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At least 325 records · Page 18

An Automated Two‐dimensional Pairwise form Registration Method for Pair‐matching of Fragmented Skeletal Remains

Abstract This study introduces an automated pairwise method for osteological pair‐matching of fragmented skeletal remains using two‐dimensional fragmented outlines extracted from photographs. The form data are used in pairwise iterative closest point registrations with rigid transformations. A modified version of the average Hausdorff distance is calculated to remove any coordinate correspondences with outline fracture margins, which allow the distance analysis of fragmented outlines. A dilation modification to the Hausdorff distance is proposed creating a greater separation between true‐ and false‐pairs. The sample consists of 122 calcanei (61 pairs) from the UI ‐Stanford collection. Performance statistics are provided for simulated fragmented and complete assemblages. Results indicate up to 98% accuracy for fragmented and complete assemblages. The dilated Hausdorff distance performed similarly across assemblages, but showed a slight decrease in performance for the complete assemblage. This approach provides a useful short listing tool to reduce the number of visual comparisons required in large commingled assemblages.

Lynch, Jeffrey James↗

Subcellular Feature-Based Classification of α and β Cells Using Soft X-ray Tomography

The dysfunction of α and β cells in pancreatic islets can lead to diabetes. Many questions remain on the subcellular organization of islet cells during the progression of disease. Existing three-dimensional cellular mapping approaches face challenges such as time-intensive sample sectioning and subjective cellular identification. To address these challenges, we have developed a subcellular feature-based classification approach, which allows us to identify α and β cells and quantify their subcellular structural characteristics using soft X-ray tomography (SXT). We observed significant differences in whole-cell morphological and organelle statistics between the two cell types. Additionally, we characterize subtle biophysical differences between individual insulin and glucagon vesicles by analyzing vesicle size and molecular density distributions, which were not previously possible using other methods. These sub-vesicular parameters enable us to predict cell types systematically using supervised machine learning. We also visualize distinct vesicle and cell subtypes using Uniform Manifold Approximation and Projection (UMAP) embeddings, which provides us with an innovative approach to explore structural heterogeneity in islet cells. This methodology presents an innovative approach for tracking biologically meaningful heterogeneity in cells that can be applied to any cellular system.

3D cell mapping↗

Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity

Here, we present Brain Modulyzer, an interactive visual exploration tool for functional magnetic resonance imaging (fMRI) brain scans, aimed at analyzing the correlation between different brain regions when resting or when performing mental tasks. Brain Modulyzer combines multiple coordinated views—such as heat maps, node link diagrams, and anatomical views—using brushing and linking to provide an anatomical context for brain connectivity data. Integrating methods from graph theory and analysis, e.g., community detection and derived graph measures, makes it possible to explore the modular and hierarchical organization of functional brain networks. Providing immediate feedback by displaying analysis results instantaneously while changing parameters gives neuroscientists a powerful means to comprehend complex brain structure more effectively and efficiently and supports forming hypotheses that can then be validated via statistical analysis. In order to demonstrate the utility of our tool, we also present two case studies—exploring progressive supranuclear palsy, as well as memory encoding and retrieval

59 BASIC BIOLOGICAL SCIENCES↗

The Role of a Curved Electrode with Controllable Direction in the Radiofrequency Ablation of Liver Tumors Behind Large Vessels

Purpose: To investigate the role of a novel curved radiofrequency ablation (RFA) electrode with controllable direction in the ablation of tumors behind large hepatic vessels in ex vivo bovine and in vivo canine liver experiments. Materials and Methods: Approval from the institutional animal care and use committee was obtained. In ex vivo experiments, conventional multi-tines expandable electrodes, conventional monopolar straight electrodes and novel curved electrodes were used in the ablation of the bovine liver (n = 90). The ablated area, parallel axis, vertical axis and shape of different electrodes were compared. Then, 24 beagle dogs (10 months old, female) were used for in vivo experiments. Visual tumor targets deeply located in the portal vein were established, and ultrasound-guided liver ablation was performed with different electrodes. The ablation range, target coverage rate, percentage of normal tissue injury and damage to adjacent vessels were evaluated. The Kruskal–Wallis test and the Chi-squared test were used for statistical analysis. Results: For the ex vivo study with a 3-cm electrode, the ablation area of the multi-tines expandable electrode group (7.14 ± 0.16 cm{sup 2}) was significantly larger than that of the novel curved electrode group (5.01 ± 0.30 cm{sup 2}, P < 0.001) and the monopolar straight electrode group (5.43 ± 0.15 cm{sup 2}, P < 0.001). The results obtained with the 4-cm electrode in the three groups were in accordance with those of the 3-cm electrode. In vivo, the normal tissue damage area of the novel curved electrode group was smaller than that of the multi-tines expandable electrode group (1.10 ± 0.18 cm{sup 2} vs. 4.00 ± 0.18 cm{sup 2}, P < 0.001). The target coverage rate of the novel curved electrode group was better than that of the monopolar straight electrode group (100% vs. 80.86 ± 1.68%, P < 0.001). The hematoxylin and eosin (H&E) and TUNEL staining results showed that the ablation necrosis area was adjacent to large vessels, but the vascular wall was not significantly damaged in the novel curved electrode group. Conclusion: Our preliminary results showed that the novel curved RFA electrode with controllable direction could achieve accurate ablation for tumors behind large hepatic vessels, with a better target coverage rate and less damage to normal tissue, than conventional multi-tines expandable electrodes and monopolar straight electrodes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Mapping Multivariate Influence of Alloying Elements on Creep Behavior for Design of New Martensitic Steels

Here, heritage data for the class of 9 to 12 wt pct Cr steels are studied using data science to quantify the statistically significant relationships among multiple processing/microstructure and performance variables. The effort is undertaken to find new martensitic steels for creep life of 10 5 hours or greater at 650 °C and 100 MPa using machine learning. Linear regression and lasso regression were utilized to identify alloying elements that contribute towards better creep strength. Visualization techniques such as t-distributed stochastic neighbor embedding and pair-wire element specific comparisons were utilized to explore information gaps that exist within the data and are in conflict with existing domain knowledge. Lastly, cfombining all results suggest that the next alloy design to be explored should be 9 wt pct Cr with high W (2 to 3 wt pct) and high Co (2 to 3 wt pct) for creep life of 10 5 hours or greater at 650 °C, 100 MPa.

36 MATERIALS SCIENCE↗

SU-E-I-51: Use of Blade Sequences in Cervical Spine MR Imaging for Eliminating Motion, Truncation and Flow Artifacts

Purpose: To assess the efficacy of the BLADE technique to eliminate motion, truncation, flow and other artifacts in Cervical Spine MRI compared to the conventional technique. To study the ability of the examined sequences to reduce the indetention and wrap artifacts, which have been reported in BLADE sagittal sequences. Methods: Forty consecutive subjects, who had been routinely scanned for cervical spine examination using four different image acquisition techniques, were analyzed. More specifically, the following pairs of sequences were compared: a) T2 TSE SAG vs. T2 TSE SAG BLADE and b) T2 TIRM SAG vs. T2 TIRM SAG BLADE. A quantitative analysis was performed using the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and relative contrast (ReCon) measures. A qualitative analysis was also performed by two radiologists, who graded seven image characteristics on a 5-point scale (0:non-visualization; 1:poor; 2:average; 3:good; 4:excellent). The observers also evaluated the presence of image artifacts (motion, truncation, flow, indentation). Results: Based on the findings of the quantitative analysis, the ReCON values of the CSF (cerebrospinal fluid)/SC (spinal cord) between TIRM SAG and TIRM SAG BLADE were found to present statistical significant differences (p<0.001). Regarding motion and truncation artifacts, the T2 TSE SAG BLADE was superior compared to the T2 TSE SAG and the T2 TIRM SAG BLADE was superior compared to the T2 TIRM SAG. Regarding flow artifacts, T2 TIRM SAG BLADE eliminated more artifacts compared to the T2 TIRM SAG. Conclusion: The use of BLADE sequences in cervical spine MR examinations appears to be capable of potentially eliminating motion, pulsatile flow and trancation artifacts. Furthermore, BLADE sequences are proposed to be used in the standard examination protocols based on the fact that a significantly improved image quality could be achieved.

60 APPLIED LIFE SCIENCES↗

Outcomes of Iodine-125 Plaque Brachytherapy for Uveal Melanoma With Intraoperative Ultrasonography and Supplemental Transpupillary Thermotherapy

Purpose: To assess the impact on local tumor control of intraoperative ultrasonographic plaque visualization and selective application of transpupillary thermotherapy (TTT) in the treatment of posterior uveal melanoma with iodine-125 (I-125) episcleral plaque brachytherapy (EPB). Methods and Materials: Retrospective analysis of 526 patients treated with I-125 EPB for posterior uveal melanoma. Clinical features, dosimetric parameters, TTT treatments, and local tumor control outcomes were recorded. Statistical analysis was performed using Cox proportional hazards and Kaplan-Meier life table method. Results: The study included 270 men (51%) and 256 women (49%), with a median age of 63 years (mean, 62 years; range, 16-91 years). Median dose to the tumor apex was 94.4 Gy (mean, 97.8; range, 43.9-183.9) and to the tumor base was 257.9 Gy (mean, 275.6; range, 124.2-729.8). Plaque tilt >1 mm away from the sclera at plaque removal was detected in 142 cases (27%). Supplemental TTT was performed in 72 patients (13.7%). One or 2 TTT sessions were required in 71 TTT cases (98.6%). After a median follow-up of 45.9 months (mean, 53.4 months; range, 6-175 months), local tumor recurrence was detected in 19 patients (3.6%). Local tumor recurrence was associated with lower dose to the tumor base (P=.02). Conclusions: Ultrasound-guided plaque localization of I-125 EPB is associated with excellent local tumor control. Detection of plaque tilt by ultrasonography at plaque removal allows supplemental TTT to be used in patients at potentially higher risk for local recurrence while sparing the majority of patients who are at low risk. Most patients require only 1 or 2 TTT sessions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

ARE THE FAINT STRUCTURES AHEAD OF SOLAR CORONAL MASS EJECTIONS REAL SIGNATURES OF DRIVEN SHOCKS?

Recently, several studies have assumed that the faint structures ahead of coronal mass ejections (CMEs) are caused by CME-driven shocks. In this study, we have conducted a statistical investigation to determine whether or not the appearance of such faint structures depends on CME speeds. For this purpose, we use 127 Solar and Heliospheric Observatory/Large Angle Spectroscopic COronagraph (LASCO) front-side halo (partial and full) CMEs near the limb from 1997 to 2011. We classify these CMEs into two groups by visual inspection of CMEs in the LASCO-C2 field of view: Group 1 has the faint structure ahead of a CME and Group 2 does not have such a structure. We find the following results. (1) Eighty-seven CMEs belong to Group 1 and 40 CMEs belong to Group 2. (2) Group 1 events have much higher speeds (average = 1230 km s{sup –1} and median = 1199 km s{sup –1}) than Group 2 events (average = 598 km s{sup –1} and median = 518 km s{sup –1}). (3) The fraction of CMEs with faint structures strongly depends on CME speeds (V): 0.93 (50/54) for fast CMEs with V ≥ 1000 km s{sup –1}, 0.65 (34/52) for intermediate CMEs with 500 km s{sup –1} ≤ V < 1000 km s{sup –1}, and 0.14 (3/21) for slow CMEs with V < 500 km s{sup –1}. We also find that the fraction of CMEs with deca-hecto metric type II radio bursts is consistent with the above tendency. Our results indicate that the observed faint structures ahead of fast CMEs are most likely an enhanced density manifestation of CME-driven shocks.

79 ASTRONOMY AND ASTROPHYSICS↗

Data Agnostic Feature-Target Analysis & Ranking Machine Learning Pipeline (DAFTAR-ML) v0.1.0

DAFTAR-ML is a specialized machine-learning pipeline that identifies relevant features based on their relationship to a target variable. Many ML pipelines focus solely on prediction, and feature ranking is often absent or lacks robust statistical methods. DAFTAR-ML performs its tasks with this outcome in mind. Model training is robust, using nested cross-validation and hyperparameter tuning. Instead of relying on native feature-importance scores, it employs SHAP (SHapley Additive exPlanations) to quantify feature importance. The pipeline also produces comprehensive results, including publication-quality visualizations.

Melie, Tina [Lawrence Berkeley National Laboratory↗

Automated, high-accuracy classification of textured microstructures using a convolutional neural network

Crystallographic texture is an important descriptor of material properties but requires time-intensive electron backscatter diffraction (EBSD) for identifying grain orientations. While some metrics such as grain size or grain aspect ratio can distinguish textured microstructures from untextured microstructures after significant grain growth, such morphological differences are not always visually observable. This paper explores the use of deep learning to classify experimentally measured textured microstructures without knowledge of crystallographic orientation. A deep convolutional neural network is used to extract high-order morphological features from binary images to distinguish textured microstructures from untextured microstructures. The convolutional neural network results are compared with a statistical Kolmogorov–Smirnov tests with traditional morphological metrics for describing microstructures. Results show that the convolutional neural network achieves a significantly improved classification accuracy, particularly at early stages of grain growth, highlighting the capability of deep learning to identify the subtle morphological patterns resulting from texture. The results demonstrate the potential of a convolutional neural network as a tool for reliable and automated microstructure classification with minimal preprocessing.

36 MATERIALS SCIENCE↗

The Surface-Topography Challenge: A Multi-Laboratory Benchmark Study to Advance the Characterization of Topography

Surface performance is critically influenced by topography in virtually all real-world applications. The current standard practice is to describe topography using one of a few industry-standard parameters. The most commonly reported number is Ra, the average absolute deviation of the height from the mean line (at some, not necessarily known or specified, lateral length scale). However, other parameters, particularly those that are scale-dependent, influence surface and interfacial properties; for example the local surface slope is critical for visual appearance, friction, and wear. The present Surface-Topography Challenge was launched to raise awareness for the need of a multi-scale description, but also to assess the reliability of different metrology techniques. In the resulting international collaborative effort, 153 scientists and engineers from 64 research groups and companies across 20 countries characterized statistically equivalent samples from two different surfaces: a “rough” and a “smooth” surface. The results of the 2088 measurements constitute the most comprehensive surface description ever compiled. We find wide disagreement across measurements and techniques when the lateral scale of the measurement is ignored. Consensus is established through scale-dependent parameters while removing data that violates an established resolution criterion and deviates from the majority measurements at each length scale. Our findings suggest best practices for characterizing and specifying topography. The public release of the accumulated data and presented analyses enables global reuse for further scientific investigation and benchmarking.

42 ENGINEERING↗

Unexpected series of regular frequency spacing of δ Scuti stars in the non-asymptotic regime - I. The methodology

In this study, a sequence search method was developed to search the regular frequency spacing in δ Scuti stars through visual inspection and an algorithmic search. We searched for sequences of quasi-equally spaced frequencies, containing at least four members per sequence, in 90 δ Scuti stars observed by CoRoT. We found an unexpectedly large number of independent series of regular frequency spacing in 77 δ Scuti stars (from one to eight sequences) in the non-asymptotic regime. We introduce the sequence search method presenting the sequences and echelle diagram of CoRoT 102675756 and the structure of the algorithmic search. Four sequences (echelle ridges) were found in the 5–21 d –1 region where the pairs of the sequences are shifted (between 0.5 and 0.59 d –1 ) by twice the value of the estimated rotational splitting frequency (0.269 d –1 ). The general conclusions for the whole sample are also presented in this paper. The statistics of the spacings derived by the sequence search method, by FT (Fourier transform of the frequencies), and the statistics of the shifts are also compared. In many stars more than one almost equally valid spacing appeared. The model frequencies of FG Vir and their rotationally split components were used to formulate the possible explanation that one spacing is the large separation while the other is the sum of the large separation and the rotational frequency. In CoRoT 102675756, the two spacings (2.249 and 1.977 d –1 ) are in better agreement with the sum of a possible 1.710 d –1 large separation and two or one times, respectively, the value of the rotational frequency.

79 ASTRONOMY AND ASTROPHYSICS↗

Thermal Conductivity of AM Fabricated Stainless Steel 316L Part

Thermal properties are an integral part of many diverse engineering applications, and additive manufacturing (AM), particularly laser powder bed fusion (LPBF) is shown to affect thermal properties due to the laser processing parameters. For 316L stainless steel, there is little prior research to determine the effects of the process on thermal properties. In this work, the temperature gradient is shown to create uniform, chess board-like distributions of grains in the build direction. These zones create dislocations which were visualized with EBSD techniques. Processing parameters cause hierarchal grain size distribution, with localized concentrations of small grains and large grains. Thermomechanical stresses in the rapid solidification increases dislocation density during grain formation. Previous research shows a higher density of dislocations decreases local thermal conductivity. Local and bulk thermal conductivity are shown in this work to have statistically lowered values to an average of 10-12 W/m-K compared to 14 W/m-K for conventional 316L.

36 MATERIALS SCIENCE↗

Neuroanatomical and cognitive correlates of visual hallucinations in Parkinson’s disease and dementia with Lewy bodies: Voxel-based morphometry and neuropsychological meta-analysis

Visual hallucinations (VH) are common in Parkinson's disease and dementia with Lewy bodies, two forms of Lewy body disease (LBD), but the neural substrates and mechanisms involved are still unclear. We conducted meta-analyses of voxel-based morphometry (VBM) and neuropsychological studies investigating the neuroanatomical and cognitive correlates of VH in LBD. For VBM (12 studies), we used Seed-based d Mapping with Permutation of Subject Images (SDM-PSI), including statistical parametric maps for 50% of the studies. For neuropsychology (35 studies), we used MetaNSUE to consider non-statistically significant unreported effects. VH were associated with smaller grey matter volume in occipital, frontal, occipitotemporal, and parietal areas (peak Hedges' g -0.34 to -0.49). In patients with Parkinson's disease without dementia, VH were associated with lower verbal immediate memory performance (Hedges' g -0.52). Both results survived correction for multiple comparisons. Here, abnormalities in these brain regions might reflect dysfunctions in brain networks sustaining visuoperceptive, attention, and executive abilities, with the latter also being at the basis of poor immediate memory performance.

60 APPLIED LIFE SCIENCES↗

WE-E-18A-10: Comparison of Patient Dose and Vessel Visibility Between Antiscatter Grid Removal and Lower Angiographic Radiation Dose Settings for Pediatric Imaging: A Preclinical Investigation

Purpose: To define an alternative to antiscatter grid (ASG) removal in angiographic systems which achieves similar patient dose reduction as ASG removal without degrading image quality during pediatric imaging. Methods: This study was approved by the local institution animal care and use committee (IACUC). Six different digital subtraction angiography settings were evaluated that altered the mAs, (100, 70, 50, 35, 25, 17.5% of reference mAs) with and without ASG. Three pigs of 5, 15, and 20 kg (9, 15, and 17 cm abdominal thickness; smaller than a newborn, average 3 yr old, and average 10 year old human abdomen respectively) were imaged using the six dose settings with and without ASG. Image quality was defined as the order of vessel branch that is visible relative to the injected vessel. Five interventional radiologists evaluated all images. Image quality and patient dose were statistically compared using analysis of variance and receiver operating curve (ROC) analysis to define the preferred dose level and use of ASG for a minimum visibility of 2nd or 3rd order branches of vessel visibility. Results: ASG grid removal reduces dose by 26% with reduced image quality. Only with the ASG present can 3rd order branches be visualized; 100% mAs is required for 9 cm pig while 70% mAs is adequate for the larger pigs. 2nd order branches can be visualized with ASG at 17.5% mAs for all three pig sizes. Without the ASG, 50%, 35% and 35% mAs is required for smallest to largest pig. Conclusion: Removing ASG reduces patient dose and image quality. Image quality can be improved with the ASG present while further reducing patient dose if an optimized radiographic technique is used. Rami Nachabe is an employee of Philips Health Care; Keith Strauss is a paid consultant of Philips Health Care.

60 APPLIED LIFE SCIENCES↗

Analytics for Investigation of Disease Outbreaks: Web-Based Analytics Facilitating Situational Awareness in Unfolding Disease Outbreaks

Background: Information from historical infectious disease outbreaks provides real-world data about outbreaks and their impacts on affected populations. These data can be used to develop a picture of an unfolding outbreak in its early stages, when incoming information is sparse and isolated, to identify effective control measures and guide their implementation. Objective: This study aimed to develop a publicly accessible Web-based visual analytic called Analytics for the Investigation of Disease Outbreaks (AIDO) that uses historical disease outbreak information for decision support and situational awareness of an unfolding outbreak. Methods: We developed an algorithm to allow the matching of unfolding outbreak data to a representative library of historical outbreaks. This process provides epidemiological clues that facilitate a user’s understanding of an unfolding outbreak and facilitates informed decisions about mitigation actions. Disease-specific properties to build a complete picture of the unfolding event were identified through a data-driven approach. A method of analogs approach was used to develop a short-term forecasting feature in the analytic. The 4 major steps involved in developing this tool were (1) collection of historic outbreak data and preparation of the representative library, (2) development of AIDO algorithms, (3) development of user interface and associated visuals, and (4) verification and validation. Results: The tool currently includes representative historical outbreaks for 39 infectious diseases with over 600 diverse outbreaks. We identified 27 different properties categorized into 3 broad domains (population, location, and disease) that were used to evaluate outbreaks across all diseases for their effect on case count and duration of an outbreak. Statistical analyses revealed disease-specific properties from this set that were included in the disease-specific similarity algorithm. Although there were some similarities across diseases, we found that statistically important properties tend to vary, even between similar diseases. This may be because of our emphasis on including diverse representative outbreak presentations in our libraries. AIDO algorithm evaluations (similarity algorithm and short-term forecasting) were conducted using 4 case studies and we have shown details for the Q fever outbreak in Bilbao, Spain (2014), using data from the early stages of the outbreak. Using data from only the initial 2 weeks, AIDO identified historical outbreaks that were very similar in terms of their epidemiological picture (case count, duration, source of exposure, and urban setting). The short-term forecasting algorithm accurately predicted case count and duration for the unfolding outbreak. Conclusions: AIDO is a decision support tool that facilitates increased situational awareness during an unfolding outbreak and enables informed decisions on mitigation strategies. AIDO analytics are available to epidemiologists across the globe with access to internet, at no cost. In this study, we presented a new approach to applying historical outbreak data to provide actionable information during the early stages of an unfolding infectious disease outbreak.

59 BASIC BIOLOGICAL SCIENCES↗

Addressing Two-Phase Flow Maldistribution in Microchannel Heat and Mass Exchangers

Multiphase flow phenomena in single micro and minichannels have been widely studied. Characteristics of two-phase flow through a large array of microchannels are investigated here. An air–water mixture is used to represent the two phases flowing through a microchannel array representative of those employed in practical applications. Flow distribution of the air and water flow across 52 parallel microchannels of 0.4 mm hydraulic diameter is visually investigated using high-speed photography. Two microchannel configurations are studied and compared, with mixing features incorporated into the second configuration. Slug and annular flow regimes are observed in the channels. Void fractions and interfacial areas are calculated for each channel from these observations. The flow distribution is tracked at various lengths along the microchannel array sheets. Statistical distributions of void fraction and interfacial area along the microchannel array are measured. The design with mixing features yields improved flow distribution. Void fraction and interfacial area change along the length of the second configuration, indicating a change in fluid distribution among the channels. The void fraction and interfacial area results are used to predict the performance of different microchannel array configurations for heat and mass transfer applications. Results from this study can help inform the design of compact thermal-fluid energy systems.

Engineering↗

Visualizing feedstock siting in biomass production: Tradeoffs between economic and water quality objectives

New domestic, renewable energy resources must be considered to increase energy security in the U.S. Ethanol production through second-generation (cellulosic) feedstocks will help the U.S. meet the legislative Renewable Fuel Standard, which mandates 36 billion gallons of renewable fuels by 2022. Yet, conversion of cropland to meet the cellulosic feedstock production goals may have unforeseen environmental consequences. Here, using Soil Water Assessment Tool (SWAT) outputs and National Agricultural Statistics Service (USDA NASS) economic data, we conducted a spatial optimization of bioenergy feedstock introduction into the Arkansas White-Red River Basin based on water quality and economic objectives, subject to constraints on total land conversion. Results displayed tradeoffs between bioenergy yield for three crops (switchgrass, sorghum and poplar) and land rent objectives. Optimal solutions tended to prioritize conversion of land in eastern AWR subbasins where yield and water quality objective improvements were greatest. A small number of subbasins contributed to basin-wide water quality improvements, whereas subbasins contributing to economic benefits were more spatially dispersed, indicating that water quality responses are more likely to constrain feedstock placement. Biomass production targets can be met vianumerous spatial arrangements, whereas marginal improvement in water quality objectives can best be achieved by selectively siting perennial feedstocks in the eastern half of the region.

09 BIOMASS FUELS↗