Technology and Caregiving: Emerging Interventions and Directions for Research.

An array of technology-based interventions has increasingly become available to support family caregivers, primarily focusing on health and well-being, social isolation, financial, and psychological support. More recently the emergence of new technologies such as mobile and cloud, robotics, connected sensors, virtual/augmented/mixed reality, voice, and the evermore ubiquitous tools supported by advanced data analytics, coupled with the integration of multiple technologies through platform solutions, have opened a new era of technology-enabled interventions that can empower and support family caregivers. This paper proposes a conceptual framework for identifying and addressing the challenges that may need to be overcome to effectively apply technology-enabled solutions for family caregivers. The paper identifies a number of challenges that either moderate or mediate the full use of technologies for the benefit of caregivers. The challenges include issues related to equity, inclusion, and access; ethical concerns related to privacy and security; political and regulatory factors affecting interoperability and lack of standards; inclusive/human-centric design and issues; and inherent economic and distribution channel difficulties. The paper concludes with a summary of research questions and issues that form a framework for global research priorities

Design Considerations for Parallel Differential Power Processing Converters in a Photovoltaic-Powered Wearable Application

Solar photovoltaic (PV) power is a widely used to supply power to the electric grid but can also be used in lower-power emerging applications, like in wearables or the internet of things. One fundamental challenge of using PV power in flexible wearable applications is that individual PV modules point at various angles, thus receiving different light intensities. Using a series configuration for the PV modules greatly decreases power utilization under uneven irradiance conditions. Parallel differential power processing (DPP) converters are employed to address this power reduction problem, while maintaining individual PV control and maximizing output power. Two parallel DPP configurations, with and without a front-end converter, are analyzed and compared for a target battery-charging application. The DPP system without a front-end converter shows consistently high performance and operates properly over a wider range of lighting conditions. Maximum power point tracking (MPPT) algorithms are also examined for parallel DPP systems. When the MPPT parameters are properly calibrated, simulation results indicate that voltage-offset resistive control is the most effective at maximizing PV power under unbalanced lighting conditions

All-Optical Ultrafast Control and Read-Out of a Single Negatively Charged Self-Assembled InAs Quantum Dot

We demonstrate the all-optical ultrafast manipulation and read-out of optical transitions in a single negatively charged self-assembled InAs quantum dot, an important step towards ultrafast control of the resident spin. Experiments performed at zero magnetic field show the excitation and decay of the trion (negatively charged exciton) as well as Rabi oscillations between the electron and trion states. Application of a DC magnetic field perpendicular to the growth axis of the dot enables observation of a complex quantum beat structure produced by independent precession of the ground state electron and the excited state heavy hole spins

Fast spin rotations by optically controlled geometric phases in a quantum dot

We demonstrate optical control of the geometric phase acquired by one of the spin states of an electron confined in a charge-tunable InAs quantum dot via cyclic 2pi excitations of an optical transition in the dot. In the presence of a constant in-plane magnetic field, these optically induced geometric phases result in the effective rotation of the spin about the magnetic field axis and manifest as phase shifts in the spin quantum beat signal generated by two time-delayed circularly polarized optical pulses. The geometric phases generated in this manner more generally perform the role of a spin phase gate, proving potentially useful for quantum information applications.Comment: 4 pages, 3 figures, resubmitted to Physical Review Letter

Power Electronics Technology for Large-Scale Renewable Energy Generation

Grid integration of renewable energy (REN) requires efficient and reliable power conversion stages, particularly with an increasing demand for high controllability and flexibility seen from the grid side. Underpinned by advanced control and information technologies, power electronics converters play an essential role in large-scale REN generation. However, the use of power converters has also exposed several challenges in conventional power grids, e.g., reducing the system inertia. In this article, grid integration using power electronics is presented for large-scale REN generation. Technical issues and requirements are discussed with a special focus on grid-connected wind, solar photovoltaic, and energy storage systems. In addition, the core of the energy generation and conversion—control for individual power converters (e.g., general current control) and for the system level (e.g., coordinated operation of large-scale energy systems)—is briefly discussed. Future research perspectives are then presented, which further advance large-scale REN generation technologies by incorporating more power electronics systems

In utero and childhood polybrominated diphenyl ether (PBDE) exposures and neurodevelopment in the CHAMACOS study.

BackgroundCalifornia children's exposures to polybrominated diphenyl ether flame retardants (PBDEs) are among the highest worldwide. PBDEs are known endocrine disruptors and neurotoxicants in animals.ObjectiveHere we investigate the relation of in utero and child PBDE exposure to neurobehavioral development among participants in CHAMACOS (Center for the Health Assessment of Mothers and Children of Salinas), a California birth cohort.MethodsWe measured PBDEs in maternal prenatal and child serum samples and examined the association of PBDE concentrations with children's attention, motor functioning, and cognition at 5 (n = 310) and 7 years of age (n = 323).ResultsMaternal prenatal PBDE concentrations were associated with impaired attention as measured by a continuous performance task at 5 years and maternal report at 5 and 7 years of age, with poorer fine motor coordination-particularly in the nondominant-at both age points, and with decrements in Verbal and Full-Scale IQ at 7 years. PBDE concentrations in children 7 years of age were significantly or marginally associated with concurrent teacher reports of attention problems and decrements in Processing Speed, Perceptual Reasoning, Verbal Comprehension, and Full-Scale IQ. These associations were not altered by adjustment for birth weight, gestational age, or maternal thyroid hormone levels.ConclusionsBoth prenatal and childhood PBDE exposures were associated with poorer attention, fine motor coordination, and cognition in the CHAMACOS cohort of school-age children. This study, the largest to date, contributes to growing evidence suggesting that PBDEs have adverse impacts on child neurobehavioral development

Statistical Workflow for Feature Selection in Human Metabolomics Data.

High-throughput metabolomics investigations, when conducted in large human cohorts, represent a potentially powerful tool for elucidating the biochemical diversity underlying human health and disease. Large-scale metabolomics data sources, generated using either targeted or nontargeted platforms, are becoming more common. Appropriate statistical analysis of these complex high-dimensional data will be critical for extracting meaningful results from such large-scale human metabolomics studies. Therefore, we consider the statistical analytical approaches that have been employed in prior human metabolomics studies. Based on the lessons learned and collective experience to date in the field, we offer a step-by-step framework for pursuing statistical analyses of cohort-based human metabolomics data, with a focus on feature selection. We discuss the range of options and approaches that may be employed at each stage of data management, analysis, and interpretation and offer guidance on the analytical decisions that need to be considered over the course of implementing a data analysis workflow. Certain pervasive analytical challenges facing the field warrant ongoing focused research. Addressing these challenges, particularly those related to analyzing human metabolomics data, will allow for more standardization of as well as advances in how research in the field is practiced. In turn, such major analytical advances will lead to substantial improvements in the overall contributions of human metabolomics investigations

The burden of acute respiratory infections in crisis-affected populations: a systematic review

Crises due to armed conflict, forced displacement and natural disasters result in excess morbidity and mortality due to infectious diseases. Historically, acute respiratory infections (ARIs) have received relatively little attention in the humanitarian sector. We performed a systematic review to generate evidence on the burden of ARI in crises, and inform prioritisation of relief interventions. We identified 36 studies published since 1980 reporting data on the burden (incidence, prevalence, proportional morbidity or mortality, case-fatality, attributable mortality rate) of ARI, as defined by the International Classification of Diseases, version 10 and as diagnosed by a clinician, in populations who at the time of the study were affected by natural disasters, armed conflict, forced displacement, and nutritional emergencies. We described studies and stratified data by age group, but did not do pooled analyses due to heterogeneity in case definitions. The published evidence, mainly from refugee camps and surveillance or patient record review studies, suggests very high excess morbidity and mortality (20-35% proportional mortality) and case-fatality (up to 30-35%) due to ARI. However, ARI disease burden comparisons with non-crisis settings are difficult because of non-comparability of data. Better epidemiological studies with clearer case definitions are needed to provide the evidence base for priority setting and programme impact assessments. Humanitarian agencies should include ARI prevention and control among infants, children and adults as priority activities in crises. Improved data collection, case management and vaccine strategies will help to reduce disease burden