Experimental Estimates Research Articles

Small Area Estimation of Poverty in Four West African Countries by Integrating Survey and Geospatial Data

The paper presents methodology to generate experimental small area estimates (SAE) of poverty in four West African countries: Chad, Guinea, Mali, and Niger. Due to the absence of recent census data in the four countries, household level survey data are integrated with grid-level geospatial data, which are used as covariates in model-based estimation. Leveraging geospatial data enables reporting of poverty estimates more frequently at disaggregated administrative levels and makes estimation feasible in areas for which survey data are not available. The paper leverages the availability of a recent census in Burkina Faso for evaluation purposes. Estimates obtained with the same survey instruments and candidate geospatial covariates as the other four countries are compared against estimates obtained using recent census data and an empirical best predictor under a unit level model. For Burkina Faso, estimates obtained using geospatial data are highly correlated with the census-based ones in sampled areas but moderately correlated in non-sampled areas. The results demonstrate that in the absence of recent census data, small area estimation with publicly available geospatial covariates is feasible, can lead to large efficiency improvements compared to direct estimation, and improve the timeliness of small area estimates.

Double machine learning and design in batch adaptive experiments

Abstract We consider an experiment with at least two stages or batches and O ( N ) O\left(N) subjects per batch. First, we propose a semiparametric treatment effect estimator that efficiently pools information across the batches, and we show that it asymptotically dominates alternatives that aggregate single batch estimates. Then, we consider the design problem of learning propensity scores for assigning treatment in the later batches of the experiment to maximize the asymptotic precision of this estimator. For two common causal estimands, we estimate this precision using observations from previous batches, and then solve a finite-dimensional concave maximization problem to adaptively learn flexible propensity scores that converge to suitably defined optima in each batch at rate O p ( N − 1 ⁄ 4 ) {O}_{p}\left({N}^{-1/4}) . By extending the framework of double machine learning, we show this rate suffices for our pooled estimator to attain the targeted precision after each batch, as long as nuisance function estimates converge at rate o p ( N − 1 ⁄ 4 ) {o}_{p}\left({N}^{-1/4}) . These relatively weak rate requirements enable the investigator to avoid the common practice of discretizing the covariate space for design and estimation in batch adaptive experiments while maintaining the advantages of pooling. Our numerical study shows that such discretization often leads to substantial asymptotic and finite sample precision losses outweighing any gains from design.

Relating flow resistance to equivalent roughness

Describing flow resistance using the physical properties of an underlying surface is a recalcitrant problem in overland flow models. If discharge measurements are available, an equivalent roughness (e.g., Manning’s n) can be calibrated to represent the effects of surface properties within the domain with a single numerical value. Alternatively, the flow resistance can be estimated from discharge and velocity measured at a point, typically a runoff plot outlet. However, such experimental estimates are often inconsistent with the equivalent roughness determined from calibration to discharge, even if both derive from the same dataset. For example, if Manning’s equation is used to parameterize flow resistance, the Manning’s n obtained by calibrating a model to discharge differs from the value of n calculated from measured flow and velocity at the hillslope outlet.Here, this discrepancy is resolved by deriving a correction factor relating experimentally-determined flow resistance to the equivalent roughness. The derived correction factor is tested for four commonly-used resistance formulations using 129 rainfall simulator experiments. The correction factor is necessary to reproduce measured velocities, and yields minor improvements in discharge prediction.Plain Language SummaryAccurate runoff prediction is needed for land and water management in dryland regions, where sporadic and limited rainfall necessitate efficient water use and drought mitigation strategies. The skill of runoff models is known to be hindered by out ability to estimate flow resistance, which is the quantity that describes how energy is lost from flowing water to the underlying surface. Typically, models represent flow resistance with an equivalent roughness, e.g., Manning’s n, that is adjusted until the model can reproduce available discharge observations at watershed scale. However, the flow resistance measured in plot-scale experiments (1–10 m) often exceeds equivalent roughness coefficients by a factor of 10. This means that the direct use of plot-scale experimental data to parameterize runoff models could cause errors in discharge and runoff velocity predictions.Here, we resolve these differences by deriving an analytic correction factor that relates flow resistance to the equivalent roughness required for models to reproduce experimental velocity and discharge data. This correction factor is tested using rainfall simulator data from 129 experiments performed in the US Southwest covering a wide range of precipitation intensities, soil textures and vegetation types. Use of the correction factor substantially improves model prediction of flow velocity, which is needed for reproducing the timing of flood events and the estimation of erosion.

Free radical copolymerization kinetics of bio-based dibutyl itaconate and n-butyl acrylate

The free radical copolymerization of dibutyl itaconate (DBI), a monomer derived from renewable resources, and n-butyl acrylate (BA) is investigated to explore the potential of incorporating itaconate monomers into commercial acrylic resins to enhance the sustainability of coating materials. Batch experiments were conducted at 50 °C and 80 °C, varying initial monomer and initiator concentrations as well as monomer compositions, with proton NMR and size exclusion chromatography used to analyze monomer conversion profiles and polymer molar mass distributions (MMDs). The data were analyzed using a kinetic model developed to guide the experimental studies and estimate key kinetic parameters controlling copolymer composition, polymerization rate and polymer MMDs. The use of the more reactive BA as comonomer significantly increases the conversion and molar mass of the resulting copolymer. Furthermore, semi-batch operating conditions similar to current industrial practice can incorporate a substantial fraction of DBI into acrylic copolymer resins, thus enhancing their sustainability profile.

Experimental adaptive Bayesian estimation for a linear function of distributed phases in photonic quantum networks

The bipartite and multipartite entanglement resources of quantum networks can enhance sensitivity for estimating distributed parameters beyond the classical limits. Recent experimental studies on distributed parameter estimation based on quantum networks have achieved high precision beyond the shot-noise limit (SNL) within certain portions of the parameter space. Towards a realistic distributed parameter estimation scenario, a next key issue is how to achieve the high precision parameter independently with limited measurement data. In this work, we present a photonic experiment employing an efficient Bayesian method to estimate a linear function of four spatially distributed unknown phases. For arbitrary true phase values, our experiment shows the capability of achieving high sensitivities beyond the SNL in a post-selected regime using a restricted amount of measurement rounds. Our work gives a start for the experimental study of distributed adaptive Bayesian quantum estimation. Additionally, this method holds promising utility for more intricate or universal tasks associated with sensing distributed parameters in quantum networks.

Reducing Laser Exposure Time of PBF-LB/P by Providing High Energy Without Thermal Degradation and Its Effect on Part Strength and Process Time

Abstract One of the most promising additive manufacturing technologies for the production of end-use parts is powder bed fusion of polymer with laser beam (PBF-LB/P). This technology can reduce production costs by increasing process efficiency and production speed. As PBF-LB/P is a layer-wise additive manufacturing process, the production speed can be increased by reducing the layering time. Although some operations such as recoating are performed during the layering process, considerable time is spent on laser scanning. To reduce the laser exposure time while maintaining proper powder melting, a high-power beam should be irradiated to the powder layer to prevent energy shortage. However, as the laser beam power increases, the irradiance at the beam center increases significantly, causing powder degradation such as thermal decomposition or sublimation. In this study, an appropriate input energy range was determined by obtaining an input energy limit that does not cause powder deterioration via experimental observations and temperature estimations during the process. Furthermore, the influence of the scanning parameters on the mechanical properties of built specimens was investigated to reduce the layering time within an indicated range. Results show that the mechanical strength of the built parts decreases slightly as the scan spacing increases following the expansion of the beam diameter. This study also validated the effects of scanning parameters on layering time. As a result, by doubling the scan speed and spacing, the layering time can be reduced by up to 1/3.

Quantifying the ultimate limit of plasmonic near-field enhancement

Quantitatively probing the ultimate limit of near-field enhancement around plasmonic nanostructures remains elusive, despite more than five decades since the discovery of surface-enhanced Raman scattering. Theoretical calculations have predicted an ultimate near-field enhancement exceeding 1000 using the best plasmonic material silver, but experimental estimations disperse by orders of magnitude. Here, we design a high-quality silver plasmonic nanocavity with atomic precision and precisely quantify the upper limit of near-field enhancement in ~1 nm junctions. A hot-spot averaged Raman enhancement of 4.27 × 1010 is recorded with a small fluctuation, corresponding to an averaged electric field enhancement larger than 1000 times. This result quantitatively delineates the ultimate limit of plasmonic field enhancement around plasmonic nanostructures, establishing a foundation for diverse plasmon-enhanced processes and strong light-matter interactions at the atomic scale.

Application of the flexible and polarisable hydration ion model to study Th(IV) aqueous solutions

Th(IV) hydration in aqueous solution is studied by means of molecular dynamics simulations based on a polarisable Th(IV)- H 2 O interaction potential developed in the framework of the hydrated ion concept. Molecular Dynamics (MD) simulations provide as the only in-solution representative motif the ennea-aqua ion, [ Th ( H 2 O ) 9 ] 4 + , with first shell water molecules at an average distance of 2.47 Å from the ion, in accordance with most of the experimental estimates. A well-defined second hydration shell is also identified, hosting ca. 19 solvent molecules at 4.65 Å. Non-structural aspects of the Th(IV) hydration phenomenon, such hydration enthalpy and ion diffusion are well reproduced by the simulation results. The analysis of the O-Th-O angle distribution suggests that the capped square antiprism arrangement prevails over the trigonal tricapped prism. The well-balanced definition of the ion–water and water–water interactions in such a demanding ion neighbourhood is confirmed by the EXAFS and XANES spectroscopies. The theoretical spectra, computed from the MD trajectory, are in fine agreement with some of the experimentally recorded. The sensitivity of the XAS spectroscopy to structural changes confirms how the presented potential manages in a proper way the response of the water molecules to the highly polarising electric field generated by the tetravalent ion.

Experimental Estimation of Horizontal Velocity and Vertical Structure of Floating Anticyclones Based on the Quasi-geostrophic Approximation

Experimental Estimation of Horizontal Velocity and Vertical Structure of Floating Anticyclones Based on the Quasi-geostrophic Approximation

Do middle-aged and older people underreport loneliness? experimental evidence from the Netherlands

Despite the growing acknowledgment of the importance of loneliness among older individuals, questionnaire length constraints may hinder the inclusion of common multi-item loneliness scales in surveys. Direct, single-item loneliness measures are a practical alternative, but scholars have expressed concerns that such measures may lead to underreporting. Our aim was to test whether such reservations are justified. We conducted a preregistered list experiment among 2,553 people aged 50 + who participated in the Dutch Longitudinal Internet studies for the Social Sciences (LISS) panel. The list experiment method has been developed to unobtrusively gather sensitive information. We compared the list experiment estimate of the prevalence of frequent loneliness with the corresponding direct question estimate to assess downward bias in the latter. Next to pooled models, we estimated models stratified by gender to assess whether loneliness underreporting differed between women and men. Relying on the direct question, we estimated that 5.9% of respondents frequently felt lonely. Our list experiment indicated that the prevalence of frequent loneliness was 13.1%. Although substantial in magnitude, the difference between both estimates was only marginally significant (Δb: 0.072, 95% CI: − 0.003;0.148, p = .06). No evidence of gender differences was found. Although we cannot be conclusive that loneliness estimates are biased downward when a direct question is used, our results call for caution with direct, single-item measures of loneliness if researchers want to avoid underreporting. Replications are needed to gain more precise insights into the extent to which direct, single-item loneliness measures are prone to downward reporting bias.

Theoretical evidence of H-He demixing under Jupiter and Saturn conditions

The immiscibility of hydrogen-helium mixture under the temperature and pressure conditions of planetary interiors is crucial for understanding the structures of gas giant planets (e.g., Jupiter and Saturn). While the experimental probe at such extreme conditions is challenging, theoretical simulation is heavily relied in an effort to unravel the mixing behavior of hydrogen and helium. Here we develop a method via a machine learning accelerated molecular dynamics simulation to quantify the physical separation of hydrogen and helium under the conditions of planetary interiors. The immiscibility line achieved with the developed method yields substantially higher demixing temperatures at pressure above 1.5 Mbar than earlier theoretical data, but matches better to the experimental estimate. Our results suggest a possibility that H-He demixing takes place in a large fraction of the interior radii of Jupiter and Saturn, i.e., 27.5% in Jupiter and 48.3% in Saturn. This indication of an H-He immiscible layer hints at the formation of helium rain and offers a potential explanation for the decrease of helium in the atmospheres of Jupiter and Saturn.

Energy barriers govern catheter herniation during endovascular procedures: a 2.5D vascular flow model analysis.

Endovascular procedures rely on navigating guidewires, catheters and other devices through tortuous vasculature to treat disease. A critical challenge in these procedures is catheter herniation, in which the device deviates from its intended path, often irrecoverably. To elucidate the mechanics of herniation, we developed a physical flow model of the aortic arch that enables direct measurement of device curvature during experimentally simulated neuroendovascular procedures conducted from an upper arterial access. Combined with measurements of initial, unstressed device shapes and flexural rigidities, the method enables the experimental estimation of the device bending energies during these simulated procedures. Characteristic energy profiles revealed distinct stages in both herniation and successful navigation, governed by the interplay between device properties and vascular anatomy. A deterministic progression from successful navigation to herniation was identified, with catheter systems following paths determined by measurable energy barriers. Increasing guidewire stiffness or decreasing catheter stiffness reduced the energy barrier for successful navigation while increasing that for herniation. This framework enables the prediction of endovascular herniation risk and offers unique insight into improved device design and clinical decision-making.

Prediction of the residual lifetime of bitumen coatings on urban gas pipelines from the change in their mechanical characteristics during thermal-oxidative aging

Residual life of bitumen insulation is an important parameter of urban gas pipelines. Its fast and reliable estimation is necessary for timely health monitoring and coating restoration. In this study, we propose to define lifespan of bitumen insulation in situ from the mechanical characteristics measured during its thermal-oxidative aging. For evaluation of elastic and viscous properties, micro-impact dynamic indentation was applied. We determined the values of activation energy under thermal destruction and the dependence of transient electrical resistance on the critical values of coating's mechanical properties. Obtained experimental data foster real-time estimation of service time of insulation without coating removal.

Performance of the Earth Explorer 11 SeaSTAR Mission Candidate for Simultaneous Retrieval of Total Surface Current and Wind Vectors

Interactions between ocean surface currents, winds and waves at the atmosphere-ocean interface are key controls of lateral and vertical exchanges of water, heat, carbon, gases and nutrients in the global Earth System. The SeaSTAR satellite mission concept proposes to better quantify and understand these important dynamic processes by measuring two-dimensional fields of total surface current and wind vectors with unparalleled spatial and temporal resolution (1 × 1 km2 or finer, 1 day) and unmatched precision over one continuous wide swath (100 km or more). This paper presents a comprehensive numerical analysis of the expected performance of the Earth Explorer 11 (EE11) SeaSTAR mission candidate in the case of idealised and realistic 2D ocean currents and wind fields. A Bayesian framework derived from satellite scatterometry is adapted and applied to SeaSTAR’s bespoke inversion scheme that simultaneously retrieves total surface current vectors (TSCV) and ocean surface vector winds (OSVW). The results confirm the excellent performance of the EE11 SeaSTAR concept, with Root Mean Square Errors (RMSE) for TSCV and OSVW at 1 × 1 km2 resolution consistently better than 0.1 m/s and 0.4 m/s, respectively. The analyses highlight some performance degradation in some relative wind directions, particularly marked at near range and low wind speeds. Retrieval uncertainties are also reported for several variations around the SeaSTAR baseline three-azimuth configuration, indicating that RMSEs improve only marginally (by ∼0.01 m/s for TSCV) when including broadside Radial Surface Velocity or broadside dual-polarisation data in the inversion. In contrast, our results underscore a) the critical need to include broadside Normalised Radar Cross Section data in the inversion; b) the rapid performance degradation when broadside incidence angles become steeper than 20° from nadir; and c) the benefits of maintaining ground squint angle separation between fore and aft lines-of-sight close to 90°. The numerical results are consistent with experimental performance estimates from airborne data and confirm that the EE11 SeaSTAR concept satisfies the requirements of the mission objectives.

Traditional and Integrated MCDM Approaches for Assessment and Ranking of Laser Cutting Conditions

Multiple benefits and advantages that offer laser cutting technology are difficult to achieve if the laser cutting parameter conditions are not adequately set. Determining laser cutting conditions is not trivial task considering large number of controllable inputs, existence of multiple process performances which are often mutually opposed as well as effects of noise factors. Different scientific methods and engineering approaches represent more sophisticated approaches which aid assessment and determination of the most favourable (optimized) cutting conditions. This study is focused assessment and ranking of laser cutting conditions in CO2 laser cutting of AISI 316L stainless steel. Based on kerf width and surface roughness experimental data and estimation of material removal rate (MRR) and total variable costs, four criteria in the multi-criteria decision making (MCDM) model were considered. For solving the developed model, six well-known MCDM methods were applied, and in addition, in order to overcome ranking inconsistency, robust decision-making rule was developed upon which final ranking was obtained.

FusionNetV2: Explicit Enhancement of Edge Features for 6D Object Pose Estimation

FusionNet is a hybrid model that incorporates convolutional neural networks and Transformers, achieving state-of-the-art performance in 6D object pose estimation while significantly reducing the number of model parameters. Our study reveals that FusionNet has local and global attention mechanisms for enhancing deep features in two paths and the attention mechanisms play a role in implicitly enhancing features around object edges. We found that enhancing the features around object edges was the main reason for the performance improvement in 6D object pose estimation. Therefore, in this study, we attempt to enhance the features around object edges explicitly and intuitively. To this end, an edge boosting block (EBB) is introduced that replaces the attention blocks responsible for local attention in FusionNet. EBB is lightweight and can be directly applied to FusionNet with minimal modifications. EBB significantly improved the performance of FusionNet in 6D object pose estimation in experiments on the LINEMOD dataset.

Comment on “Tunneling-tip-induced collapse of the charge gap in the excitonic insulator Ta2NiSe5 ”

In this study, we investigate the discrepancy between the estimate of Q. He [], who observed a remarkable collapse of the exciton gap in Ta2NiSe5 due to the electrostatic field between the scanning tunneling microscope (STM) tip and the sample, and that of a recent angle-resolved photoemission spectroscopy investigation [C. Chen , ]. It is proposed that a critical factor contributing to this discrepancy is due to He 's assumption of a constant work function of the STM tip. This assumption led to an underestimation of the tip-induced electric field. Using a literature value for the sample work function, a more substantial electric field strength is obtained, which resolves the apparent conflict between the doping estimates of these two techniques. Furthermore, our findings highlight the importance of the STM tip condition, which can significantly impact the tip work function and, consequently, influence the doping estimation in experiments involving tip-induced electric fields. Published by the American Physical Society 2024

Retrofit of damaged reinforced concrete frame by autoclaved aerated concrete blocks infill wall: Experimental validation and strength estimation

This study introduces a novel approach for the global retrofitting of seismic performance in destructively damaged reinforced concrete (RC) frames through the application of autoclaved aerated concrete (AAC) blocks infill walls to enhance both structural strength and stiffness. Three full-scale RC frames are designed and fabricated, comprising an intact bare frame, a damaged frame strengthened by carbon fiber-reinforced polymer (CFRP), and a damaged frame retrofitted with the same CFRP and AAC blocks infill walls. To verify the cyclic behaviors and working principle of the retrofitted system, the two frames undergo a pre-damage scenario with a maximum inter-story drift ratio (MIDR) of 2.52%, and then both specimens are retrofitted. Afterward, a pseudo-static cyclic test is conducted on three specimens, with a MIDR of 3.36%. The test data is analyzed and discussed in terms of hysteretic responses, secant stiffness, displacement ductility, and energy dissipation capacity. The findings indicate a significant improvement in the lateral strength and stiffness of the seismic-damaged frame through the implementation of AAC blocks infill walls, demonstrating performance comparable to the intact RC frame. Also, the slight local crushing of AAC blocks and their interaction with mortar joints effectively dissipates a considerable amount of input energy, thereby reducing the energy dissipation demands on retrofitted structural components. Moreover, the theoretical deduction of the lateral strength of the retrofitted RC frames is presented. The errors between the predicted and test results fall within 5%, suggesting that the analytical outcomes can reasonably predict the lateral strength of the specimens.

Chemical engineering perspective of pyrolysis reactor and condenser system for biomass valorisation

The manuscript investigates the design, operating, and economic parameters of components in a biomass pyrolysis system. It covers two key components, the pyrolysis reactor and condenser, with plans to discuss other components in future publications. The study relies on experimental data from a fixed-bed reactor, bio-oil retention experiments using various vials, and computational modeling of the pyrolysis process using a lumped model. The experimental data were thoroughly analysed, considering different types of pyrolysis reactors and heating methods. Dimensionless numbers were employed to predict the impact of changing feed characteristics during pyrolysis. The second part of the study focuses on the operation of conventional condensers and how Bio-oil deposition on their surfaces affects efficiency and cost. Experimental estimation of Bio-oil film thickness on stainless steel and glass surfaces is presented, along with its effects. Finally, a hybrid condenser, combining stainless steel with a glass lining, is proposed to enhance efficiency and reduce costs based on operational requirements.

Experimental and numerical estimation of complex stress intensity factor for the completely debonded anti-crack embedded into a weak matrix using domain integral method

The problem of interface debonding is of fundamental importance in understanding the stress transfer mechanism and behavior of weak interfaces present due to rigid stiffeners. A domain integral method based on Betti’s reciprocal theorem was adopted to compute the complex stress intensity factor (SIF) for the completely debonded anti-crack (discontinuity) with mixed boundary conditions. The domain integral approach is based on two admissible mechanical states, which comprise of actual and auxiliary elastic fields. The singular auxiliary fields in terms of angular variations for the completely debonded anticrack were obtained using the full-field solution. The obtained angular variations were compared with the Williams eigenvalue problem for completeness. The displacement and strains were obtained using digital image correlation (DIC) experiments and numerical simulation for parallel and perpendicular orientations of the discontinuity. The obtained DIC strain contours revealed the presence of anti-symmetric and symmetric variation on the bonded side of the anti-crack. The complex SIF is estimated experimentally and numerically based on the domain integral method to seek a better comparison with the analytical estimate. The SIF estimated for the perpendicular orientation is higher than the parallel orientation.