Spatial Regression With Multiplicative Errors, and Its Application With Lidar Measurements

Multiplicative errors in addition to spatially referenced observations often arise in geodetic applications, particularly in surface estimation with light detection and ranging (LiDAR) measurements. However, spatial regression involving multiplicative errors remains relatively unexplored in such applications. In this regard, we present a penalized modified least squares estimator to handle the complexities of a multiplicative error structure while identifying significant variables in spatially dependent observations for surface estimation. The proposed estimator can be also applied to classical additive error spatial regression. By establishing asymptotic properties of the proposed estimator under increasing domain asymptotics with stochastic sampling design, we provide a rigorous foundation for its effectiveness. A comprehensive simulation study confirms the superior performance of our proposed estimator in accurately estimating and selecting parameters, outperforming existing approaches. To demonstrate its real-world applicability, we employ our proposed method, along with other alternative techniques, to estimate a rotational landslide surface using LiDAR measurements. The results highlight the efficacy and potential of our approach in tackling complex spatial regression problems involving multiplicative errors

Metamorphic concentrator solar cells with over 40% conversion efficiency

ABSTRACT: Multijunction III-V concentrator cells have attracted much interest for concentrator photovoltaic (PV) systems recently due to their unparalleled conversion efficiencies. As high as these efficiencies are, they can be made even higher if the combination of subcell bandgaps for the multijunction solar cell are chosen from metamorphic semiconductors that are not all lattice-matched to the same growth substrate. Advances in the design of metamorphic subcells to reduce carrier recombination and increase voltage, wide-bandgap tunnel junctions capable of operating at high concentration, metamorphic buffers to transition from the substrate lattice constant to the active subcells, concentrator cell AR coating and grid design, and integration into 3-junction cells current matched under the terrestrial spectrum have resulted in new heights in solar cell performance. A metamorphic Ga 0.44 In 0.56 P/ Ga 0.92 In 0.08 As/ Ge 3-junction solar cell from this research has reached a record 40.7% efficiency at 240 suns, under the standard reporting spectrum for terrestrial concentrator cells (AM1.5 direct, low-AOD, 24.0 W/cm 2 25°C), and experimental lattice-matched 3-junction cells have now also achieved over 40% efficiency, with 40.1% measured at 135 suns. This metamorphic 3-junction device is the first solar cell to reach over 40% in efficiency, and has the highest solar conversion efficiency for any type of photovoltaic cell developed to date

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

The typical AV accident scenarios in the urban area obtained by clustering and association rule mining of real-world accident reports

Automated Vehicles (AVs) based on a collection of advanced technologies such as big data and artificial intelligence have opened an opportunity to reduce traffic accidents caused by human drivers. Nevertheless, traffic accidents of AVs continue to occur, which raises safety and reliability concerns about AVs. AVs are particularly vulnerable to accidents on urban roads than on highways due to various dynamic objects and more complex infrastructure. Several studies proposed a scenario-based approach of experimenting with the response of AVs to specific situations as a way to test their safety. Reliable and concrete scenarios are necessary to test AV safety under critical conditions accurately. This study aims to derive a typical accident scenario for evaluating the safety of AVs, specifically in urban areas, by analysing collisions reported by the DMV of California, USA. We applied a hierarchical clustering method to find groups of similar reports and then executed association rule mining on each cluster to correlate between accident factors and collision types. We combined statistically significant association rules to constitute a total of 14 scenarios that are described according to an adapted PEGASUS framework. The newly obtained scenarios exhibit significantly different accident patterns than the typical Human-driven Vehicles (HVs) in urban areas reported by National Highway Traffic Safety Administration. Our discovery urges AV safety to be tested reliably under scenarios more relevant than the existing HV accident scenarios

Effects of Skin Surface Temperature on Photoplethysmograph

Photoplethysmograph (PPG) has been widely used to investigate various cardiovascular conditions. Previous studies demonstrated effects of temperature of the measurement environment; however, an integrated evaluation has not been established in environments with gradual air temperature variation. The purpose of this study is to investigate variations and relationships of blood pressure (BP), PPG and cardiovascular parameters such as heart rate (HR), stroke volume (SV), cardiac output (CO) and total peripheral resistance (TPR), by changing skin surface temperature (SST). Local mild cooling and heating was conducted on 16 healthy subjects. The results showed that local SST changes affected Finometer blood pressures (Finger BP), PPG components and TPR, but not the oscillometric blood pressure (Central BP), HR, SV and CO, and indicated that temperature must be maintained and monitored to reliably evaluate cardiovascular conditions in temperature-varying environments

Laser scanning reflection-matrix microscopy for aberration-free imaging through intact mouse skull

A mouse skull is a barrier for high-resolution optical imaging because its thick and inhomogeneous internal structures induce complex aberrations varying drastically from position to position. Invasive procedures creating either thinned-skull or open-skull windows are often required for the microscopic imaging of brain tissues underneath. Here, we propose a label-free imaging modality termed laser scanning reflection-matrix microscopy for recording the amplitude and phase maps of reflected waves at non-confocal points as well as confocal points. The proposed method enables us to find and computationally correct up to 10,000 angular modes of aberrations varying at every 10 × 10 µm2 patch in the sample plane. We realized reflectance imaging of myelinated axons in vivo underneath an intact mouse skull, with an ideal diffraction-limited spatial resolution of 450 nm. Furthermore, we demonstrated through-skull two-photon fluorescence imaging of neuronal dendrites and their spines by physically correcting the aberrations identified from the reflection matrix11Nsci