Plant endogenous small RNAs (sRNAs) are important regulators of gene expression. There are two broad categories of plant sRNAs: microRNAs (miRNAs) and endogenous short interfering RNAs (siRNAs). ...MicroRNA loci are relatively well-annotated but compose only a small minority of the total sRNA pool; siRNA locus annotations have lagged far behind. Here, we used a large data set of published and newly generated sRNA sequencing data (1333 sRNA-seq libraries containing more than 20 billion reads) and a uniform bioinformatic pipeline to produce comprehensive sRNA locus annotations of 47 diverse plants, yielding more than 2.7 million sRNA loci. The two most numerous classes of siRNA loci produced mainly 24- and 21-nucleotide (nt) siRNAs, respectively. Most often, 24-nt-dominated siRNA loci occurred in intergenic regions, especially at the 5'-flanking regions of protein-coding genes. In contrast, 21-nt-dominated siRNA loci were most often derived from double-stranded RNA precursors copied from spliced mRNAs. Genic 21-nt-dominated loci were especially common from disease resistance genes, including from a large number of monocots. Individual siRNA sequences of all types showed very little conservation across species, whereas mature miRNAs were more likely to be conserved. We developed a web server where our data and several search and analysis tools are freely accessible.
•Explain similarities and differences in energy use of adjacent refugee settlements.•Household energy expenditures were on average 12.8% of total monthly welfare income.•Greater expenditure on ...fuelwood reduced purchasing power for other needs.•Businesses expressed demand for increased electrical capacity to expand operations.•Businesses could be anchor client for mini-gridserving households and other services.
Energy security and development in refugee settlements is hampered by limited data on the existing energy ecosystem, which is necessary to understand current energy needs and plan short- and long-term energy transitions to self-sustainment. This study addresses the knowledge gap by acquiring primary data from two neighboring refugee settlements, Ayilo I and Ayilo II, in Northern Uganda. A mixed-methods approach obtained data on energy supply and use for households, small- to medium-sized enterprises, and public services. Reduced fuelwood availability in one settlement decreased household wood use by 23.4% relative to the adjacent settlement, and led to households spending an average of 121.8% and 33.5% more per month to purchase wood and charcoal, respectively. Findings indicate current short-term energy decisions are unsustainable and that a move towards using alternative thermal energy sources is needed to reduce the deforestation and lessen tensions with host populations. The study also identifies electricity use in households that primarily consists of cellphones, lighting, and radios, that are best served by solar home systems or charging stations. Electricity demand from small- to medium-sized enterprises is rising to follow aspirations of business owners to expand services offered, whereas energy demand from public services is high with some issues in the reliability of existing power infrastructure. Findings also suggest that hybrid mini-grids can meet the growing demand of small- to medium-sized enterprises, provide reliable power to critical public services, and accommodate for the growth in electricity demand for refugee settings transitioning from temporary, semi-permanent, to permanent settlements.
Single-cell RNA sequencing (scRNA-seq) is a recent technology that enables fine-grained discovery of cellular subtypes and specific cell states. Analysis of scRNA-seq data routinely involves machine ...learning methods, such as feature learning, clustering, and classification, to assist in uncovering novel information from scRNA-seq data. However, current methods are not well suited to deal with the substantial amount of noise that is created by the experiments or the variation that occurs due to differences in the cells of the same type. To address this, we developed a new hybrid approach, deep unsupervised single-cell clustering (DUSC), which integrates feature generation based on a deep learning architecture by using a new technique to estimate the number of latent features, with a model-based clustering algorithm, to find a compact and informative representation of the single-cell transcriptomic data generating robust clusters. We also include a technique to estimate an efficient number of latent features in the deep learning model. Our method outperforms both classical and state-of-the-art feature learning and clustering methods, approaching the accuracy of supervised learning. We applied DUSC to a single-cell transcriptomics data set obtained from a triple-negative breast cancer tumor to identify potential cancer subclones accentuated by copy-number variation and investigate the role of clonal heterogeneity. Our method is freely available to the community and will hopefully facilitate our understanding of the cellular atlas of living organisms as well as provide the means to improve patient diagnostics and treatment.
This work establishes and validates a Grid Graph Signal Processing (G-GSP) framework for estimating the state vector of a radial distribution feeder. One of the key insights from GSP is the ...generalization of Shannon's sampling theorem for signals defined over the irregular support of a graph, such as the power grid. Using a GSP interpretation of Ohm's law, we show that the system state can be well approximated with relatively few components that correspond to low-pass Graph Fourier Transform (GFT) frequencies. The target application of this theory is the formulation of a three-phase unbalanced Distribution System State Estimation (DSSE) formulation that recovers the GFT approximation of the system state vector from sparse Advanced Metering Infrastructure (AMI) measurements. To ensure convergence of G-GSP for DSSE, the proposed solution relies on a convex relaxation technique. Furthermore, we propose an optimal sensor placement algorithm for AMI measurements. Numerical results demonstrate the efficacy of the proposed method.
•Optimal solar array size (lowest LCOE) reduces by 20–50% if net metering is removed.•Batteries are cost-effective without net metering and a price decrease of at least 55%.•Simulations show “duck ...curve” behavior for 10,000 homes at various solar PV levels.•Energy use (kWh) reduces by an equivalent percent increase in solar PV penetration.•Utility revenue recovery models are evaluated through increased rates and fees.
Residential energy markets in the United States are undergoing rapid change with increasing amounts of solar photovoltaic (PV) systems installed each year. This study examines the combined effect of electric rate structures and local environmental forcings on optimal solar home system size, ratepayer financials, utility financials, and electric grid ramp rate requirements for three urban regions in the United States. Techno-economic analyses are completed for Chicago, Phoenix, and Seattle and the results contrasted to provide both generalizable findings and site-specific findings. Various net metering scenarios and time-of-use rate schedules are investigated to evaluate the optimal solar PV capacity and battery storage in a typical residential home for each locality. The net residential load profile is created for a single home using BEopt and then scaled to assess technical and economic impacts to the utility for a market segment of 10,000 homes modeled in HOMER. Emphasis is given to intraday load profiles, ramp rate requirements, peak capacity requirements, load factor, revenue loss, and revenue recuperation as a function of the number of ratepayers with solar PV. Increases in solar PV penetration reduced the annual system load factor by an equivalent percentage yet had little to no impact on peak power requirements. Ramp rate requirements were largest for Chicago in October, Phoenix in July, and Seattle in January. Net metering on a monthly or annual basis had a negligible impact on optimal solar PV capacity, yet optimal solar PV capacity reduced by 20–50% if net metering was removed altogether. Technical and economic data are generated from simulations with solar penetration up to 100% of homes. For the scenario with 20% homes using solar PV, the utility would need a 16%, 24%, and 8% increase in time-of-use electricity rates ($/kWh) across all ratepayers to recover lost revenue in Chicago, Phoenix, and Seattle, respectively. The $15 monthly connection fee would need to increase by 94%, 228%, or 50% across the same cities if time-of-use electricity rates were to remain unchanged. Batteries were found to be cost-effective in simulations without net metering and at cost reductions of at least 55%. Batteries were not cost-effective—even if they were free—when net metering was in effect. As expected, Phoenix had the most favorable economic scenario for residential solar PV, primarily due to the high solar insolation.
•Introduced a thermodynamic model for a 100 kWe/165 kWt solarized microturbine.•Electric output of thermodynamic model is within 1.6% of the as-built system.•Fuel use reduced by 26.0% verse ...traditional microturbine at maximum power output.•Annual operating time is 59.8% fuel only, 12.4% hybrid, and 27.8% solar only modes.•Electrical efficiency most sensitive to ambient air temperature.
Combined heat and power (CHP) plants utilize exhaust heat from thermal-based power generators to increase system efficiency beyond electrical efficiency alone. Many existing CHP systems use fossil-fueled generators to create electrical power for retail sale or on-site industrial or commercial uses. This study develops, validates, and exercises a quasi-steady state thermodynamic model of a 100 kWe/165 kWt rated microturbine that has been coupled with a concentrating solar power (CSP) tower to offset natural gas consumption. Exhaust heat is rejected at approximately 270 °C for CHP applications. Governing equations developed for eight components incorporate manufacturer data and empirical data to describe system-level operation with respect to intraday variation in the solar resource. Model validation at ISO conditions shows electric output of the simulated system is within 1.6% of the as-built system. Simulation results of the complete solarized system gave 31.5% electrical efficiency, 83.2% system efficiency, 99.5 kWe electrical power, and 163.5 kWt thermal power at nominal operating conditions for a DNI of 515 W/m2. The thermodynamic model is exercised under rated electrical load (base loading) and variable electrical load (load following) conditions with performance measured on 13 operating characteristics. Sensitivity analyses evaluate changes in performance with respect to operating variables (e.g., turbine inlet temperature) and environmental variables (e.g., elevation). Results show that a CSP plant with solarized microturbine can meet target performance specifications of a non-solarized microturbine (pure natural gas). Annual time series simulations completed for Phoenix, Arizona, USA indicate a solarized microturbine can reduce natural gas use by 26.0% and 28.4% when supplying rated power and variable power output, respectively. Annual operating time of the solarized microturbine at rated capacity included 59.8% fuel only, 12.4% hybrid, and 27.8% solar only modes for the selected study location.
•Evaluated precooling, thermal storage, and combined cooling strategies for homes.•Precooling strategy dynamically sets indoor temperature from outdoor temperature.•On-peak demand and energy use ...reduced by up to 75.6% and 78.5%.•Economics savings of 23.5%, 1.7%, and 14.9% for Phoenix, Los Angeles, and Kona.•Precooling had the highest rate of return with payback between 0.2 and 6.2 years.
Increased residential cooling loads often correlate with peak electricity demand in warm and temperate climates. Solutions such as precooling and thermal energy storage (TES) being separately shown to shift energy use to off-peak times and reduce electricity expenses for commercial and residential applications. This study advances prior research to jointly implement and optimize precooling and TES strategies, and further develops a precooling strategy that dynamically adjusts precooling set points with respect to outdoor temperatures. Six strategies for residential cooling are evaluated and compared on metrics including system sizing, intraday dispatch, electricity use, energy expenditures, and investment rate of return. Case study data include a simulated one-year period for the cities of Phoenix, Los Angeles, and Kona in the United States. After accounting for capital cost, operating cost savings, and discount factors, a smart thermostat with the proposed dynamic precooling technique is found to have the best return on investment with payback rates between 0.2 and 6.2 years across all locations and rate structures. However, if technology costs lower or electricity rates change, it could be beneficial to use a combined approach with TES and precooling that gives the greatest reduction in daily on-peak demand and energy use at 75.6% and 78.5%, respectively. These individual and combined strategies provide value to ratepayers and electric utilities by reducing energy expenditures and shifting cooling loads to reduce system-wide peak demand.
Validity of activity-based devices to estimate sleep Weiss, Allison R; Johnson, Nathan L; Berger, Nathan A ...
Journal of clinical sleep medicine,
2010-Aug-15, 2010-08-15, 20100815, Letnik:
6, Številka:
4
Journal Article
Odprti dostop
The aim of this study was to examine the feasibility of sleep estimation using a device designed and marketed to measure core physical activity.
Thirty adolescent participants in an epidemiological ...research study wore 3 actigraphy devices on the wrist over a single night concurrent with polysomnography (PSG). Devices used include Actical actigraph, designed and marketed for placement around the trunk to measure physical activity, in addition to 2 standard actigraphy devices used to assess sleep-wake states: Sleepwatch actigraph and Actiwatch actigraph. Sleep-wake behaviors, including total sleep time (TST) and sleep efficiency (SE), were estimated from each wrist-device and PSG. Agreements between each device were calculated using Pearson product movement correlation and Bland-Altman plots.
Statistical analyses of TST revealed strong correlations between each wrist device and PSG (r = 0.822, 0.836, and 0.722 for Sleepwatch, Actiwatch, and Actical, respectively). TST measured using the Actical correlated strongly with Sleepwatch (r = 0.796), and even stronger still with Actiwatch (r = 0.955). In analyses of SE, Actical correlated strongly with Actiwatch (r = 0.820; p < 0.0001), but not with Sleepwatch (0.405; p = 0.0266). SE determined by PSG correlated somewhat strongly with SE estimated from the Sleepwatch and Actiwatch (r = 0.619 and 0.651, respectively), but only weakly with SE estimated from the Actical (r = 0.348; p = 0.0598).
The results from this study suggest that a device designed for assessment of physical activity and truncal placement can be used to measure sleep duration as reliably as devices designed for wrist use and sleep wake inference.
Previous reports have noted cerebrovascular regulation differs across the cardiac cycle, with greater regulation occurring within systole. However, this methodological notion has not been ...meticulously scrutinized during temporally deduced neurovascular coupling (NVC) metrics with additional respect to biological sex. Analyses of 111 healthy individuals (40 females/71 males) were performed where participants engaged in the "Where's Waldo?" paradigm. All NVC parameters were quantified in the posterior and middle cerebral arteries at 310 unique timepoints. Several individuals completed repeat testing which enabled for between-day (3 timepoints) and within-day (7 timepoints) reliability comparisons in 17 and 11 individuals, respectively. One-way analysis of variance compared NVC metrics between diastole, mean, and systole values, as well as differences between biological sexes. Greater absolute cerebral blood velocity (CBv; baseline and peak) and total activation (area under the curve) were noted within systole for both posterior cerebral artery (PCA;
< 0.001) and middle cerebral artery (MCA;
< 0.001) values; however, the relative percent increase in CBv was greater within diastole (
< 0.001). Females had an elevated diastolic and mean CBv and a greater diastolic cerebrovascular conductance (
< 0.050). No sex differences were present for systolic CBv measures and within parameters quantifying the NVC response (area under the curve/relative CBv increase) across the cardiac cycle (
> 0.072). Future investigations seeking to differentiate cerebral regulatory mechanisms between clinical populations may benefit by performing their analyses across the cardiac cycle, as certain pathogenesis may affect one aspect of the cardiac cycle independently. Minimal differences were noted between females and males for metrics characterizing the NVC response across the cardiac cycle.
Neurovascular coupling (NVC) studies commonly assess the mean cerebral hemodynamic response with little consideration for diastole, systole, and biological sex. Greater total activation expressed as the area under the curve was seen within systole compared with mean and diastole. Resting cerebral blood velocity sex differences were more prevalent during diastole when the cerebrovasculature was pressure-passive. Future studies should assess the NVC response across the cardiac cycle as it may help delineate the underlying pathophysiology of various clinical populations.
The human ability to flexibly alternate between tasks represents a central component of cognitive control. Neuroimaging studies have linked task switching with a diverse set of prefrontal cortex ...(PFC) regions, but the contributions of these regions to various forms of cognitive flexibility remain largely unknown. Here, subjects underwent functional brain imaging while they completed a paradigm that selectively induced stimulus, response, or cognitive set switches in the context of a single task decision performed on a common set of stimuli. Behavioral results indicated comparable reaction time costs associated with each switch type. Domain-general task-switching activation was observed in the inferior frontal junction and posterior parietal cortex, suggesting core roles for these regions in switching such as updating and representing task sets. In contrast, multiple domain-preferential PFC activations were observed across lateral and medial PFC, with progressively more rostral regions recruited as switches became increasingly abstract. Specifically, highly abstract cognitive set switches recruited anterior-PFC regions, moderately abstract response switches recruited mid-PFC regions, and highly constrained stimulus switches recruited posterior-PFC regions. These results demonstrate a functional organization across lateral and medial PFC according to the level of abstraction associated with acts of cognitive flexibility.
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