Drift Measurements Research Articles

A comparative test of the ΛCDM and Rh=ct cosmologies based on upcoming redshift drift measurements

A comparative test of the ΛCDM and R_h=ct cosmologies based on upcoming redshift drift measurements

Analysis of the drift of the South Atlantic Anomaly using particle monitors onboard Insight-HXMT

Using the particle monitors aboard Insight-HXMT satellite, we analyzed over 6.5 years of continuous data to study the South Atlantic Anomaly (SAA) position, average count rate, and surface size, as well as its evolution from June 2017 to March 2024. We confirm the anti-correlation between the particle count rate obtained by particle monitors and the solar activity, as well as the anti-correlation between the evolution of the SAA surface size and the solar activity. Furthermore, this study confirms earlier measurements of a westward drift of the SAA with a rate of 0.343±0.002o/yr in longitude. However, it reveals a smaller northward drift with a rate of 0.028±0.002o/yr in latitude. Two irregular drifts both in longitude and latitude were observed. We suggest that the irregular drifts may be not driven by solar cycle variation of the atmosphere but may be associated with geomagnetic jerks.

Exploring the potential of cobalt-based catalysts in the methane dry reforming for sustainable energy applications

Cobalt-based powder catalysts with different Co loadings were synthesized via wet impregnation using MgAl2O4 spinel as support. The catalytic properties of the solids were evaluated in the dry-reforming methane at different reaction temperatures and two CH4:CO2 ratios. The catalyst with higher cobalt content (13 %) presented superior performance due to increased Co0 species availability, confirmed by XPS analysis. Besides, this catalyst displayed remarkable resistance to carbon deposition at 550 °C and CH4:CO2 1: 1 ratio. In-situ DRIFT measurements demonstrated the formation and transformation of carbonate and hydrogen carbonate species during the DRM reaction, highlighting efficient CO2 and CH4 activation on the catalyst surface. Based on this data, a structured catalyst was deposited on top of the FeCrAlloy monolith, which was active, stable, selective for H2, and resistant against on/off cycles. Compared with the powder catalyst, the structured system displayed higher catalytic activity, possibly due to higher reducibility of metal species and improved heat transfer provided by the FeCrAlloy substrate. The results highlight the potential of Co-based structured catalysts for H2 or synthesis gas production processes.

Experimental Study of Fiber-Optic Temperature Sensor Based on Dual FSIs

To improve the sensitivity measurement of temperature sensors, a fiber optic temperature sensor structure based on the harmonic Vernier effect with two parallel fiber Sagnac interferometers (FSIs) is designed, and theoretical analysis and experimental testing are conducted. The FSI consisting of two polarization maintaining fibers (PMFs) with lengths of 13.62 m and 15.05 m respectively is used to achieve the basic Vernier effect. Then by changing the length of one PMF to approximately i times that of the others, the FSI composed of two PMFs of 7.1 m and 15.05 m is used to achieve the first-order harmonic Vernier effect. Afterward, temperature sensing tests are conducted to observe the wavelength drift during temperature changes and ultimately achieve high sensitivity. The experimental results show that the temperature sensitivity of the sensor based on the first-order harmonic Vernier effect is −28.89 nm/°C, which is 17.09 times that of a single FSI structure (−1.69 nm/°C) and 1.84 times that of the sensitivity generated by the structure based on the basic Vernier effect (−15.69 nm/°C). The experimental results are consistent with the theoretical analysis. The structure proposed in this paper achieves drift measurement of 0.1 °C variation based on 1 °C drift, making the fiber optic temperature sensor applicable to related fields that require high precision temperature. The proposed temperature sensor has the simple structure, low production cost, high sensitivity, and broad application prospects.

Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States.

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here, we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection ynamics, presumably via heterosubtypic cross-immunity.

Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here, we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997—2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection ynamics, presumably via heterosubtypic cross-immunity.

Reduced Streamflow From Water Diversion Alters Stream Ecology and Fish Behavior

ABSTRACTUnderstanding invertebrate and fish responses to altered streamflows is important for water management that balances ecological function and societal needs. We studied the impacts of a significant water diversion on a stream food web, including benthic biofilms, benthic macroinvertebrates (BMI), and drifting macroinvertebrates. In the dry season, drift flux (number of aquatic individuals or biomass/s) and drift concentration (individual/m3) were lower below the diversion than above. Drift concentration (biomass/m3) was slightly higher below the diversion, due to the presence of large Trichopterans. All measures of drift dropped to nearly zero at the end of the dry season below the diversion, when streamflows were reduced by > 90% below the diversion relative to above, representing a significant loss of food resources for trout. Simultaneously, native Rainbow Trout (Oncorhynchus mykiss) switched from drift to benthic foraging 1 month earlier below the diversion as drift and water velocities declined. The ecology of the benthos was not as impacted by the diversion: BMI densities were higher below the diversion, while benthic biofilm densities were similar at the two sites. The taxonomic composition of BMI was also similar between the sites, but fewer Ephemeroptera entered the drift below the diversion. Overall, the late season decrease in drift below the diversion despite the similar or higher benthic production suggests that streamflows influence food availability for trout even in the absence of benthic responses. Reduced streamflows, due to water diversions as studied here, or due to climate change, will likely reduce food resources and growth opportunities for fishes.

Data Assimilation of Ion Drift Measurements for Estimation of Ionospheric Plasma Drivers

AbstractDuring geomagnetic storms, the capabilities of current climate models in predicting ionospheric behavior are notably limited. A data assimilation tool, Estimating Model Parameters Reverse Engineering (EMPIRE), implements a Kalman filter to ingest electric density rate correcting the background electric potential and neutral wind. For the baseline setup, or case (1), EMPIRE ingests electron density global map output from the Ionospheric Data Assimilation 4‐Dimensional (IDA4D) algorithm. In this work, a new augmentation method is evaluated in which ion drift measurements are also assimilated into EMPIRE. The ion drift measurements used in the new augmentation method are obtained from Super Dual Auroral Radar Network (SuperDARN) sites in the mid‐to‐high latitude region of the northern hemisphere. Cases (2) and (3) are set up for evaluating the impacts from ingesting different types of observations: SuperDARN fit and grid data, respectively. Six independent data sources are used as validation data sets to compare outcomes with or without ingesting ion drifts. One is the vector ion velocities derived from the Millstone Hill Incoherent Scatter Radar (MHISR) and a second is the vertical drift from Arecibo site. The other four are SuperDARN ion velocity grid data from Saskatoon, Kapuskasing, Christmas Valley West, and Hokkaido East. Results show improvements in performance at mid‐latitudes by augmenting electron density rates with 3D spatially distributed line‐of‐sight ion drift measurements, with negligible improvements to low and high latitude estimations. The lack of improvement at high‐latitudes is attributed to the increase in EMPIRE ion drift error poleward of 60° magnetic.

A machine learning approach for estimating the drift velocities of equatorial plasma bubbles based on All-Sky Imager and GNSS observations

Equatorial Plasma Bubbles (EPBs) are zones characterized by fluctuations in plasma densities which form in the low-latitude ionosphere primarily during the post-sunset. They subject radio signals to amplitude and phase variabilities, affecting the functioning of technological systems that utilize the Global Navigation Satellite Systems (GNSS) signals for navigation. Thus, understanding EPB occurrence patterns and morphological features is vital for mitigating their effects. In this work, we employed two GNSS receivers and an All-Sky Imager (ASI) to conduct simultaneous observations on the morphology of EPBs over Brazil. The main objectives of the study were (1) to develop a Random Forest (RF) machine-learning model to estimate and predict the zonal drift velocities of EPBs, and (2) to compare the model predictions with actual EPB drifts inferred from the two instruments, as well as zonal neutral wind speeds obtained from the Horizontal Wind Model (HWM-14). In the model development, we utilized reliable EPB drift measurements made during geomagnetically quiet days between 2013 and 2017 in Brazil. The model predicted the velocities based on parameters including the day of the year, universal time, critical frequency of the F2 layer (foF2), solar and interplanetary indices. The correlation coefficients of 0.98 and 0.96 and RMSE values of 10.61 m/s and 10.06 m/s were obtained upon training and validation correspondingly. We evaluated the accuracy of the model in predicting EPB drifts on two geomagnetically quiet nights where an average correlation coefficient of 0.89 and an RMSE of 15.74 m/s were obtained. The predicted drifts, the zonal neutral wind velocities, and the GNSS and ASI velocity measurements were put into context for validation purposes. Overall, the velocities were comparable and ranged between ∼100 m/s and ∼30 m/s from the hours of 00 UT to 05 UT. The results confirmed the accuracy and applicability of the model, revealing the ionosphere-thermosphere coupling influence on the nocturnal propagation of EPBs under the full activation of the F region dynamo.

Does high-latitude ionospheric electrodynamics exhibit hemispheric mirror symmetry?

Abstract. Ionospheric electrodynamics is a problem of mechanical stress balance mediated by electromagnetic forces. Joule heating (the total rate of frictional heating of thermospheric gases and ionospheric plasma) and ionospheric Hall and Pedersen conductances comprise three of the most basic descriptors of this problem. More than half a century after identification of their central role in ionospheric electrodynamics, several important questions about these quantities, including the degree to which they exhibit hemispheric symmetry under reversal of the sign of dipole tilt and the sign of the y component of the interplanetary magnetic field (so-called “mirror symmetry”), remain unanswered. While global estimates of these key parameters can be obtained by combining existing empirical models, one often encounters some frustrating sources of uncertainty: the measurements from which such models are derived, usually magnetic field and electric field or ion drift measurements, are typically measured separately and do not necessarily align. The models to be combined moreover often use different input parameters, different assumptions about hemispheric symmetry, and/or different coordinate systems. We eliminate these sources of uncertainty in model predictions of electromagnetic work J⋅E (in general not equal to Joule heating ηJ2) and ionospheric conductances by combining two new empirical models of the high-latitude ionospheric electric potential and ionospheric currents that are derived in a mutually consistent fashion: these models do not assume any form of symmetry between the two hemispheres; are based on Apex magnetic coordinates (denoted Apex), spherical harmonics, and the same model input parameters; and are derived exclusively from convection and magnetic field measurements made by the Swarm and CHAMP satellites. The model source code is open source and publicly available. Comparison of high-latitude distributions of electromagnetic work in each hemisphere as functions of dipole tilt and interplanetary magnetic field clock angle indicates that the typical assumption of mirror symmetry is largely justified. Model predictions of ionospheric Hall and Pedersen conductances exhibit a degree of symmetry, but clearly asymmetric responses to dipole tilt and solar wind driving conditions are also identified. The distinction between electromagnetic work and Joule heating allows us to identify where and under what conditions the assumption that the neutral wind corotates with the Earth is not likely to be physically consistent with predicted Hall and Pedersen conductances.

Base Isolation and Energy Dissipating System in Earthquake Resistant Building Design

The utilization of base isolation is a crucial strategy for enhancing seismic resilience in structures. The method involves installing isolators and energy-absorbing devices beneath a building's superstructure to mitigate the destructive effects of earthquakes. When base isolation is implemented in a building, it not only makes the structure stronger and more stable, but also helps to safeguard lives and properties. This technique is particularly valuable for seismic retrofitting of historical buildings. In the present study, software called simulation of seismic isolation systems in structural analysis is employed, considering isolator characteristics, whether they exhibit nonlinear or equivalent linear behavior. Adhering to the IS 1893:2016 Code, the analysis utilized the SAP 2000 software package. A study was carried out to compare the effectiveness of base isolation systems versus fixed-base buildings in dealing with seismic activity. The study focused on analyzing various seismic indicators such as joint displacement, shear force, bending moment, building torsion, and the period of natural frequency. Results showed that models utilizing base isolation systems had significantly higher base shear values than those with a fixed-base building configuration. However, there was a significant 35% reduction in story shear values for the rubber isolation system and a 40% decrease for the friction pendulum model. Additionally, there was a 25% reduction in story drift for the rubber base model and a 30% decrease for the friction pendulum model. The friction pendulum model demonstrated the most effective control of these parameters across various seismic zone conditions. Key words: The topic of discussion pertains to Seismic Isolation with Rubber Bearing System and the Friction Pendulum Technique. Additionally, it includes SAP2000 Analysis, Story Drift Measurement, and Shear Force Evaluation in relation to these techniques.

Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States.

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection dynamics, presumably via heterosubtypic cross-immunity.

A Numerical Study on the Impact of E × B Drift on the Vertical Distribution of the Plasma Density Over the Geomagnetic Equatorial Ionospheric Region

AbstractUsing an in–house developed Quasi Two–Dimensional (QTD) physics–based ionospheric model, the impact of E × B drift velocity on the vertical distribution of the electron density over the equatorial latitude has been investigated. The vertical drift measurements from (a) drift analysis software of Digisonde (b) derived from Digisonde ionograms (c) calculated from the Scherliess–Fejer (SF) model, and (d) obtained from the magnetometer ΔH measurements have been used in this study. Four quiet days in a low solar activity year, representing four seasons of the year 2010, have been chosen for the study. The model–derived electron density profiles using the vertical drifts from all four methods matched well with the Digisonde observation below ∼150 km at all the Local Times (LTs) for all 4 days. However, since the Digisonde–derived drifts were very low, centered mostly around zero, it led to the overestimation/underestimation of the F–region peak plasma density (nmF2)/height (hmF2). The model simulated electron density profiles using the SF model, and ΔH derived vertical drifts showed good agreement with the observation up to an altitude of ∼350 km. The study showed that vertical drift is a factor that controls the nmF2 trough around noon over the equatorial latitude. It is seen that plasma diffusion occurs only beyond an altitude of 350 km, while the range of altitudes between 320 and 350 km acts as the “diffusion threshold height.” This finding has significant implications for understanding plasma dynamics in the equatorial ionosphere.

A new method for instrumental profile reconstruction of high-resolution spectrographs

Context. Knowledge of the spectrograph’s instrumental profile (IP) provides important information needed for wavelength calibration and for the use in scientific analyses. Aims. This work develops new methods for IP reconstruction in high-resolution spectrographs equipped with astronomical laser frequency comb (astrocomb) calibration systems and assesses the impact that assumptions on the IP shape have on achieving accurate spectroscopic measurements. Methods. Astrocombs produce ≈ 10 000 bright, unresolved emission lines with known wavelengths, making them excellent probes of the IP. New methods based on Gaussian process regression were developed to extract detailed information on the IP shape from these data. Applying them to HARPS, an extremely stable spectrograph installed on the ESO 3.6m telescope, we reconstructed its IP at 512 locations of the detector, covering 60% of the total detector area. Results. We found that the HARPS IP is asymmetric and that it varies smoothly across the detector. Empirical IP models provide a wavelength accuracy better than 10m s−1 (5m s−1) with a 92% (64%) probability. In comparison, reaching the same accuracy has a probability of only 29% (8%) when a Gaussian IP shape is assumed. Furthermore, the Gaussian assumption is associated with intra-order and inter-order distortions in the HARPS wavelength scale as large as 60 m s−1. The spatial distribution of these distortions suggests they may be related to spectrograph optics and therefore may generally appear in cross-dispersed echelle spectrographs when Gaussian IPs are used. Empirical IP models are provided as supplementary material in machine readable format. We also provide a method to correct the distortions in astrocomb calibrations made under the Gaussian IP assumption. Conclusions. Methods presented here can be applied to other instruments equipped with astrocombs, such as ESPRESSO, but also ANDES and G-CLEF in the future. The empirical IPs are crucial for obtaining objective and unbiased measurements of fundamental constants from high-resolution spectra, as well as measurements of the redshift drift, isotopic abundances, and other science cases.

Investigating the activity of modified TiO2 photocatalysts used for the photoreforming of biomass derivatives

Different TiO2 modified (with Pt, Cu2O, Nb) photocatalysts have been compared for the photo-reforming of glucose and fructose at ambient conditions with the aim of linking the photoactivity to some structural and surface characteristics. A different degree of conversion, distribution of intermediates and H2 production were observed with the various photocatalysts. Moreover, the results obtained with the same catalysts were slightly different with the two substrates, highlighting the importance of the interaction between the catalyst surface and the organic compound. Bare TiO2 was inactive towards H2 production, Cu2O was effective in replacing Pt for hydrogen generation, and the presence of Pt/Nb was beneficial for both H2 production and selective oxidation. Moreover, Pt not only works as a sink for the photoproduced electrons, as it is well known in the literature, but also modifies the surface acid-base properties of catalysts as revealed by DRIFT and TPD measurements.

Creep-free polyelectrolyte elastomer for drift-free iontronic sensing.

Artificial pressure sensors often use soft materials to achieve skin-like softness, but the viscoelastic creep of soft materials and the ion leakage, specifically for ionic conductors, cause signal drift and inaccurate measurement. Here we report drift-free iontronic sensing by designing and copolymerizing a leakage-free and creep-free polyelectrolyte elastomer containing two types of segments: charged segments having fixed cations to prevent ion leakage and neutral slippery segments with a high crosslink density for low creep. We show that an iontronic sensor using the polyelectrolyte elastomer barely drifts under an ultrahigh static pressure of 500 kPa (close to its Young's modulus), exhibits a drift rate two to three orders of magnitude lower than that of the sensors adopting conventional ionic conductors and enables steady and accurate control for robotic manipulation. Such drift-free iontronic sensing represents a step towards highly accurate sensing in robotics and beyond.

FPGA and computer-vision-based atom tracking technology for scanning probe microscopy

Atom tracking technology enhanced with innovative algorithms has been implemented in this study, utilizing a comprehensive suite of controllers and software independently developed domestically. Leveraging an on-board field-programmable gate array (FPGA) with a core frequency of 100 MHz, our system facilitates reading and writing operations across 16 channels, performing discrete incremental proportional-integral-derivative (PID) calculations within 3.4 microseconds. Building upon this foundation, gradient and extremum algorithms are further integrated, incorporating circular and spiral scanning modes with a horizontal movement accuracy of 0.38 pm. This integration enhances the real-time performance and significantly increases the accuracy of atom tracking. Atom tracking achieves an equivalent precision of at least 142 pm on a highly oriented pyrolytic graphite (HOPG) surface under room temperature atmospheric conditions. Through applying computer vision and image processing algorithms, atom tracking can be used when scanning a large area. The techniques primarily consist of two algorithms: the region of interest (ROI)-based feature matching algorithm, which achieves 97.92% accuracy, and the feature description-based matching algorithm, with an impressive 99.99% accuracy. Both implementation approaches have been tested for scanner drift measurements, and these technologies are scalable and applicable in various domains of scanning probe microscopy with broad application prospects in the field of nanoengineering.

Calibration of Swarm Ion Density, Drift, and Effective Mass Measurements

AbstractWe calibrate the Swarm Langmuir Probe Ion Drift, Density and Effective Mass (SLIDEM) products using the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC‐1) electron density measurements. SLIDEM combines electric current measurements from the Electric Field Instrument faceplate (situated on the ram‐facing side of the satellite) with ion admittance measurements from a spherical Langmuir probe to estimate ionospheric ion density, bulk ion drift parallel to the satellite trajectory in the polar regions, and effective ion mass at low and middle latitudes. SLIDEM processing includes an eight‐parameter empirical geometry model that expresses the corrections to the effective faceplate area and spherical probe radius arising from satellite‐plasma interactions. Validation of SLIDEM density by conjunctions with COSMIC density altitude profiles reveals systematic errors, with SLIDEM underestimating corresponding COSMIC data by around 10%. Using the same conjunctions to calibrate the SLIDEM density processor, a simple one‐parameter geometry model is obtained, which significantly reduces bias in ion density. This leads to reduced bias in the ion ram speed and in the effective mass, both of which are more consistent with empirical ionospheric models. We examined three models characterizing the variation of probe effective electrode current collection areas. Faceplate geometries are statistically indistinguishable from the physical faceplate cross section. Spherical Langmuir probe radius is effectively reduced by about 10% due to satellite‐plasma interactions. We recommend updating the SLIDEM processor to use a smaller value for the spherical probe's radius.

Toward a remote sensing method based on commercial LiDAR sensors for the measurement of spray drift and potential drift reduction

Spray drift is inevitable in chemical applications, drawing global attention because of its potential environmental pollution and the risk of exposing bystanders to pesticides. This issue has become more pronounced with a growing consensus on the need for enhanced environmental safeguards in agricultural practices. Traditionally, spray drift measurements, crucial for refining spray techniques, relied on intricate, time-consuming, and labor-intensive sampling methods utilizing passive collectors. In this study, we investigated the feasibility of using close-range remote sensing technology based on Light Detection and Ranging (LiDAR) point clouds to implement drift measurements and drift reduction classification. The results show that LiDAR-based point clouds vividly depict the spatial dispersion and movement of droplets within the vertical plane. The capability of LiDAR to accurately determine drift deposition was demonstrated, evident from the high R2 values of 0.847, 0.748 and 0.860 achieved for indoor, wind tunnel and field environments, respectively. Droplets smaller than 100 μm and with a density below 50 deposits·cm−2·s−1 posed challenges for LiDAR detection. To address these challenges, the use of multichannel LiDAR with higher wavelengths presents a potential solution, warranting further exploration. Furthermore, we found a satisfactory consistency when comparing the drift reduction classification calculated from LiDAR measurements with those obtained though passive collectors, both in indoor tests and the unmanned air-assisted sprayer (UAAS) field test. However, in environments with less dense clouds of larger droplets, a contradiction emerged between higher drift deposition and lower scanned droplet counts, potentially leading to deviations in the calculated drift potential reduction percentage (DPRP). This was exemplified in a field test using an unmanned aerial vehicle sprayer (UAVS). Our findings provide valuable insights into the monitoring and quantification of pesticide drift at close range using LiDAR technology, paving the way for more precise and efficient drift assessment methodologies.

Sub-50 fs temporal resolution in an FEL-optical laser pump-probe experiment at FLASH2.

High temporal resolution is essential for ultra-fast pump-probe experiments. Arrival time jitter and drift measurements, as well as their control, become critical especially when combining XUV or X-ray free-electron lasers (FELs) with optical lasers due to the large scale of such facilities and their distinct pulse generation processes. This paper presents the application of a laser pulse arrival time monitor that actively corrects the arrival time of an optical laser relative to the FEL's main optical clock. Combined with post-analysis single pulse jitter correction this new approach improves the temporal resolution for pump-probe experiments significantly. Benchmark measurements on photo-ionization of xenon atoms performed at FLASH beamline FL26, demonstrate a sub-50 fs FWHM overall temporal resolution.