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In graduate education, there is often a great divide between classroom learning and research endeavors. Using learning community (LC) values and strategies, our goal is to build stronger and more meaningful ties between these two aspects of graduate education so that students see them as complimentary learning rather than separate components. This article describes a collaborative learning project between two core topics to strengthen links between course concepts and research, raise student interest in regional environmental issues, prepare students for postgraduate success, and help foster LC values. The project requires collaborative learning and integration of individual research to achieve team products, for example, reports and presentations, conference poster, or a manuscript submission to a peer-review journal. Although the LC model is tailored toward undergraduate education, student feedback shows our transfer of its values and strategies into the graduate classroom has been successful in three student cohorts. (Contains 2 tables and 1 figure.)

In this study, independent classifications of Landsat Thematic Mapper imagery and Jet Propulsion Laboratory AirSAR were combined to create an integrated classification of pasture and other vegetation types for a study area in the agricultural zone of Western Australia. The resulting classification combines greenness and brightness information from optical data with structure and water content information from synthetic aperture radar (SAR). Field observations of vegetation type, botanical composition, ground cover percentage, wet and dry biomass, canopy height, and soil water content were collected at 34 sites representing a range of pastures, browse shrubs, and crops. An unsupervised version of the Complex Wishart classification procedure, based on preserving scattering characteristics from the Freeman and Durden backscatter decomposition, was applied to the C-, L-, and P-band polarimetric SAR data. The optical classification was carried out using a principle component analysis on the green, red, and near-infrared bands and clustering on the basis of a class centroid distance measure and knowledge of ground targets. These two classification results were then fused together. Assessment of a confusion matrix using the individual sites showed that identification of more uniform, dense, and structurally distinct canopies was better than that of more diverse, sparse, and structurally ambiguous canopies, as the former were better represented by the canopy height attribute used in the SAR classification component. The optical classification enabled correction of SAR misclassification of vegetation due to surface roughness and soil moisture effects, or similar backscatter responses from herbaceous or arboreal canopies. The results show that simplification of vegetation into groups based upon properties with sensitive responses in both the optical and SAR domains, and combination of separate SAR and optical classifications, has potential for improving classification of diverse and heterogeneous herbaceous and browse cover in grazing lands. However, collection of ground calibration data must be at an appropriate spatial scale and include canopy and surface measurements directly related to backscatter mechanisms and spectral sensitivity. Index Terms--Botanical composition, grazing lands, herbage height, land-use classification, radar polarimetry, synthetic aperture radar (SAR).

This investigation used a modified parameterization of the Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) model to improve simulated growth and biomass yield of upland switchgrass (Panicum virgatum L.) ecotypes in northern U.S. locations. Leaf area development, biomass accumulation, and N utilization of upland ecotypes were parameterized by field evaluations from Montreal, QC, Canada, and sites throughout the northern U.S. Great Plains. Resulting ALMANAC simulations were validated against measured yields from 66 location–years of switchgrass production across 13 sites in Minnesota, North Dakota, and South Dakota. As contrasted to the model defaults, the modified parameterization reduced RMSE of annual simulated yields from 3.77 to 2.62 Mg ha−1 and improved percentage bias from −16 to 13%. Model performance was most improved in environments with no N fertilization, where ALMANAC simulated annual yields with an RMSE of 1.73 Mg ha−1 and percentage bias of −0.5%. Relative to the default ALMANAC parameterization, the modified parameterization also simulated a longer growing season and extended the median simulated maturity date from 1 to 28 August, greatly improving the estimation of switchgrass phenology within the study region. Sensitivity analyses revealed that simulated switchgrass yield was unaffected by modifications of runoff curve number and was most affected by modifications of radiation use efficiency. The other seven parameter modifications each had a median yield impact of 0.57–1.4 Mg ha−1. This work provides an improved characterization of upland switchgrass ecotypes in northern U.S. locations for future ALMANAC users. Core Ideas: The ALMANAC model for upland switchgrass in the northern United States had improved calibration.Error of annual and multiyear‐average yield estimates was reduced by more than 30%.Nitrogen stress estimation and phenology was consistent with northern U.S. field observations. [ABSTRACT FROM AUTHOR]

Greenup dates and their responses to elevation and temperature variations across the mountains of Acadia National Park are monitored using remote sensing data, including Landsat 8 surface reflectances (at a 30‐m spatial resolution) and VIIRS reflectances adjusted to a nadir view (gridded at a 500‐m spatial resolution), during the 2013–2016 growing seasons. The 30‐m resolution provides a better scale for studying the phenology variation across elevational gradients than the 500‐m resolution, as greenup dates monitored at 30‐m scale have better agreement with leaf‐out dates recorded in the field alongside the north–south‐oriented hiking trails on three of the park's tallest mountains (466 m, 418 m, and 380 m), and can provide landcover‐specific analysis. The spring phenology responses to temperature and elevation vary among different spatial scales. Greenup dates of Acadia National Park monitored at 30‐m scale show a weak advancing trend with higher spring temperature, while greenup dates monitored at 500 m show a weak delaying trend. The species mix within landcover at 30‐m scale could weaken the advancing trend detected at field observation level. The landcover mix and elevation variation within 500‐m scale could alter the spring phenology response to spring temperature variation. Greenup dates monitored at both 30‐m and 500‐m scales vary among different elevational zones, aspects, landcovers, and years. However, the relationship between greenup dates and elevation is rather weak. [ABSTRACT FROM AUTHOR]

The ever-increasing demand for higher bandwidth and lower loss makes the predictability of high-speed interconnect performance increasingly challenging. Validating models against measurements of manufactured test structures requires not only accurate methodology but also understanding of the uncertainty impact. S-parameter measurements, characterization of materials, manufacturing processes, and models constructed based on measured inputs all cause uncertainty in the performance metrics of interest. Therefore, it is critical to anticipate the results with the associated uncertainty to assess the correlation quality more objectively. This article investigates the reproducibility of measurements required for high-speed package interconnect validation through rigorous analysis and presents a methodology to quantify the impact of measurement uncertainty on commonly used performance metrics. [ABSTRACT FROM AUTHOR]

Intel's microprocessors are powered by high-frequency fully-integrated switching regulators implemented on die. Current products use non-magnetic inductors designed in the package substrate. This article investigates the use of magnetic thin film inductors fabricated on silicon wafers as an alternative that improves conversion efficiency while achieving higher inductance per area density. This article builds on the earlier work done on thin film inductors at Intel, and explores the feasibility of using them in a high volume product. A number of different design variations are studied to look at tradeoffs between efficiency, saturation characteristics, transient response, and voltage ripple. This is accomplished through a combination of passive measurements using a vector network analyzer (VNA) and active measurements on a fully functioning integrated voltage regulator system. [ABSTRACT FROM AUTHOR]

Mapping the spatial distribution of woody and herbaceous vegetation in high temporal resolution in savannas would be beneficial for modeling interrelationships between trees and grasses, and monitoring fuel loads and biomass for livestock. In this study, we developed a frequency decomposition method to separate woody and herbaceous vegetation components using Normalized Difference Vegetation Index (NDVI) time series. The results were validated using fractional cover data derived from high-resolution images. The validation revealed a close relationship between our decomposed NDVI and corresponding fractional cover (R2 = 0.55 and 0.64 for woody and herbaceous components, respectively). We examined the spatial and temporal patterns of the decomposed NDVI, where woody and herbaceous NDVI showed different responses to precipitation. The methods proposed in this study can be used to separate the woody and herbaceous NDVI time series as an alternative approach for monitoring woody and herbaceous vegetation interrelationships related to climatic drivers. [ABSTRACT FROM AUTHOR]

Greenup dates of the mountainous Acadia National Park, were monitored using remote sensing data (including Landsat 8 surface reflectances (at a 30m spatial resolution) and VIIRS reflectances adjusted to a nadir view (gridded at a 500m spatial resolution)) during the 2013-2016 growing seasons. Ground-level leaf-out monitoring in the areas alongside the north-south-oriented hiking trails on three of the park's tallest mountains (466m, 418m, and 380m) was used to evaluate satellite derived greenup dates in this study. While the 30m resolution would be expected to provide a better scale for phenology detection in this mountainous region than the 500m resolution, the daily temporal resolution of the 500m data would be expected to offer vastly superior monitoring of the rapid variations experienced during vegetation greenup along elevational gradients. Therefore, the greenup dates derived from the Landsat 8 Enhanced Vegetation Index (EVI) data, augmented with Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) simulated EVI values, does provide more spatial details than VIIRS data alone and agree well with field monitored leaf out dates. Satellite derived greenup dates from the 30m of Acadia National Park vary among different elevational zones, although the date of greenup is not always the most advanced at the lowest elevation. This indicates that the spring phenology is not only determined by microclimates associated with different elevations in this mountainous area, but is also possibly affected by the species mixture, localized temperatures, and other factors in Acadia. [ABSTRACT FROM AUTHOR]

Fractional cover of photosynthetic vegetation (FPV), non-photosynthetic vegetation (FNPV) and bare soil (FBS) is an important input for assessment of the productivity of global pastures and rangelands. Here we describe the updating of this product using the new Moderate Resolution Imaging Spectroradiometer (MODIS) Nadir BRDF-Adjusted Reflectance (NBAR) Collection 6 reflectance product (C6) and a major expansion of the field calibration database. Fractional cover based on the C6 input exhibited reduced bias and root mean square error compared with the Collection 5 (C5) product. The expanded calibration database with more sites in arid areas provided greater separation between reflectance values of end-members for FNPV and FBS. Specific site variations in FNPV and FBS in arid areas could be traced to small but consistent changes in blue and green band, and occasional changes in short wave infrared reflectance in C6 when compared to C5. The recalibration described here provides an Australian fractional cover product with reduced uncertainty and improves the basis for a prototype global product for use in modelling of rangeland and pasture productivity. [ABSTRACT FROM AUTHOR]

Abstract: Producing mature and functional cardiomyocytes (CMs) by in vitro differentiation of induced pluripotent stem cells (iPSCs) using only biochemical cues is challenging. To mimic the biophysical and biomechanical complexity of the native in vivo environment during the differentiation and maturation process, polydimethylsiloxane substrates with 3D topography at the micrometer and sub‐micrometer levels are developed and used as cell‐culture substrates. The results show that while cylindrical patterns on the substrates resembling mature CMs enhance the maturation of iPSC‐derived CMs, sub‐micrometer‐level topographical features derived by imprinting primary human CMs further accelerate both the differentiation and maturation processes. The resulting CMs exhibit a more‐mature phenotype than control groups—as confirmed by quantitative polymerase chain reaction, flow cytometry, and the magnitude of beating signals—and possess the shape and orientation of mature CMs in human myocardium—as revealed by fluorescence microscopy, Ca2+ flow direction, and mitochondrial distribution. The experiments, combined with a virtual cell model, show that the physico‐mechanical cues generated by these 3D‐patterned substrates improve the phenotype of the CMs via the reorganization of the cytoskeletal network and the regulation of chromatin conformation. [ABSTRACT FROM AUTHOR]

Assessing the effects of human land use and management decisions requires an understanding of how temporal changes in biodiversity influence the rate of ecosystem functions and subsequent delivery of ecosystem services. In highly modified anthromes, the spatial distribution of natural vegetation types is often unknown or coarsely represented challenging comparative analyses seeking to assess changes in biodiversity and potential downstream effects on ecosystem processes and functions. In this context, the objectives of this study were to construct a multi-resolution representation of potential natural vegetation at four hierarchical classification levels of increasing floristic and physiognomic detail for the state of Minnesota, USA. Using a collection of natural/near-natural vegetation relevés, a series of Random Forest classification models were used to project the potential distribution of natural vegetation types based on their association with a variety of environmental variables. Model performance varied within and between classification levels with overall accuracy ranging between 64–99% (kappa 0.44–0.99). Model performance tended to decrease and become more variable with increasing floristic complexity at finer classification levels. Classwise performance metrics including precision and sensitivity were also reported. A method for exploring potential class confusion resulting from niche overlap using Random Forest proximities and Nonmetric Multidimensional Scaling is demonstrated. Collectively, the results presented here provide an analytically supported baseline representation of potential natural vegetation for the state of Minnesota, USA. These data can provide a backdrop to further analyses surrounding the influence of human activity on ecosystem processes and services as well as inform future conservation and restoration efforts. [ABSTRACT FROM AUTHOR]

Colloidal gels are three-dimensional networks of microgel particles and can be utilized to design microtissues where the differential adhesive interactions between the particles and cells, guided by their surface energetics, are engineered to spatially assemble the cellular and colloidal components into three-dimensional microtissues. In this work we utilized a colloidal interaction approach to design cell-polyurethane (PU) microgel bimodal microtissues using endothelial cells (ECs) as a normal cell model and a nonmalignant breast cancer cell line (MCF-7) as a cancer cell model. PU microgels were developed from a library of segmental polyurethanes with poly(ethylene glycol) soft segment and aliphatic diisocyanate/L-tyrosine based chain extender as hard segment to modulate the interactions between PU colloidal particles and cells. The surface energies of the microgel particles and cells were estimated using Zisman's critical surface tension and van Oss-Good-Chaudhury theory (vOGCT) from liquid contact angle analysis. Binary interaction potentials between colloidal PU particles and cells and the ternary interaction between colloidal PU particle, cell, and collagen I/Matrigel were calculated to explain the formation of microtissues and their spreading in extraneous biomatrix respectively by using classical and extended DLVO theory (XDLVO). Furthermore, rheological analysis and in silico simulations were used to analyze the assembly and spreading of the PU microgel based microtissues. In vitro experiments showed that ECs and MCF-7 displayed more differentiated (EC spreading/MCF-7 lumen formation) character when mixed with microgel particles that were stable in aqueous medium and more undifferentiated character (EC nonspreading/MCF-7 spreading) when mixed with microgel particles unstable in aqueous medium. [ABSTRACT FROM AUTHOR]

Changes in Brazil's climate have aggravated drought conditions, yet the government continues to favor populist policies over ensuring sustainable energy and water resources. This paper analyses the underlying environmental and policy conditions that have led to Brazil's current power and water crisis and argues in favor of an overhaul of the federal energy infrastructure to reduce political influence in a regulated market and to improve initiatives of reforestation to mitigate the effects of climate change. The effects of poor climate and energy policies so clearly manifested in the Brazilian crisis should serve as a warning to other countries that sustainability is a choice, not a causal eventuality. [ABSTRACT FROM AUTHOR]

This study explores the use of the relationship between the normalized difference vegetation index (NDVI) and the shortwave infrared ratio (SWIR32) vegetation indices (VI) to retrieve fractional cover over the structurally complex natural vegetation of the Cerrado of Brazil using a time series of imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS). Data from the EO-1 Hyperion sensor with 30 m pixel resolution is used to sample geographic and seasonal variation in NDVI, SWIR32, and the hyperspectral cellulose absorption index (CAI), and to derive end-member values for photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and bare soil (BS) from a suite of protected and/or natural vegetation sites across the Cerrado. The end-members derived from relatively pure 30 m pixels are then applied to a 500 m pixel resolution MODIS time series using linear spectral unmixing to retrieve PV, NPV, and BS fractional cover (FPV, FNPV, and FBS). The two-way interaction response of MODIS-equivalent NDVI and SWIR32 was examined for regions of interest (ROI) collected within protected areas and nearby converted lands. The MODIS NDVI, SWIR32 and retrieved FPV, FNPV, and FBS are then compared to detailed cover and structural composition data from field sites, and the influence of the structural and compositional variation on the VIs and cover fractions is explored. The hyperion ROI analysis indicated that the twoway NDVI-SWIR32 response behaved as an effective surrogate for the two-way NDVI-CAI response for the campo limpo/grazed pasture to cerrado sensu stricto woody gradient. The SWIR32 sensitivity to the NPV and BS variation increased as the dry season progressed, but Cerrado savannah exhibited limited dynamic range in the NDVI-CAI and NDVI-SWIR32 two-way responses compared to the entire landscape, which also comprises fallow croplands and forests. Validation analysis of MODIS retrievals with Quickbird-2 images produced an RMSE value of 0.13 for FPV. However, the RMSE values of 0.16 and 0.18 for FBS and FNPV, respectively, were large relative to the seasonal and inter-annual variation. Analysis of site composition and structural data in relation to the MODIS-derived NDVI, SWIR32 and FPV, FNPV, and FBS, indicated that the VI signal and derived cover fractions were influenced by a complex mix of structure and cover but included a strong year-to-year seasonal effect. Therefore, although the MODIS NDVI-SWIR32 response could be used to retrieve cover fractions across all Cerrado land covers including bare cropland, pastures and forests, sensitivity may be limited within the natural Cerrado due to sub-pixel heterogeneity and limited BS and NPV sensitivity. [ABSTRACT FROM AUTHOR]