Model Input Values Research Articles

Interrelationship between Wall and Beach Erosion in Loc An, Vietnam: Remote Sensing and Numerical Modeling Approaches

Beach erosion and coastal protection are complex and interconnected phenomena that have a substantial impact on coastal environments worldwide. Among the various coastal protection measures, seawalls have been widely implemented to mitigate erosion and protect coastal assets. However, the interrelationship between beach erosion and seawalls remains a critical topic for investigation to ensure effective and sustainable coastal management strategies. Seawalls impact the shoreline, particularly through the “end effect”, where the seawall functions similarly to a groin, causing erosion on the downdrift side relative to the direction of wave approach. This study provides a detailed analysis of the interplay between beach erosion and seawall structures in Loc An, Vietnam, employing both remote sensing and numerical approaches. Sentinel-2 images were employed together with an analytical solution to observe the shoreline change at the Loc An sand spit and to determine input values for the numerical model. Based on the shoreline dynamics, a numerical scheme was employed to study the shoreline evolution after the construction of a seawall. Our findings show that the shoreline evolution can be divided into three stages: (1) The first stage corresponds to the elongation of the sand spit without interference from coastal structures. (2) The second stage shows the effect of jetties on the shoreline, as signaled by the buildup of sand updrift of the jetties. (3) The third stage shows the effectiveness of the seawall, where the shoreline reaches its equilibrium condition. The study provides a quick and simple method for estimating shoreline diffusivity (ε) in situations where measured data is scarce.

Имитационная модель дисковой лесопосадочной машины

To carry out artificial reforestation, it is necessary to use mechanized means – tree-planting machines. The lack of domestic tree-planting machines is one of the problems of artificial reforestation in Russia. The purpose of the study is to substantiate the design parameters of a tree-planting machine with a disk operating device. To achieve this goal, the use of modern software environments is required with the possibility of full consideration of all factors affecting the machine. In the course of this research, a solid model of a tree-planting machine has been developed by means of a computer-aided design system. The “Universal Mechanism 9.1” software package, designed for modeling the dynamics and kinematics of mechanical systems, has been chosen as a computational environment studying the parameters of the model. Only the input values for the simulation model have been introduced into the software package, since the mathematical apparatus is embedded in the core of the program. Using the software package, a simulation model of a tree-planting machine has been created, taking into account both the interaction of the machine links and the discrete contact interaction of the seedling with the machine and the soil. A computational experiment has been carries out and the kinematic and dynamic parameters of the tree-planting machine have been established, in which the feeder would not interfere with the free fallout of the briquette with the seedling. The geometric parameters of the mechanism have been determined to match the cam profile with its movement along with the disk and the operation of the roller tappet so that the grippers install the briquette with the seedling into the soil in a timely manner. The trajectory of movement of the briquette with the seedling has been found. With the help of FDM 3D-printing, a full-size model of a disk planting apparatus has been made, and a laboratory experiment has been conducted to establish the required torque on the hub of the planting apparatus disk and the shaft of the drum. The results of the experiment have confirmed the adequacy of the developed simulation model.

Stroke rehabilitation pathways during the first year: A cost-effectiveness analysis from a cohort of 460 individuals

BackgroundStroke burden challenges global health, and social and economic policies. Although stroke recovery encompasses a wide range of care, including in-hospital, outpatient, and community-based rehabilitation, there are no published cost-effectiveness studies of integrated post-stroke pathways. ObjectiveTo determine the most cost-effective rehabilitation pathway during the first 12 months after a first-ever stroke. MethodsA cohort of people in the acute phase of a first stroke was followed after hospital discharge; 51 % women, mean (SD) age 74.4 (12.9) years, mean National Institute of Health Stroke Scale score 11.7 (8.5) points, and mode modified Rankin Scale score 3 points. We developed a decision tree model of 9 sequences of rehabilitation care organised in 3 stages (3, 6 and 12 months) through a combination of public, semi-public and private entities, considering both the individual and healthcare service perspectives. Health outcomes were expressed as quality-adjusted life years (QALY) over a 1-year time horizon. Costs included healthcare, social care, and productivity losses. Sensitivity analyses were conducted on model input values. ResultsFrom the individual perspective, pathway 3 (Short-term Inpatient Unit » Community Clinic) was the most cost-effective, followed by pathway 1 (Rehabilitation Centre » Community Clinic). From the healthcare service perspective, pathway 3 was the most cost-effective followed by pathway 7 (Outpatient Hospital » Private Clinic). All other pathways were considered strongly dominated and excluded from the analysis. The total 1-year mean cost ranged between €12104 and €23024 from the individual's perspective and between €10992 and €31319 from the healthcare service perspective. ConclusionAssuming a willingness-to-pay threshold of one times the national gross domestic product (€20633/QALY), pathway 3 (Short-term Inpatient Unit » Community Clinic) was the most cost-effective strategy from both the individual and healthcare service perspectives. Rehabilitation pathway data contribute to the development of a future integrated care system adapted to different stroke profiles.

Measurement error prediction-based reliability assessment framework for electric metering devices under harsh natural environments

Reliability assessment for electric metering devices (EMDs), which includes environmental stress analysis, measurement error (ME) prediction, and reliability estimation, can be utilized for predictive instrument maintenance, especially under harsh environmental stresses. Nevertheless, the actual evaluation process is limited by data noise and the unavailability of future environmental inputs for the degradation model. To this end, we first extract the main environmental factors affecting ME and then fuse them using the weighted principal component analysis (WPCA) method to provide future environmental input values for the prediction model. Next, a bi-directional (BD) outlier detection method based on MCD robust analysis and the Thompson tau method is proposed to detect outliers from horizontal and longitudinal perspectives. Then, an ME prediction method called multi-stress fusion nonlinear degradation (MFND) is put forward, which considers the cyclic variation of ME over time and the effect of environmental stresses on ME. Real-world datasets from a high-dry-hot area manifest that our proposed BD-based MFND reliability assessment framework enjoys pleasurable prediction performance. Compared to some well- known methods, our framework excels in outlier detection and ME prediction.

Estimating Flood Inundation in Urban Areas Using a Scenario Generation Method and Inundation Graphs

As the frequency and intensity of natural and social disasters increase due to climate change, damage caused by disasters affects urban areas and facilities. Of those disasters, inundation occurs in urban areas due to rising water surface elevation because of concentrated rainfall from storm surges or urban drainage system failures. For this research, a scenario generation method for estimating flood inundation was developed to analyze the flood effects on urban areas to prepare for disasters and minimize damage. A scenario generation method using various distribution functions and return periods was developed and applied to create input values for the flow model for inundation analysis. By simulating multiple scenarios using a two-dimensional flow model and storing its results into a graph-form database called an inundation graph, it is possible to assess the probability and potential impact of different flood events quickly, which could be later used for disaster response and prevention. The flood risk and flood vulnerability of each section of the urban area could be evaluated based on the input data from the scenarios and the results of the flood analysis.

New data-driven estimation of metal element in rocks using a hyperspectral data and geochemical data

The inversion of Cu contents in rocks based on hyperspectral remote sensing is indicative of geochemical exploration as well as mineral resource exploration. Due to the strong redundancy of band information in hyperspectral data, characteristic band selection is the key to improving the accuracy of metal element inversion models in hyperspectral data. In this study, we proposed a framework that innovatively focuses on secondary screening method (SSM) as the core, allowing users to add different data preprocessing methods and machine learning algorithms to the framework based on expert experience, to obtain high-precision metal element inversion models suitable for sampling data. we first preprocessed the measured spectral curves using the first order derivative, second order derivative, continuum removal, multiple scattering correction and variance analysis to highlight band absorption characteristics. In addition, we performed SSM to obtain Cu-related characteristic bands, which were further used as input data to train and compare the performance of Partial Least Square Regression (PLSR), Support Vector Regression (SVR), Multi-Layer Perceptron (MLP), Random Forest (RF) and Gradient Boosting Regression Tree (GBRT). The results show that both the spectral pretreatment and modeling method could potentially impact the inversion accuracy. The accuracy of the ensemble method applied in fresh faces data (i.e., a CR-SSM-RF with R2 values of 0.77 and CR-SSM-GBRT with R2 values of 0.81) performed better than other models with an accuracy improvement of up to 80%. Compared to the full band model, the accuracy of characteristic bands selection model increased 50%. This also illustrates that the CR-SSM-RF or CR-SSM-GBRT model significantly improves the accuracy of the inversion of Cu contents in rocks compared to the original spectral reflectance. Our study provides a new idea for selecting different spectral preprocessing methods as the input values for the future model and will also offer an executable framework for the inversion of Cu contents in rocks of different lithology on a large scale in the future.

Enhancing effluent quality prediction in wastewater treatment plants through the integration of factor analysis and machine learning

Precisely predicting the concentration of nitrogen-based pollutants from the wastewater treatment plants (WWTPs) remains a challenging yet crucial task for optimizing operational adjustments in WWTPs. In this study, an integrated approach using factor analysis (FA) and machine learning (ML) models was employed to accurately predict effluent total nitrogen (Ntoteff) and nitrate nitrogen (NO3-Neff) concentrations of the WWTP. The input values for the ML models were honed through FA to optimize factors, thereby significantly enhancing the ML prediction accuracy. The prediction model achieved a highest coefficient of determination (R2) of 97.43 % (Ntoteff) and 99.38 % (NO3-Neff), demonstrating satisfactory generalization ability for predictions up to three days ahead (R2 >80 %). Moreover, the interpretability analysis identified that the denitrification factor, the pollutant load factor, and the meteorological factor were significant. The model framework proposed in this study provides a valuable reference for optimizing the operation and management of wastewater treatment.

Assessing human internal exposure to chemicals at different physical activity levels: A physiologically based kinetic (PBK) model incorporating metabolic equivalent of task (MET)

Physical activity levels have the potential to impact human internal exposure to environmental chemicals. However, the current lack of simple modeling approaches hinders the high-throughput screening of chemical exposure at different physical activity levels. To address this gap, this study proposes a straightforward model for assessing human internal exposure to chemicals. Our approach is based on the physiologically based kinetic (PBK) model and utilizes the metabolic equivalent of task (MET) to characterize internal exposure to chemicals at varying activity levels. To facilitate the application of this model, we have developed an Excel-based operation tool, allowing users to easily modify the MET value and generate simulation results for different physical activity levels. The simulation results demonstrate that as physical activity levels increase, the biotransfer factors (BTFs) of chemicals decrease, suggesting that higher physical activity levels reduce the bioaccumulation potential of chemicals. The intensified physical activity enhances the overall elimination kinetics of chemicals from the human body. However, the simulated concentrations of chemicals in the human body increase with higher physical activity levels, due to the significantly increased external exposure to chemicals, such as through inhalation. Our proposed modeling approach, along with the operational tool, enables high-throughput simulation of human chronic internal exposure to chemicals at different physical activity levels, where the findings can assist in screening chemicals for further health risk assessment. To accomplish this, the model incorporates certain assumptions and utilizes generic model input values. However, due to the intricate nature of the interaction between external and internal exposures at different physical activity levels, validating the simulation through experimental studies becomes challenging and is not performed in this study. For future studies, we recommend incorporating more MET-related physiological input variables, improving energy balance estimates, comprehending external exposure estimates, and conducting cohort studies to enhance and validate the proposed modeling approach.

Performance-based three-level fortification goal and its application in anti-dislocation countermeasures: A case study of Shantou Submarine tunnel

The dislocation momentum is the design basis for anti-dislocation to tunnel when a tunnel crosses an active fault. The influence of different dislocation levels on tunnel performances is not clear. Thus, based on seismic activity parameters at the site of interest and probability of fault dislocation, probability fault displacement hazard analysis (PFDHA) methodology was introduced in this paper to ascertain the fault dislocation level under different exceeding probabilities (63%, 10%, and 2%–3%). Then, based on the definition of different ground motion strength and fortification goals of the tunnel, a three-level fortification goal with different performance requirements of the tunnel was proposed. The first attempt to use the proposed indexes including the maximum dislocation of the tunnel and maximum relative deformation of the tunnel was tried to evaluate deformation and failure states with an experimental approach. Subsequently, the feasibility of the three-level fortification goal was further investigated according to the self-defined qualitative description and quantitative indexes in the segmental design and sectional expansion tunnels comprehensively. The results show that the fault dislocations relying on PFDHA at the site of the Shantou Submarine Tunnel are firstly ascertained as 0.04, 1.8, and 2.4 m respectively. Taking the fault dislocation as model input values into account, the dislocation mechanism of the tunnel under the three levels was revealed. More importantly, judging from the dislocation performance requirements of the three-level fortification goal, the tunnel deformation and failure states are mitigated by adopting the countermeasures. The sectional expansion design can well meet the requirements without the restriction of a strong earthquake, while the effectiveness of the segmental tunnel can be proved under frequently occurred and fortification earthquake. The final research results are expected to provide a new fortification goal for anti-dislocation hazard evaluation on expansion design in high-intensity seismic regions and segmental design in slight and moderate-intensity seismic regions.

Diverse e-cigarette regulations in the Asia Pacific: A health economic perspective.

Diverse e-cigarette regulations in the Asia Pacific: A health economic perspective.

Cost-Effectiveness Analysis of 68Ga-DOTATATE PET/MRI in Radiotherapy Planning in Patients with Intermediate-Risk Meningioma.

While contrast-enhanced MR imaging is the criterion standard in meningioma diagnosis and treatment response assessment, gallium 68Ga-DOTATATE PET/MR imaging has increasingly demonstrated utility in meningioma diagnosis and management. Integrating 68Ga-DOTATATE PET/MR imaging in postsurgical radiation planning reduces the planning target volume and organ-at-risk dose. However, 68Ga-DOTATATE PET/MR imaging is not widely implemented in clinical practice due to higher perceived costs. Our study analyzes the cost-effectiveness of 68Ga-DOTATATE PET/MR imaging for postresection radiation therapy planning in patients with intermediate-risk meningioma. We developed a decision-analytical model based on both recommended guidelines on meningioma management and our institutional experience. Markov models were implemented to estimate quality-adjusted life-years (QALY). Cost-effectiveness analyses with willingness-to-pay thresholds of $50,000/QALY and $100,000/QALY were performed from a societal perspective. Sensitivity analyses were conducted to validate the results. Model input values were based on published literature. The cost-effectiveness results demonstrated that 68Ga-DOTATATE PET/MR imaging yields higher QALY (5.47 versus 5.05) at a higher cost ($404,260 versus $395,535) compared with MR imaging alone. The incremental cost-effectiveness ratio analysis determined that 68Ga-DOTATATE PET/MR imaging is cost-effective at a willingness to pay of $50,000/QALY and $100,000/QALY. Furthermore, sensitivity analyses showed that 68Ga-DOTATATE PET/MR imaging is cost-effective at $50,000/QALY ($100,000/QALY) for specificity and sensitivity values above 76% (58%) and 53% (44%), respectively. 68Ga-DOTATATE PET/MR imaging as an adjunct imaging technique is cost-effective in postoperative treatment planning in patients with meningiomas. Most important, the model results show that the sensitivity and specificity cost-effective thresholds of 68Ga-DOTATATE PET/MR imaging could be attained in clinical practice.

Small-scale oxygen distribution patterns in a coral reef

One mechanism giving fleshy algae a competitive advantage over corals during reef degradation is algal-induced and microbially-mediated hypoxia (typically less than 69.5 µmol oxygen L−1). During hypoxic conditions oxygen availability becomes insufficient to sustain aerobic respiration in most metazoans. Algae are more tolerant of low oxygen conditions and may outcompete corals weakened by hypoxia. A key question on the ecological importance of this mechanism remains unanswered: How extensive are local hypoxic zones in highly turbulent aquatic environments, continuously flushed by currents and wave surge? To better understand the concert of biological, chemical, and physical factors that determine the abundance and distribution of oxygen in this environment, we combined 3D imagery, flow measurements, macro- and micro-organismal abundance estimates, and experimentally determined biogenic oxygen and carbon fluxes as input values for a 3D bio-physical model. The model was first developed and verified for controlled flume experiments containing coral and algal colonies in direct interaction. We then developed a three-dimensional numerical model of an existing coral reef plot off the coast of Curaçao where oxygen concentrations for comparison were collected in a small-scale grid using fiberoptic oxygen optodes. Oxygen distribution patterns given by the model were a good predictor for in situ concentrations and indicate widespread localized differences exceeding 50 µmol L-1 over distances less than a decimeter. This suggests that small-scale hypoxic zones can persist for an extended period of time in the turbulent environment of a wave- and surge- exposed coral reef. This work highlights how the combination of three-dimensional imagery, biogenic fluxes, and fluid dynamic modeling can provide a powerful tool to illustrate and predict the distribution of analytes (e.g., oxygen or other bioactive substances) in a highly complex system.

Phenol Degradation Performance in Batch and Continuous Reactors with Immobilized Cells of Pseudomonas putida

Phenol is a highly persistent environmental pollutant and is toxic to living organisms. The main objective of this study is to observe the phenol degradation performance by free and immobilized Pseudomonas putida (P. putida) in batch and continuous reactors, respectively. Batch experiments were evaluated to determine the maximum specific growth rate, saturation constant, inhibition constant, and cell yield. These kinetic parameters were used as the input values for the continuous-flow immobilized cells model. The immobilized cells model was validated by experimental results obtained from an immobilized cells continuous reactor. The model-predicted and experimental results showed good agreement for phenol effluent concentration in the continuous mode. In the steady-state condition, high phenol removal was achieved under various hydraulic retention times. The corresponding removal of phenol ranged from 93.3 to 95.9%, while the hydraulic retention times were maintained at 3.1–10.5 h. Furthermore, polyvinyl alcohol-immobilized cells with nanoscale particles were also prepared. The polyvinyl alcohol-immobilized P. putida cells with nanoscale Fe3O4 enhanced the ability of phenol degradation. The experimental results revealed that immobilized cells with nano-Fe3O4 had the highest phenol degradation performance at a low salinity of 1%. However, the advantage of the addition of nano-Fe3O4 was insignificant for phenol degradation at a higher salinity of 5%. The approaches of the batch and continuous column tests were practical in the treatment of actual phenol-containing wastewater.

Cost-Effectiveness of Neoadjuvant Pembrolizumab Plus Chemotherapy Followed by Adjuvant Single-Agent Pembrolizumab for High-Risk Early-Stage Triple-Negative Breast Cancer in the United States.

The randomized phaseIII KEYNOTE-522 trial demonstrated that addition of pembrolizumab to neoadjuvant chemotherapy provided a significant improvement in event-free survival and a favorable trend in overall survival for high-risk early-stage triple-negative breast cancer (eTNBC). This analysis evaluated the cost-effectiveness of pembrolizumab in combination with chemotherapy as neoadjuvant treatment and continued as a single-agent adjuvant treatment after surgery vs. neoadjuvant chemotherapy for patients with high-risk eTNBC in the USA. The analysis was conducted from a US third-party public healthcare payer perspective. A multistate transition model was developed using efficacy and safety data from the KEYNOTE-522 trial. The model included four mutually exclusive health states: event-free, locoregional recurrence, distant metastasis, and death to simulate patients' lifetime disease course. Quality-adjusted life years (QALYs) were calculated on the basis of EuroQoL-5 Dimensions utility data collected in KEYNOTE-522. Costs for drug acquisition/administration, adverse events, disease management, and subsequent therapies were reported (2021 US dollars). Costs and outcomes were discounted at 3% annually. A series of sensitivity analyses were performed to test the robustness of the main results. In the base case scenario, pembrolizumab plus chemotherapy followed by pembrolizumab resulted in expected gains of 3.37 life years (LYs) and 2.90QALYs, and an incremental cost of $79,046 versus chemotherapy. The incremental cost per QALY gained was $27,285, which is lower than all commonly cited US willingness-to-pay thresholds. Sensitivity analyses showed the results were robust over plausible values of key model inputs and assumptions. Compared with neoadjuvant chemotherapy, pembrolizumab in combination with chemotherapy as neoadjuvant treatment and continued as a single-agent adjuvant treatment after surgery is considered a cost-effective option for high-risk eTNBC in the USA.

Cost-Effectiveness Analysis of Routine Use of 15-Valent Pneumococcal Conjugate Vaccine in the US Pediatric Population.

This study evaluated the clinical and economic impact of routine pediatric vaccination with the 15-valent pneumococcal conjugate vaccine (PCV15, V114) compared with the 13-valent PCV (PCV13) from a societal perspective in the United States (US). A Markov decision-analytic model was constructed to estimate the outcomes for the entire US population over a 100-year time horizon. The model estimated the impact of V114 versus PCV13 on pneumococcal disease (PD) incidence, post meningitis sequalae, and deaths, taking herd immunity effects into account. V114 effectiveness was extrapolated from the observed PCV13 data and PCV7 clinical trials. Costs (2021$) included vaccine acquisition and administration costs, direct medical costs for PD treatment, direct non-medical costs, and indirect costs, and were discounted at 3% per year. In the base case, V114 prevented 185,711 additional invasive pneumococcal disease, 987,727 all-cause pneumonia, and 11.2 million pneumococcal acute otitis media cases, compared with PCV13. This led to expected gains of 90,026 life years and 96,056 quality-adjusted life years with a total saving of $10.8 billion. Sensitivity analysis showed consistent results over plausible values of key model inputs and assumptions. The findings suggest that V114 is a cost-saving option compared to PCV13 in the routine pediatric vaccination program.

578. Cost-effectiveness of Infant Vaccination with PCV15 Compared to PCV13 in the United States

Abstract Background Streptococcus pneumoniae is a major cause of mortality and morbidity in young children. The 13-valent pneumococcal conjugate vaccine (PCV13) has been in routine use in children in the United States (US) since 2010. An investigational 15-valent vaccine (PCV15) that protects against two additional serotypes is currently under review by the FDA. This study aimed to evaluate the clinical and economic impact of routine infant vaccination with PCV15 compared with PCV13 from a US societal perspective. Methods A Markov decision-analytic model was developed to estimate the impact of PCV15 vs. PCV13 on pneumococcal disease incidence, post meningitis sequalae, and deaths. The model followed the entire US population over a 100-year time horizon, taking herd immunity effects into account. Each vaccination program comprised 3 primary doses and one booster for the new birth cohorts. Model inputs were obtained from the published literature, online databases, and unpublished data. PCV15 effectiveness was extrapolated from observed PCV13 data and PCV7 clinical trials. Costs (in 2021 USD) and quality-adjusted life years (QALYs) were discounted at 3% per year. Because the price for PCV15 in the pediatric indication is currently unknown, an analysis was conducted to determine the threshold price, which was defined as the maximum price for PCV15 to remain cost-saving. A series of sensitivity analyses were performed to test the robustness of model results. Results The base case results projected that PCV15 prevented 185,711 more invasive pneumococcal disease cases, 987,727 all-cause pneumonia cases and 11,151,473 pneumococcal acute otitis media and tube-replacement cases compared with PCV13. This resulted in an expected gain of 96,056 QALYs and total reduction of $7 billion in direct medical costs (excluding vaccine costs), and $4 billion in direct non-medical and indirect costs in the US population over the 100-year time horizon. The threshold price per dose for PCV15 was $28 higher than PCV13’s price. Sensitivity analyses showed the results to be robust over plausible values of key model inputs and assumptions. Conclusion Infant vaccination with PCV15 is projected to provide both clinical benefits and cost-savings compared with PCV13. Disclosures Min Huang, PhD, Merck & Co., Inc.: full-time employee Tianyan Hu, Ph.D., Merck & Co., Inc.: full time employee Jessica Weaver, PhD, MPH, Merck & Co., Inc.: Employee Kwame Owusu-Edusei, Ph.D., Merck & Co., Inc.: full time employee Elamin Elbasha, Ph.D., Merck & Co., Inc.: full time employee.

Model construction and validation of airflow velocity attenuation through pear tree canopies.

To investigate the airflow velocity attenuation inside pear tree canopies and the factors that influence its effect on air-assisted spraying, the relationship between the resistance of the canopies to airflow and airflow velocity inside the canopies was determined. At the same time, the theoretical model of airflow velocity attenuation in the canopy was constructed, in which the velocity attenuation factor k and the incoming velocity were the model input values, and the airflow velocity in the canopy was the model output value. Then, experimental verification of the theoretical model was completed. The determination test of airflow velocity inside canopies with three leaf area densities revealed that the error range between the established theoretical model and the experimental airflow velocity inside the pear tree canopy was 0.11-1.25 m/s, and the mean size of the model accuracy was 83.4% under various working conditions. The results revealed that the region from a depth of 0m to 0.3m inside the canopy was the rapid attenuation area of the airflow and that from 0.3m to 0.9m was the low attenuation area. Furthermore, they revealed that high-speed airflow could strongly disturb the outer branches and leaves, greatly changing the windward area of the canopy blades and thus affecting the accuracy of the model. By introducing a dynamic parameter of the canopy leaf windward area for model correction, the R2 of the model was above 0.9. Finally, validation of the model was performed in an air-assisted spraying operation in an orchard. This study can provide a theoretical basis for the regulation of airflow parameters of air-assisted spraying of pear trees.

Winter Wheat SPAD Value Inversion Based on Multiple Pretreatment Methods

SPAD value was measured by a portable chlorophyll instrument, which can reflect the relative chlorophyll content of vegetation well. Chlorophyll is an important organic chemical substance in plants that acquires and transmits energy during photosynthesis. The continuous spectral curve of winter wheat can be obtained rapidly in a specific band range by using hyperspectral remote sensing technology to estimate the SPAD value of winter wheat, which is of great significance to the growth monitoring and yield estimation research of winter wheat. In this study, with winter wheat as the research object, the spectral data and corresponding SPAD value in different growth stages were used as the data source, 20 kinds of data preprocessing spectra and sensitive spectral indices set the data as model input values, the partial least square regression (PLSR) model was established to estimate the SPAD value, and the model estimation results of different model input values at different growth stages were compared in detail. The results showed that the set of sensitive spectral indices selected in this study as input values can effectively improve the accuracy and stability of the PLSR model. In addition, the effects of 20 spectral data pretreatment methods on the estimation results of the SPAD value were compared and analyzed in different growth stages. It was found that the spectral data pretreated by the combination of wavelet packet denoising, first-order derivative transformation and principal component analysis can improve the accuracy and stability of PLSR model, and it is suitable for all growth stages. The results also showed that the estimation model is highly sensitive to the standard deviation of the SPAD value (STDchl) in sample sets. When the standard deviation is greater than 5.5 SPAD, the larger the STDchl is, the higher the model estimation accuracy is, and the more stable the model is. At this time, the model estimation accuracy is higher (R2V is greater than 0.5, ratio of performance to deviation is greater than 1.4), which can meet the estimation requirements of the SPAD value.

Possibilities of using numerical modelling to determine the residual load capacity of concrete elements with composite reinforcement after fire

During the service life of a structure, a number of phenomena occur that can affect the ability of the concrete structure to continue to perform its function. In the case of concrete load-bearing elements, fire and its effects represent significant influencing factor. Exposure to fire can, among other things, cause a great reduction of material properties of both concrete and reinforcement itself, but also affect their interaction. After a fire incident, it is necessary to assess the residual load capacity of the reinforced concrete elements. As part of the diagnostic work, material samples are usually taken from the structure after a fire. The purpose of the present paper was to investigate whether the experimentally obtained material characteristics can be used to verify the basic behaviour of concrete structures after fire. The structural material properties were used as input values for simplified numerical models of the structures. ATENA Cervenka Consulting software was chosen to construct a numerical model simulating the behaviour of the structural elements after exposure to fire loads. Finally, the effect of high temperatures on the residual load capacity of the beams determined by the numerical approach was compared with the experimental values of the load capacity of the beams after fire. The behaviour of concrete beams of dimensions 100 × 150 × 1800 mm reinforced with composite reinforcement was investigated. The specimens exposed to temperatures of 1000°C were subjected to mechanical bending tests after cooling to determine their residual load capacity.

Multi-head self-attention bidirectional gated recurrent unit for end-to-end remaining useful life prediction of mechanical equipment

In order to reduce error accumulation caused by multistep modeling and achieve a generally accurate model, this paper proposes an end-to-end remaining useful life (RUL) prediction model based on a multi-head self-attention bidirectional gated recurrent unit (BiGRU). Taking multivariable samples with long time series as the model input and multistep RUL values as the model output, the BiGRU model is constructed for continuous prediction of RUL. In addition, single-head self-attention models are applied for time series and variables of samples before or after the BiGRU, which can be fused into a multi-head attention BiGRU. Aeroengines and rolling bearings are selected to testify the effectiveness of the proposed method from the system level and component level respectively. The results show that the proposed method can achieve end-to-end RUL prediction efficiently and accurately. Compared with single-head models and individual deep learning models, the prediction mean square error of the proposed method is reduced by 20%–70%.