Healthy aging among older adults requires the maintenance of good physical and cognitive activity. However, in the natural course of aging, older adults usually experience a decline in their physical and cognitive activity, causing an increasingly sedentary lifestyle. Some older adults may not have a choice but to become increasingly sedentary as they age due to injury or deteriorated physicality. As such they require a manner of assistive technologies to aid in their daily lives and activities to maintain healthy cognitive function. Social Robots are a newer form of assistive technology, specifically designed for social interactions and gameplay. As with other assistive technologies, compliance barriers to the acceptance and use of social robots and types of meaningful, seated activities among older adults are expected. To better explore this phenomenon, improve quality of life and understand what drives older adults to accept and use newer forms of technology like social robots, this research conjoins two conceptual frameworks: The Activity Theory of Aging (ATA) and the Unified Theory of Acceptance and Use of Technology (UTAUT). As social robots hold great promise for improving the quality of life for older adults, exploring what driving factors could enable their greater acceptance and use is essential to furthering this field of study within Australia.

Background: The Covid-19 pandemic was in reality a syndemic there the balance between a multitude of biological (Nature-made) and socio-political (men-made) factors determined individually the outcome of every single infection, on a scale of nothing-to-fatal. Blaming the virus for everything bad that happened to us after January 2020 is incorrect. Now, in ~ 2 years distance from the syndemic, it may be timely and possible to uncover the human contribution to this historical event and learn of it. Objective: To identify and use some qualitative approach to estimate the objective, statistical / epidemiological ‘value’ of the virus-selected individuals (in age-normalized groups) for the rest of the society. This non-political, non-religious approach may be the only way to understand the benefit / cost ratio of actions and emergency orders we had to survive in addition to the virus itself. Methods: Statistical data were obtained from publicly available official databases, including the relevant actuarial tables and evaluated by widely used statistical methods. The estimation of statistical/epidemiological ‘value of life’ was based, strictly and exclusively, on the real age and the statistically calculated Residual Life Expectancy (RLE, i.e. remaining years alive at a given age). The American healthcare expenses were compared to the corresponding healthcare costs/capita in other similarly well-developed west-European countries. This was the only available method to get some ideas about the magnitude of the well-established (rational) healthcare spending and compare it to the American standards. Results 1) Life expectancy uninterruptedly increased in USA since 1933, due to continuous reduction of Mortality Rate of the youngest and oldest citizens. COVID didn’t stop the population growth (+8.2 M /2020-2023). 2) The total count of Excess COVID associated Deaths (XCD) is ~ 2-times as much as the official statistic was able to explain by virus infection. It is speculated that these Complementary Covid Deaths (CCD) are probably the unexpected side-effects of the pandemic related emergency orders. 3) The worldwide ‘longevity’ trend exponentially increased the healthcare expenses, especially the care of elderly. However the USA is unique in this aspect and the healthcare costs are irrationally much higher than in any other country. 4) We can see a large economic incentive in the development of excesses under COVID syndemic. Conclusions The harm of the COVID virus - as well as the benefits of the mandatory, emergency actions during the pandemic - were grossly over-estimated. Professional, unbiased (non-religious, non-political) and independent reviews are strongly recommended.

Retired Electric vehicles (EVs) batteries are reused in second life energy storage applications. However, the overall performance of repurposed energy storage system (ESS) is limited by the unevenness of individual batteries use in it. Therefore, battery grading is required for optimal performance of ESS. Electrochemical impedance spectroscopy (EIS) based evaluation of battery aging is a promising way to grade lithium-ion batteries. However, it is not practical to measure impedance of mass retired batteries due to high complexity and slowness. In this paper, a broadband multi-sine binary signal (MSBS) perturbation integrated with multichannel EIS system is presented to measure impedance spectra for high-speed aging evaluation of lithium-ion batteries or modules. The measurement speed is multi-times higher than conventional EIS with single-channel configuration. The broadband MSBS is validated with reference sinusoidal sweep perturbation and corresponding root-mean-square error (RMSE) analysis is performed. Moreover, the accuracy of the presented multichannel EIS system is validated by impedance spectra measurement of Samsung INR18650-29E batteries and comparing it with those measured with commercial EIS instrument. A chi-squared error under 0.641% is obtained for all 8-channels. Since the non-linearity of battery has significant impact on quality of impedance spectra. Therefore, Kronig-Kramer (KK) transform validation is also performed.

At the molecular level, aging is often accompanied by dysfunction of stress-induced membrane-less organelles (MLOs) and changes in their material state. In this work, we analyzed the proteins included in the proteome of stress granules (SGs) and P-bodies for their tendency to transform the material state of these MLOs. Particular attention was paid to proteins whose gene expression changes during replicative aging. It was shown that the proteome of the studied MLOs practically does not differ in the analyzed characteristics and consists of completely or partially intrinsically disordered proteins, 30 - 40% of which are potentially capable of liquid-liquid phase separation (LLPS). At the same time, the proportion of proteins capable of spontaneous LLPS is relatively small, which indicates the leading role of nucleic acids in the biogenesis of these membrane-less organelles. Proteins whose gene expression changes during the transition of human cells to a senescent state make up about 20% of the studied proteomes. There is a statistically significant increase in the number of positively charged proteins in both datasets studied compared to the complete proteomes of these organelles. An increase in the relative content of DNA-, but not RNA-binding proteins, was also found in the stress-granules dataset with senescence-related processes. Among SG proteins potentially involved in senescent processes, there is an increase in the abundance of potentially amyloidogenic proteins compared to the whole proteome. The hnRPDL protein has the highest degree of disorder and highest propensity for LLPS among such proteins, which allows us to consider it as “potentially dangerous.” Proteins common to SGs and P bodies, potentially involved in processes associated with senescence, form clusters of interacting proteins. The largest cluster is represented by RNA-binding proteins involved in RNA processing and translation regulation. These data indicate that SG proteins, but not proteins of P-bodies, are more likely to transform the material state of MLOs. Furthermore, these MLOs can participate in processes associated with aging in a coordinated manner.

Neurodegeneration is a major problem in neuroscience and medicine as it causes and worsens many neurological and psychiatric disorders. It involves gradual loss of neurons at different levels of the brain, affecting cognition, emotion, behavior, consciousness, and attention. Understanding the causes and consequences of neurodegeneration is crucial for identifying the risk factors, biomarkers, and treatments. However, the current therapies are mostly symptomatic and ineffective. Therefore, new and innovative methods, such as noninvasive brain stimulation (NIBS), are needed to modulate brain activity and plasticity in a safe and reversible manner. This field is rapidly developing, with a focus on exploring new clinical applications, mechanisms, and combinations of NIBS and drugs. This special issue covers the latest progress and challenges in the study of neurodegeneration in cognitive impairment and mood disorders from the experimental, clinical, and translational perspectives. It addresses the complexity and diversity of these conditions, the lack of disease-modifying treatments, the ethical and practical issues of conducting research in vulnerable and diverse populations, the integration and interpretation of data from multiple sources and modalities, and the development and validation of novel methods such as NIBS, artificial intelligence, and drug repurposing. Collaborative efforts among various stakeholders are needed to improve our knowledge and treatment of neurodegeneration underlying cognitive impairment and mood disorders.