A New Model of Air-Oxygen Blender for Mechanical Ventilators Using Dynamic Pressure Sensors.

Respiratory diseases are among the leading causes of death globally, with the COVID-19 pandemic serving as a prominent example. Issues such as infections affect a large population and, depending on the mode of transmission, can rapidly spread worldwide, impacting thousands of individuals. These diseases manifest in mild and severe forms, with severely affected patients requiring ventilatory support. The air-oxygen blender is a critical component of mechanical ventilators, responsible for mixing air and oxygen in precise proportions to ensure a constant supply. The most commonly used version of this equipment is the analog model, which faces several challenges. These include a lack of precision in adjustments and the inspiratory fraction of oxygen, as well as gas wastage from cylinders as pressure decreases. The research proposes a blender model utilizing only dynamic pressure sensors to calculate oxygen saturation, based on Bernoulli's equation. The model underwent validation through simulation, revealing a linear relationship between pressures and oxygen saturation up to a mixture outlet pressure of 500 cmH2O. Beyond this value, the relationship begins to exhibit non-linearities. However, these non-linearities can be mitigated through a calibration algorithm that adjusts the mathematical model. This research represents a relevant advancement in the field, addressing the scarcity of work focused on this essential equipment crucial for saving lives.

Percolation theory for the recognition of patterns in topographic images of the cortical activity.

Electroencephalogram (EEG) is one of the mechanisms used to collect complex data. Its use includes evaluating neurological disorders, investigating brain function and correlations between EEG signals and real or imagined movements. The Topographic Image of Cortical Activity (TICA) records obtained by the EEG make it possible to observe, through color discrimination, the cortical areas that represent greater or lesser activity. Percolation Theory (PT) reveals properties on the aspects of fluid spreading from a central point, these properties being related to the aspects of the medium, topological characteristics and ease of penetration of a fluid in materials. The hypothesis presented so far considers that synaptic activities originate in points and spread from them, causing different areas of the brain to interact in a diffusive associative behavior, generating electric and magnetic fields by the currents that spread through the brain tissue and have an effect on the scalp sensors. Brain areas spatially separated create large-scale dynamic networks that are described by functional and effective connectivity. The proposition is that this phenomenon behaves like a fluidic spreading, so we can use the PT, through the topological analysis we detect specific signatures related to neural phenomena that manifest changes in the behavior of synaptic diffusion. This signature must be characterized by the Fractal Dimension (FD) values of the scattering clusters, these values will be used as properties in the k-Nearest Neighbors (kNN) method, an TICA will be categorized according to the degree of similarity to the preexisting patterns. In this context, our hypothesis will consolidate as a more computational resource in the service of medicine and another way that opens with the possibility of analysis and detailed inferences of the brain through TICA that go beyond a simply visual observation, as it happens in the present day.

Low-frequency rTMS stimulation over superior parietal cortex medially improves time reproduction and increases the right dorsolateral prefrontal cortex predominance.

AIM OF THE STUDY: Previous studies have shown that several cortical regions are involved in temporal tasks in multiple timescales. However, the hemispheric predominance of the dorsolateral prefrontal cortex (DLPFC) during time reproduction after repetitive low-frequency transcranial magnetic stimulation (rTMS) is relatively unexplored. Here, we study the effects of 1 Hz rTMS and sham stimulation applied medially over the superior parietal cortex (SPC) on the DLPFC alpha and beta band asymmetry and on time reproduction. MATERIALS AND METHODS: For this purpose, we have combined rTMS with electroencephalography in 20 healthy subjects who performed the time reproduction task in two conditions (sham and 1 Hz). RESULTS: The worst performance was observed in sham and 1Hz conditions for longer time intervals (p < .05), with the 1Hz condition subjects sub-reproducing the time interval, closer to the target interval (p < .05). The right DLPFC hemispheric predominance was found in both conditions, but after low-frequency rTMS, the right hemisphere predominance increased in the 1Hz condition (p < .05). CONCLUSIONS: Results of this study suggest that rTMS applied over the SPC influences time interval interpretation and the DLPFC functions. Future studies would explore the effects of the rTMS application to other cortical areas, and study how it influences time interval interpretation.

Time Perception Mechanisms at Central Nervous System.

The five senses have specific ways to receive environmental information and lead to central nervous system. The perception of time is the sum of stimuli associated with cognitive processes and environmental changes. Thus, the perception of time requires a complex neural mechanism and may be changed by emotional state, level of attention, memory and diseases. Despite this knowledge, the neural mechanisms of time perception are not yet fully understood. The objective is to relate the mechanisms involved the neurofunctional aspects, theories, executive functions and pathologies that contribute the understanding of temporal perception. Articles form 1980 to 2015 were searched by using the key themes: neuroanatomy, neurophysiology, theories, time cells, memory, schizophrenia, depression, attention-deficit hyperactivity disorder and Parkinson's disease combined with the term perception of time. We evaluated 158 articles within the inclusion criteria for the purpose of the study. We conclude that research about the holdings of the frontal cortex, parietal, basal ganglia, cerebellum and hippocampus have provided advances in the understanding of the regions related to the perception of time. In neurological and psychiatric disorders, the understanding of time depends on the severity of the diseases and the type of tasks.