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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.

This report describes a technique for measuring lung shunt fraction (LSF) twice in a single session during planning arteriography for radioembolization using low and standard dose technetium-99m macroaggregated albumin (99mTc-MAA). A patient with a 16.0 cm hepatocellular carcinoma and LSF of 70% was treated with lenvatinib for 4 weeks. Planning arteriography with administration of 0.5 millicuries of 99mTc-MAA was then performed. Arterial access was maintained while the LSF was calculated, which was persistently elevated at 54%. Embolization of arteriovenous shunts was performed during the same session and 5.0 millicuries of 99mTc-MAA were administered. The repeat LSF was 29%. Successful radioembolization was subsequently performed.

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.

The package integrated inductors employed by Intel's Fully Integrated Voltage Regulator (FIVR) have had to scale in tandem with the circuits they power. This reduction in available volume has resulted in degraded inductor quality factor and reduced conversion efficiency. In this work, a novel coaxial magnetic composite core inductor, called Coax MIL, is described. Coax MIL dramatically improves inductor performance and quality factor. This improvement in inductor metrics translates to reduced ripple current and enhanced efficiency.

The central nervous system (CNS) plays a key role in the sense-and-respond system which maintains proper energy stores. However, the molecular, cellular, and circuit mechanisms through which the CNS achieves this goal is poorly understood. We have recently identified the dorsal raphe nucleus (DRN) as a key node in the CNS, responsible for regulating numerous aspects of energy balance. Neurons within the DRN can potently regulate feeding, thermogenesis, and locomotor activity, and prolonged changes in their activity can ultimately drive changes in body weight. Despite playing a key role in regulating energy homeostasis, the molecular heterogeneity of the DRN had, until recently, hindered further progress in understanding it’s intricate role in the regulation of body weight. Here, we use a combination of nuclear labeling, sorting, and single-nuclear RNA-sequencing to identify the component cell types of key DRN populations, themselves known to regulate the various facets of energy balance. In particular, we identify over twenty candidate subpopulations of DRN neurons, principally defined by the neurotransmitters serotonin, glutamate, and GABA. Many of the subpopulations of these ‘principal’ cell types differentially express peptides, receptors, and signaling molecules that are directly implicated in the regulation of energy balance. We have begun to validate the expression and neuroanatomy of these molecules, including such neuropeptides as thyrotropin-releasing hormone and neuropeptide Y, and we have leveraged available recombinase-driver lines to modulate the activity of neurons expressing these genes to effectively assay their function. Together, this work represents important progress towards identifying the key cell subtypes that regulate the various aspects of energy balance. Disclosure V. M. Bhave: None. M. J. Hill-oliva: None. N. Kamatkar: None. S. Chowdhury: None. A. R. Nectow: None. Funding American Diabetes Association/Pathway to Stop Diabetes (1-18-ACE-49 to A.R.N.)

Plants actively regulate excess absorbed energy to protect photosynthetic machinery through heat dissipation in a process known as non-photochemical quenching (NPQ), a process useful for quantifying plant health and productivity. NPQ can be indirectly measured in the visible wavelengths between 500 nm and 560 nm, most commonly through the Photochemical Reflectance Index (PRI). However, there remains a lack of consensus regarding the optimal functional form and band selection to calculate PRI for the purpose of measuring NPQ mechanisms. Here, we quantitatively evaluate the effectiveness of leaf-level parametric and non-parametric spectral formulations, band locations, and number of bands to track the xanthophyll pigment cycle in a tall mature Eucalypt forest. Subsequently, our recommended approach is the new ‘tri-PRI’ index robust to constitutive pigment pool sizes across the canopy profile. tri-PRI is a Triangular Vegetation Index (TVI) (tri-PRI = 0.5[(520 - 490)(R545nm - R490nm) - (545 – 490)(R520nm - R490nm)]) using three reflectance bands around 490 nm, 520 nm and 545 nm, and has a physiological photosynthetic basis. We found that tri-PRI significantly outperformed PRI and other two band combinations for quantifying the xanthophyll EPoxidation State ‘EPS’ (tri-PRI R2 = 0.75 versus PRI R2 = 0.23), as well as the Φ NPQ and Φ PSII active chlorophyll fluorescence quenching yields. The new band placement enhanced the dynamic EPS absorption peak, while the third band provided an additional normalisation to minimise the confounding effects of pigments with overlapping spectral features. tri-PRI also performed comparably to parametric and non-parametric hyperspectral techniques and formulations using continuous spectral regions, highlighting the utility of targeted multispectral indices over hyperspectral approaches. This leaf-level study represents a foundational step toward indirectly measuring dynamic photosynthetic activity across the canopy profile in a tall mature Eucalypt forest to inform upscaling efforts from above-canopy remote sensing platforms. The application of tri-PRI and other top-performing multi-band TVI formulations for predicting EPS presented here should be explored across different canopy types, temporal-, and spatial scales.

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.

Validating the performance of high-speed interconnect modeling against measurements of fabricated test structures requires an understanding of the robustness of the measurement methods as well as the physical variations present in an imperfectly fabricated test structure. This paper presents a methodology for evaluating the performance of interconnect modeling considering the actual metrology variation and the realworld manufacturing tolerances used to fabricate the test vehicle. By ensuring that measurement results, inclusive of operator and equipment variations, overlap the modeling inclusive of expected manufacturing variations, confidence in the high-speed interconnect modeling is established.

Vegetation Fractional Cover (VFC) is an important indicator of the condition of the terrestrial surface of the Earth. The dynamics of bare soil (BS), non-photosynthetic vegetation (NPV) and photosynthetic vegetation (PV) fractions reveal patterns of growth, senescence, dormancy and regeneration. The dynamics also reveal trends in land cover and land use management across the globe. Analysis of satellite data has indicated increasing greenness of the land surface however the dynamics of the NPV and BS fractions are equally important indicators of many elements of ecosystem function and sustainability. In this study, we provide a comprehensive assessment of trends in VFC for the global terrestrial land surface based on a trend analysis over the period 2001–2018 using the Global Vegetation Fractional Cover Product. Trends were analysed by Mann-Kendell regressions over 18 years for each month of the year. Monthly maps of significant trend areas were aggregated to provide seasonal assessments. Areas and percentage areas of positive and negative trends were compiled for United Nations Subregions, Countries and Ecoregions. Significant negative trends in BS occurred across 20 M km2 of the terrestrial land surface. Although the areas of negative trends in BS were largest in China and India, the top 24 countries by area were widely distributed across the world. However, BS increased significantly across more than 11 M km2. Eleven of the top 24 ranked countries for area of increasing BS were in Africa. Substantial areas exhibited negative trends in NPV split between China and India where PV was increasing, and drylands in Asia and Africa where BS was increasing. Analysis of covariate factors at country scale inferred an association between significant increase in BS and long-term drought and increases in livestock populations. The positive trends in BS and negative trends in NPV are indicators of current and future risk for soil erosion, habitat change, and reduction in ecosystem health across heavily populated regions of the developing world.

Circuit area scaling driven by Moore’s law coupled with the push to thinner packages for mobile microprocessors has reduced the volume available for Air Core Inductors (ACI). This translates to a reduction in the conversion efficiency of Fully Integrated Voltage Regulator (FIVR). Magnetic Inductor Array (MIA) modules are used for the first time on the 10th generation Intel Core™ microprocessor in mobile segments to improve FIVR efficiency. In addition to improving the peak efficiency, it is also possible to realize large light load efficiency gains and minimize voltage ripple through the use of magnetic inductors. This paper covers the magnetic inductor array (MIA) design considerations for improving performance as well as meeting high volume manufacturability and reliability requirements.

Vegetation Fractional Cover (VFC) is an important global indicator of land cover change, land use practice and landscape, and ecosystem function. In this study, we present the Global Vegetation Fractional Cover Product (GVFCP) and explore the levels and trends in VFC across World Grassland Type (WGT) Ecoregions considering variation associated with Global Livestock Production Systems (GLPS). Long-term average levels and trends in fractional cover of photosynthetic vegetation (FPV), non-photosynthetic vegetation (FNPV), and bare soil (FBS) are mapped, and variation among GLPS types within WGT Divisions and Ecoregions is explored. Analysis also focused on the savanna-woodland WGT Formations. Many WGT Divisions showed wide variation in long-term average VFC and trends in VFC across GLPS types. Results showed large areas of many ecoregions experiencing significant positive and negative trends in VFC. East Africa, Patagonia, and the Mitchell Grasslands of Australia exhibited large areas of negative trends in FNPV and positive trends FBS. These trends may reflect interactions between extended drought, heavy livestock utilization, expanded agriculture, and other land use changes. Compared to previous studies, explicit measurement of FNPV revealed interesting additional information about vegetation cover and trends in many ecoregions. The Australian and Global products are available via the GEOGLAM RAPP (Group on Earth Observations Global Agricultural Monitoring Rangeland and Pasture Productivity) website, and the scientific community is encouraged to utilize the data and contribute to improved validation.

Fully Integrated Voltage Regulators (FIVRs) are switching voltage regulators integrated on to the same die as the CPU and Graphics cores, in 4th and 5th generation Intel® Core™ microprocessors. Practical limitations prevent the application of traditional voltage regulator characterization methods to FIVRs. To overcome these challenges, new methods and techniques had to be developed for the testing and characterization of FIVRs. Power Efficiency (η) is one of the key performance metrics of voltage regulators. In this paper we explain the methods used to measure the Power Efficiency of FIVRs. These methods are applicable to Integrated VRs in general and are not specific to FIVRs alone. Description of power loss components and extraction of the loss coefficients from curve fitting technique is also presented. Measured results show that the proposed methods are highly repeatable with worst-case run-to-run variation of 0.4%. The results also show that the worst-case error is

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 fraction...

The clumping index (CI) characterizes the grouping of foliage relative to a random spatial distribution of leaves and is an important structural parameter for plant canopies that can influence canopy radiation regimes. Consequently, the CI is very useful for ecological and meteorological models. One method used to retrieve the CIs of plant canopies is to construct a linear relationship between the CI and the normalized difference between hotspot and dark spot (NDHD) angular index. This method requires a particularly accurate reconstruction of hotspot signatures, which are difficult to measure. In this study, we propose a framework to retrieve CIs from Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) parameters, which are generally based on linear CI-NDHD equations. The main algorithm is designed to retrieve CIs in the closed interval [0.33, 1.00]. This range is derived from the CI-NDHD equations and is thus called as the physical range here, although a modified lower boundary can be implemented in the future if necessary. If CIs are outside of this range, then a backup algorithm is designed to reprocess these so-called outlier CIs. The hotspot-adjusted version of the RossThick-LiSparseReciprocal (RTLSR) model (i.e., the RTCLSR model) is employed to reconstruct the hotspot signatures for the MODIS BRDF parameters. This method simplifies the hotspot reconstruction by using two hotspot parameters that are not distinctly scale-dependent particularly in the context of an inhomogeneous coarse spatial resolution. To evaluate this algorithm framework, we collect dozens of global field-measured CIs and calculate their determination coefficient (R2), root mean square error (RMSE) and bias relative to MODIS CIs derived using both the main algorithm and the backup algorithm. Our results show that this framework can derive MODIS CIs with a high accuracy (i.e., R2 = 0.80 (0.72), RMSE = 0.07 (0.12), bias = −0.03 (−0.10)) using the main (backup) algorithms and that it shows promise for various ecological applications, especially in combination with the leaf area index (LAI).

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 releves, 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.

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.

The Mediterranean-type oak/grass savanna of California is composed of widely spaced oak trees with understory grasses. These savanna regions are interspersed with large areas of more open grasslands. The ability of remotely sensed data (with various spatial resolutions) to monitor the phenology in these water-limited oak/grass savannas and open grasslands is explored over the 2012–2015 timeframe using data from Landsat (30 m), the MODerate resolution Imaging Spectroradiometer (MODIS – gridded 500 m), and the Visible Infrared Imaging Radiometer Suite (VIIRS – gridded 500 m) data. Vegetation phenology detected from near-ground level, webcam based PhenoCam imagery from two sites in the Ameriflux Network (long-term flux measurement network of the Americas) (Tonzi Ranch and Vaira Ranch) is upscaled, using a National Agriculture Imagery Program (NAIP) aerial image (1 m), to evaluate the detection of vegetation phenology of these savannas and grasslands with the satellite data. Results show that the Normalized Difference Vegetation Index (NDVI) time series observed from the satellite sensors are all strongly correlated with the PhenoCam NDVI values from Tonzi Ranch (R 2 > 0.67) and Vaira Ranch (R 2 > 0.81). However, the different viewing geometries and spatial coverage of the PhenoCams and the various satellite sensors may cause differences in the absolute phenological transition dates. Analysis of frequency histograms of phenological dates illustrate that the phenological dates in the relatively homogeneous open grasslands are consistent across the different spatial resolutions, in contrast, the relatively heterogeneous oak/grass savannas display has somewhat later greenup, maturity, and dormancy dates at 30 m resolution than at 500 m scale due to the different phenological cycles exhibited by the overstory trees and the understory grasses. In addition, phenologies derived from the MODIS view angle corrected reflectance (Nadir BRDF-Adjusted Reflectance – NBAR) and the newly developed VIIRS NBAR are shown to provide comparable phenological dates (majority absolute bias ≤2 days) in this area.

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 two-way 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.

International audience; The semi-empirical, kernel-driven, linear RossThick-LiSparseReciprocal (RTLSR) Bidirectional Reflectance Distribution Function (BRDF) model is used to generate the routine MODIS BRDF/Albedo product due to its global applicability and the underlying physics. A challenge of this model in regard to surface reflectance anisotropy effects comes from its underestimation of the directional reflectance signatures near the Sun illumination direction; also known as the hotspot effect. In this study, a method has been developed for improving the ability of the RTLSR model to simulate the magnitude and width of the hotspot effect. The method corrects the volumetric scattering component of the RTLSR model using an exponential approximation of a physical hotspot kernel, which recreates the hotspot magnitude and width using two free parameters (C1 and C2, respectively). The approach allows one to reconstruct, with reasonable accuracy, the hotspot effect by adjusting or using the prior values of these two hotspot variables. Our results demonstrate that: (1) significant improvements in capturing hotspot effect can be made to this method by using the inverted hotspot parameters; (2) the reciprocal nature allow this method to be more adaptive for simulating the hotspot height and width with high accuracy, especially in cases where hotspot signatures are available; and (3) while the new approach is consistent with the heritage RTLSR model inversion used to estimate intrinsic narrowband and broadband albedos, it presents some differences for vegetation clumping index (CI) retrievals. With the hotspot-related model parameters determined a priori, this method offers improved performance for various ecological remote sensing applications; including the estimation of canopy structure parameters.

The Grassland Vegetation Inventory (GVI), which represents a comprehensive biophysical, anthropogenic, and land-use inventory of grasslands in Alberta, is widely used as a baseline for grassland co...

Greenup dates of the mountainous Acadia National Park, were 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. Ground-level leaf-out monitoring in the areas alongside the north-south-oriented hiking trails on three of the park's tallest mountains (466 m, 418 m, and 380 m) was used to evaluate satellite derived greenup dates in this study. While the 30 m resolution would be expected to provide a better scale for phenology detection in this mountainous region than the 500 m resolution, the daily temporal resolution of the 500 m 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 30 m 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.

Myocardial infarction (MI) is projected to increase globally in the coming decades. The long-term outlook for patients with ischemic heart injury undergoing current treatment modalities is bleak, due to the lack of regenerative capacity of native heart tissue. Tissue engineering and regenerative medicine have developed numerous strategies to repair or replace injured myocardium. One of the most promising strategies to date is the attempt to engineer tissues and cells at the nanoscale by utilizing nanobiomaterials to mimic the native nanoscale structure of the heart. Nanobiomaterials have proliferated enormously in the past few decades and have great potential for creating biomimetic systems that can replace or repair injured myocardium. Tissue engineering scaffolds with precisely controlled nanotopography, electrically conductive nanomaterials with the potential for mimicking conductive pathways in the heart, and numerous nanocarriers for targeted cardiac drug delivery have now been achieved. In this chapter we review the rationale for engineering biological tissues at the nanoscale as well as recent applications in nanofabrication and nanomedicine for cardiac regeneration.

Increasing high speed data rates for digital signaling and emerging technologies such as 5G have expanded the frequency range of interest for package dielectric materials characterization and generated interest in characterization over use conditions such as temperature and humidity. In this paper, a robust dielectric material characterization metrology with high repeatability under different temperature and humidity conditions is presented. Temperature and humidity dependent interpolation of material properties based on measured data is also presented and shown to provide good estimates for environmental conditions not in the original data set.

Retrieval from remote sensing of separate temporal dynamics for the understorey layer in tropical savannahs would be beneficial for monitoring fuel loads, biomass for livestock, interrelationships between trees and grasses, and modelling of savannah systems. In this study, we combined unmixing of fractional cover with normalized difference vegetation index NDVI and the short wave infrared ratio SWIR32 with time series decomposition of the NDVI to attempt to fully resolve the dynamics of the herbaceous understorey in the Australian tropical savannah based on the fractions of photosynthetic herbaceous vegetation FPVH and non-photosynthetic vegetation FNPV, from the woody overstorey, represented by the fraction of photosynthetic vegetation in the tree canopy FPVW. Evaluation of FPVH against field data gave moderate relationships between predicted and observed values R2 between 0.5 and 0.6; since semivariogram metrics of representativeness indicated that field sites were relatively unrepresentative of variation at the Moderate Resolution Imaging Spectroradiometer MODIS pixel scale. Both FPVW and FPVH produced strong linear relationships root mean square error < 0.1 units with high-resolution Orbview 3 cover fractions classified from tasselled cap transformations. However, FNPVH non-photosynthetic herbaceous cover fraction retrievals at southern arid locations produced an evaluation relationship with a greater deviation from the 1:1 line than for northern locations. This suggested that there may be limitations on the NDVI–SWIR32 unmixing approach in more sparsely vegetated savanna. Maps of average annual maximum FPVH, FNPVH, and total herbaceous cover fraction could be used as indicators of savannah productivity and landscape health. However, close examination of the limitations of the NDVI–SWIR32 response may be required for application of this method in other global savannahs.

Fractional cover of photosynthetic vegetation FPV, non-photosynthetic vegetation FNPV, and bare soil FBS has been retrieved for Australian tropical savannah based on linear unmixing of the two-dimensional response envelope of the normalized difference vegetation index NDVI and short wave infrared ratio SWIR32 vegetation indices VI derived from Moderate Resolution Imaging Spectroradiometer MODIS reflectance data. The approach assumes that cover fractions are made up of a simple mixture of green leaves, senescent leaves, and bare soil. In this study, we examine retrieval of fractional cover using this approach for a study area in southern Africa with a more complex vegetation structure. Region-specific end-members were defined using Hyperion images from different locations and times of the season. These end-members were applied to a 10-year time series of MODIS-derived NDVI and SWIR32 from 2002 to 2011 to unmix FPV, FNPV, and FBS. Results of validation with classified high-resolution imagery indicated major bias in estimation of FNPV and FBS, with regression coefficients for predicted versus observed data substantially less than 1.0 and relatively large intercept values. Examination with Hyperion images of the inverse relationship between the MODIS-equivalent SWIR32 index and the Hyperion-derived cellulose absorption index CAI to which it nominally approximates revealed: 1 non-compliant positive regression coefficients for certain vegetation types; and 2 shifts in slope and intercept of compliant regression curves related to day of year and geographical location. The results suggest that the NDVI–SWIR32 response cannot be used to approximate the NDVI–CAI response in complex savannah systems like southern Africa that cannot be described as simple mixtures of green leaves, dry herbaceous material high in cellulose, and bare soil. Methods that use a complete set of multispectral channels at higher spatial resolution may be needed for accurate retrieval of fractional cover in Africa.

Savannas are multi-layered tree–grass–forb systems which exhibit a high level of diversity in vegetation structure and arrangement, and complex ecosystem functions dependent upon highly seasonal cl...

Intel fourth-generation and fifth-generation Core microprocessors are powered by high-frequency integrated switching voltage regulators. The inductors required to implement these regulators are constructed using the routing layers of conventional organic flip chip packaging. This paper provides an overview of the construction of these inductors including representative results from production packages. Measured inductors reported in this paper span from 1 to 6.7 nH under 2.4 mm2 and achieve $Q$ of up to 24 at 140 MHz (the switching frequency).

The Western Prairie Fringed Orchid ( Platanthera praeclara ) is a threatened species found on the Sheyenne National Grassland (SNG) in southeast North Dakota, USA. The SNG is subject to management for multiple uses including biodiversity conservation, livestock grazing and recreation. Therefore, there is a need for the development of indicators of suitable orchid habitat. The orchids are continuously monitored, but understanding of the relationship between landscape properties and orchid locations is limited. In this study data that characterize topography, moisture, and groundwater were used to construct indicators of landscape suitability and an overall Habitat Suitability Index (HSI) for the orchid. A LiDAR-derived DEM and groundwater well observations were used to develop landscape indicators. The Topographic Wetness Index (TWI: a measure of moisture on the landscape), the Topographic Position Index (TPI: a measure of position on the landscape), and the distance to groundwater (DTG: a measure of the distance from the land surface to the groundwater surface) provided the best set of indicators of orchid habitat. Point-based field observations of orchid occurrence were used to develop Orchid Suitability Metrics (OSMs) that identified the range of indicator values most strongly associated with orchids. These OSMs were used to define year by year suitability zones for each indicator that were combined to create the HSI. Comparison of orchid locations with groundwater elevations showed that orchids occurred on average 0.98 ± 0.39 (2 σ ) m above the water table. TWI and TPI demonstrated that orchids occur near flow paths and areas of lower elevation than their surroundings. HSI values of 0.67 and above were associated with 89.8% of all orchid observations used in the analysis. The landscape indicators, OSM concept and HSI could be generally applied to monitoring and conservation management of orchid habitat and the concept may be applicable to other valued species with similar niche properties.

The development of fractional vegetation cover products for Australia that resolve cover into photosynthetic vegetation (FPV), non-photosynthetic vegetation (FNPV) and bare soil/rock (FBS) provides a new basis for examination of responses of vegetation cover to long term precipitation cycles, and to explore the interaction between these responses and land cover type, land use and other land surface properties. In this study, the relationship between accumulated antecedent precipitation (AAP) from 1 to 60 months and average monthly FPV and FNPV from the MODIS Fractional Cover Product is examined over a 17 year period from 2001 to 2018. The maximum R2 value, regression coefficients for the maximum R2, and number of accumulated months to the maximum R2 were mapped for each month of the year for FPV and FNPV. Behaviour of responses in relation to land use, land cover, and soil water holding capacity was analysed based on pixel frequencies of classes at sub-region scale in the Interim Biogeographic Regionalisation of Australia. The analysis showed that FPV is largely dependent upon AAP in the preceding 12 months, however responses to longer periods of AAP also occur in specific land use-vegetation type combinations. The study also showed that positive responses in FNPV could be driven by AAP from as much as 60 months, but that FNPV is reduced in many areas in response to increased AAP. The presence or absence of domesticated livestock grazing as defined by Australian land use mapping was a major influence on response to AAP of both FPV and FNPV with statistical analysis indicating interactions between major natural vegetation type and grazing. In highly responsive areas (R2 > 0.6) monitoring of land condition could be enhanced by testing of regional cover levels for major deviations from the long terms responses that might suggest land management concerns.

We present a global analysis of the changing face of vegetation persistence in savanna ecosystems by boreal seasons. We utilized nearly 30 years of monthly normalized difference vegetation index data in an innovative time-series approach and developed associated statistical significance tests, making the application of continuous vegetation metrics both more rigorous and more useful to research. We found that 8,000,000–11,000,000 km2 of savanna have experienced significant vegetation decline during each season, while 20,000,000–23,000,000 km2 have experienced an increase in vegetation persistence during each season, relative to the baseline period (1982–1985). In addition, with the exception of the March–April–May season, which is mixed, the pattern of significant vegetation persistence in the Northern Hemisphere is almost exclusively positive, while it is negative in the Southern Hemisphere. This finding highlights the increasing vulnerability of the Southern Hemisphere savanna landscapes; either resulti...

Leaf area index (LAI) is a primary descriptor of vegetation structure, function, and condition. It is a vegetation product commonly derived from earth observation data. Independently obtained ground-based LAI estimates are vital for global satellite product validation. Acceptable uncertainties of these estimates are guided by satellite product accuracy thresholds stipulated by the World Meteorological Organisation (WMO) and the Global Climate Observing System (GCOS). This study compared canopy openness, gap fraction and LAI estimates derived from ground-based instruments; the primary focus was to compare high- and low-resolution (HR and LR) digital hemispherical photography (DHP) to a terrestrial laser scanner (TLS), augmented with measurements using the LAI-2200 plant canopy analyser in a subset of plots. Additionally, three common DHP classification methods were evaluated including a manual supervised (S) classification, a global (G) binary automated threshold, and a two-corner (TC) automated threshold applied to mixed pixels only. Coincident measurements were collected across five diverse forest systems in Eastern Australia with LAI values ranging from 0.5 to 5.5. Canopy openness, gap fraction and LAI were estimated following standard operational field data collection and data processing protocols. A total of 75 method-to-method pairwise comparisons were conducted, out of which 37 had an RMSD ≥ 0.5 LAI and 26 were significantly different (p 0.75). Although TLS produced on average 55% higher openness and LAI than the HR-DHP (S) and (TC) classification methods, the strong coefficient of determination indicated the potential to calibrate these methods (R2 = 0.88 and 0.79, respectively). Overall, results demonstrate a level of variability typically above the targeted uncertainty levels stipulated by the WMO and GCOS for satellite product validation. Further instrument calibration of TLS and improved DHP image capture and processing methods are expected to reduce these uncertainties.

Native grasslands are an important forage resource for the cattle industry and play a vital role in hydrological, carbon, and nutrient cycles; energy flow; faunal and floral biodiversity; and recreational services. Despite their importance, information on the health of Canada's native grasslands is extremely limited. This study investigated the use of functional relationships, namely, differences in the Normalized Difference Vegetation Index (NDVI) and a shortwave infrared index (SWIR75 or CAI) related to cellulose and lignin content, along with spectral mixture analysis (SMA), to derive estimates of broad categories of grassland ground cover at 4 test sites established in the mixed prairie grassland in southern Alberta, Canada. Field campaigns were carried out in 2009 and 2010, at peak grass production, to collect fractional ground cover of photosynthetic vegetation (fPV), nonphotosynthetic vegetation (fNPV), and background (fB), as well as ground spectra of various grassland components. The ab...

Understanding of the surface energetic aspects of the spontaneously deposited proteins on biomaterial surfaces and how this influences cell adhesion and differentiation is an area of regenerative medicine that has not received adequate attention. Current controversies surround the role of the biomaterial substratum surface chemistry, the range of influence of said substratum, and the effects of different surface energy components of the protein interface. Endothelial cells (ECs) are a highly important cell type for regenerative medicine applications, such as tissue engineering, and In-vivo they interact with collagen I based stromal tissue and basement membranes producing different behavioral outcomes. The surface energetic properties of these tissue types and how they control EC behavior is not well known. In this work we studied the surface energetic properties of collagen I and Matrigel

Within the context of climate change, it is of utmost importance to quantify the stability of ecosystems with respect to climate anomalies. It is well acknowledged that ecosystem stability may change over time. As these temporal stability changes may provide a warning for increased vulnerability of the system, this study provides a methodology to quantify and assess these temporal changes in vegetation stability. Within this framework, vegetation stability changes were quantified over Australia from 1982 to 2006 using GIMMS NDVI and climate time series (i.e., SPEI (Standardized Precipitation and Evaporation Index)). Starting from a stability assessment on the complete time series, we aim to assess: (i) the magnitude and direction of stability changes; and (ii) the similarity in these changes for different stability metrics, i.e., the standard deviation of the NDVI anomaly (SD), auto-correlation at lag one of the NDVI anomaly (AC) and the correlation of NDVI anomaly with SPEI (CS). Results show high variability in magnitude and direction for the different stability metrics. Large areas and types of Australian vegetation showed an increase in variability (SD) over time; however, vegetation memory (AC) decreased. The association of NDVI anomalies with drought events (CS) showed a mixed response: the association increased in the western part, while it decreased in the eastern part. This methodology shows the potential for quantifying vegetation responses to major climate shifts and land use change, but results could be enhanced with higher resolution time series data.