Experimental Precision Research Articles

Site‐specific weed management on organic grain farms using variable rate seeding and data driven simulation

AbstractIntegrated weed management is integral to organic farming, with increased crop seeding rates as one effective weed suppression tactic. Precision agriculture, which uses guidance and sensor technologies to direct site‐specific management, could allow for targeted weed management using variable seeding rates. On farm precision experimentation (OFPE) can be used to predict site‐specific sub‐field weed biomass response to a range of varied crop and cover crop seed rates across whole fields to provide decision support directly to farmers. We used OFPE to compare five simulated precision seeding strategies to either maximize net return or minimize weed biomass. Five site‐years of OFPE data were collected from organic farms in Manitoba, Canada and Montana, USA. Seeding rate, weed biomass, crop yield, topographic variables and other remotely sensed data were collected on a 10‐m grid to model yield and weed response to seeding rates for each field. Simulated site‐specific variable seeding rate net returns improved upon farmer chosen uniform seeding rate net returns on average by $115 ha−1. When variable seeding rates were optimized to minimize weed biomass, simulated weeds were reduced on average by 10 kg ha−1 relative to the farmer chosen uniform seed rates. A combined variable rate approach which balanced net return and weed minimization improved both net return and weed suppression compared to farmer‐chosen seeding rates in every site‐year. The various seeding rate strategies represent different methods from which farmers can choose to implement OFPE to optimize sub‐field‐specific planting rates and to increase their field‐scale ecological knowledge.

Behavioral Experiments Online?

Online experiments offer several advantages over traditional laboratory experiments. However, for reaction time experiments, precise stimulus presentation and response detection is crucial. The precision of online experiments could be compromised due to increased variance arising from varying hardware configurations among participants, lack of control over experimental conditions, and the absence of an examiner. In this study, we conducted an online experiment using the avatar-Simon task to investigate whether small differences in reaction times could be examined using online experiments conducted with the experimental toolkit PsyToolkit. In the avatar-Simon task, participants respond to the color of vertically presented stimuli in front of avatars by pressing a left or right button. Reactions are faster when the position of the stimulus, defined from the avatar's point of view, matches the position of the response. Compared to the previous laboratory experiment, we observed lower effect sizes and more timeouts but were able to replicate the avatar-Simon effect overall. Based on further distributional and reliability analyses, PsyToolkit appears to be suitable tool to detect behavioral effects in the range of tens of milliseconds. We discuss differences and similarities with the original laboratory study and suggest how to address potential problems associated with online experiments.

Proposal of methods for determining the optimal size of experimental plots

Adequate planning of experiments is extremely important and for this to occur, the appropriate choice ofplot size is essential. Thus, determining the plot size seeks to increase experimental precision, since precision decreases when a plot size smaller than the ideal is chosen; on the other hand, when opting for plot sizes larger than the ideal, the researcher may use more resources than necessary, as well as increasing the time to set up the experiment. Therefore, this work aimed to propose two new methods for determining the optimal size of experimental plots, which were applied in experiments with yellow passion fruit in the field, and compare them to the modified maximum curvature method. The maximum curvature method of the modified Vx function uses the equation proposed by Smith and the maximum curvature method of the modified CVx function uses the equation proposed by Thomas. The modified maximum curvature method of the CV(x) function proved to be suitable for estimating the optimal size of plots in experiments with yellow passion fruit. It is recommended to use the optimal plot size of 4 plants per plot for variables related to the fruit, 5 plants per plot for variables related to the pulp and for the production variables of 9 plants per plot.

A General Model for the Ductility of Intermetallics Applied to Fe-Co Alloys

The mechanical properties, specifically ductility, of high performing soft magnets such as Fe-Co alloys are a limiting factor to their broader use in a number of systems. The understanding of the mechanical robustness in these materials is currently insufficient to be able to support the growing interest in applications such as magnetic shielding or electric motors. Fe-Co alloys provide the highest commercially available magnetic saturation and high magnetic permeability but have very poor ductility. The addition of vanadium to these alloys has allowed for significant commercialization and some ductility improvements, but the fundamental reasons for the observed improvements are not well understood. In most published work on mechanical properties in these alloys, the precise chemistry of the alloys investigated, often a critical aspect of intermetallics, is not reported or controlled and thermal history is unclear. This work creates a ductility model that is sensitive to changes in chemistry and can predict relative strain to failure as well as brittle fracture mode for intermetallics and is applied to Fe-Co alloys. Through the application of density functional theory (DFT), this model identifies defect stabilities, anti-phase boundary (APB) energies, the energy necessary to cross-slip, and cleavage energies and combines them through energetic competition to determine a relative failure strain. The model correctly predicts ductility improvements with the addition of vanadium as well as the transition from intergranular to transgranular cleavage, though more precise experiments are necessary to appropriately validate the various improvements observed.

Computational Analysis of Cell Type-Specific Transcriptional Dynamics in Major Depressive Disorder

Depression, also known as major depressive disorder (MDD), is a complex mental health condition that affects millions of people worldwide. Since disease treatments often depend on levels of understanding, this project strives to learn more about the transcriptional components of MDD to delineate the transcriptomic dynamics in MDD. The sample includes the single-cell transcriptomic profiles in the dorsolateral prefrontal cortex (dlPFC) of 34 postmortem patients. This data was acquired from publicly available datasets and run through R-Studio code. Cell clusters were classified into cell types using cell-type-specific signature markers in the original resource datasets. After analyzing immediate early genes (IEGs), MDD-associated genes, and differentially expressed genes, the trend showed broadly lowered expression levels and frequency in MDD patients than in healthy control with some exceptions. After studying 10 different IEGs, the trend showed a lowered gene expression frequency in MDD patients than in control. For MDD-associated genes, a similar trend showed lower frequency and expression levels in the MDD sample, apart from GAD1 and RELN, which had a higher expression level in the MDD sample. Then, by analyzing the top differentially expressed genes in each cell type, most cells showed a lowered frequency in MDD patients besides macrophage/microglial, which had higher expression frequency in IGHG1 and RP11-315A16.1 for the control sample. With each analytical finding, the underlying elements of MDD may be better understood, leading to more precise wet lab experiments and the eventual treatment of MDD.

Prospect of measuring the top quark mass through energy correlators

Reaching a high precision of the top quark mass is an important task of the Large Hadron Collider. We perform a feasibility study of measuring the top quark mass through the three-point energy correlator. The expected sensitivity of the top quark mass in the boosted regime is presented. We further introduce its application to the low top pT regime and demonstrate that both the W boson and the top quark masses could be extracted from this single observable. Compared to traditional observables, the energy correlator shows robustness to uncertainties that usually dominate experimental measurements and provides a promising way to improve experimental precision.

Principles and prospects of Bose-Einstein correlation study at BESIII* *This study was supported by the National Key R&D Program of China (2020YFA0406403) and the National Natural Science Foundation of China (11275211, 11335008, 12035013)

One method for determining the characteristic parameters of a hadron production source is to measure the Bose-Einstein correlation functions. In this study, we present fundamental concepts and formulas related to the Bose-Einstein correlations, focusing on the measurement principles and the Lund model from an experimental perspective. We perform Monte Carlo simulations using the Lund model generator in the 2–3 GeV energy range. Through these feasibility studies, we identify key features of the Bose-Einstein correlations that offer valuable insights for experimental measurements. Utilizing data samples collected at BESIII, we perform measurements of the Bose-Einstein correlation functions, with an expected experimental precision of a few percent for the hadron source radius and incoherence parameter.

Adaptability and Stability of Irrigated Barley Genotypes in the Cerrado of the Federal District

Barley (Hordeum vulgare L.) is a significant cereal globally, widely used in human and animal food. Furthermore, it has a strong influence on genotype-by-environment interactions, being considered a highly adaptable crop. This study aimed to estimate the parameters of adaptability and stability for 17 barley genotypes, compared with two controls (BRS 180 and BRS 195) grown under irrigation in the Cerrado. The experiments were conducted from 2017 to 2020, from May to September, in two different experimental areas of Embrapa in the Federal District, Brazil. Five traits were evaluated: 1. Esti mated grain yield (kg ha−1); 2. CL1—commercial classification of first grains (>2.5 mm) (%); 3. TGW—1000-grain weight (g); 4. plant height (cm); 5. cycle—days after emergence to earing (days). The data obtained were analyzed for normality and homogeneity of variance, subjected to individual and joint analysis of variance, with means compared by Tukey’s test at 5% significance and the adaptability and stability parameters estimated for the genotypes. The coefficients of environmental variation (CV%) were generally low, indicating good experimental precision. The PFC 2006053 and PFC 2006054 genotypes have broad adaptability and high stability for most traits and outperformed the controls and the overall experiment average.

B-231 Evaluation of the KingFisher Flex for DNA Isolation From FFPE Tissue Utilizing Autolys M Tubes and the MagMAX FFPE DNA/RNA Ultra Kit

Abstract Background Our institution is facing increasing demand for oncology testing that requires high quality DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissue. The current DNA extraction workflow involves a time and labor-intensive manual process that limits our ability to accommodate increasing downstream clinical testing volumes. We evaluated the KingFisher (KF) Flex utilizing Autolys M Tubes and the MagMAX FFPE DNA/RNA Ultra Kit as a possible high-throughput, automated DNA isolation workflow option that would decrease hands-on time and be conducive to volume growth without the need for additional staff. Methods DNA from 52 FFPE tissue samples (n=24 unique cases previously extracted by the current “manual method”) were extracted using Autolys M tubes, the MagMAX FFPE DNA/RNA Ultra Kit, and the KF Flex (Thermo Fisher Scientific Waltham, MA) over 4 “automated method” runs. Method modifications to the published procedure were introduced over the runs to determine any effects on DNA quality/quantity. Timings were taken during each run to compare hands-on and total run time against that of the manual method. Precision experiments were performed by extracting 4 replicates of sample on a single run (intra-assay precision) and 2 samples from 2 cases over 2 runs (inter-assay precision). Three cases were processed using varying tissue input levels to assess input-yield correlation. DNA yield was measured using HS dsDNA Qubit (Thermo Fisher Scientific, Waltham, MA). A subset of samples was tested by digital droplet PCR (ddPCR) (n=10), chromosomal microsomal microarray (CMA) (n=1), and next-generation sequencing (NGS) (n=3). Variants and QC metrics of the KF DNA were compared to those of the manual method DNA. Results The average total DNA yield was 3% lower from samples extracted following the manufacturer recommended KF procedure compared to matched samples extracted using the manual method (n=28 samples from 23 unique cases). A CV of 2.8% was observed in an intra-assay experiment (n=4 replicates from 1 case) and 3.0% in an average inter-assay experiment (n=2 replicates from 2 cases). There was a direct correlation between the tissue input amount (4 amounts of varied tissue input) and the total DNA yield (n=3 samples). We observed concordant fractional abundance values for ddPCR samples and concordant variant detection for NGS and CMA samples. We did not see a significant difference in the quality metrics tracked for any of the downstream testing assays. Conclusions This evaluation demonstrated that, as compared to our manual method, the automated method resulted in comparable DNA yields and downstream assay results. The incorporation of this automation would significantly increase our FFPE DNA extraction capacity without requiring additional staff while reducing hands-on time per run by about six hours. We would also be able to reduce ergonomic hazards related to tube cap manipulation, eliminate use of hazardous reagents, and leverage the plate format to better integrate extracted DNA into our clinical sample preparation workflows. These operational benefits highlight the value of automating high-throughput workflows.

Measurements of Lund subjet multiplicities in 13 TeV proton-proton collisions with the ATLAS detector

This Letter presents a differential cross-section measurement of Lund subjet multiplicities, suitable for testing current and future parton shower Monte Carlo algorithms. This measurement is made in dijet events in 140 fb−1 of s=13 TeV proton–proton collision data collected with the ATLAS detector at CERN's Large Hadron Collider. The data are unfolded to account for acceptance and detector-related effects, and are then compared with several Monte Carlo models and to recent resummed analytical calculations. The experimental precision achieved in the measurement allows tests of higher-order effects in QCD predictions. Most predictions fail to accurately describe the measured data, particularly at large values of jet transverse momentum accessible at the Large Hadron Collider, indicating the measurement's utility as an input to future parton shower developments and other studies probing fundamental properties of QCD and the production of hadronic final states up to the TeV-scale.

Optimizing crop seeding rates on organic grain farms using on farm precision experimentation

Organic agriculture is often regarded as less damaging to the environment than conventional agriculture, though at the expense of lower yields. Field-specific precision agriculture may benefit organic production practices given the inherent need of organic farmers to understand spatiotemporal variation on large-scale fields. Here the primary research question is whether on-farm precision experimentation (OFPE) can be used as an adaptive management methodology to efficiently maximize farmer net returns using variable cover crop and cash crop seeding rates. Inputs of cash crop seed and previous-year green manure cover crop seed were experimentally varied on five different farms across the Northern Great Plains from 2019 to 2022. Experiments provided data to model the crop yield response, and subsequently net return, in response to input (seeding) rates plus a suite of other spatially explicit data from satellite sources. New, field-specific spatially explicit optimum input rates were generated to maximize net return including temporal variation in economic variables. Inputs were spatially optimized and using simulations it was found that the optimization strategies consistently out-performed other strategies by reducing inputs and increasing yields, particularly for non-tillering crops. By adopting site specific management, the average increase in net return for all fields was $50 ha−1. These results showed that precision agriculture technologies and remote sensing can be utilized to provide organic farmers powerful adaptive management tools with a focus on within-field spatial variability in response to primary input drivers of economic return. Continued OFPE for seeding rate optimization will allow quantification of temporal variability and subsequent probabilistic recommendations.

Comprehensive Analysis of Impurity Detection in Linear Alkyl Benzene–Based Liquid Scintillators Using Infrared Spectroscopy for Enhanced Neutrino Detection

Abstract We present a comprehensive analysis of infrared (IR) spectra for linear alkyl benzene (LAB)-based scintillation solutions, focusing on the detection and identification of impurities. Previous research primarily utilized ultraviolet-visible spectroscopy to investigate electronic structures and transitions, whereas our approach emphasizes vibrational transitions and IR spectral characteristics. We specifically examined the presence of common impurities, such as acetone, water, and three impurity compounds (IMP1, IMP2, and IMP3) identified by the JUNO Collaboration. Acetone, a common contaminant from cleaning procedures, was detected by its characteristic absorption peaks at 1200, 1360, and 1700 $\rm {cm}^{-1}$. Water, an inevitable by-product of Gd-loaded LAB using a neutralization reaction process, was identified through distinct O-H stretching and H-O-H bending vibrations at 3200–3600 $\rm {cm}^{-1}$ and 1600 $\rm {cm}^{-1}$, respectively. The IR spectra of IMP1, IMP2, and IMP3 were theoretically calculated, revealing unique absorption bands for key functional groups, including carbonyl (C=O), amide (C-N), sulfoxide (S=O), aryl chloride (Ar-Cl), azo (N=N), and ether (C-O-C) groups. The findings confirm the absence of these impurities in the LAB (+ 2,5-Diphenyloxazole [PPO] + 1,4-Bis(2-methylstyryl)benzene [bis-MSB]) sample, ensuring the high performance and accuracy of neutrino detectors. This study demonstrates the effectiveness of IR spectroscopy as a powerful analytical tool for quality assurance in liquid scintillation solutions, providing a robust framework for enhancing the reliability and precision of neutrino detection experiments.

Comparative Study on Precision and Interference of Maltose and Vitamin C among three Glucometers Commonly Used in United Arab Emirates [U.A.E

Aim: To evaluate the suitability of commercially available glucometers in the UAE in terms of accurate and reliable blood glucose measurements. Background: Portable glucometers are employed for measuring blood glucose levels, offering distinct advantages such as providing instant results and being user-friendly when compared to laboratory reference analyzers. However, certain molecules, such as those found in medications, can interfere with the accuracy of glucometer readings. Objective: To evaluate the precision and interference in the presence of maltose and vitamin C of three glucometers commercially available in the UAE. Results: Accu-Chek InstantTM demonstrated the highest precision among the glucometers tested, with a coefficient of variation of less than 5% for all measured glucose values. In contrast, OneTouch Select Plus FlexTM and Trister GlucoscanTM exhibited higher variability in precision, with coefficients of variation of 11.4% and 11%, respectively. Accu-Chek InstantTM consistently performed well in terms of bias and precision in the presence of interferences, and does not display glucose readings above 50mg/dL of Vitamin C. Notably, Ascorbic acid induced a greater bias compared to Maltose for all three glucometers. Methods: We utilized plasma samples to conduct two types of experiments: a precision experiment and an interference experiment. We compared the precision of three glucometer brands available in the United Arab Emirates [Accu-Chek InstantTM, One Touch Select Plus FlexTM, and Trister GlucoScanTM] in the presence or not of various interfering molecules, such as Maltose and Ascorbic Acid [Vitamin C]. Conclusion: The performance of the glucometer is affected by its testing methodology. Accu-Chek InstantTM shows improved precision and is able to detect the presence of Vitamin C. When it comes to Maltose interference, it results in a higher bias change but lower variability, which can be addressed by applying a correction factor.

Atomic binding corrections for high-energy fixed target experiments

High-energy beams incident on a fixed target may scatter against atomic electrons. To a first approximation, one can treat these electrons as free and at rest. For precision experiments, however, it is important to be able to estimate the size of, and when necessary calculate, subleading corrections. We discuss atomic binding corrections to relativistic lepton-electron scattering. We analyze hydrogen in detail, before generalizing our analysis to multi-electron atoms. Using the virial theorem, and many-body sum rules, we find that the corrections can be reduced to measured binding energies, and the expectation value of a single one-body operator. We comment on the phenomenological impact for neutrino flux normalization and an extraction of hadronic vacuum polarization from elastic muon electron scattering at MUonE. Published by the American Physical Society 2024

Cosmic-dawn 21-cm signal from dynamical dark energy

The 21-cm signal is the most important measurement for us to understand physics during cosmic dawn. It is the key for us to understand the expansion history of the Universe and the nature of dark energy. In this paper, we focused on the characteristic 21-cm power spectrum of a special dynamic dark energy – the Interacting Chevallier-Polarski-Linder (ICPL) model – and compared it with those of the ΛCDM and CPL models. From the expected noise of HERA, we found more precise experiments in the future can detect the features of interacting dark energy in the 21-cm power spectra. By studying the brightness temperature, we found the ICPL model is closer to the observation of EDGES compared to the ΛCDM, thus alleviating the tension between theory and experiments.

Experimental and numerical analysis of ballistic impat and material characterization of GFRP and Kevlar 29/epoxy composite laminate

Through experimental testing and numerical simulations, this study examines the effects of ballistic events on thin FRP composite laminated plates fabricated using a hand lay-up method. Experimental ballistic impact tests using a pneumatic gun are conducted on composite plates reinforced with woven glass and woven Kevlar 29 fibers. An advanced three-dimensional finite element model programed in Ansys/Autodyn v19.1 is employed to verify the experimental findings and analyze the ballistic perforation characteristics of the target. The crucial material constants needed for the constitutive material model used in the simulation are acquired through precise experimentation on samples prepared from the fabricated laminates. Significant agreement is observed between the FE simulations and experimental findings, particularly concerning the assessment of residual velocities of the projectile and damage pattern in the laminates. The results of this study show that when subjected to ballistic impact by a flat-ended cylindrical projectile, the thin woven FRP composite primarily experiences damage characterized by delamination, fiber breakage and matrix cracking. Additionally, based on current simulations, it is observed that the ballistic limit velocity of the Kevlar 29/epoxy laminate exceeds that of GFRP by 25.64% when both materials have an equal thickness of 2.8 mm.

Tectonic Physical Simulation Experiments: Evolution from Qualitative Exploration to Quantitative Analysis and Future Prospects

This review synthesizes the historical development, research methodologies, and current scientific issues of tectonic physical simulation experiments, while also looking forward to future research directions in the field. Since the early 19th century when James Hall first simulated fold formation, the field has undergone a transition from qualitative studies to quantitative analysis. We analyze key research and technological advancements across the early exploration, mid-term development, and late maturation stages, with a particular focus on the introduction and application of the similarity principles, as well as the incorporation of Particle Image Velocimetry (PIV) technology. Despite significant progress, challenges remain in the selection of experimental materials, precise application of similarity principles, and experimental precision. Future research should explore new materials, interdisciplinary collaboration, and the application of big data technology to enhance the accuracy and reliability of simulation experiments.

An enhanced approach for predicting air pollution using quantum support vector machine

The essence of quantum machine learning is to optimize problem-solving by executing machine learning algorithms on quantum computers and exploiting potent laws such as superposition and entanglement. Support vector machine (SVM) is widely recognized as one of the most effective classification machine learning techniques currently available. Since, in conventional systems, the SVM kernel technique tends to sluggish down and even fail as datasets become increasingly complex or jumbled. To compare the execution time and accuracy of conventional SVM classification to that of quantum SVM classification, the appropriate quantum features for mapping need to be selected. As the dataset grows complex, the importance of selecting an appropriate feature map that outperforms or performs as well as the classification grows. This paper utilizes conventional SVM to select an optimal feature map and benchmark dataset for predicting air quality. Experimental evidence demonstrates that the precision of quantum SVM surpasses that of classical SVM for air quality assessment. Using quantum labs from IBM’s quantum computer cloud, conventional and quantum computing have been compared. When applied to the same dataset, the conventional SVM achieved an accuracy of 91% and 87% respectively, whereas the quantum SVM demonstrated an accuracy of 97% and 94% respectively for air quality prediction. The study introduces the use of quantum Support Vector Machines (SVM) for predicting air quality. It emphasizes the novel method of choosing the best quantum feature maps. Through the utilization of quantum-enhanced feature mapping, our objective is to exceed the constraints of classical SVM and achieve unparalleled levels of precision and effectiveness. We conduct precise experiments utilizing IBM’s state-of-the-art quantum computer cloud to compare the performance of conventional and quantum SVM algorithms on a shared dataset.

Establishing CRISPR-Cas9 in the sexually dimorphic moss, Ceratodon purpureus.

The development of CRISPR technologies provides a powerful tool for understanding the evolution and functionality of essential biological processes. Here we demonstrate successful CRISPR-Cas9 genome editing in the dioecious moss species, Ceratodon purpureus. Using an existing selection system from the distantly related hermaphroditic moss, Physcomitrium patens, we generated knock-outs of the APT reporter gene by employing CRISPR-targeted mutagenesis under expression of native U6 snRNA promoters. Next, we used the native homology-directed repair (HDR) pathway, combined with CRISPR-Cas9, to knock in two reporter genes under expression of an endogenous RPS5A promoter in a newly developed landing site in C. purpureus. Our results show that the molecular tools developed in P. patens can be extended to other mosses across this ecologically important and developmentally variable group. These findings pave the way for precise and powerful experiments aimed at identifying the genetic basis of key functional variation within the bryophytes and between the bryophytes and other land plants.

Video watching and hands-on experiments to learn science: what can each uniquely contribute?

An experimental group and control group pretest and posttest design was used to conduct qualitative coding and quantitative analysis on two classes in grade 5. The aim was to investigate whether science education videos can be used in place of simulation experiments. The results showed that (1) in terms of scientific knowledge, the difference between science videos and hands-on experiments was not significant; (2) in terms of modeling capability, the hands-on class had better results regarding the perception and application of materials; and (3) more precise experiments had better effects on health behavior, but there was no significant difference between imprecise experiments and science videos. In the absence of laboratory equipment, science videos could therefore be an alternative solution.