Immediate fall prevention: the missing key to a comprehensive solution for falling hazard in older adults.

The world is witnessing an unprecedented demographic shift due to increased life expectancy and declining birth rates. By 2050, 20% of the global population will be over 60, presenting significant challenges like a shortage of caregivers, maintaining health and independence, and funding extended retirement. The technology that caters to the needs of older adults and their caregivers is the most promising candidate to tackle these issues. Although multiple companies and startups offer various aging solutions, preventive technology, which could prevent trauma, is not a big part of it. Trauma is the leading cause of morbidity, disability, and mortality in older adults, and statistics constitute traumatic fall accidents as its leading cause. Therefore, an immediate preventive technology that anticipates an accident on time and prevents it must be the first response to this hazard category to decrease the gap between life expectancy and the health/wellness expectancy of older adults. The article outlines the challenges of the upcoming aging crisis and introduces falls as one major challenge. After that, falls and their mechanisms are investigated, highlighting the cognitive functions and their relation to falls. Moreover, since understanding predictive cognitive mechanisms is critical to an effective prediction-interception design, they are discussed in more detail, signifying the role of cognitive decline in balance maintenance. Furthermore, the landscape of available solutions for falling and its shortcomings is inspected. Finally, immediate fall prevention, the missing part of a wholesome solution, and its barriers are introduced, and some promising methodologies are proposed.

"Extended Descriptive Risk-Averse Bayesian Model" a More Comprehensive Approach in Simulating Complex Biological Motion Perception.

The ability to perceive biological motion is crucial for human survival, social interactions, and communication. Over the years, researchers have studied the mechanisms and neurobiological substrates that enable this ability. In a previous study, we proposed a descriptive Bayesian simulation model to represent the dorsal pathway of the visual system, which processes motion information. The model was inspired by recent studies that questioned the impact of dynamic form cues in biological motion perception and was trained to distinguish the direction of a soccer ball from a set of complex biological motion soccer-kick stimuli. However, the model was unable to simulate the reaction times of the athletes in a credible manner, and a few subjects could not be simulated. In this current work, we implemented a novel disremembering strategy to incorporate neural adaptation at the decision-making level, which improved the model's ability to simulate the athletes' reaction times. We also introduced receptive fields to detect rotational optic flow patterns not considered in the previous model to simulate a new subject and improve the correlation between the simulation and experimental data. The findings suggest that rotational optic flow plays a critical role in the decision-making process and sheds light on how different individuals perform at different levels. The correlation analysis of human versus simulation data shows a significant, almost perfect correlation between experimental and simulated angular thresholds and slopes, respectively. The analysis also reveals a strong relation between the average reaction times of the athletes and the simulations.

Corrigendum to "Multiband rabi antenna using nest microstrip add-drop filter (NMADF) for relativistic sensing applications" [Heliyon 9(2) (February 2023) e13611].

[This corrects the article DOI: 10.1016/j.heliyon.2023.e13611.].

Multiband Rabi antenna using nest microstrip add-drop filter (NMADF) for relativistic sensing applications.

A microstrip circuit is designed, constructed, and tested based on the nest microstrip add-drop filters (NMADF). The multi-level system oscillation is generated by the wave-particle behaviors of AC driven along the microstrip ring circular path. The continuous successive filtering is applied via the device input port. The higher-order harmonic oscillations can be filtered, from which the two-level system known as a Rabi oscillation is achieved. The outside microstrip ring energy is coupled to the inside rings, from which the multiband Rabi oscillations can be formed within the inner rings. The resonant Rabi frequencies can be applied for multi-sensing probes. The relationship between electron density and Rabi oscillation frequency of each microstrip ring output can be obtained and used for multi-sensing probe applications. The relativistic sensing probe can be obtained by the warp speed electron distribution at the resonant Rabi frequency respecting the resonant ring radii. These are available for relativistic sensing probe usage. The obtained experimental results have shown that there are 3-center Rabi frequencies obtained, which can be used for 3-sensing probes simultaneously. The sensing probe speeds of 1.1c, 1.4c, and 1.5c are obtained using the microstrip ring radii of 14.20, 20.12, and 34.49 mm, respectively. The best sensor sensitivity of 1.30 ms is achieved. The relativistic sensing platform can be used for many applications.

"Descriptive Risk-Averse Bayesian Decision-Making," a Model for Complex Biological Motion Perception in the Human Dorsal Pathway.

Biological motion perception is integral not only to survival but also to the social life of human beings. Identifying the underlying mechanisms and their associated neurobiological substrates has been a matter of investigation and debate for some time. Although, in general, it is believed that the integration of local motion and dynamic form cues in the brain empowers the visual system to perceive/recognize biological motion stimuli, some recent studies have indicated the importance of dynamic form cues in such a process. Inspired by the previous neurophysiologically plausible biological motion perception models, a new descriptive risk-averse Bayesian simulation model, capable of discerning a ball's direction from a set of complex biological motion soccer kick stimuli, is proposed. The model represents only the dorsal pathway as a motion information processing section of the visual system according to the two-stream theory. The stimuli used have been obtained from a previous psychophysical study on athletes in our lab. Furthermore, the acquired psychophysical data from that study have been used to re-enact human behavior using our simulation model. By adjusting the model parameters, the psychometric function of athlete subjects has been mimicked. A correlation analysis between human and simulation data shows a significant and robust correlation between angular thresholds and slopes of the psychometric functions of both groups. Although it is established that the visual system optimally integrates all available information in the decision-making process, the results conform to the speculations favoring motion cue importance over dynamic form by testing the limits in which biological motion perception only depends on motion information processing.