studies are demonstrating relevant results in rehabilitation. Here we describe the steps required to properly place and train patients in ExoAtlet ® powered exoskeletons (Moscow, Russia), for which there is currently limited information available. These steps combine actions related to the hardware, software, as well as safety, rehabilitation, and psycho-emotional state of the subject. Training starts with a general preparation of the environment, the equipment, and the patient. When the actual training program begins, the patient needs to gradually learn to perform the different actions that will be required to control the exoskeleton. Initially, training requires transferring weight between legs to guarantee adequate equilibrium control. Then, actions assisted by computer-controlled motors begin, namely: standing up, walking in place, moving small distances and sitting down. As the patient becomes comfortable with the exoskeleton and the cardiovascular system becomes adjusted to the upright position, training can then include walking over longer distances, inclined planes, opening doors, and climbing stairs. • Powered exoskeletons are becoming a common method in rehabilitation. • The use of ExoAtlet ® powered exoskeletons in clinical research requires manipulation of variables thought to promote rehabilitation, without compromising safety standards. • The phases of training are: transferring weight between legs, walk in place, and walk over longer distances.

Objective We compared the cognitive performance and neuroelectric responses during a selective attentional task in judo athletes with different levels of expertise. Methods Judo black and white belt athletes performed both general and specific fitness tests while simultaneously completing a Stroop color-word test recorded by 64 electroencephalogram channels. Results Cognitive behavioral performance and event-related spectral perturbation (ERSP) present no differences between groups. However, the topographic analysis found different neural source patterns in each group. Judo black belts compared to judo white belts presented a greater peak amplitude of P300 in the middle frontal gyrus and of N200 in the cuneus, but slower latency of P300 in the precuneus. Conclusion Despite no difference in cognitive behavioral performance, judo expertise causes a difference in the allocation of attentional and conflict detection neural resources.