Scaling Model Research Articles

Application of MK trend and test of Sen's slope estimator to measure impact of climate change on the adoption of conservation agriculture in Ethiopia

AbstractThe objective of this study is to identify the adoption level of this agricultural technology affected by climate change and to confirm the relationship with conservation agriculture. The assessment was carried out using the Mann–Kendall trend test and the Sen's slope is used. The collected data were statistically analyzed by Statistical Down Scaling Model Software to compare the observed and climate model scenarios of temperature and precipitation. According to the results of the study, earth analysis of the 2001–2021 data revealed that 26.68% of the land area has improved productivity, 67.38% of the territory is stable, 5.93% of the area has degraded productivity, and 0.02% of the area has no productivity data. The study result indicated that there is variability, a decrease in rainfall, and a rise in temperature in the area. The Mann–Kendall and Sen's slope test findings for the total maximum annual rainfall reveal a P-value of 0.307, indicating that there is no pattern in the series or variability of rainfall and that there is a diminishing trend in the rainfall data. The study's findings may help decision-makers and water managers provide more sustainable strategies and methods for managing water resources.

How does searching for faces among similar-looking distractors affect distractor memory?

Prior research has shown that searching for multiple targets in a visual search task enhances distractor memory in a subsequent recognition test. Three non-mutually exclusive accounts have been offered to explain this phenomenon. The mental comparison hypothesis states that searching for multiple targets requires participants to make more mental comparisons between the targets and the distractors, which enhances distractor memory. The attention allocation hypothesis states that participants allocate more attention to distractors because a multiple-target search cue leads them to expect a more difficult search. Finally, the partial match hypothesis states that searching for multiple targets increases the amount of featural overlap between targets and distractors, which necessitates greater attention in order to reject each distractor. In two experiments, we examined these hypotheses by manipulating visual working memory (VWM) load and target-distractor similarity of AI-generated faces in a visual search (i.e., RSVP) task. Distractor similarity was manipulated using a multidimensional scaling model constructed from facial landmarks and other metadata of each face. In both experiments, distractors from multiple-target searches were recognized better than distractors from single-target searches. Experiment 2 additionally revealed that increased target-distractor similarity during search improved distractor recognition memory, consistent with the partial match hypothesis.

Nucleation-Growth Versus Spinodal Decomposition in Fe-Cr Alloys: An Experimental Verification by Atom Probe Tomography and Small Angle Neutron Scattering.

Identifying the operative mode of phase separation [spinodal decomposition (SD) or nucleation-growth (NG)] remains an extremely important area of research. The present work examines this critically in the Fe-Cr system using atom probe tomography (APT) and small angle neutron scattering (SANS), and establishes the framework to distinguish the two different modes of α' phase separation in thermally aged Fe-35 at% Cr and Fe-20 at% Cr alloys. Independent APT analysis determines the mode of phase separation on the basis of (i) the presence/absence of periodic chemical fluctuation through radial distribution function analysis and (ii) interphase interface characteristics (diffuse/sharp). SANS analysis, in contrast, yields virtually indistinguishable correlation peaks for both the modes, which necessitates further investigation of the several different aspects of SANS profiles in the light of APT results. For the first time, key features of SANS profiles have been identified that can unambiguously distinguish SD from NG in the Fe-Cr system: (i) nature of temporal evolution of FWHM of the correlation peak and (ii) appropriate value of γ for fitting with the dynamic scaling model (γ = 6 for SD, Fe-35 at% Cr alloy; γ = 4 for NG, Fe-20 at% Cr alloy).

Deformation Driven Deswelling of Brush Gels

We studied equilibrium swelling in brush gels undergoing large uniaxial deformations in contact with solvent by using a combination of the Flory–Rehner and scaling models of gels and coarse-grained molecular dynamics simulations of swollen brush networks. Our analysis showed that the swelling ratio of the brush gels Qeq(λ), describing the volume change upon swelling, is a nonmonotonic function of the gel uniaxial deformation ratio λ characterizing the gel shape. It first increases with increasing strand elongation from its value for the free-standing gel then begins to decrease. This behavior is a result of the optimization of polymer/solvent interactions and conformational entropy of brush strands in the nonlinear deformation regime. The location of the maximum in the Qeq(λ) function is directly related to the value of the strain-stiffening parameter β. This parameter depends on the degree of polymerization of the brush backbone and the backbone Kuhn length defined by both the grafting density and degree of polymerization of the side chains. Analysis of the nonlinear gel modulus confirmed that the strain-stiffening parameter β is identical in both dry networks and gels. However, the structural modulus of the gels, Gs, is smaller than that of the dry networks, Gdr, by a factor equal to the ratio of the Kuhn length of brush strands in the dry state, bK, and in the gel, bK,s, such that Gs = GdrbK/bK,s.

Improved milling stability analysis for chatter-free machining parameters planning using a multi-fidelity surrogate model and transfer learning with limited experimental data

Decision-making on chatter-free machining parameters is essential for process planning since chatter significantly affects production quality and efficiency. Stability lobe diagram (SLD) is commonly used for selecting chatter-free machining parameters, but its analytical prediction often has poor accuracy and experiment-based prediction is time-consuming. This paper proposes a multi-fidelity (MF) surrogate model and transfer learning-based method to improve the milling stability analysis. Firstly, an analytical stability model is constructed to predict low-fidelity (LF) SLDs for key combinations of radial cutting width (a e) and feed rate per tooth (ft ). A few spindle speeds (n s) are selected from each key LF SLD to detect high-fidelity (HF) stability limits (ap lim) through milling experiments. Subsequently, sufficient LF and limited HF combinations of n s, a e, ft , and ap lim are taken to construct additive scaling function-based MF stability models. Predicted MF combinations of n s, a e, ft , and ap lim are combined with limited HF combinations to construct more accurate stability models through transfer learning. Then, a neural network is ultimately trained to predict ap lim values for arbitrary combinations of n s, a e, and ft . A detailed experimental validation indicates that the proposed method can provide more accurate lobe boundaries for machining parameters selection by introducing fewer experimental samples.

Numerical investigation on hydrodynamic performance of a pre-swirl stator pump-jet propulsor with special emphasis on energy loss mechanism

The objective of this paper is to evaluate the hydrodynamic performance of the newly developed pre-swirl stator pump-jet propulsor (PJP) and to investigate its underlying flow characteristics and energy loss mechanisms. Numerical simulations are carried out for the scaling model of the PJP, the experimental tests are also performed to verify the numerical simulation results. The energy balance equation is loaded to investigate the energy loss combining with vortex structures. The numerical results show a reasonable agreement with the available experiments. The stator performs well for generating pre-swirl flow with tangential velocity, which could be effectively absorbed by the rotating rotor to varying levels under different operating conditions. The stator-rotor interaction flow is complicated and causes obvious non-uniformity for the flow field due to the generation of trailing vortices. The energy losses within the PJP are well quantified and visualized by different loss terms in energy balance equation. The production of turbulent kinetic energy and then dissipates due to viscous effects is the leading cause for energy loss, which originates from vortex evolutions and impact loss without considering the friction loss. The generation of tip leakage vortex dominates the energy loss in the rotor domain and wake field of PJP.

Diffusion of surfactant from a micellar solution to a bare interface. 1. Absorbing boundary

We analyze dynamic adsorption of surfactant from a micellar solution to a rapidly created surface that acts as an absorbing boundary for surfactant monomers (single molecules), along which the monomer concentration vanishes, with no direct micelle adsorption. This somewhat idealized situation is analyzed as a prototype for situations in which strong suppression of monomer concentration accelerates micelle dissociation, and will be used as a starting point for analysis of more realistic boundary conditions in subsequent work. We present scaling arguments and approximate models for particular time and parameter regimes and compare the resulting predictions to numerical simulations of the reaction–diffusion equations for a polydisperse system containing surfactant monomers and clusters of arbitrary aggregation number. The model considered here exhibits an initial period of rapid shrinkage and ultimate dissociation of micelles within a narrow region near the interface. This opens a micelle-free region near the interface after some time τe, the width of which increases as t1/2 at times t≫τe. In systems that exhibit disparate fast and slow bulk relaxation times τ1 and τ2 in response to small perturbations, τe is usually comparable to or greater than τ1 but much less than τ2. Such systems exhibit a wide intermediate time regime τe<t<τ2 in which the remaining micellar region reaches a state of partial local equilibrium, followed by a final stage t≫τ2 in which full local equilibrium is established.

Microscopic foundation of the μ(I) rheology for dense granular flows on inclined planes

Macroscopic and microscopic properties of dense granular layers flowing down inclined planes are obtained from Discrete-Element-Method simulations for both frictionless and frictional grains. Three fundamental observations for dense granular flows are recovered, namely the occurrence of a critical stress, the Bagnold velocity profile, as well as well-defined friction and dilatancy laws. The microscopic aspects of the grain motion highlight the formation of transient clusters. From this microscopic picture, we derive a theoretical scaling model without any empirical input that explains quantitatively the fundamental laws of dense granular flows in incline plane and shear geometries. The adequacy between the model and the observed results suggests that granular flows can be viewed as flows from thermal fluids of hard spheres.

Structural modifications, optical response, and electrical conductivity mechanism of Bi2O3 doped in P2O5–V2O5–MoO3 nanocomposite glass systems

Structural, optical and electrical conductivity mechanism of four compositional series of xBi2O3-(1-x)(0.30P2O5–0.35V2O5–0.35MoO3) [x = 0.05, 0.15, 0.25, and 0.35] have been investigated. XRD pattern affirms the existence of nanocrystallites in the glassy network, which affects the structural, optical and electrical alterations. The structural variation leads to an increase in the density of all the glassy systems. The FTIR analysis reveals the shift of different band positions suggesting structural alterations. The electrical conductivity investigation reveals the decreasing values of ac and dc activation energy, which enhances the ac and dc conductivity. The validity of Mott's VRH model has been examined and the value of hopping energy has been estimated. The obtained DC conductivity spectra of all samples have been fitted with Greaves's model. The AC conductivity scaling model of Pan and Ghosh has been used to demonstrate the electrical conduction relaxation method. In the spectroscopic investigation, by deploying the Tauc's plot, the optical band gap energies of the studied glass compositions are estimated. The calculation of Urbach energy values allows us to estimate the disorders of glassy nanocomposites. Different spectroscopic parameters like refractive index, polarizability, reflection factor, and reflectivity have been studied.

Scaling of Floods With Geomorphologic Characteristics and Precipitation Variability Across the Conterminous United States

AbstractAccurate flood risk assessment requires a comprehensive understanding of flood sensitivity to regional drivers and climate factors. This paper presents the scaling of floods (duration, peak, volume) with geomorphologic characteristics of the basin (i.e., drainage area, slope, elevation) and precipitation patterns (rainfall accumulation, variability). Long‐term daily streamflow observations over the 20th and early 21st centuries from Hydro‐Climatic Data Network streamgages across the conterminous United States are used to create a flood event database based on their flood stage information. Antecedent daily rainfall accumulation and variability corresponding to these floods are computed using Global Historical Climatology Network daily data set. Two Bayesian scaling models are developed, and the spatial organization of scaling exponents is investigated. The baseline model quantifies the scaling of floods to geomorphologic characteristics. The dynamic model quantifies the scaling of floods to antecedent precipitation distribution which is further conditioned on geomorphologic characteristics. Results show that small and low‐elevation basins have a stronger response to antecedent rainfall distribution in amplifying flood peaks, while high‐elevation steeper basins have a lower response for flood duration and volume. The dynamic models demonstrate that there are significant variations in the flood scaling rates, with the largest rates up to 40% and 4.5% for flood duration, 64% and 44% for peak, and 98% and 40% for volume found across the Northeast, Coastal Southeast, and Northwest with intensifying rainfall accumulation and variability, respectively. This study advances flood predictions by better informing the flood attributes in the context of dynamical land‐atmosphere perturbations.

Analytical model of critical buckling transition for smectic liquid crystal based on the viscoelastic scaling of coarse-grained molecular dynamics.

The buckling transition of smectic liquid crystals (LCs) is important not only as fundamental physics but also for the rational design of devices to make use of their optical and mechanical properties. However, there exists a huge gap between the specific knowledge and universal analytical formulation. We have conducted coarse-grained molecular dynamics (CGMD) simulations with the force field optimized for the description of buckling phenomena including topological defects to link the molecular nature and continuum formulation. The simulations reveal the viscoelastic characteristics where the critical strain and the compression modulus highly depend on the strain rate as well as the number of layers. Therefore, we formulate the scaling model whose coupling constants depend on both strain rate and domain size. The model reproduces the CGMD results as well as experimental and theoretical values in existing literature. Furthermore, we elucidate from this model that the critical buckling behavior is determined by the competition between the suppression of compression-induced flow and the undulation fluctuation of layers. The framework consisting of the CGMD simulation and the scaling model enables us to estimate the buckling characteristics of smectic LCs reflecting their molecular structures in a wide range from the low-frequency regime that can be verified by experiments to the high-frequency regime beyond the reach of it.

Universal scaling theory of electrochemical immunosensors: An analytical approach to define and compare performance metrics

Electrochemical immunosensors have emerged as a versatile, sensitive, and selective sensor technology of choice for a variety of applications, including detection of proteins, food pathogens, bacteria, viruses, and cancerous molecules. The combination of highly specific biorecognition elements and electrical readout systems facilitates the detection of antigens down to femtomolar concentrations. However, a lack of quantitative theoretical framework has made the design, optimization, and comparison of sensors difficult, without a clear and definitive understanding of the limits of detection, dynamic range, and sensitivity. In this paper, we integrate reaction-diffusion and effective media theories to derive a generalized scaling model for an arbitrary immunosensor that relates the relative change of redox current to the corresponding change in antigen concentration, through scaling exponents related to the geometry of biomolecules diffusion and the measurement resolution. Experimental data from dozens of immunosensors (for a variety of antigens, material systems, and sensor geometry) validate our sensor-agnostic scaling formula. Our results would allow cross-calibration of the emerging and traditional immunosensors reported across the literature and define a physics-based, standardized methodology to compare performance metrics, such as limits of detection, dynamic range, and sensitivity.

The scalings of the thermal energy confinement time in EAST H-mode plasmas

This paper describes scalings of the H-mode confinement database of neutral beam injection (NBI)-lower hybrid wave (LHW) and electron cyclotron resonant heating-LHW plasmas in the EAST tokamak. Fundamental information of the EAST H-mode database and the details of calculation of the thermal energy confinement time in EAST are presented. The result of the scaling model of the thermal energy confinement time in NBI-LHW plasmas with root-mean-square-error , compared with the multi-machine scaling model derived from the multi-machine database (mainly NBI heating) with , is obtained. The scaling presents a similar dependency on plasma current and power loss and a lower dependency on plasma density and elongation, but stronger dependency on toroidal field than in . The scaling demonstrates a similar dependency on plasma current and power loss and lower dependency on plasma density, but a negative dependency with large error bars on elongation compared with in NBI-LHW plasmas. The comparison of EAST models with the more recent multi-tokamak scaling ITPA20-IL shows a similar engineering dependency on plasma current, power loss and plasma density, but opposite dependency on toroidal field.

A simple scaling model for balling defect formation during laser powder bed fusion

Balling is one of the cornerstone defects in laser powder bed fusion of metals, leading to high porosity of the 3D printed parts and substantially deteriorating their performance. The transition to the balling mode is commonly identified through a series of trial-and-error experiments, an extremely inefficient approach. Here, we propose an outstandingly simple thermal scaling model for predicting the threshold from balling mode to conduction mode in laser powder bed fusion. The resulting balling criterion can be expressed as a dimensionless number which combines the material properties, the powder size and the pre-heating of the substrate. The model predictions are well in agreement with our validation experiments for three different materials (copper, bronze and steel). The applicability of the model assumptions is verified through a set of suitably designed multiphysics computational fluid dynamics simulations. The combination of first-hand experiments and simulations substantiates the balling model as a readily usable and reliable scaling criterion for establishing the minimum required power for laser powder bed fusion, applicable to different materials, as well as suggesting viable strategies to adjust the operating parameters towards the defect-free regime.

Time Domain Source Parameter Estimation of Natural and Man-Induced Microearthquakes at the Geysers Geothermal Field

Water injection in geothermal areas is the preferential strategy to sustain the natural production of geothermal resources. In this context, monitoring microearthquakes is a fundamental tool to track changes in the reservoirs in terms of soil composition, response to injections, and resource exploitation with space and time. Therefore, refined source characterization is crucial to better estimate the size, source mechanism, and rupture process of microearthquakes, as they are possibly related to industrial activities, and to identify any potential variation in the background seismicity. Standard approaches for source parameter estimation are ordinarily based on the modelling of Fourier displacement spectra and its characteristic parameters: the low-frequency spectral level and corner frequency. Here, we apply an innovative time domain technique that uses the curves of P-wave amplitude vs. time along the seismogram. This methodology allows estimation of seismic moment, source radius, and stress release from the plateau level and the corner time of the average logarithm of P-wave displacement versus time with the assumption of a triangular moment rate function, uniform rupture speed, and a constant/frequency-independent Q-factor. In the current paper, this time domain methodology is implemented on a selected catalog of microearthquakes consisting of 83 events with a moment magnitude ranging between 1.0 and 1.5 that occurred during a 7-year period (2007–2014) of fluid extraction/injection around Prati-9 and Prati-29 wells at The Geysers geothermal field. The results show that the time domain technique provides accurate seismic moment (moment magnitude) and rupture duration/radius estimates of microearthquakes down to the explored limit (M 1) while accounting for the anelastic attenuation effect in the radiated high-frequency wavefield. The retrieved source radius vs. moment scaling is consistent with a self-similar, constant stress drop scaling model, which proves an appropriate attenuation correction and the validity of the assumed, triangular moment rate function for microearthquake ruptures. Two alternative mechanical models are proposed to explain the observed difference (about two orders of magnitude) in the retrieved average stress release estimates between the time and frequency domain methods. We argue that the two quantities may not refer to the same physical quantity representing the stress release of earthquake ruptures. Either the smaller stress release values from the time domain method may indicate a larger fracture area (by a factor of 20) radiating the observed P-waveforms than the one estimated from the corner frequencies, or the frequency domain estimate is a proxy for dynamic stress release while the time domain is more representative of the static release. The latter is associated with a much lower dynamic friction value than static friction value at the fault during the rupture process.

Agglomeration effects as spatially embedded social interactions: identifying urban scaling beyond metropolitan areas

Agglomeration is the tell-tale sign of cities and urbanization. Identifying and measuring agglomeration economies has been achieved by a variety of means and by various disciplines, including urban economics, quantitative geography, and regional science. Agglomeration is typically expressed as the non-linear dependence of many different urban quantities on city size, proxied by population. The identification and measurement of agglomeration effects is of course dependent on the choice of spatial units. Metropolitan areas (or their equivalent) have been the preferred spatial units for urban scaling modeling. The many issues surrounding the delineation of metropolitan areas have tended to obscure that urban scaling is principally about the measurable consequences of social and economic interactions embedded in physical space and facilitated by physical proximity and infrastructure. These generative processes obviously must exist in the spatial subcomponents of metropolitan areas. Using data for counties and urbanized areas in the United States, we show that the generative processes that give rise to scaling effects are not an artifact of metropolitan definitions and exist at smaller spatial scales.

Ends Against the Middle: Measuring Latent Traits when Opposites Respond the Same Way for Antithetical Reasons

AbstractStandard methods for measuring latent traits from categorical data assume that response functions are monotonic. This assumption is violated when individuals from both extremes respond identically, but for conflicting reasons. Two survey respondents may “disagree” with a statement for opposing motivations, liberal and conservative justices may dissent from the same Supreme Court decision but provide ideologically contradictory rationales, and in legislative settings, ideological opposites may join together to oppose moderate legislation in pursuit of antithetical goals. In this article, we introduce a scaling model that accommodates ends against the middle responses and provide a novel estimation approach that improves upon existing routines. We apply this method to survey data, voting data from the U.S. Supreme Court, and the 116th Congress, and show that it outperforms standard methods in terms of both congruence with qualitative insights and model fit. This suggests that our proposed method may offer improved one-dimensional estimates of latent traits in many important settings.

Verifying in vitro-determined enzyme contributions to cannabidiol clearance for exposure predictions in human through physiologically-based pharmacokinetic modeling.

Cannabidiol (CBD) is approved for treatment of seizures associated with two forms of epilepsy that become apparent in infancy or early childhood. To consider an adult physiologically-based pharmacokinetic (PBPK) model for pediatric scaling, we assessed in vitro-derived cytochrome P450 (CYP) and uridine 5'-diphospho-glucuronosyltransferase (UGT) enzyme contributions to CBD clearance in human. An i.v. PBPK model was constructed using CBD physicochemical properties and knowledge of disposition. The i.v. datasets were used for model building and evaluation. Oral PBPK models for CBD administered in fasted and fed states were developed using single dose oral datasets and parameters optimized from the i.v. model and evaluated with multiple dose datasets. Relative contributions of CBD metabolizing enzymes were partitioned according to in vitro studies. Clinical drug-drug interaction (DDI) studies were simulated using CBD fed state, itraconazole, fluconazole, and rifampicin PBPK models. Linear mixed effect modeling was used to estimate area under the concentration-time curve from zero to infinity (AUC0-∞ ) perpetrator + CBD versus CBD alone. The i.v. and oral datasets used in model evaluation produced acceptable average fold error (AFE) of 1.28 and absolute AFE of 1.65. Relative contributions of drug-metabolizing enzymes to CBD clearance were proposed from in vitro data: UGT1A7 4%, UGT1A9 16%, UGT2B7 10%, CYP3A4 38%, CYP2C19 21%, and CYP2C9 11%. The simulated DDI studies using the in vitro-derived values produced AUC0-∞ treatment ratios comparable to observed: itraconazole 1.24 versus 1.07, fluconazole 1.45 versus 1.22, and rifampicin 0.49 versus 0.69. The constructed CBD PBPK models can predict adult exposures and have potential for use in pediatrics where exposure estimates are limited.

Experimental Study of Vertical Tail Model Flow Control Based on Oscillating Jet

In this paper, wind tunnel experiments are conducted to study the control law and mechanism of oscillating jet flow control to improve the aerodynamic characteristics of the vertical tail when a civil aircraft encounters left side gust or significant crosswind during takeoff and landing. We measured the vertical tail scaling model’s aerodynamics, spatial flow field, and surface pressure when the Reynolds number was 2.12 × 105. The maximum momentum coefficient of the oscillating jet actuator reaches 0.332%. In addition, we studied the flow control effect of the three-dimensional vertical tail scaled model in different spanwise positions. The experimental results show that the oscillating jet at the rear edge of the stabilizer can significantly increase the lateral force of the vertical tail, and the increment of the lateral force can reach 36.5% under the worst condition of the negative side slip angle of the vertical tail. We can improve the lateral force coefficient of the vertical tail model by applying flow control alone at different spanwise locations. The wing root’s control effect and the vertical tail’s middle section are better than the wing tip’s. The oscillating jet can effectively restrain the flow separation on the rudder. In addition, the input of a high-energy jet “ejects” the mainstream, which increases the flow velocity at the side of the vertical tail actuator. It increases the circulation of the vertical tail. The oscillating jet flow control technology can effectively improve the vertical tail’s steering efficiency and increase the vertical tail’s lateral force, which is of great significance in improving the safety and economy of civil aircraft.

Game bird carcasses are less persistent than raptor carcasses, but can predict raptor persistence dynamics.

Researchers conduct post-construction fatality monitoring (PCFM) to determine a wind energy facility's direct impacts on wildlife. Results of PCFM can be used to evaluate compliance with permitted take, potentially triggering adaptive management measures or offsetting mitigation; reducing uncertainty in fatality rates benefits wind companies, wildlife agencies, and other stakeholders. As part of PCFM, investigators conduct carcass persistence trials to account for imperfect detection during carcass surveys. In most PCFM studies, pen-raised game birds and other non-raptor surrogates have been used to estimate persistence of all large birds, including raptors. However, there is a growing body of evidence showing carcass persistence varies by bird type; raptor fatality estimates based on game bird carcass persistence may therefore be biased high. We conducted raptor and game bird carcass persistence field trials for 1 year at 6 wind energy facilities. Raptor carcass persistence varied by habitat and season, whereas the best-supported game bird model only included habitat. Raptor persistence probabilities were higher than corresponding game bird persistence probabilities for 13 of the 16 habitat and season combinations. Analysis of a curated large bird persistence meta-dataset showed that raptor carcass persistence varied by season, habitat, and region. The probability of persisting through a 30-day search interval ranged from 0.44 to 0.99 for raptors and from 0.16 to 0.79 for game birds. Raptor persistence was significantly higher than game bird persistence for 95% of the sampled strata. We used these carcass persistence estimates to develop linear mixed-effects models that predict raptor persistence probabilities based on estimated game bird persistence probabilities. Our scaling model provides an important statistical method to address gaps in raptor persistence data at sites in a broad range of landscape contexts in the continental United States and should be used to inform fatality estimation when site-specific raptor persistence data are limited or absent.