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Research summaries on systems analysis, guidance and control, environmental factors, engineering development, propulsion, space sciences, and telecommunications
A basic geographic information system (GIS) for the North Cache Soil Conservation District (SCD) was sought for selected resource problems. Since the resource management issues in the North Cache SCD are very complex, it is not feasible in the initial phase to generate all the physical, socioeconomic, and political baseline data needed for resolving all management issues. A selection of critical varables becomes essential. Thus, there are foud specific objectives: (1) assess resource management needs and determine which resource factors ae most fundamental for building a beginning data base; (2) evaluate the variety of data gathering and analysis techniques for the resource factors selected; (3) incorporate the resulting data into a useful and efficient digital data base; and (4) demonstrate the application of the data base to selected real world resoource management issues.
Unmanned space mission to determine Martian environmental factors influencing design of systems for manned space mission to Mars - mission sensitivity analysis
A kill curve for Phanerozoic species is developed from an analysis of the stratigraphic ranges of 17,621 genera, as compiled by Sepkoski. The kill curve shows that a typical species' risk of extinction varies greatly, with most time intervals being characterized by very low risk. The mean extinction rate of 0.25/m.y. is thus a mixture of long periods of negligible extinction and occasional pulses of much higher rate. Because the kill curve is merely a description of the fossil record, it does not speak directly to the causes of extinction. The kill curve may be useful, however, to li inverted question markmit choices of extinction mechanisms.
Long non-coding RNAs (lncRNAs) are a crucial member of the non-coding RNA family, and increasing evidence demonstrates that lncRNAs participate in the initiation and progression of cancers. Our study aimed to explore the role of the lncRNA LINC00165 in gastric cancer (GC) development. In the present study, our results showed that LINC00165 was upregulated in GC tissues and cell lines and high expression of LINC00165 was correlated with tumor-node-metastasis stage, invasion depth, and overall survival of GC patients. Functional assays showed that LINC00165 knockdown inhibited the proliferation, migration and invasion of GC cells and LINC00165 overexpression stimulated their proliferation, migration and invasion. Online transcription factor binding site prediction analysis showed that there were STAT3 binding sites in the LINC00165 promoter region. Furthermore, luciferase reporter and chromatin immunoprecipitation assays provided evidence that STAT3 could bind directly to the region between −547 bp to −537 bp (ATGTTGGGAAA) of LINC00165 promoter and activate its transcription. Then GC cells were partitioned into nuclear and cytoplasmic fractions and we found that LINC00165 was localized preferentially to the nucleus. Mechanistically, we revealed that LINC00165 functioned as a scaffold for interaction with Polycomb Repressive Complex 2 to promote the epithelial-mesenchymal transition in GC cells. Taken together, our study revealed that LINC00165 was involved in the progression and poor prognosis of GC as an oncogenic role. Therefore, LINC00165 might become a new potential target for GC chemotherapy and further predict prognosis of patients.
Available capacity, power, and cell conductance figure centrally into performance characterization of electrochemical cells (such as Li-ion cells) over their service life. For example, capacity loss in Li-ion cells is due to a combination of mechanisms, including loss of free available lithium, loss of active host sites, shifts in the potential-capacity curve, etc. Further distinctions can be made regarding irreversible and reversible capacity loss mechanisms. There are tandem needs for accurate interpretation of capacity at characterization conditions (cycling rate, temperature, etc.) and for robust self-consistent modeling techniques that can be used for diagnostic analysis of cell data as well as forecasting of future performance. Analogous issues exist for aging effects on cell conductance and available power. To address these needs, a modeling capability was developed that provides a systematic analysis of the contributing factors to battery performance loss over aging and to act as a regression/prediction platform for cell performance. The modeling basis is a summation of self-consistent chemical kinetics rate expressions, which as individual expressions each covers a distinct mechanism (e.g., loss of active host sites, lithium loss), but collectively account for the net loss of premier metrics (e.g., capacity) over time for a particular characterization condition. Specifically, sigmoid-based rate expressions are utilized to describe each contribution to performance loss. Through additional mathematical development another tier of expressions is derived and used to perform differential analyses and segregate irreversible versus reversible contributions, as well as to determine concentration profiles over cell aging for affected Li+ ion inventory and fraction of active sites that remain at each time step. Reversible fade components are surmised by comparing fade rates at fast versus slow cycling conditions. The model is easily utilized for predictive calculations so that future capacity performance can be estimated. The invention covers mathematical and theoretical frameworks, and demonstrates application to various Li-ion cells covering test periods that vary in duration, and shows model predictions well past the end of test periods. Version 2.0 Enhancements: the code now covers path-dependent aging scenarios, wherein the framework allows for arbitrarily-chosen aging conditions over a timeline to accommodate prediction of battery aging over a multiplicity of changing conditions. The code framework also allows for cell conductance and power loss evaluations over cell aging, analysis of series strings that contain a thermal anomaly (hot spot), and evaluation of battery thermal management parameters that impact battery lifetimes. Lastly, a comprehensive GUI now resides in the Ver. 2.0 code.
To survive diverse host environments, the human pathogen Streptococcus pneumoniae must prevent its self-produced, extremely high levels of peroxide from reacting with intracellular iron. However, the regulatory mechanism(s) by which the pneumococcus accomplishes this balance remains largely enigmatic, as this pathogen and other related streptococci lack all known redox-sensing transcription factors. Here we describe a two-component-derived response regulator, RitR, as the archetype for a novel family of redox sensors in a subset of streptococcal species. We show that RitR works to both repress iron transport and enable nasopharyngeal colonization through a mechanism that exploits a single cysteine (Cys128) redox switch located within its linker domain. Biochemical experiments and phylogenetics reveal that RitR has diverged from the canonical two-component virulence regulator CovR to instead dimerize and bind DNA only upon Cys128 oxidation in air-rich environments. Atomic structures show that Cys128 oxidation initiates a “helical unravelling” of the RitR linker region, suggesting a mechanism by which the DNA-binding domain is then released to interact with its cognate regulatory DNA. Expanded computational studies indicate this mechanism could be shared by many microbial species outside the streptococcus genus.
As social distancing policies and recommendations went into effect in response to COVID-19, people made rapid changes to the places they visit. These changes are clearly seen in mobility data, which records foot traffic using location trackers in cell phones. While mobility data is often used to extract the number of customers that visit a particular business or business type, it is the frequency and duration of concurrent occupancy at those sites that governs transmission. Understanding the way people interact at different locations can help target policies and inform contact tracing and prevention strategies. This paper outlines methods to extract interactions from mobility data and build networks that can be used in epidemiological models. Several measures of interaction are extracted: interactions between people, the cumulative interactions for a single person, and cumulative interactions that occur at particular businesses. Network metrics are computed to identify structural trends which show clear changes based on the timing of stay-at-home orders. Measures of interaction and structural trends in the resulting networks can be used to better understand potential spreading events, the percent of interactions that can be classified as close contacts, and the impact of policy choices to control transmission.
Coronagraphs (together with starshades) are an important tool to directly image and characterize exoplanets, and enable the search for biomarkers in reflected light on potentially habitable worlds. Their performance and efficiency has steadily been improving over the past several decades, but has not yet reached performance limits. In particular, the expected exoplanet yield for missions such as the Astro2020-recommended “IR/O/UV Flagship” can still be improved by factors of at least 2-3, simply by continued improvements in coronagraph performance, before they plateau due to physics limits. One possible architecture that can enable at least a part of this improvement is the Phase-Induced Amplitude Apodization Complex Mask Coronagraph (PIAACMC). Itoffersthe advantages of high throughput, small inner working angle (IWA),and almost noloss inPSF sharpness, and natively supports obstructed and segmented apertures, which is essential to the Astro2020 “IR/O/UV Flagship”mission. Historically, key disadvantages of PIAA have been poor tolerance to stellar angular sizes and maturity, but latest designs and demonstrations have made significant strides in this respect.In this paper, we present the current status and overview of our program to mature the PIAACMC technology. We first review PIAACMC designs for LUVOIR-A and B, which resultedin improved expected yield of Exo-Earths relative tothe baselines for both mission concepts. In particular, for LUVOIR-B, the yield improves from 28 to 42due to improvedtolerance to stellar angular size in our design. The improvement in yield is marginal for LUVOIR-A, but our design enables detecting planets around smaller diameter stars (nearby K-dwarfs and/or farther FG stars). We also describe our modeling and vacuum demonstrationsfor the LUVOIR-A aperture(which is more challengingthan LUVOIR-B due to the central obstruction).The demonstration included a LUVOUR-A pupil mask, an on-axis PIAA set of 2 mirrors with central holes, a Boston Micromachines DM, a patterned CMC mask, Lyot stop, and supporting masks and optics. Demonstrations were conducted at JPL’s High Contrast Imaging Testbed (HCIT) using several characterization andwavefront control techniques (primarily standard EFC, several experimental techniques were attempted, as well as speckle nulling). So far, our results include 1.9e-8 raw contrast in 10% broadband light between 3.5 and 8 l/D; 4.1e-8 and 1.6e-9 coherent contrasts in monochromatic light between 2-4 and 4-8 l/D, respectively. We also present measurements and analysis of sensitivity to tip/tilt jitter and stellar angular size. Finally, we compare our test results to models, present an analysis of our limiting factors, and explorefuture prospectsfor improvement based on validated models.
Maintaining optimal alertness and neurobehavioral functioning during space operations is critical to enable the National Aeronautics and Space Administration's (NASA's) vision "to extend humanity's reach to the Moon, Mars and beyond" to become a reality. Field data have demonstrated that sleep times and performance of crewmembers can be compromised by extended duty days, irregular work schedules, high workload, and varying environmental factors. This paper documents evidence of significant sleep loss and disruption of circadian rhythms in astronauts and associated performance decrements during several space missions, which demonstrates the need to develop effective countermeasures. Both sleep and circadian disruptions have been identified in the Behavioral Health and Performance (BH&P) area and the Advanced Human Support Technology (AHST) area of NASA's Bioastronautics Critical Path Roadmap. Such disruptions could have serious consequences on the effectiveness, health, and safety of astronaut crews, thus reducing the safety margin and increasing the chances of an accident or incident. These decrements oftentimes can be difficult to detect and counter effectively in restrictive operational environments. NASA is focusing research on the development of optimal sleep/wake schedules and countermeasure timing and application to help mitigate the cumulative effects of sleep and circadian disruption and enhance operational performance. Investing research in humans is one of NASA's building blocks that will allow for both short- and long-duration space missions and help NASA in developing approaches to manage and overcome the human limitations of space travel. In addition to reviewing the current state of knowledge concerning sleep and circadian disruptions during space operations, this paper provides an overview of NASA's broad research goals. Also, NASA-funded research, designed to evaluate the relationships between sleep quality, circadian rhythm stability, and performance proficiency in both ground-based simulations and space mission studies, as described in the 2003 NASA Task Book, will be reviewed.
Prior studies suggest that postprandial hypotension in elderly persons may be due to defective sympathetic nervous system activation. We examined autonomic control of heart rate (HR) after a meal using spectral analysis of HR data in 13 old (89 +/- 6 years) and 7 young (24 +/- 4 years) subjects. Total spectral power, an index of overall HR variability, was calculated for the frequency band between 0.01 and 0.40 Hz. Relatively low-frequency power, associated with sympathetic nervous system and baroreflex activation, was calculated for the 0.01 to 0.15 Hz band. High-frequency power, representing parasympathetic influences on HR, was calculated for the 0.15 to 0.40 Hz band. Mean arterial blood pressure declined 27 +/- 8 mm Hg by 60 minutes after the meal in elderly subjects, compared with 9 +/- 8 mm Hg in young subjects (p less than or equal to 0.0001, young vs old). The mean change in low-frequency HR power from 30 to 50 minutes after the meal was +19.4 +/- 25.3 U in young subjects versus -0.1 +/- 1.5 U in old subjects (p less than or equal to 0.02). Mean change in total power was also greater in young (19.0 +/- 26.6 U) subjects compared with old subjects (0.0 +/- 1.6 U, p greater than or equal to 0.02). Mean ratio of low:high-frequency power increased 3.1 +/- 3.3 U in young subjects vs 0.5 +/- 2.7 U in old subjects (p less than or equal to 0.01). The increase in low-frequency HR power and in the low:high frequency band ratio in young subjects is consistent with sympathetic activation in the postprandial period.(ABSTRACT TRUNCATED AT 250 WORDS).
This review provides an update on the progress in understanding formation and degradation mechanisms in halide perovskites for photovoltaic applications, as supported by in situ and operando X–ray scattering techniques. The value of these real–time analyses is particularly high for gaining insights into the structural evolution during crystal formation and decomposition upon exposure to external stress factors. This type of analysis reveals the pathways between starting and end points of a process rather than being limited to comparing states before and after the process. Special attention is put on the successful efforts toward upscaling including deposition techniques that are compatible to roll–to–roll processing. These processes are realized using fast annealing procedures. The development of these processes strongly benefited from in situ studies exploring the direct transition from precursor to perovskite without going through observable crystalline intermediate phases. A particular focus of this review is the benefit of using in situ and operando X–ray scattering techniques to better understand and ultimately improve device stability. In conclusion, the difference between structural stability of thin films and structural stability under device operation is highlighted, convincingly demonstrating the indispensability of operando studies.
Abstract Fault detection and classification in photovoltaic (PV) systems through real‐time monitoring is a fundamental task that ensures quality of operation and significantly improves the performance and reliability of operating systems. Different statistical and comparative approaches have already been proposed in the literature for fault detection; however, accurate classification of fault and loss incidents based on PV performance time series remains a key challenge. Failure diagnosis and trend‐based performance loss routines were developed in this work for detecting PV underperformance and accurately identifying the different fault types and loss mechanisms. The proposed routines focus mainly on the differentiation of failures (e.g., inverter faults) from irreversible (e.g., degradation) and reversible (e.g., snow and soiling) performance loss factors based on statistical analysis. The proposed routines were benchmarked using historical inverter data obtained from a 1.8 MWp PV power plant. The results demonstrated the effectiveness of the routines for detecting failures and loss mechanisms and the capability of the pipeline for distinguishing underperformance issues using anomaly detection and change‐point (CP) models. Finally, a CP model was used to extract significant changes in time series data, to detect soiling and cleaning events and to estimate both the performance loss and degradation rates of fielded PV systems.
Dhurrin, a cyanogenic glucoside, plays an important role in Sorghum bicolor physiology and defense. The concentration of dhurrin in sorghum is influenced by both nitrogen status and stage of plant organ development. While nitrogen resupply activates the expression of genes for dhurrin biosynthesis, the molecular mechanisms underlying this regulation remain unclear. In this study, we investigated the transcriptional response of sorghum to nitrogen resupply following growth under nitrogen-limiting conditions. Using a time-course design, we measured hydrogen cyanide potential (HCNp), growth, and nitrate content at 0-, 2-, 6-, 12-, 24-, 36-, 48-, and 60-h after resupply and collected tissue for RNAseq analysis in parallel for analysis of gene expression and construction of gene regulatory networks (GRNs). HCNp (mg g −1 DW) increased significantly in leaf and stem tissues following nitrogen resupply, with increases in the leaf partially driven by continued declines in controls under ongoing nitrogen stress. Expression of the dhurrin pathway genes was upregulated in leaves from 24 h after nitrogen resupply, with diel expression patterns observable over the remaining time points. No upregulation was observed in roots or stems, suggesting that developmental context overrides environmental cues. GRN analysis identified candidate transcription factors regulating dhurrin biosynthesis genes, including members of the MYB, bZIP, and GARP-type transcription factor families. Some of these candidate transcription factors may be involved in relieving senescence-associated suppression of dhurrin biosynthesis and link nitrogen signaling to pathway activation. These findings provide new insight into the nitrogen-responsive regulation of dhurrin in sorghum, highlighting candidate regulators for future functional characterization.
First-principles density functional theory calculations are carried out to evaluate energy barriers and mechanisms for the dehydrogenation reactions of CH 4 on clean and oxygen-covered surfaces of Cu (111) and Ni (111) with low and moderate oxygen coverage. In the presence of oxygen, two possible pathways have been evaluated. The more likely pathway, which is further analyzed, is that CH 4 loses an H to the surface O. Results from this pathway agree with previous findings showing that oxygen promotes CH 4 dissociation on Cu (111) and hinders that on Ni (111). In addition, our results show lower energy barriers on Cu with higher oxygen coverages up to 0.38 monolayer. However, such an increase in oxygen coverage did not show any favorable effect for CH 4 dissociation on Ni (111). Fianlly, the findings are analyzed through electronic factors revealed by charge analysis and density of states.
To understand phosphorus (P) mobility in agricultural soils and its potential environmental risk, it is essential to directly measure solid phase P speciation. Often, bulk P K-edge X-ray absorption near edge structure (XANES) spectroscopy followed by linear combination fitting (LCF) is utilized to determine the solid P phases in soil. However, this method may limit results to only a few major phases. Additionally, XANES spectra for different P species may have very similar features, leading to an over- or underestimate of their contribution to LCF. Here, an improved P speciation by pairing multimodal microbeam-X-ray fluorescence (µ-XRF) mapping coupled with µ-XANES (microbeam-X-ray absorption near edge structure) analysis to directly speciate major and minor P phases on the micron scale is provided. We combined maps of both tender (P, sulfur, aluminum, and silicon) and hard energy (calcium, iron [Fe], and manganese) elements to evaluate the elemental co-locations with P. To better account for uncertainty assigning XANES peaks to individual compounds, a more quantitative fingerprinting by “spectral feature analysis” was completed. With this analysis, an R-factor is reported for the fit. These results were compared to traditional LCF. Pre-edge fitting results revealed the presence of a two-component pre-edge feature for phosphate adsorbed to ferrihydrite. Additionally, phytate co-precipitated with ferrihydrite (Phytate-Fe-Cop) had a pre-edge feature, indicating direct association with Fe. Lastly, a unique P species associated with manganese oxide was identified in the soil via multimodal mapping and µ-XANES. These results allow for better prediction of P dissolution and mobility.
Abstract The$$ {D}_s^{+}\to {K}^{+}{K}^{-}{\mu}^{+}{\nu}_{\mu } $$ D s + → K + K − μ + ν μ decay is studied based on 7.33 fb −1 ofe + e − collision data collected with the BESIII detector at center-of-mass energies in the range from 4.128 to 4.226 GeV. The absolute branching fraction is measured as$$ \mathcal{B}\left({D}_s^{+}\to \phi {\mu}^{+}{\nu}_{\mu}\right)=\left(2.25\pm 0.09\pm 0.07\right)\times {10}^{-2} $$ B D s + → ϕ μ + ν μ = 2.25 ± 0.09 ± 0.07 × 10 − 2 , the most precise measurement to date. Combining with the world average of$$ \mathcal{B}\left({D}_s^{+}\to \phi {e}^{+}{\nu}_e\right) $$ B D s + → ϕ e + ν e , the ratio of the branching fractions obtained is$$ \frac{\mathcal{B}\left({D}_s^{+}\to \phi {\mu}^{+}{\nu}_{\mu}\right)}{\mathcal{B}\left({D}_s^{+}\to \phi {e}^{+}{\nu}_e\right)}=0.94\pm 0.08 $$ B D s + → ϕ μ + ν μ B D s + → ϕ e + ν e = 0.94 ± 0.08 , in agreement with lepton universality. By performing a partial wave analysis, the hadronic form factor ratios atq 2 = 0 are extracted, finding$$ {r}_V=\frac{V(0)}{A_1(0)}=1.58\pm 0.17\pm 0.02 $$ r V = V 0 A 1 0 = 1.58 ± 0.17 ± 0.02 and$$ {r}_2=\frac{A_2(0)}{A_1(0)}=0.71\pm 0.14\pm 0.02 $$ r 2 = A 2 0 A 1 0 = 0.71 ± 0.14 ± 0.02 , where the first uncertainties are statistical and the second are systematic. No significantS-wave contribution fromf 0 (980)→ K + K − is found. The upper limit$$ \mathcal{B}\left({D}_s^{+}\to {f}_0(980){\mu}^{+}{\nu}_{\mu}\right)\cdot \mathcal{B}\left({f}_0(980)\to {K}^{+}{K}^{-}\right)<5.45\times {10}^{-4} $$ B D s + → f 0 980 μ + ν μ ⋅ B f 0 980 → K + K − < 5.45 × 10 − 4 is set at 90% credibility level.
The compression tests were carried out on a coarse-grained Mg-8Al-1.5Ca-0.2Sr magnesium alloy samples at temperatures from 300 to 450 °C and strain rates from 0.001 to 10 s{sup −1}. The flow stress curves were analyzed using the double-differentiation method, and double minima were detected on the flow curves. The first set of minima is shown to identify the critical strain for twinning, while the second set indicates the critical strain for the initiation of dynamic recrystallization (DRX). Twin variant selection was numerically identified by comprehensive analysis of the Schmid factors for different deformation modes and the accommodation strains imposed on neighboring grains. It was found that twinning is initiated before DRX. Dynamic recrystallization volume increases with strain rate at a given deformation temperature. At high strain rate, various twin variants are activated to accommodate deformation, leading to the formation of twin intersections and high DRX volume. Fully dynamic recrystallized structure can be obtained at both high and low strain rates due to the high mobility of the grain and twin boundaries at the temperature of 400 °C.