Wnt3a-coated beads can induce asymmetric divisions of mouse embryonic stem cells (mESCs), resulting in one self-renewed mESC and one differentiating epiblast stem cell. This provides an opportunity for studying histone inheritance pattern at a single-cell resolution in cell culture. Here, we report that mESCs with Wnt3a-bead induction display nonoverlapping preexisting (old) versus newly synthesized (new) histone H3 patterns, but mESCs without Wnt3a beads have largely overlapping patterns, Furthermore, H4K20me2/3, an old histone-enriched modification, displays a higher instance of asymmetric distribution on chromatin fibers from Wnt3a-induced mESCs than those from non-induced mESCs. These locally distinct distributions between old and new histones have both cellular specificity in Wnt3a-induced mESCs and molecular specificity for histones H3 and H4. Given that post-translational modifications at H3 and H4 carry the major histone modifications, our findings provide a mammalian cell culture system to study histone inheritance for maintaining stem cell fate and for resetting it during differentiation.

Vegetation indices are widely used to derive land surface phenology (LSP). However, due to inconsistent illumination geometries, reflectance varies with solar zenith angles (SZA), which in turn affects the vegetation indices, and thus the derived LSP. To examine the SZA effect on LSP, the MODIS bidirectional reflectance distribution function (BRDF) product and a BRDF model were employed to derive LSPs under several constant SZAs (i.e., 0 & DEG;, 15 & DEG;, 30 & DEG;, 45 & DEG;, and 60 & DEG;) in the Harvard Forest, Massachusetts, USA. The LSPs derived under varying SZAs from the MODIS nadir BRDF-adjusted reflectance (NBAR) and MODIS vegetation index products were used as baselines. The results show that with increasing SZA, NDVI increases but EVI decreases. The magnitude of SZA-induced NDVI/EVI changes suggests that EVI is more sensitive to varying SZAs than NDVI. NDVI and EVI are comparable in deriving the start of season (SOS), but EVI is more accurate when deriving the end of season (EOS). Specifically, NDVI/EVI-derived SOSs are relatively close to those derived from ground measurements, with an absolute mean difference of 8.01 days for NDVI-derived SOSs and 9.07 days for EVI-derived SOSs over ten years. However, a considerable lag exists for EOSs derived from vegetation indices, especially from the NDVI time series, with an absolute mean difference of 14.67 days relative to that derived from ground measurements. The SOSs derived from NDVI time series are generally earlier, while those from EVI time series are delayed. In contrast, the EOSs derived from NDVI time series are delayed; those derived from the simulated EVI time series under a fixed illumination geometry are also delayed, but those derived from the products with varying illumination geometries (i.e., MODIS NBAR product and MODIS vegetation index product) are advanced. LSPs derived from varying illumination geometries could lead to a difference spanning from a few days to a month in this case study, which highlights the importance of normalizing the illumination geometry when deriving LSP from NDVI/EVI time series.

In this study, a machine learning method and a piece of cassiterite trace element composition data were used to find fingerprint trace elements that distinguish different tin (Sn) mineralization types and build tools for exploring primary Sn deposit exploration. The trace element dataset of cassiterite from the granite-related Sn metallogenic system was built using the following two approaches: (1) by analyzing the cassiterite samples from nine Sn deposits in Myanmar using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and (2) collecting published data. The resulting dataset contains 661 records of 12 trace elements in cassiterite from 4 mineralization types: pegmatite, greisen, quartz-vein, and skarn. The spider diagrams of trace elements and the principal component analysis indicate that cassiterite samples from the same one mineralization type are clustered together and have unique geochemical characteristics. Using recursive feature elimination with cross -validation and simulation, tantalum (Ta), niobium (Nb), manganese (Mn), hafnium (Hf), iron (Fe), scandium (Sc) and Sc/Ta, Sc/Hf, and Sc/Mn were selected as the fingerprint elements and ratios, respectively. The cluster distribution in the biplots of the fingerprint elements and ratios indicates that these fingerprints are sensitive to the mineralization type. The distribution in the biplots also reveals that there is an evolutionary sequence of magmatic-hydrothermal fluids from pegmatite to skarn at the cassiterite crystallization environment. This data -driven study improves our understanding of the isomorphism between Sn and ions with similar charge and ionic radii in cassiterite from different hydrothermal environments. The complementary relationships between va-nadium (V), Nb, and Ta are also identified. The element V is preferred to form a charge balance pair with Sc in cassiterite from skarn, whereas Ta and Nb are preferred to constitute a charge balance pair in cassiterite from the quartz-vein, pegmatite, and greisen. Our findings demonstrate that trace element compositions of detrital cassiterite grains from stream sediments can be used as an exploration tool to discover concealed primary Sn deposits and to evaluate the economic value based on the grade-tonnage model in the preliminary stage of mineral exploration.

The Sloan Digital Sky Survey (SDSS) has been in operation since 2000 April. This paper presents the Tenth Public Data Release (DR10) from its current incarnation, SDSS-III. This data release includes the first spectroscopic data from the Apache Point Observatory Galaxy Evolution Experiment (APOGEE), along with spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS) taken through 2012 July. The APOGEE instrument is a near-infrared R similar to 22,500 300 fiber spectrograph covering 1.514-1.696 mu m. The APOGEE survey is studying the chemical abundances and radial velocities of roughly 100,000 red giant star candidates in the bulge, bar, disk, and halo of the Milky Way. DR10 includes 178,397 spectra of 57,454 stars, each typically observed three or more times, from APOGEE. Derived quantities from these spectra (radial velocities, effective temperatures, surface gravities, and metallicities) are also included. DR10 also roughly doubles the number of BOSS spectra over those included in the Ninth Data Release. DR10 includes a total of 1,507,954 BOSS spectra comprising 927,844 galaxy spectra, 182,009 quasar spectra, and 159,327 stellar spectra selected over 6373.2 deg(-2).

We used x-ray magnetic circular dichroism (XMCD) to probe the ferromagnetic properties of As p-symmetric (4p) states in the recently synthesized diluted magnetic semiconductor (Ba1-x K-x)(Zn1-yMny)(2)As-2 system under ambient-and high-pressure conditions. The As K-edge XMCD signal scales with the sample magnetization (dominated by Mn) and scales with the ferromagnetic ordering temperature Tc, and hence it is representative of the bulk magnetization. The XMCD intensity gradually decreases upon compression and vanishes at around 25 GPa, indicating quenching of ferromagnetism at this pressure. Transport measurements show a concomitant increase in conductivity with pressure, leading to a nearly metallic state at about the same pressure where magnetic order collapses. High-pressure x-ray diffraction shows an absence of structural transitions to 40 GPa. The results indicate that the mobility of doped holes, probed by both transport and x-ray absorption spectroscopy (4p band broadening), is intimately connected with the mechanism of magnetic ordering in this class of compounds and that its control using external pressure provides an alternative route for tuning the magnetic properties in diluted magnetic semiconductor materials.

We investigate doping-and pressure-induced changes in the electronic state of Mn 3d and As 4p orbitals in II-II-V-based diluted magnetic semiconductor (Ba1-x K (x))(Zn1-y Mn-y) As-2(2) to shed light into the mechanism of indirect exchange interactions leading to high ferromagnetic ordering temperature (Tc = 230K in optimally doped samples). A suite of x-ray spectroscopy experiments (emission, absorption, and dichroism) show that the emergence and further enhancement of ferromagnetic interactions with increased hole doping into the As 4p band is accompanied by a decrease in local 3d spin density at Mn sites. This is a result of increasing Mn 3d-As 4p hybridization with hole doping, which enhances indirect exchange interactions between Mn dopants and gives rise to induced magnetic polarization in As 4p states. On the contrary, application of pressure suppresses exchange interactions. While Mn K beta emission spectra show a weak response of 3d states to pressure, clear As 4p band broadening (hole delocalization) is observed under pressure, ultimately leading to loss of ferromagnetism concomitant with a semiconductor to metal transition. The pressure response of As 4p and Mn 3d states is intimately connected with the evolution of the As-As interlayer distance and the geometry of theMnAs(4) tetrahedral units, which we probed with x-ray diffraction. Our results indicate that hole doping increases the degree of covalency between the anion (As) p states and cation (Mn) d states in the MnAs4 tetrahedron, a crucial ingredient to promote indirect exchange interactions between Mn dopants and high T c ferromagnetism. The instability of ferromagnetism and semiconducting states against pressure is mainly dictated by delocalization of anion p states.

The pressure effect on the crystalline structure of the I-II-V semiconductor Li(Zn,Mn) As ferromagnet is studied using in situ high-pressure x-ray diffraction and diamond anvil cell techniques. A phase transition starting at similar to 11.6 GPa is found. The space group of the high-pressure new phase is proposed as P-mca. Fitting with the Birch-Murnaghan equation of state, the bulk modulus B-0 and its pressure derivative B-0(') of the ambient pressure structure with space group of F(4) over bar 3m are B-0 = 75.4 GPa and B-0' = 4.3, respectively.

The vast majority of stars with mass similar to that of the Sun are expected to destroy lithium (Li) gradually over the course of their lives, via low-temperature nuclear burning. This has now been supported by observations of hundreds of thousands of red giant stars(1-5). Here we perform a large-scale systematic investigation into the Li content of stars in the red clump phase of evolution, which directly follows the red giant branch phase. Surprisingly, we find that all red clump stars have high levels of Li for their evolutionary stage, with an increase of a factor of 40 over the end of the red giant branch stage, on average. This suggests that all low-mass stars undergo an Li production phase between the tip of the red giant branch and the red clump. We demonstrate that our finding is not predicted by stellar theory, revealing a stark tension between observations and models. We also show that the well-studied(1,2,4-6)very Li-rich giants, withA(Li) > +1.5 dex, represent only the extreme tail of the Li enhancement distribution, comprising 3% of red clump stars. Our findings suggest a new definition limit for Li-richness in red clump stars,A(Li) > -0.9 dex, which is much lower than the limit ofA(Li) > +1.5 dex used over many decades(1,5-9).

Process-based grass models (PBGMs) are widely used for predicting grass growth under potential climate change and different management practices. However, accurate predictions using PBGMs heavily rely on field observations for data assimilation. In data-limited areas, performing robust and reliable estimates of grass growth remains a challenge. In this paper, we incorporated satellite-based MODIS data products, including leaf area index, gross primary production and evapotranspiration, as an additional supplement to field observations. Popular data assimilation methods, including Bayesian calibration and the updating method ensemble Kalman filter, were applied to assimilate satellite derived information into the BASic GRAssland model (BASGRA). A range of different combinations of data assimilating methods and data availability were tested across four grassland sites in Norway, Finland and Canada to assess the corresponding accuracy and make recommendations regarding suitable approaches to incorporate MODIS data. The results demonstrated that optimizing the model parameters that are specific for grass species and cultivar should be targeted prior to updating model state variables. The MODIS derived data products were capable of constraining model's simulations on phenological development and biomass accumulation by parameter optimization with its performance exceeding model outputs driven by default parameters. By integrating even a small number of field measurements into the parameter calibration, the model's predictive accuracy was further improved - especially at sites with obvious biases in the input MODIS data. Overall, this comparative study has provided flexible solutions with the potential to strengthen the capacity of PBGMs for grass growth estimation in practical applications.

Global reservoir information can not only benefit local water management but can also improve our understanding of the hydrological cycle. This information includes water area, elevation, and storage; evaporation rate and volume values; and other characteristics. However, operational wall-to-wall reservoir storage and evaporation monitoring information is lacking on a global scale. Here we introduce NASA's new MODIS/VIIRS Global Water Reservoir product suite based on moderate resolution remote sensing data-the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Visible Infrared Imaging Radiometer Suite (VIIRS). This product consists of 8-day (MxD28C2 and VNP28C2) and monthly (MxD28C3 and VNP28C3) measurements for 164 large reservoirs (MxD stands for the product from both Terra (MOD) or Aqua (MYD) satellites). The 8-day product provides area, elevation, and storage values, which were generated by first extracting water areas from surface reflectance data and then applying the area estimations to the pre-established Area-Elevation (A-E) relationships. These values were then further aggregated to monthly, with the evaporation rate and volume information added. The evaporation rate and volume values were calculated after the Lake Temperature and Evaporation Model (LTEM) using MODIS/VIIRS land surface temperature product and meteorological data from the Global Land Data Assimilation System (GLDAS). Validation results show that the 250 m area classifications from MODIS agree well with the high-resolution classifications from Landsat (R-2 = 0.99). Validation of elevation and storage products for twelve Indian reservoirs show good agreement in terms of R-2 values (0.71-0.96 for elevation, and 0.79-0.96 for storage) and normalized root-mean-square error (NRMSE) values (5.08-19.34% for elevation, and 6.39-18.77% for storage). The evaporation rate results for two reservoirs (Lake Nasser and Lake Mead) agree well with in situ measurements (R-2 values of 0.61 and 0.66, and NRMSE values of 16.25% and 21.76%). Furthermore, preliminary results from the VIIRS reservoir product have shown good consistency with the MODIS based product, confirming the continuity of this 20-year product suite. This new global water reservoir product suite can provide valuable information with regard to water-sources-related studies, applications, management, and hydrological modeling and change analysis such as drought monitoring.