Principles Of Experimental Design Research Articles

A Combined Paddy Field Inter-Row Weeding Wheel Based on Display Dynamics Simulation Increasing Weed Mortality

Weeds compete with rice for sunlight and nutrients and are prone to harboring pathogens, leading to reduced rice yields. Addressing the issues of low weeding efficiency and weed mortality rates in existing inter-row weeding devices, the study proposes the design of a combination paddy field inter-row weeding wheel. The device’s operation process is theoretically analyzed based on the weed control requirements in the northeastern region of China, leading to the determination of specific structural parameters. This research conducted experiments on the mechanical properties of weed cutting to obtain geometric parameters for paddy field weeds. It was found that the range for the cutting gap of the dynamic–fixed blade is between 0.6 mm to 1.4 mm and the cutting angle is between 5° to 15°, resulting in the lowest peak cutting force for weeds. Using LS-DYNA R12.0.0 dynamic simulation software, a fluid–structure interaction (FSI) model of the weeding wheel–water–soil system was established. By employing the central composite experimental design principle and considering the soil stir rate and coupling stress as indicators, the optimal structural parameter combination for the device is obtained: a dynamic–fixed blade cutting gap of 1.4 mm, a cutting angle of 10.95°, and a dynamic blade install angle of −3.44°. Field experiments demonstrated that the device achieved an average weeding rate of 89.7% and an average seedling damage rate of 1.9%, indicating excellent performance. This study contributes to improving weed mortality rates and provides valuable guidance for inter-row mechanical weeding technology.

Machine learning for bending behavior of sandwich beams with 3D‐printed core and natural fiber‐reinforced composite face sheets

AbstractThe primary objective of this study was to demonstrate the effectiveness of machine learning (ML) in predicting the mechanical behavior of sandwich structures. To achieve this, the study focused on assessing the bending response of environmentally friendly sandwich beams consisting of auxetic cores made from polylactic acid (PLA) and flax/epoxy composite face sheets reinforced with halloysite nanotubes (HNTs). Two ML techniques, specifically shallow neural networks (SNNs) and deep neural networks (DNNs), were employed to predict the specific energy absorption (SEA) and load‐deflection curves of these sandwich beams, respectively. The key design parameters under consideration included the HNT content in the face sheets and three geometric characteristics of the auxetic cells. Subsequently, 16 distinct specimens were meticulously designed for manufacturing, following Taguchi's experimental design principles. The cores of the structures were produced using 3D printing techniques, while the face sheets were meticulously fabricated using a hand layup process. These prepared specimens were then subjected to a three‐point bending test, and the collected data were employed to train the aforementioned neural networks. The outcomes of this study revealed that an SNN with a single hidden layer comprising seven neurons effectively predicted the SEA of the structures across various design parameter values. Additionally, the remarkable performance of a DNN, consisting of five hidden layers with 128, 64, 32, 16, and 8 units, respectively, was demonstrated by comparing its predicted results with the experimental results for a randomly designed sandwich beam.Highlights ML techniques were used for bending behavior of sandwich beams. The beams were made of flax/epoxy/HNT face sheets and 3D‐printed auxetic core. SNN was successfully employed to predict the SEA of the structures. DNN effectively predicted the load‐deflection curves. HNT content and auxetic cells significantly impacted the bending properties.

Optimization of the Green Fibre Paper Film Preparation Process Based on Box–Behnken Response Surface Methodology

To improve the utilization rate of flax straw and the clean treatment of livestock manure, an experimental study was conducted on the process and performance of making fibre paper films by mixing cow dung and flax straw fibre. Cow dung and flax straw were used as the main raw materials, and functional additives were not added. The whole technological process of the pretreatment, the beating process, the determination of the beating degree, the basis weight of the paper, papermaking, drying, sample cutting, and the determination and analysis of the related mechanical properties of the film-making materials were studied. In this study, the Box–Behnken experimental design principle in the response surface methodology was adopted, and the effect of each factor on the tensile strength and tear strength of fibre paper film made of mixed fibres was determined using the combined experimental design comprising four factors and three levels centres. The results showed that the optimum technological parameters were as follows: the beating degree of the cow dung fibre was 37 °SR, the beating degree of the flax straw fibre was 85 °SR, the paper basis weight was 80 g/m2, and the addition of flax straw fibre was 65%. At a drying temperature of 80 °C and a drying time of 8 min, under the conditions of the hybrid fibre paper film placed in the laboratory environment (humidity of 30%~40%, temperature of 18 °C) for 24 h, the measured tensile strength was about 8.26 MPa, and the tear strength was about 19.91 N/mm. This study provides a reference that can be used for the further study of fibre paper film.

Investigating immersion and migration decisions for agent-based modelling: A cautionary tale

Background Agent-based modelling provides an appealing methodological choice for simulating human behaviour and decisions. The currently dominant approaches based on static transition rates or unverified assumptions are restrictive, and could be enhanced with insights from cognitive experiments on actual decision making. Here, one common concern is that standard surveys or experiments may lack ecological validity, limiting the extent to which research findings can be generalised to real-life settings. For complex, highly emotive decision-making scenarios, such as those related to migration, the typically used short, methodical survey questions may not appropriately map onto complex real-world decisions of interest. Immersive contexts may offer more accurate representations of reality, potentially enhancing the usefulness of experimental information in multi-disciplinary modelling endeavours. Methods This pre-registered study of migration decisions, aimed at informing a multi-disciplinary construction of an agent-based model of migration, presents a choice-based interactive fiction game in which players make migration decisions to advance through a story. Participants (N = 1000 Prolific users) were randomly assigned to one of four experimental conditions, three involving different renditions of the game attempting to create immersion, with the last condition presenting the decisions in standard survey format. Results Although addressing the lack of ecological validity in survey data is important for improving agent-based modelling methodology, the experimental design used to tackle this issue, while responding directly to modelling needs, proved too complex. The created experimental conditions ended up too distinct from each other, involving stimuli that differed in quantity and content. This introduced several unintended and uncontrolled confounds, making it impossible to meaningfully interpret the results of this experiment on its own. Our results act as a cautionary tale for agent-based modellers, highlighting that the modelling needs should not override the principles of experimental design, and provide motivation for more rigorous research on this topic.

Simulation and Experiment of Fertilizer Discharge Characteristics of Spiral Grooved Wheel with Different Working Parameters

Fertilizer particles have strong hygroscopicity and agglomeration often occurs during their storage, which leads to a blocked phenomenon during the operation of the external grooved wheel fertilizer discharger. In this study, the bond model of fertilizer block was constructed based on the discrete element method (DEM) to further explore the effect of different working parameters of the spiral grooved wheel on the fertilizer discharge characteristics. According to the Box–Behnken experimental design principle, a three-factor and three-level simulation experiment was carried out with the factors of grooved wheel speed, grooved wheel section shape, and spiral rise angle. The simulation results showed the variation coefficient of fertilizer uniformity was affected, from important to secondary, mainly by the rotating speed of the grooved wheel, the cross-sectional shape of the grooved wheel, and the spiral rise angle. The broken rate of fertilizer block bond was affected, from important to secondary, mainly by the spiral rise angle, the cross-sectional shape of the grooved wheel, and the rotational speed of the grooved wheel. The optimal combination of working parameters was obtained by optimizing and analyzing the data; the rotating speed of the grooved wheel was 21 r/min, the scoop section, and the spiral rise angle was 70°. Under the best working parameters, the variation coefficient of fertilizer uniformity was 8.56%, and the broken rate of fertilizer block bond was 97.67%. The validation experiment results showed that the variation coefficient of fertilizer uniformity was 9.23%, the broken rate of fertilizer block bond was 94.28%, and the relative data error was less than 10%. The experimental results are close to the simulation results. The research results can provide a reference for the structural design and parameter optimization of spiral grooved wheel fertilizer discharger.

Row selection in remote sensing from four-row plots of maize and sorghum based on repeatability and predictive modeling.

Remote sensing enables the rapid assessment of many traits that provide valuable information to plant breeders throughout the growing season to improve genetic gain. These traits are often extracted from remote sensing data on a row segment (rows within a plot) basis enabling the quantitative assessment of any row-wise subset of plants in a plot, rather than a few individual representative plants, as is commonly done in field-based phenotyping. Nevertheless, which rows to include in analysis is still a matter of debate. The objective of this experiment was to evaluate row selection and plot trimming in field trials conducted using four-row plots with remote sensing traits extracted from RGB (red-green-blue), LiDAR (light detection and ranging), and VNIR (visible near infrared) hyperspectral data. Uncrewed aerial vehicle flights were conducted throughout the growing seasons of 2018 to 2021 with data collected on three years of a sorghum experiment and two years of a maize experiment. Traits were extracted from each plot based on all four row segments (RS) (RS1234), inner rows (RS23), outer rows (RS14), and individual rows (RS1, RS2, RS3, and RS4). Plot end trimming of 40cm was an additional factor tested. Repeatability and predictive modeling of end-season yield were used to evaluate performance of these methodologies. Plot trimming was never shown to result in significantly different outcomes from non-trimmed plots. Significant differences were often observed based on differences in row selection. Plots with more row segments were often favorable for increasing repeatability, and excluding outer rows improved predictive modeling. These results support long-standing principles of experimental design in agronomy and should be considered in breeding programs that incorporate remote sensing.

OPTIMIZATION OF THE MANUFACTURING OF METASEQUOIA-BASED THREE-LAYER STRUCTURE PARQUET FLOORING BY A RESPONSE SURFACE METHODOLOGY

On the basis of a single-factor experiment, a mathematical model was established by the response surface analysis method based on the Box-Behnken experimental design principle. The effects of three factors, including hot-pressing temperature, hot-pressing time, and hot-pressing pressure, and their interactions on the modulus of rupture (MOR) of Metasequoia-based three-layered structure parquet flooring were studied. The results show that the quadratic polynomial model in the regression equation is significant, and the correlation between the value predicted by the model and the experimental value is 91.17%. The optimized best hot-pressing process parameters are determined to be as follows: hot-pressing temperature of 96.03°C, hot-pressing time of 6.70 min, and hot-pressing pressure of 8 kg·cm-2. Under these conditions, the best MOR are obtained, reaching a value of 102.05 MPa. The theoretically predicted value is in good agreement with the experimental results.

Performance simulation and perforated parameters optimize for perforated wells with compaction zone and drilling damage in tight gas reservoirs

It is essential to understand how to improve the production of perforated well in tight reservoirs. In this paper, based on the experiment of experiment evaluation of perforation tunnel and perforation compaction zone, the drilling mud invasion zone and stress sensitivity, a new productivity numerical model is established considering the damaged zone being drilling, and the compaction zone being penetrated and the sensitivity in tight gas reservoirs. Considering perforation interaction, drill damage and seepage interference, the production rate under different parameters of perforation, compaction zone, damaged zone is discussed to yield the highest productivity. The numerical results show that it exists an optimal hole density in specific formation and when the perforated hole penetrates the invasion zone, increasing the depth of the perforation hole by the same amount would not result in a significant increase in gas production. The invasion and compaction zone permeability have little effect on the cumulative gas production, but an inflexion point still existed. Further, according to the principle of orthogonal experimental design, forty-one groups of orthogonal experimental calculations are designed and conducted. By analyzing the experimental results, the perforation density, hole diameter, invasion thickness, compaction zone thickness, invasion permeability, compaction zone permeability and stress sensitivity on productivity of perforated well is in descending order. The work presented in this paper can offer a technological basis and theoretical foundation for optimizing perforation parameters in specific tight gas reservoirs.

Discussion of ‘Is designed data collection still relevant in the Big Data era?'

AbstractGiven the popularity of Big Data (BD), there can be an impression that fields such as design of experiments (DOE) are now irrelevant. We would like to thank the authors for starting the conversation about the possible relationship between these two fields. A key contribution of this paper is in showing how DOE principles, as summarized under the name designed data collection (DDC), can be applied throughout the BD process. This name is quite appropriate, demonstrating that these principles apply not just to designed experiments, but to any form of data collection. This is especially important for situations where designed experiments are either impossible (i.e., assessing how a country's economy may impact certain responses) or unethical (i.e., certain sensitive types of medical studies). It shows that DOE is more than a particular choice of design type, but is rather a methodology for approaching data collection. One that seeks to extract the most relevant information from the data while also taking into account the various nuances and constraints of physical and social processes, which are ever present, even in massive datasets. The paper divides BD efforts into three general phases: Before BD, During BD, and After BD. As such, we have grouped our discussion accordingly, with general comments provided for the suggested contributions of DDC in each phase. We then close with some additional thoughts.

Is designed data collection still relevant in the big data era? – A discussion

Is designed data collection still relevant in the big data era? – A discussion

Rapid Development of Cell State Identification Circuits with Poly-Transfection.

Mammalian genetic circuits have demonstrated the potential to sense and treat a wide range of disease states, but optimization of the levels of circuit components remains challenging and labor-intensive. To accelerate this process, our lab developed poly-transfection, a high-throughput extension of traditional mammalian transfection. In poly-transfection, each cell in the transfected population essentially performs a different experiment, testing the behavior of the circuit at different DNA copy numbers and allowing users to analyze a large number of stoichiometries in a single-pot reaction. So far, poly-transfections that optimize ratios of three-component circuits in a single well of cells have been demonstrated; in principle, the same method can be used for the development of even larger circuits. Poly-transfection results can be easily applied to find optimal ratios of DNA to co-transfect for transient circuits or to choose expression levels for circuit components for the generation of stable cell lines. Here, we demonstrate the use of poly-transfection to optimize a three-component circuit. The protocol begins with experimental design principles and explains how poly-transfection builds upontraditional co-transfection methods. Next, poly-transfection of cells is carried out and followed by flow cytometry a few days later. Finally, the data is analyzed by examining slices of the single-cell flow cytometry data that correspond to subsets of cells with certain component ratios. In the lab, poly-transfection has been used to optimize cell classifiers, feedback and feedforward controllers, bistable motifs, and many more. This simple but powerful method speeds up design cycles for complex genetic circuits in mammalian cells.

Single-Case Experimental Design in Rehabilitation: Basic Concepts, Advantages, and Challenges.

Single-case experimental design is a family of experimental methods that can be used to examine the efficacy of interventions by testing a small number of patients or cases. This article provides an overview of single-case experimental design research for use in rehabilitation as another option along with traditional group-based research when studying rare cases and rehabilitation interventions of unknown efficacy. Basic concepts related to single-case experimental design and the characteristics of common subtypes ( N-of-1 randomized controlled trial, withdrawal design, multiple-baseline design, multiple-treatment design, changing criterion/intensity design, and alternating treatment design) are introduced. The advantages and disadvantages of each subtype are discussed along with challenges in data analysis and interpretation. Criteria and caveats for interpreting single-case experimental design results and their use in evidence-based practice decisions are discussed. Recommendations are provided for appraising single-case experimental design articles as well as using single-case experimental design principles to improve real-world clinical evaluation.

Investigating immersion and migration decisions for agent-based modelling: A cautionary tale

Background: Agent-based modelling provides an appealing methodological choice for simulating human behaviour and decisions. The currently-dominant approaches based on static transition rates or unverified assumptions are restrictive, and could be enhanced with insights from cognitive experiments on actual decision making. Here, one common concern is that standard surveys or experiments may lack ecological validity, limiting the extent to which research findings can be generalised to real-life settings. For complex, highly emotive decision-making scenarios, such as those related to migration, the typically-used short, methodical survey questions may not appropriately map onto complex real-world decisions of interest. Immersive contexts may offer more accurate representations of reality, potentially enhancing the usefulness of experimental information in multi-disciplinary modelling endeavours. Methods: This pre-registered study of migration decisions, aimed at informing a multi-disciplinary construction of an agent-based model of migration, presents a choice-based interactive fiction game in which players make migration decisions to advance through a story. Participants (N = 1000 Prolific users) were randomly assigned to one of four experimental conditions, three involving different renditions of the game attempting to create immersion, with the last condition presenting the decisions in standard survey format. Results: Although addressing the lack of ecological validity in survey data is important for improving agent-based modelling methodology, the experimental design used to tackle this issue, while responding directly to modelling needs, proved too complex. The created experimental conditions ended up too distinct from each other, involving stimuli that differed in quantity and content. This introduced several unintended and uncontrolled confounds, making it impossible to meaningfully interpret the results of this experiment on its own. Our results act as a cautionary tale for agent-based modellers, highlighting that the modelling needs should not override the principles of experimental design, and provide motivation for more rigorous research on this topic.

Testing three coping strategies for time pressure in categorizations and similarity judgments

This article compares three psychological mechanisms to make multi-attribute inferences under time pressure in the domains of categorization and similarity judgments. Specifically, we test if people under time pressure attend to fewer object features (attention focus), if they respond less precisely (lower choice sensitivity), or if they simplify a psychological similarity function (simplified similarity). The simpler psychological similarity considers the number of matching features but ignores the actual feature value differences. We conducted three experiments (two of them preregistered) in which we manipulated time pressure: one was a categorization task, which was designed based on optimal experimental design principles, and the other two involved a similarity judgment task. Computational cognitive modeling following an exemplar-similarity framework showed that the behavior of most participants under time pressure is in line with a lower choice sensitivity, this means less precise response selection, especially when people make similarity judgments. We find that the variability of participants’ behavior increases with time pressure, to a point where participants are unlikely to make inferences anymore but instead start choosing readily available response options repeatedly. These findings are consistent with related research in other cognitive domains, such as risky choices, and add to growing evidence that time pressure and other forms of cognitive load do not necessarily alter core cognitive processes themselves but rather affect the precision of response selection.

Single-Cell Proteomics Preparation for Mass Spectrometry Analysis Using Freeze-Heat Lysis and an Isobaric Carrier.

Single-cell proteomics analysis requires sensitive, quantitatively accurate, widely accessible, and robust methods. To meet these requirements, the Single-Cell ProtEomics (SCoPE2) protocol was developed as a second-generation method for quantifying hundreds to thousands of proteins from limited samples, down to the level of a single cell. Experiments using this method have achieved quantifying over 3,000 proteins across 1,500 single mammalian cells (500-1,000 proteins per cell) in 10 days of mass spectrometer instrument time. SCoPE2 leverages a freeze-heat cycle for cell lysis, obviating the need for clean-up of single cells and consequently reducing sample losses, while expediting sample preparation and simplifying its automation. Additionally, the method uses an isobaric carrier, which aids protein identification and reduces sample losses. This video protocol provides detailed guidance to enable the adoption of automated single-cell protein analysis using only equipment and reagents that are widely accessible. We demonstrate critical steps in the procedure of preparing single cells for proteomic analysis, from harvesting up to injection to liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Additionally, viewers are guided through the principles of experimental design with the isobaric carrier, quality control for both isobaric carrier and single-cell preparations, and representative results with a discussion of limitations of the approach.

Corrugation-Induced Active Sites on Pristine Graphene for H2 Activation

Pristine graphene is widely considered to be chemically inert, but recent experimental studies have suggested that it can provide frustrated Lewis pairs (FLPs) for activating H2 under mild conditions. Using density functional theory (DFT) and ab initio molecular dynamics (AIMD) calculations, we explore in this work the possibility that corrugation in pristine graphene is responsible for the formation of FLPs and thus its observed catalytic activity. Our DFT results demonstrate that the ease of H2 activation is proportional to the degree of corrugation of graphene. For corrugated graphene, the two catalytic para-carbon sites show clear signs of transient Lewis acid/base properties along the reaction coordinate, a pre-requisite for FLPs. Furthermore, the two dissociating H atoms carry opposite charges, suggesting heterolytic activation of H2. This behavior is confirmed by AIMD simulations at room temperature, which show that fluctuations of the corrugated graphene lead to C sites with diverse distances and varying charges. These observations offer a plausible rationalization of the experimental observations and possible design principles for FLP catalysts using homogeneous two-dimensional materials.

Understanding the importance of quality control and quality assurance in preclinical PET/CT imaging

The fundamental principle of experimental design is to ensure efficiency and efficacy of the performed experiments. Therefore, it behoves the researcher to gain knowledge of the technological equipment to be used. This should include an understanding of the instrument quality control and assurance requirements to avoid inadequate or spurious results due to instrumentation bias whilst improving reproducibility. Here, the important role of preclinical positron emission tomography/computed tomography and the scanner's required quality control and assurance is presented along with the suggested guidelines for quality control and assurance. There are a multitude of factors impeding the continuity and reproducibility of preclinical research data within a single laboratory as well as across laboratories. A more robust experimental design incorporating validation or accreditation of the scanner performance can reduce inconsistencies. Moreover, the well-being and welfare of the laboratory animals being imaged is prime justification for refining experimental designs to include verification of instrumentation quality control and assurance. Suboptimal scanner performance is not consistent with the 3R principle (Replacement, Reduction, and Refinement) and potentially subjects animals to unnecessary harm. Thus, quality assurance and control should be of paramount interest to any scientist conducting animal studies. For this reason, through this work, we intend to raise the awareness of researchers using PET/CT regarding quality control/quality assurance (QC/QA) guidelines and instil the importance of confirming that these are routinely followed. We introduce a basic understanding of the PET/CT scanner, present the purpose of QC/QA as well as provide evidence of imaging data biases caused by lack of QC/QA. This is shown through a review of the literature, QC/QA accepted standard protocols and our research. We also want to encourage researchers to have discussions with the PET/CT facilities manager and/or technicians to develop the optimal designed PET/CT experiment for obtaining their scientific objective. Additionally, this work provides an easy gateway to multiple resources not only for PET/CT knowledge but for guidelines and assistance in preclinical experimental design to enhance scientific integrity of the data and ensure animal welfare.

Characterization and optimization of the properties of untreated high land bamboo fibres

In this experimental study, untreated Ethiopian high land bamboo fibres were characterized and detected the optimal properties. In the investigation, SEM was applied to examine the surface texture of the fibres. The chemical bonds of the molecules (functional groups) were identified by Fourier transform infrared spectra (FTIR). The thermal properties of the fibre were explored with a thermogravimetric analyser, and the results were confirmed by differential thermo-gravimetric analysis (DTG). Mechanical properties were improved using the experimental design principle. The design is based on the RSM methodology three-factor three-level to present mathematical models. At various plant ages, the culm wall thickness in the radial direction and soaking duration of the single fibre is extracted using a roller crusher machine. The operating parameters and optimal mechanical properties were validated using confirmation tests. Breaking force 796.5cN, tenacity 46.8cNtex-1, work done 456cNmm, and modulus 1814cNtex-1 were the optimal mechanical characteristics achieved at the operating parameters 2.0 years age, a calm thickness layer coded values of 0.6 along the radial direction, and 3.8 days soaking time when compared to mechanical properties 1–3 years plant age, calm thickness layers of from primary (-1) to secondary layers (1) along with the radial direction, and 3–9 days soaking time.

Measuring Client’s Feelings on Mobile Banking

Mobile banking is relatively a new service offered by banks around the world. Banks are obliged to keep investing in new technologies as otherwise, they would lose competitiveness and market share. It is interesting to know how clients react to these innovation efforts. This study aims to understand the client’s responses to bank innovation, especially to mobile banking technology in Albania. An online experiment is conceived based on Experimental Design Principles. Participants evaluate combinations of messages (elements) about mobile banking and rate each combination. The collected data are used to create individual models and later a general model to calculate the statistical relevance of each of the messages. The models use ordinary least squares regression and advanced data mining techniques (k—means clustering) to analyze the data and classify participants accordingly. At the end of the analyses, a set of two or three mindsets are depicted to show what pushes participants in the study in their decision-making process. These mindsets help banks understand client’s reactions and allow banks to address different issues to serve their clients better.

Reflections on the past, present and future of developmental biology

Developmental Biology embodies some of the most fundamental questions in Biology and can trace its roots back to several thousand years ago; the last 100 years have been particularly extraordinary. In part the advances have been fuelled by new technical advances and knowledge in many other areas, which have contributed to shaping the field as truly interdisciplinary. During those 100 years some of our predecessors identified some key questions and a few important principles especially by trying to find general rules that govern what cells are able to do and how they choose between different options, as well as principles of experimental design that can be used to uncover those rules even before we know their physicochemical underpinnings. But the field has been changing rapidly in the last two decades. Here I present a brief overview of some of the changes that have taken place over the last Century and a personal view of current directions. The picture that emerges is of some dark clouds on the horizon, so this is also a call to arms for our colleagues to try to regain what the field has been losing.