The role of off-board EV battery chargers in smart homes and smart grids: operation with renewables and energy storage systems

Concerns about climate changes and environmental air pollution are leading to the adoption of new technologies for transportation, mainly based on vehicle electrification and the interaction with smart grids, and also with the introduction of renewable energy sources (RES) accompanied by energy storage systems (ESS). For these three fundamental pillars, new power electronics technologies are emerging to transform the electrical power grid, targeting a flexible and collaborative operation. As a distinctive factor, the vehicle electrification has stimulated the presence of new technologies in terms of power management, both for smart homes and smart grids. As the title indicates, this book chapter focuses on the role of off-board EV battery chargers in terms of operation modes and contextualization for smart homes and smart grids in terms of opportunities. Based on a review of on-board and off-board EV battery charging systems (EV-BCS), this chapter focus on the off-board EV-BCS framed with RES and ESS as a dominant system in future smart homes. Contextualizing these aspects, three distinct cases are considered: (1) An ac smart home using separate power converters, according to the considered technologies; (2) A hybrid ac and dc smart home with an off-board EV-BCS interfacing RES and ESS, and with the electrical appliances plugged-in to the ac power grid; (3) A dc smart home using a unified 2 off-board EV-BCS with a single interface for the electrical power grid, and with multiple dc interfaces (RES, ESS, and electrical appliances). The results for each case are obtained in terms of efficiency and power quality, demonstrating that the off-board EV-BCS, as a unified structure for smart homes, presents better results. Besides, the off-board EV-BCS can also be used as an important asset for the smart grid, even when the EV is not plugged-in at the smart home.(undefined

Are estimates of food insecurity among college students accurate? Comparison of assessment protocols.

A growing body of literature suggests that post-secondary students experience food insecurity (FI) at greater rates than the general population. However, these rates vary dramatically across institutions and studies. FI assessment methods commonly used in studies with college students have not been scrutinized for psychometric properties, and varying protocols may influence resulting FI prevalence estimates. The objective of this study was to assess the performance of standard food security assessment protocols and to evaluate their agreement as well as the relative accuracy of these protocols in identifying student FI. A randomized sample of 4,000 undergraduate students were invited to participate in an online survey (Qualtrics, LLC, Provo, Utah, USA) that evaluated sociodemographic characteristics and FI with the 2-item food sufficiency screener and the 10-item USDA Adult Food Security Survey Module (FSSM; containing the abbreviated 6-item module). Four hundred sixty-two eligible responses were included in the final sample. The psychometric analysis revealed inconsistencies in college student response patterns on the FSSM when compared to national evaluations. Agreement between FI protocols was generally high (>90%) but was lessened when compared with a protocol that incorporated the 2-item screener. The 10-item FSSM with the 2-item screener had the best model fit (McFadden's R2 = 0.15 and Bayesian Information Criterion = -2049.72) and emerged as the tool providing the greatest relative accuracy for identifying students with FI. Though the 10-item FSSM and 2-item screener yields the most accuracy in this sample, it is unknown why students respond to FSSM items differently than the general population. Further qualitative and quantitative evaluations are needed to determine which assessment protocol is the most valid and reliable for use in accurately identifying FI in post-secondary students across the U.S

Longitudinal Study of Differential Protein Expression in an Alzheimer’s Mouse Model Lacking Inducible Nitric Oxide Synthase

Alzheimer’s disease (AD) is a complex neurodegenerative process that involves altered brain immune, neuronal and metabolic functions. Understanding the underlying mechanisms has relied on mouse models that mimic components of AD pathology. We used gel-free, label-free LC–MS/MS to quantify protein and phosphopeptide levels in brains of APPSwDI/NOS2–/– (CVN–AD) mice. CVN–AD mice show a full spectrum of AD-like pathology, including amyloid deposition, hyperphosphorylated and aggregated tau, and neuronal loss that worsens with age. Tryptic digests, with or without phosphopeptide enrichment on an automated titanium dioxide LC system, were separated by online two-dimensional LC and analyzed on a Waters Synapt G2 HDMS, yielding relative expression for >950 proteins and >1100 phosphopeptides. Among differentially expressed proteins were known markers found in humans with AD, including GFAP and C1Q. Phosphorylation of connexin 43, not previously described in AD, was increased at 42 weeks, consistent with dysregulation of gap junctions and activation of astrocytes. Additional alterations in phosphoproteins suggests dysregulation of mitochondria, synaptic transmission, vesicle trafficking, and innate immune pathways. These data validate the CVN–AD mouse model of AD, identify novel disease and age-related changes in the brain during disease progression, and demonstrate the utility of integrating unbiased and phosphoproteomics for understanding disease processes in AD

Longitudinal Study of Differential Protein Expression in an Alzheimer’s Mouse Model Lacking Inducible Nitric Oxide Synthase

Alzheimer’s disease (AD) is a complex neurodegenerative process that involves altered brain immune, neuronal and metabolic functions. Understanding the underlying mechanisms has relied on mouse models that mimic components of AD pathology. We used gel-free, label-free LC–MS/MS to quantify protein and phosphopeptide levels in brains of APPSwDI/NOS2–/– (CVN–AD) mice. CVN–AD mice show a full spectrum of AD-like pathology, including amyloid deposition, hyperphosphorylated and aggregated tau, and neuronal loss that worsens with age. Tryptic digests, with or without phosphopeptide enrichment on an automated titanium dioxide LC system, were separated by online two-dimensional LC and analyzed on a Waters Synapt G2 HDMS, yielding relative expression for >950 proteins and >1100 phosphopeptides. Among differentially expressed proteins were known markers found in humans with AD, including GFAP and C1Q. Phosphorylation of connexin 43, not previously described in AD, was increased at 42 weeks, consistent with dysregulation of gap junctions and activation of astrocytes. Additional alterations in phosphoproteins suggests dysregulation of mitochondria, synaptic transmission, vesicle trafficking, and innate immune pathways. These data validate the CVN–AD mouse model of AD, identify novel disease and age-related changes in the brain during disease progression, and demonstrate the utility of integrating unbiased and phosphoproteomics for understanding disease processes in AD