Probing Local pH Change during Electrode Oxidation of TEMPO Derivative: Implication of Redox-Induced Acidity Alternation by Imidazolium-Linker Functional Groups.

The chemical degradation of 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO)-based aqueous energy storage and catalytic systems is pH sensitive. Herein, we voltammetrically monitor the local pH (pHlocal) at a Pt ultramicroelectrode (UME) upon electro-oxidation of imidazolium-linker functionalized TEMPO and show that its decrease is associated with the greater acidity of the cationic (oxidized) rather than radical (reduced) form of TEMPO. The protons that drive the decrease in pH arise from hydrolysis of the conjugated imidazolium-linker functional group of 4-[2-(N-methylimidazolium)acetoxy]-2,2,6,6-tetramethylpiperidine-1-oxyl chloride (MIMAcO-T), which was studied in comparison with 4-hydroxyl-TEMPO (4-OH-T). Voltammetric hysteresis is observed during the electrode oxidation of 4-OH-T and MIMAcO-T at a Pt UME in an unbuffered aqueous solution. The hysteresis arises from the pH-dependent formation and dissolution of Pt oxides, which interact with pHlocal in the vicinity of the UME. We find that electrogenerated MIMAcO-T+ significantly influences pHlocal, whereas 4-OH-T+ does not. Finite element analysis reveals that the thermodynamic and kinetic acid-base properties of MIMAcO-T+ are much more favorable than those of its reduced counterpart. Imidazolium-linker functionalized TEMPO molecules comprising different linking groups were also investigated. Reduced TEMPO molecules with carbonyl linkers behave as weak acids, whereas those with alkyl ether linkers do not. However, oxidized TEMPO+ molecules with alkyl ether linkers exhibit more facile acid-base kinetics than those with carbonyl ones. Density functional theory calculations confirm that OH- adduct formation on the imidazolium-linker functional group of TEMPO is responsible for the difference in the acid-base properties of the reduced and oxidized forms.

Self-assembly prediction of architecture-controlled bottlebrush copolymers in solution using graph convolutional networks.

The investigation of bottlebrush copolymer self-assembly in solution involves a comprehensive approach integrating simulation and experimental research, due to their unique physical characteristics. However, the intricate architecture of bottlebrush copolymers and the diverse solvent conditions introduce a wide range of parameter spaces. In this study, we investigated the solution self-assembly behavior of bottlebrush copolymers by combining dissipative particle dynamics (DPD) simulation results and machine learning (ML) including graph convolutional networks (GCNs). The architecture of bottlebrush copolymers is encoded by graphs including connectivity, side chain length, bead types, and interaction parameters of DPD simulation. Using GCN, we accurately predicted the single chain properties of bottlebrush copolymers with over 95% accuracy. Furthermore, phase behavior was precisely predicted using these single chain properties. Shapley additive explanations (SHAP) values of single chain properties to the various self-assembly morphologies were calculated to investigate the correlation between single chain properties and morphologies. In addition, we analyzed single chain properties and phase behavior as a function of DPD interaction parameters, extracting relevant physical properties for vesicle morphology formation. This work paves the way for tailored design in solution of self-assembled nanostructures of bottlebrush copolymers, offering a GCN framework for precise prediction of self-assembly morphologies under various chain architectures and solvent conditions.

The Value of Cultural Models in Eating Disorders Research in Korea: A Call for More Culturally Specific Works.

The study by Monocello et al. presents findings from a cultural model analysis providing support for culturally bounded understandings of weight and shape and body ideals, and identifying factors that vary across culturally anchored weight categories. In this commentary, we highlight the value of utilizing emic perspectives and employing cultural models in research focused on body image and disordered eating, and the usefulness of these empirical data among Korean men who constitute an underrepresented group in the eating disorders literature. In addition, methodological and contextual aspects that warrant consideration in the interpretation of the results are highlighted. Finally, directions for future research are presented focused on body image and disordered eating among Korean men, as well as leveraging cultural models more broadly in the field. We hope that the study by Monocello and colleagues will stimulate additional research that centers the perspectives of underrepresented groups in ways that elevate and honor their experiences and help to shift the field away from a White-centered perspective.

Efficiency Analysis of Powertrain for Internal Combustion Engine and Hydrogen Fuel Cell Tractor According to Agricultural Operations.

As interest in eco-friendly work vehicles grows, research on the powertrains of eco-friendly tractors has increased, including research on the development of eco-friendly vehicles (tractors) using hydrogen fuel cell power packs and batteries. However, batteries require a long time to charge and have a short operating time due to their low energy efficiency compared with hydrogen fuel cell power packs. Therefore, recent studies have focused on the development of tractors using hydrogen fuel cell power packs; however, there is a lack of research on powertrain performance analysis considering actual working conditions. To evaluate vehicle performance, an actual load measurement during agricultural operation must be conducted. The objective of this study was to conduct an efficiency analysis of powertrains according to their power source using data measured during agricultural operations. A performance evaluation with respect to efficiency was performed through comparison and an analysis with internal combustion engine tractors of the same level. The specifications of the transmission for hydrogen fuel cell and engine tractors were used in this study. The power loss and efficiency of the transmission were calculated using ISO 14179-1 equations, as shown below. Plow tillage and rotary tillage operations were conducted for data measurement. The measurement system consists of four components. The engine data load measurement was calculated using the vehicle's controller area network (CAN) data, the axle load was measured using an axle torque meter and proximity sensors, and fuel consumption was measured using the sensor installed on the fuel line. The calculated capacities, considering the engine's fuel efficiency for plow and rotary tillage operations, were 131.2 and 175.1 kWh, respectively. The capacity of the required power, considering the powertrain's efficiency for hydrogen fuel cell tractors with respect to plow and rotary tillage operations, was calculated using the efficiency of the motor, inverter, and power pack, and 51.3 and 62.9 kWh were the values obtained, respectively. Considering these factors, the engine exhibited an efficiency of about 47.9% compared with the power pack in the case of plow tillage operations, and the engine exhibited an efficiency of about 29.3% in the case of rotary tillage operations. A hydrogen fuel cell tractor is considered suitable for high-efficiency and eco-friendly vehicles because it can operate on eco-friendly power sources while providing the advantages of a motor.

Molecular dynamics study of shear-induced lamellar alignment of ABA triblock copolymer thin films.

In this study, the shear-induced lamellar alignment of a thin-film ABA triblock copolymer melt was achieved via a non-equilibrium coarse-grained molecular dynamics simulation. The ABA triblock copolymer system displayed a slightly different phase behavior under different shear conditions compared to the AB diblock copolymer system. Unlike previous studies that only considered the wall velocity, the Flory-Huggins parameter was considered in our study as a factor that determines lamellar alignment. Pre-aligned lamellae and randomly mixed polymers were used as the initial states for the shear simulation to compare the shear-induced lamellar alignment on each. The two initial conditions displayed different alignment behaviors; specifically, in the pre-aligned lamellae, a tilted structure was observed when the system was not aligned in the shear direction. To explain the difference between the tilted and realigned structures, the potential energy over the simulation time, polymer dynamics from the Van Hove correlation function, and the directional order parameter were investigated. It was inferred that a tilted structure is induced by the energy barrier of realignment originating from the restricted movement of the local polymer chains. Once they cross the energy barrier, block copolymers tend to align in the shear direction to attain energy stabilization through the polymer flow.

The Impact of Moderate Earthquakes on Antidepressant Prescriptions in Ulsan, South Korea: A Controlled Interrupted Time Series Analysis.

BACKGROUND: In 2016, two consecutive moderate magnitude earthquakes occurred in Ulsan, South Korea. Therefore, we aimed to investigate the impact of earthquakes on the mental health of residents in Ulsan. METHODS: We used data from the 2015-2017 Korean Health Insurance Review & Assessment Service National Patient Sample. We conducted an interrupted time series analysis using location-based controls. Changes in the number of antidepressants, benzodiazepines, and zolpidem prescriptions in Ulsan were compared to controls. Overall changes in weekly prescriptions 1 year after the first earthquake, compared to a non-earthquake scenario, were estimated. RESULTS: In antidepressant prescriptions, the increase in trend after an earthquake was significantly higher than controls. However, the changes in benzodiazepines and zolpidem prescribing were not significant. Overall, the impact of the earthquake on weekly antidepressant prescriptions at 1 year was estimated as a 1.32 (95% CI, 1.18-1.56) rate ratio compared to the non-earthquake scenario. This corresponded to an increase of 1,989.7 (95% CI, 1,202.1-3,063.0) in the number of prescriptions. Among subgroups, the increase was highest among males aged 20-39 years. CONCLUSION: The moderate earthquake in Ulsan was associated with an increase in antidepressant prescriptions. The increase in the male group aged 20-39 was the highest. The impact may vary according to the context of the population.

Trends of Surgical Service Utilization for Lumbar Spinal Stenosis in South Korea: A 10-Year (2010-2019) Cross-Sectional Analysis of the Health Insurance Review and Assessment Service-National Patient Sample Data.

Background and Objectives: This retrospective, cross-sectional, and descriptive study used claims data from the Korean Health Insurance Review and Assessment Service (HIRA) between 2010 and 2019 to analyze the trend of surgical service utilization in patients with lumbar spinal stenosis (LSS). Materials and Methods: The national patient sample data provided by the HIRA, which consisted of a 2% sample of the entire Korean population, was used to assess all patients who underwent decompression or fusion surgery at least once in Korea, with LSS as the main diagnosis from January 2010 to December 2019. An in-depth analysis was conducted to examine the utilization of surgical services, taking into account various demographic characteristics of patients, the frequency of claims for different types of surgeries, reoperation rates, the specific types of inpatient care associated with each surgery type, prescribed medications, and the overall expense of healthcare services. Results: A total of 6194 claims and 6074 patients were analyzed. The number of HIRA claims for patients increased from 393 (2010) to 417 (2019) for decompression, and from 230 (2010) to 244 (2019) for fusion. As for the medical expenses of surgery, there was an increase from United States dollar (USD) 867,549.31 (2010) to USD 1,153,078.94 (2019) for decompression and from USD 1,330,440.37 (2010) to USD 1,780,026.48 (2019) for fusion. Decompression accounted for the highest proportion (65.8%) of the first surgeries, but more patients underwent fusion (50.6%) than decompression (49.4%) in the second surgery. Across all sex and age groups, patients who underwent fusion procedures experienced longer hospital stays and incurred higher medical expenses for their inpatient care. Conclusion: The surgical service utilization of patients with LSS and the prescribing rate of opioids and non-opioid analgesics for surgical patients increased in 2019 compared to 2010. From mid-2010 onward, claims for fusion showed a gradual decrease, whereas those for decompression showed a continuously increasing trend. The findings of this study are expected to provide basic research data for clinicians, researchers, and policymakers.

Multiple variants of African swine fever virus circulating in Vietnam.

African swine fever (ASF) is a contagious and deadly viral disease affecting swine of all ages. ASF was first reported in Vietnam in February 2019, and it is now considered endemic in Vietnam. In this study, 122 ASF-positive samples collected from domestic pigs in 28 different provinces of northern, central, and southern Vietnam during outbreaks in 2019-2021 were genetically characterized. The findings confirmed that all ASF virus (ASFV) strains circulating in Vietnam belonged to p72 genotype II, p54 genotype II, CD2v serogroup 8, and CVR gene variant type I. However, further analysis based on the tandem repeat sequences located between I73R and I329L genes revealed that there were three different variants of ASFV, IGR I, II, and III, circulating in the domestic pig population in Vietnam. The IGR II variants were the most prevalent (117/122 strains) and were detected in pigs in all of the provinces tested, followed by IGR III (4/122 strains) and IGR I (1/122 strains). This study confirms for the first time the presence of IGR III variants in Vietnam.

Quarantining: a mentally distressful but physically comfortable experience in South Korea.

OBJECTIVE: Quarantine is the first response to the COVID-19 pandemic. Restricting daily life can cause several problems. This study aimed to measure the impact of the COVID-19 quarantine on health-related quality of life (HRQoL) by comparing to the pre-pandemic. METHODS: HRQoL during COVID-19 quarantine was surveyed online using EQ-5D index and matched to that of the pre-pandemic-extracted from nationwide representative data of the Korea Community Health Survey- with propensity scores. A beta regression for the EQ-5D scores and a logistic analysis for individual dimensions of the EQ-5D index were performed to measure the impact of the COVID-19 quarantine on health utility. RESULTS: The overall scores of the EQ-5D index were significantly higher in the group under quarantine during the COVID-19 pandemic (0.971 SD 0.064) than those before the pandemic (0.964 SD 0.079, Diff. 0.007 SD 0.101, p = 0.043). The beta regression for the overall scores of EQ-5D revealed that quarantining during the COVID-19 pandemic increased by 52.7% compared to normal life before the outbreak(p = 0.045). Specifically, "Depression/Anxiety" deteriorated significantly during quarantining (OR = 0.62, 95% CI:0.48-0.80). However, "Pain/Discomfort" and "Mobility" significantly improved (OR = 5.37, 95% CI:3.71-7.78 and OR = 2.05, 95% CI:1.11-3.80, respectively). CONCLUSION: Although the world is facing a challenging moment that it has never been through before, mandatory quarantine has served as an experience that provided mental distress but physical comfort in the Korean context.

Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage.

Current genome-editing technologies introduce double-stranded (ds) DNA breaks at a target locus as the first step to gene correction. Although most genetic diseases arise from point mutations, current approaches to point mutation correction are inefficient and typically induce an abundance of random insertions and deletions (indels) at the target locus resulting from the cellular response to dsDNA breaks. Here we report the development of 'base editing', a new approach to genome editing that enables the direct, irreversible conversion of one target DNA base into another in a programmable manner, without requiring dsDNA backbone cleavage or a donor template. We engineered fusions of CRISPR/Cas9 and a cytidine deaminase enzyme that retain the ability to be programmed with a guide RNA, do not induce dsDNA breaks, and mediate the direct conversion of cytidine to uridine, thereby effecting a C→T (or G→A) substitution. The resulting 'base editors' convert cytidines within a window of approximately five nucleotides, and can efficiently correct a variety of point mutations relevant to human disease. In four transformed human and murine cell lines, second- and third-generation base editors that fuse uracil glycosylase inhibitor, and that use a Cas9 nickase targeting the non-edited strand, manipulate the cellular DNA repair response to favour desired base-editing outcomes, resulting in permanent correction of ~15-75% of total cellular DNA with minimal (typically ≤1%) indel formation. Base editing expands the scope and efficiency of genome editing of point mutations.

Analysis of the Effect of Tillage Depth on the Working Performance of Tractor-Moldboard Plow System under Various Field Environments.

The purpose of this study was to analyze the tillage depth effect on the tractor-moldboard plow systems in various soil environments and tillage depths using a field load measurement system. A field load measurement system can measure the engine load, draft force, travel speed, wheel axle load, and tillage depth in real-time. In addition, measurement tests of soil properties in the soil layer were preceded to analyze the effect of field environments. The presented results show that moldboard plow at the same tillage depth had a wide range of influences on the tractor's working load and performance under various environments. As the draft force due to soil-tool interaction occurred in the range of 5.6-17.7 kN depending on the field environment, the overall mean engine torque and rear axle torque were up to 2.14 times and 1.67 times higher in hard and clayey soil, respectively, than in soft soil environments. In addition, the results showed tractive efficiency of 0.56-0.73 and were analyzed to have a lugging ability of 67.8% with a 44% maximum torque rise. The engine power requirement in hardpan was similar within 3.6-9.6%, but the power demand of the rear axle differed by up to 18.4%.

Traction Performance Evaluation of the Electric All-Wheel-Drive Tractor.

This study aims to design, develop, and evaluate the traction performance of an electric all-wheel-drive (AWD) tractor based on the power transmission and electric systems. The power transmission system includes the electric motor, helical gear reducer, planetary gear reducer, and tires. The electric system consists of a battery pack and charging system. An engine-generator and charger are installed to supply electric energy in emergency situations. The load measurement system consists of analog (current) and digital (battery voltage and rotational speed of the electric motor) components using a controller area network (CAN) bus. A traction test of the electric AWD tractor was performed towing a test vehicle. The output torques of the tractor motors during the traction test were calculated using the current and torque curves provided by the motor manufacturer. The agricultural work performance is verified by comparing the torque and rpm (T-N) curve of the motor with the reduction ratio applied. The traction is calculated using torque and specifications of the wheel, and traction performance is evaluated using tractive efficiency (TE) and dynamic ratio (DR). The results suggest a direction for the improvement of the electric drive system in agricultural research by comparison with the conventional tractor through the analysis of the agricultural performance and traction performance of the electric AWD tractor.

Posttraumatic stress disorder and changes in diet quality over 20 years among US women.

BACKGROUND: Individuals with posttraumatic stress disorder (PTSD) are at increased risk of various chronic diseases. One hypothesized pathway is via changes in diet quality. This study evaluated whether PTSD was associated with deterioration in diet quality over time. METHODS: Data were from 51 965 women in the Nurses' Health Study II PTSD sub-study followed over 20 years. Diet, assessed at 4-year intervals, was characterized via the Alternative Healthy Eating Index-2010 (AHEI). Based on information from the Brief Trauma Questionnaire and Short Screening Scale for DSM-IV PTSD, trauma/PTSD status was classified as no trauma exposure, prevalent exposure (trauma/PTSD onset before study entry), or new-onset (trauma/PTSD onset during follow-up). We further categorized women with prevalent exposure as having trauma with no PTSD symptoms, trauma with low PTSD symptoms, and trauma with high PTSD symptoms, and created similar categories for women with new-onset exposure, resulting in seven comparison groups. Multivariable linear mixed-effects spline models tested differences in diet quality changes by trauma/PTSD status over follow-up. RESULTS: Overall, diet quality improved over time regardless of PTSD status. In age-adjusted models, compared to those with no trauma, women with prevalent high PTSD and women with new-onset high PTSD symptoms had 3.3% and 3.6% lower improvement in diet quality, respectively, during follow-up. Associations remained consistent after adjusting for health conditions, sociodemographics, and behavioral characteristics. CONCLUSIONS: PTSD is associated with less healthy changes in overall diet quality over time. Poor diet quality may be one pathway linking PTSD with a higher risk of chronic disease development.

Self-assembly of rod-coil diblock copolymer-nanoparticle composites in thin films: dissipative particle dynamics.

In this study, the assembled structures of rod-coil diblock copolymer and nanoparticle blends were studied via dissipative particle dynamics (DPD). Thin films were composed of soft confinement DPD fluid beads and the fluctuating film structure was maintained during the simulation process. Analysis of the position of nanoparticles was done in the smectic lamellar phase of the rod-coil polymer matrix, and density distributions of rods, coils, and nanoparticles were obtained as functions of the size of the nanoparticle and the DPD repulsion constant between the rod and the nanoparticle. The distribution of nanoparticles was explained by using the concept of translational entropy of nanoparticles, stretching energy of the polymer chain, relative repulsion enthalpy of nanoparticles to rods or coils, and the effect of the liquid crystalline rod.

Weakly Supervised Crop Area Segmentation for an Autonomous Combine Harvester.

Machine vision with deep learning is a promising type of automatic visual perception for detecting and segmenting an object effectively; however, the scarcity of labelled datasets in agricultural fields prevents the application of deep learning to agriculture. For this reason, this study proposes weakly supervised crop area segmentation (WSCAS) to identify the uncut crop area efficiently for path guidance. Weakly supervised learning has advantage for training models because it entails less laborious annotation. The proposed method trains the classification model using area-specific images so that the target area can be segmented from the input image based on implicitly learned localization. This way makes the model implementation easy even with a small data scale. The performance of the proposed method was evaluated using recorded video frames that were then compared with previous deep-learning-based segmentation methods. The results showed that the proposed method can be conducted with the lowest inference time and that the crop area can be localized with an intersection over union of approximately 0.94. Additionally, the uncut crop edge could be detected for practical use based on the segmentation results with post-image processing such as with a Canny edge detector and Hough transformation. The proposed method showed the significant ability of using automatic perception in agricultural navigation to infer the crop area with real-time level speed and have localization comparable to existing semantic segmentation methods. It is expected that our method will be used as essential tool for the automatic path guidance system of a combine harvester.

Estimation of Axle Torque for an Agricultural Tractor Using an Artificial Neural Network.

The objective of this study was to develop a model to estimate the axle torque (AT) of a tractor using an artificial neural network (ANN) based on a relatively low-cost sensor. ANN has proven to be useful in the case of nonlinear analysis, and it can be applied to consider nonlinear variables such as soil characteristics, unlike studies that only consider tractor major parameters, thus model performance and its implementation can be extended to a wider range. In this study, ANN-based models were compared with multiple linear regression (MLR)-based models for performance verification. The main input data were tractor engine parameters, major tractor parameters, and soil physical properties. Data of soil physical properties (i.e., soil moisture content and cone index) and major tractor parameters (i.e., engine torque, engine speed, specific fuel consumption, travel speed, tillage depth, and slip ratio) were collected during a tractor field experiment in four Korean paddy fields. The collected soil physical properties and major tractor parameter data were used to estimate the AT of the tractor by the MLR- and ANN-based models: 250 data points were used for developing and training the model were used, the 50 remaining data points were used to test the model estimation. The AT estimated with the developed MLR- and ANN-based models showed agreement with actual measured AT, with the R2 value ranging from 0.825 to 0.851 and from 0.857 to 0.904, respectively. These results suggest that the developed models are reliable in estimating tractor AT, while the ANN-based model showed better performance than the MLR-based model. This study can provide useful results as a simple method using ANNs based on relatively inexpensive sensors that can replace the existing complex tractor AT measurement method is emphasized.

Changes in plant-based diet quality and health-related quality of life in women.

Few studies have evaluated the association between a healthful plant-based diet and health-related quality of life (HRQoL). We followed 50 290 women in the Nurses' Health Study (NHS; 1992-2000) and 51 784 women in NHSII (1993-2001) for 8 years to investigate changes in plant-based diet quality in relation to changes in physical and mental HRQoL. Plant-based diet quality was assessed by three plant-based diet indices: overall plant-based diet index (PDI), healthful PDI (hPDI) and unhealthful PDI (uPDI). Physical and mental HRQoL were measured by physical component score (PCS) and mental component score (MCS) of the 36-Item Short Form Health Survey. Diet was assessed 2 years before the HRQoL measurements and both were updated every 4 years. The associations between 4-year changes in PDIs and HRQoL were evaluated. Each 10-point increase in PDI was associated with an improvement of 0·07 (95 % CI 0·01, 0·13) in PCS and 0·11 (95 % CI 0·05, 0·16) in MCS. A 10-point increase in hPDI was associated with an increment of 0·13 (95 % CI 0·08, 0·19) in PCS and 0·09 (95 % CI 0·03, 0·15) in MCS. Conversely, a 10-point increase in uPDI was associated with decreases in PCS and MCS (-0·07 (95 % CI -0·12, -0·02) and -0·10 (95 % CI -0·16, -0·05), respectively). Compared with a stable diet, an increase in hPDI was significantly associated with improvements in physical HRQoL in older women and with mental HRQoL in younger women. In conclusion, adherence to a healthful plant-based diet was modestly associated with improvements in both physical and mental dimensions of HRQoL.

Analysis of Tillage Depth and Gear Selection for Mechanical Load and Fuel Efficiency of an Agricultural Tractor Using an Agricultural Field Measuring System.

This study was conducted to analyze the effects of tillage depth and gear selection on the mechanical load and fuel efficiency of an agricultural tractor during plow tillage. In order to analyze these effects, we developed an agricultural field measuring system consisting of a load measurement part (wheel torque meter, proximity sensor, and real-time kinematic (RTK) global positioning system (GPS)) and a tillage depth measurement part (linear potentiometer and inclinometer). Field tests were carried out using moldboard plows with a maximum tillage depth of 20 cm and three gear selections (M2H, M3L, and M3H) in a rice stubble paddy field for plow tillage. The average travel speed and slip ratio had the lowest M2H and the highest M3L. M3H had the highest theoretical speed, but the travel speed was 0.13 km/h lower than M3L due to the reduction in the axle rotational speed at deep tillage depth. Regarding engine load, the higher the gear, the greater the torque and the lower the axle rotation speed. The front axle load was not significantly affected by the tillage depth as compared to other mechanical parts, except for the M3H gear. The rear axle load generated about twice the torque of the front wheel and overall, it tended to show a higher average rear axle torque at higher gear selection. The rear axle load and fuel rate were found to be most affected by the combination of the tillage depth and gear selection combination. Overall, field test results show that the M3H had the highest fuel efficiency and a high working speed while overcoming high loads at the same tillage depth. In conclusion, M3H is the most suitable gear stage for plow cultivation, and the higher the gear stage and the deeper the tillage depth during plowing, the higher the fuel efficiency. The results of this study will be useful for analyzing mechanical load and fuel efficiency during farm operations. In a future study, we will conduct load analysis studies in other farming operations that consider various soil mechanics factors as well as tillage depths and gear selections.

Development of a Real-Time Tillage Depth Measurement System for Agricultural Tractors: Application to the Effect Analysis of Tillage Depth on Draft Force during Plow Tillage.

The objectives of this study were to develop a real-time tillage depth measurement system for agricultural tractor performance analysis and then to validate these configured systems through soil non-penetration tests and field experiment during plow tillage. The real-time tillage depth measurement system was developed by using a sensor fusion method, consisting of a linear potentiometer, inclinometer, and optical distance sensor to measure the vertical penetration depth of the attached implement. In addition, a draft force measurement system was developed using six-component load cells, and an accuracy of 98.9% was verified through a static load test. As a result of the soil non-penetration tests, it was confirmed that sensor fusion type A, consisting of a linear potentiometer and inclinometer, was 6.34-11.76% more accurate than sensor fusion type B, consisting of an optical distance sensor and inclinometer. Therefore, sensor fusion type A was used during field testing as it was found to be more suitable for use in severe working environments. To verify the accuracy of the real-time tillage depth measurement system, a linear regression analysis was performed between the measured draft and the predicted values calculated using the American Society of Agricultural and Biological Engineers (ASABE) standards-based equation. Experimental data such as traveling speed and draft force showed that it was significantly affected by tillage depth, and the coefficient of determination value at M3-Low was 0.847, which is relatively higher than M3-High. In addition, the regression analysis of the integrated data showed an R-square value of 0.715, which is an improvement compared to the accuracy of the ASABE standard prediction formula. In conclusion, the effect of tillage depth on draft force of agricultural tractors during plow tillage was analyzed by the simultaneous operation of the proposed real-time tillage depth measurement system and draft force measurement system. In addition, system accuracy is higher than the predicted accuracy of ±40% based on the ASABE standard equation, which is considered to be useful for various agricultural machinery research fields. In future studies, real-time tillage depth measurement systems can be used in tractor power train design and to ensure component reliability, in accordance with agricultural working conditions, by predicting draft force and axle loads depending on the tillage depth during tillage operations.

Simulation of Design Factors of a Clutch Pack for Power-Shift Transmission for an Agricultural Tractor.

The objective of this study is the simulation of the most affected design factors and variables of the clutch pack for the power-shift transmission (PST) of a tractor based measured data. The simulation model, the mathematical model of sliding velocity, a moment of inertia, and clutch engagement pressure of clutch pack were developed using the powertrain and configurations of the real PST tractor. In this study, the sensor fusion method was used to precisely measure the proportional valve pressure by test bench, which was applied to the simulation model. The clutch engagement times were found 1.20 s at all temperatures for determined factors. The engagement pressures have a significant difference at various temperatures (25 to 100 °C) of the hydraulic oils after the 1.20 s but the most affected factors were satisfied with the simulation conditions that ensure the clutch engagement on time. Finally, this sensor fusion method is believed to be helpful in realizing precision agriculture through minimization of power loss and maximum energy efficiency of tractors.