Background: Dementia is a neurodegenerative syndrome that affects one’s ability to remember, think, make decisions, and live independently. It is predicted that over 150 million people will be affected by dementia by 2030. There is currently no cure for dementia, and the best course of action is early detection and the management of modifiable risk factors. Motoric cognitive risk syndrome (MCR) is used to assess risk for developing dementia by taking into account two risk factors: slow gait speed and memory complaints. Its simplistic nature would allow for easy integration in clinical settings, rather than performing costly and arduous tests to predict dementia. Methods: The Framingham Heart Study (FHS) was established in 1948 in Framingham, Massachusetts. The Offspring cohort was initiated in 1971 with the children of the original Framingham cohort. Omni I was initiated in 1994 to include participants of mixed races. We excluded participants with dementia and those unable to complete activities of daily living from our study sample, leaving a sample size of n=2,435. MCR was defined as self-reported memory complaint and slow gait-speed, using a cut-off of 0.879 m/s (the average of male and female mean gait speeds minus one standard deviation). The Harvard semi-quantitative food frequency questionnaire was used to assess the Alternative Healthy Eating Index and its components. Accelerometer data was used to assess physical activity. Neuropsychological tests from the Wechsler Adult Intelligence Scale and Mini-Mental State Exam were used to assess cognition. Results: We reported an MCR prevalence of 7.3% (n=166) in our cohort of mostly older adults (>60 years). Participants with MCR were older (mean age 77.05 vs. 69.02 years in non-MCR) and more likely to be female (64.46% vs 54.91% in non-MCR). The presence of MCR was associated with depression (14.46% vs. 7.54%), lower scores on the Mini-Mental State Exam (28.27 vs. 28.81) and Alternative Healthy Eating Index (61.88 vs. 65.33), as well as higher sedentary time (15.50 vs. 14.18 hours per day) and fewer steps (3576 vs. 6227 steps per day), compared to those without MCR, even after adjusting for age, sex, BMI, and depression. Conclusion: People with MCR have distinct health characteristics, and different dietary and physical activity profiles compared to those without MCR. Additional studies characterizing those with MCR would allow for better detection of those who may be at the highest risk for dementia, which would lead to more patients receiving care to postpone the onset of dementia.

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The smart grid is forecasted to be the future of the grid by integrating the traditional grid with information and communication technology. However, the use of this technology has not only brought its benefits but also the vulnerability to cyber-attacks. False data injection (FDI) attacks are a new category of attacks targeting the smart grid that manipulates the state estimation process to trigger a chain of incorrect control decisions leading to severe impacts. This research proposes the use of cognitive dynamic systems (CDS) to address the cyber-security issue and improve state estimation. CDS is a powerful research tool inspired by certain features of the brain that can be used to study complex systems. As two of its special features, Cognitive Control (CC) is concerned with control in the absence of uncertainty, Cognitive Risk Control (CRC) uses the concept of predictive adaptation to bring risk under control in the presence of unexpected uncertainty. The primary research objective of this thesis is to apply the CDS for the SG with emphasis on state estimation and cyber-security. The main objective of CC is to improve the state estimation process while CRC is concerned with mitigating cyber-attacks. Simulation results show that the proposed methods have robust performance for both state estimation and cyber-attack mitigation under various challenging scenarios. This thesis contributes to the body of knowledge by achieving the following objectives: proposes the first theoretical work that integrates the CDS with the DC model of the SG for control and cyber-attack detection; demonstrates the first experimental work that brings a new concept of CRC for cyber-attack mitigation for the DC state estimator; introduces a new CDS architecture adapted for the AC model of the SG for state estimation and cyber-attack mitigation which builds upon all the research efforts made previously. / Thesis / Doctor of Philosophy (PhD) / The smart grid is forecasted to be the future of the grid by integrating the traditional grid with information and communication technology. However, the use of this technology has not only brought its benefits but also the vulnerability to cyber-attacks. False data injection attacks is a new category of attacks targeting the smart grid that can cause serious damage by manipulating the state estimation process and starting a chain of incorrect control decisions. The cognitive dynamic system is a powerful research tool inspired by the brain that can be used to study real time cyber physical systems. The key goal of this thesis is to apply cognitive dynamic systems to the smart grid to improve the state estimation process, detect cyber-attacks and mitigate their effects. Simulation results show that the proposed methods have robust performance in both state estimation and cyber-attack mitigation under various challenging scenarios.