Adaptive Network Model for Assisting People with Disabilities through Crowd Monitoring and Control.

Here, we present an effective application of adaptive cooperative networks, namely assisting disables in navigating in a crowd in a pandemic or emergency situation. To achieve this, we model crowd movement and introduce a cooperative learning approach to enable cooperation and self-organization of the crowd members with impaired health or on wheelchairs to ensure their safe movement in the crowd. Here, it is assumed that the movement path and the varying locations of the other crowd members can be estimated by each agent. Therefore, the network nodes (agents) should continuously reorganize themselves by varying their speeds and distances from each other, from the surrounding walls, and from obstacles within a predefined limit. It is also demonstrated how the available wireless trackers such as AirTags can be used for this purpose. The model effectiveness is examined with respect to the real-time changes in environmental parameters and its efficacy is verified.

Formulation of Common Spatial Patterns for Multi-Task Hyperscanning BCI.

This work proposes a new formulation for common spatial patterns (CSP), often used as a powerful feature extraction technique in brain-computer interfacing (BCI) and other neurological studies. In this approach, applied to multiple subjects' data and named as hyperCSP, the individual covariance and mutual correlation matrices between multiple simultaneously recorded subjects' electroencephalograms are exploited in the CSP formulation. This method aims at effectively isolating the common motor task between multiple heads and alleviate the effects of other spurious or undesired tasks inherently or intentionally performed by the subjects. This technique can provide a satisfactory classification performance while using small data size and low computational complexity. By using the proposed hyperCSP followed by support vector machines classifier, we obtained a classification accuracy of 81.82% over 8 trials in the presence of strong undesired tasks. We hope that this method could reduce the training error in multi-task BCI scenarios. The recorded valuable motor-related hyperscanning dataset is available for public use to promote the research in this area.

Bioconversion of Lignocellulosic Biomass into Value Added Products under Anaerobic Conditions: Insight into Proteomic Studies.

Production of biofuels and other value-added products from lignocellulose breakdown requires the coordinated metabolic activity of varied microorganisms. The increasing global demand for biofuels encourages the development and optimization of production strategies. Optimization in turn requires a thorough understanding of the microbial mechanisms and metabolic pathways behind the formation of each product of interest. Hydrolysis of lignocellulosic biomass is a bottleneck in its industrial use and often affects yield efficiency. The accessibility of the biomass to the microorganisms is the key to the release of sugars that are then taken up as substrates and subsequently transformed into the desired products. While the effects of different metabolic intermediates in the overall production of biofuel and other relevant products have been studied, the role of proteins and their activity under anaerobic conditions has not been widely explored. Shifts in enzyme production may inform the state of the microorganisms involved; thus, acquiring insights into the protein production and enzyme activity could be an effective resource to optimize production strategies. The application of proteomic analysis is currently a promising strategy in this area. This review deals on the aspects of enzymes and proteomics of bioprocesses of biofuels production using lignocellulosic biomass as substrate.

Effect of an obesogenic diet during the juvenile period on growth pattern, fatness and metabolic, cardiovascular and reproductive features of Swine with obesity/leptin resistance.

The objective of this study was to determine, in a female swine model of leptin resistance (Iberian pig), the effect of an obesogenic diet, with high saturated fat content, during the juvenile period, on the appearance of early obesity and its possible effects on metabolic syndrome-related parameters and reproductive features (puberty attainment). Thus, from 130 to 245 days-old, seven Iberian gilts had ad libitum access to food enriched with saturated fat whilst six females acted as controls and had ad libitum access to a commercial maintenance diet. Results showed that a high fat intake-level during the juvenile period induces early obesity with lower body weight and size but a higher body fat-content. Such obesity was related with impairments of glucose regulation predisposing for insulin resistance, but also with an earlier onset of puberty. However, there were no signs of hypertriglyceridemia and hypertension; the gilts diminish their intake level and modify their metabolic features by increasing insulin secretion. In conclusion, Iberian gilts freely eating saturated fat diets during the juvenile period have the prodrome of metabolic syndrome but, during their juvenile period, are still able to develop an adaptive response to the diet.