Trend Curves Research Articles

Modeling the Multiwavelength Radiation Properties in Pulsar Dissipative Magnetospheres

We explore the multiwavelength radiation properties of the light curves and energy spectra in the dissipative magnetospheres of pulsars. The dissipative magnetospheres are simulated by the pseudo-spectral method with the combined force-free and Aristotelian electrodynamics, which can produce self-consistent accelerating electric fields mainly distributed in the equatorial current sheet outside the light cylinder. The multiwavelength light curves and spectra are computed by using the multiple emission mechanisms of both the primary particles accelerated by the accelerating electric fields in the equatorial current sheet and the secondary pairs with an assumed distribution spectrum. We then compare the predicted multiwavelength light curves and spectra with the observed data from the Crab, Vela, and Geminga pulsars. Our modeling results can systematically reproduce the observed trends of the multiwavelength light curves and the spectra for these three pulsars well.

Seepage disturbance mechanism and interface force of cylindrical barrier in fracture

The fluid flow in the crack is disturbed by the contact area. The parallel-plate model with a circular cylindrical contact area is regarded as an idealization of the real contact fracture, and a computational fluid dynamics simulation is performed on it to analyze the interaction between the contact area and the flow around it. The size of the contact area controls the disturbance intensity to the flow velocity magnitude and the disturbance range to the velocity direction. Due to the existence of viscosity, the flow near the wall has a larger shear rate. The intermediate transition region is located between the contact area and the fracture lateral wall and does not contain the region with strong viscous friction caused by the wall. The flow velocity magnitude in the intermediate transition zone changes exponentially in space and has a peak value near the contact area. After the flow bypasses the contact area, the inertial effect caused by the increase in flow velocity magnitude in the local flow channel controls the generation and development of the low-velocity region and the asymmetric degree of the velocity direction distribution. Both the mechanical aperture and the inlet flow velocity affect the stress distribution on the surface of the contact area. The occurrence of the nonlinear flow behavior of fracture seepage and nonlinear change trend of logarithmic drag coefficient curve can be predicted with the same critical Reynolds number. These results provide a useful guide for further exploring the local flow and the surface stress distribution of the local interior geometric property in a single rough-walled fracture on the mesoscopic scale.

Seismic motion incoherency effects on SSSI responses of nuclear buildings

AbstractThe spatial variation of ground motion may significantly aggravate the seismic damage of large‐scale structures such as nuclear buildings. Establishing the seismic wave field with spatial features is the basis and key to seismic analysis of large‐scale complex structures. For the nuclear island buildings, which are arranged close to each other, the influence of structure–soil–structure interaction (SSSI) and incoherent motion on the structural seismic response should be considered. Taking a domestic nuclear power project as an example, the seismic response analyses under incoherent seismic motion and coherent seismic motion are carried out respectively. The seismic motion incoherency effects on the nuclear island buildings on the common raft and the adjacent seismic category I structure are explored by comparing the results of the in‐structure response spectrum (ISRS) at key elevations. The results indicate that the seismic motion incoherency does not change the trend of the response spectrum curve and the dominant frequency. Both the peak acceleration and zero‐period acceleration of ISRS are changed to some extent. Overall, seismic motion incoherency has a more significant impact on the ISRS of nuclear buildings with smaller volumes.

Numerical modeling of structural body deformation under free surface flow based on volume of fluid–discrete element method coupling

In this work, we proposed a numerical model based on the coupling of the volume of fluid–discrete element method and bond particle method (BPM). The simulation of particle bonding and the structural body formation process had been presented, and the inter-particle bonding mechanism was introduced. We also tested dam-busting impact elastic and wedge plates at high Reynolds numbers (1.26 × 107 and 2.16 × 106) and compared the results with numerical simulations. The results show that the model has mean errors of 3.9% and 6.5% for the large and the micro-deformations, respectively. It is in perfect agreement with the curve trends of the test and keeps good convergence for different particle sizes. In addition, we also used the model used to study the hydrodynamic changes in underwater box net structures in offshore aquaculture, and the deformation kinematic properties of box nets under different material strengths were evaluated. This numerical model of this study provides the effective theoretical support and engineering guidance for the further study of the behavior of structural bodies under hydrodynamic action.

Cumulative summation analysis of learning curve for endoscopic endonasal transsphenoidal resection of craniopharyngiomas.

To evaluate the cumulative summation (CUSUM) analysis of the learning curve for Endoscopic Endonasal Transsphenoidal resection of craniopharyngioma (EETC). Retrospectively analyzed the clinical data of 113 patients who underwent EETC by the same neurosurgery team of the first affiliated Hospital of Nanchang University from June 2012 to November 2020. The learning curve was created by the CUSUM method and analyzed, which was divided into two groups: the learning stage and stable stage based on the learning curve trend. The median operation time and minimum surgical case number was calculated and the operation time and postoperative complications were compared between the two groups. The median operation time was 318 min. The best fitting curve equation was y = 227.72 + 49.06x + 0.14x2 - 0.05x3, R2 = 0.949, (p < 0.001). The minimum number of surgical cases was 65. Between the two groups, the operation time decreased from 360.8 ± 106.4 min in the learning group to 281.6 ± 69.9 min in the stable group (p < 0.05). The incidence of postoperative complications (intracranial infection, cerebrospinal fluid rhinorrhea, and diabetes insipidus) was significantly reduced (p < 0.05). The CUSUM learning curve of craniopharyngioma resection via endoscope endonasal transsphenoidal approach could better describe the learning process for a neurosurgeon. The frequency of surgery could be a good factor for strengthening the learning effect and help to shorten the learning time. After 65 cases of EETC, the surgical skills can reach a stable stage, the operation time is obviously shortened, and the postoperative complications are significantly reduced.

Tensile strength analysis of sandwich composite-to-metal joints based on experimental investigation and progressive failure method

In this study, the tensile strength characteristics of the hybrid sandwich composite-to-metal specimen consisting of two steel I-beams and a T-shaped sandwich composite structure were studied. The tensile strength of the sandwich hybrid joints under design load and ultimate load has been tested. The progressive failure model is established according to the modified Shokrieh-Hashin criterion. The interface cohesive zone model is applied to reveal the damage development of the bonding layer. The stresses, strains, ultimate strength, and main damage modes of the hybrid joint under design load and ultimate load conditions are simulated and the predicted results are compared with those from tests. The experimental and numerical results show that the strain, the trend of load-displacement curves and the damage modes are in good agreement. The strength of matrix is the main factor limiting ultimate strength. Therefore, the influences of the overlapping width and thickness on ultimate bearing capacity were analyzed to obtain the optimized structural strength of the sandwich composite-to-metal bolted joints.

Antiviral effectiveness and survival correlation of azvudine and nirmatrelvir/ritonavir in elderly severe patients with COVID-19: a retrospective real-world study

Azvudine and nirmatrelvir/ritonavir are approved to treat mild-to-moderate coronavirus disease 2019 (COVID-19) in adults with a high risk for progression to severe infection. We sought to compare the antiviral effectiveness and clinical outcomes of elderly severe patients with COVID-19 receiving these two antiviral agents. In this observational study, we identified 249 elderly patients with severe COVID-19 infection who were admitted to the Second Medical Center of the People's Liberation Army General Hospital from December 2022 to January 2023, including 128 azvudine recipients, 66 nirmatrelvir/ritonavir recipients and 55 patients not received antiviral treatments. We compared the cycle threshold (Ct) value dynamic change of all three groups. The primary outcome was a composite outcome of disease progression, including all-cause death, intensive care unit admission, and initiation of invasive mechanical ventilation. The outcomes of all enrolled patients were followed up from the electronic medical record system. Kaplan-Meier and Cox risk proportional regression analyses were used to compare the clinical outcomes of all three groups. To more directly compare the effectiveness of the two antiviral drugs, we performed propensity-score matching between the two antiviral groups and compared antiviral efficacy and clinical outcomes in the matched population. Among 249 patients (mean age, 91.41 years), 77 patients died during the follow-up period. When compared to patients who did not receive any antivirals, neither nirmatrelvir/ritonavir nor azvudine demonstrated a survival benefit. The Cox analysis of the all-cause death of the three groups showed that the risk of death was 0.730 (0.423-1.262) in the azvudine group 0.802 (0.435-1.480) and in the nirmatrelvir/ritonavir group compared with the non-antiviral group. After propensity score matching, we included 58 azvudine recipients and 58 nirmatrelvir/ritonavir recipients. The fitted curve of the Ct value after matching illustrated that the rate of viral decline in the early stage of nirmatrelvir/ritonavir treatment seems to surpass that of azvudine, but there was no statistical significance. Azvudine was seemly associated with a lower risk of composite outcomes (HR:1.676, 95% CI:0.805-3.488) and short-term all-cause death (HR: 1.291, 95%CI: 0.546-3.051). Patients who received azvudine have a similar antiviral effectiveness and survival curve trend compared to nirmatrelvir/ritonavir. In this limited series, antiviral treatment was not associated with a significant clinical benefit. This lack of clinical benefit might be attributed to potential bias. This study was supported by the "National Key R&D Program of China" (Funding No. 2020YFC2008900) and the National Defense Science and Technology Innovation Special Zone Project (223-CXCY-N101-07-18-01).

Deriving location-specific synthetic seasonal hyetographs using GPM records and comparing with SCS curves

Abstract The hyetograph represents the temporal spread of rainfall intensity occurring at a point or over a watershed during a storm. The importance of regionally derived/developed hyetographs and the pooled sets of categorical seasonal curves on intensity-duration, intensity-depth, and depth-duration are of multifarious conveniences and importance. Twenty-one years of daily and sub-daily rainfall records (2000–2020) regained via satellite-observed precipitation products were examined and used to retrieve a valid understanding towards annual, monthly, daily, and hourly based variability of rainfall across six different stations. An attempt was made to compare the shapes of synthesized seasonal rain mass curves with that of the historic Soil Conservation Service (SCS) mass curve. The results indicate that the location-specific patterns and trends of curves do not align closely with any historical SCS curves or theoretical curves prevalent in the literature and commonly adopted. It has been observed that region-specific rainfall and its temporal distributions exhibit unique trends, not necessarily conforming to the standard SCS-based curves categorized as Types I, Ia, II, and III. This emphasizes the need to rely more on region-specific curves rather than instinctively adopting a standard set of curves.

Synchronies and asynchronies in the development of COVID-19 pandemic in Italy

the study of the possible determinants of the rise and fall of infections can be of great relevance, as was experienced during the COVID-19 pandemic. One of the methods to understand whether determinants are simultaneous or develop through contiguity between different areas is the study of the diagnostic replication index RDt among regions. to introduce the analysis of RDt variability and the subsequent application of a recently introduced functional clustering method as highly useful procedures for recognizing the presence of clusters with similar trends in epidemic curves. within the considered period, trends in regional RDt are analyzed in detail over four different time intervals. to exemplify this methodology, the study of variability in the period from the end of 2021 to the beginning of 2022 may be of interest. the variability in the regional RDt indices is assessed by means of the correlation coefficient weighted with respect to the populations of the individual regions. The clustering procedure is applied to the time series of absolute RDt values. it emerges that the periods of increasing variability in the RDt correspond to the initial growth or decrease in the number of infections, while functional clustering identifies macro-areas in which the epidemic curves have had similar trends. What caused contagions to increase seems to relate to a factor that is not specific to certain areas, with the contribution in some cases of a contagion dynamic between adjacent areas. the variability in the trend of regional diagnostic replication indices, which are calculated with only a few days delay, is a further indicator for the early detection of major changes in the trend of epidemic curves. The clustering of epidemic index curves may be useful to determine whether determinants act simultaneously or by contiguity between adjacent areas.

The Energy-dependent Gamma-Ray Light Curves and Spectra of the Vela Pulsar in the Dissipative Magnetospheres

We study the pulsar energy-dependent γ-ray light curves and spectra from curvature radiation in the dissipative magnetospheres. The dissipative magnetospheres with the combined force-free (FFE) and Aristotelian are computed by a pseudo-spectral method with a high-resolution simulation in the rotating coordinate system, which produces a near-FFE field structure with the dissipative region only near the equatorial current sheet outside the light cylinder. We use the test-particle trajectory method to compute the energy-dependent γ-ray light curves and phase-average and phase-resolved spectra by including both the accelerating electric field and radiation reaction. The predicted energy-dependent γ-ray light curves and spectra are then compared with those of the Vela pulsar observed by Fermi. Our results can generally reproduce the observed trends of the energy-dependent γ-ray light curves and spectra for the Vela pulsar.

A planting optimization strategy to improve the carbon sink benefit for urban green-Taking the communal green of Nanjing Forestry University as an example

This research study identified the communal green at Nanjing Forestry University as an example and focused on the carbon sink benefits of the plant communities. Firstly, the representative plant communities in the communal green were investigated, and the parameters of the plant communities were established so that the carbon sink benefits of each plant community could be quantified. Secondly, by applying correlation analysis to study the influence degree of varied plant community factors on the benefits of carbon sink, it was found that the canopy closure, diameter class structure and tree density showed significant positive correlation; the correlation between community density and daily carbon sequestration per unit area was significant; the correlation between community density and carbon storage per unit area showed none significance; and the correlation between the proportion of trees and shrubs and the carbon sink benefits was of no significance. Thirdly, regression analysis was used to study the curve trends of the carbon sink benefits of the plant communities, from which it was concluded that increasing canopy density, average plant height, average crown width and tree density will improve carbon sink benefits. Increasing the average DBH would achieve positive effects for increasing daily carbon sequestration per unit area only at the early stage of the community growth. The plant community density showed positive effects on the increase of the daily carbon sequestration per unit area within a limited range. Since most regression formulas resulted in S-curves, certain threshold bottlenecks were found existed of improving the carbon sinks benefits by increasing the plant community factors. Finally, the characteristics of plant communities with high carbon sink benefit were summarized to provide theoretical references for forming a planting optimization strategy of urban green.

Prediction for Some Tech Stock Prices of U.S. Stock Market based on ARIMA Model

Predicting the future price of stocks is a common practice in the financial industry. Individuals and organizations engage in stock price forecasting for investment decision-making, risk management, portfolio optimization and asset allocation. However, the predicting stock prices is challenging due to the complexity of financial markets, the influence of numerous variables, and the presence of random and unpredictable events, which all make it harder to predict. This paper uses predicted future stock price trends for technology companies in The United States based on ARIMA and breaks it down using APPLE as a specific example for a more in-depth discussion of ARIMA. The raw data is collected from 2001/5/11 to 2021/4/22. Then it predicted the stock prices for the next two weeks (working days) by ARIMA and made a fitted trend curve, and finally compared it with the real data from 2021/4/23 to 2021/5/12 to see if ARIMA's predictions were accurate. The result shows that prediction model is in the form of ARIMA (1,1,1), and the prediction of APPL from 2021/4/23 to 2021/5/12 is trending down, which matches the real trend.

Estimation of the Smallest Acceptable Sample Size in Bilateral Approaches to Coefficient Estimation and Accuracy Prediction

This study is about smallest acceptable sample size determination in experimental design studies involving a driving simulator. The smallest acceptable sample size should be specified so researchers can make accurate inferences about their studied populations. However, the number of samples typically collected is largely subject to the expense of data collection. Working out the methodology of estimating the required number of subjects based on an initially small number is a better way for researchers to determine the smallest acceptable sample size in the experiment. Predictor estimate precision and prediction accuracy are major factors for conducting experiments. Accordingly, this study estimates the smallest acceptable sample size, with emphasis on coefficient estimation and prediction accuracy for selected significant variables. The smallest acceptable sample size is chosen to be the maximum value returned by both coefficient estimation calculation and accuracy prediction calculation approaches. This methodology is flexible and scalable, and can be tailored to other experimental situations. To validate the appropriateness of this procedure, a more than sufficient sample of 50 drivers was recruited. The smallest acceptable sample size was determined backwardly, based on the variable coefficient convergence trends of the mean squared error (MSE) curves of the significant variables. Both the clear converging trends of the MSE curves and the proposed method indicated that 30 was an acceptable sample size.

Quantitative assessment of sedimentation in Moroccan dam reservoirs: analysis and projections

The siltation of dam reservoirs is the phenomenon that most embarrasses dam managers and water reservoir operators. In Morocco, this phenomenon affects all the watersheds to different degrees. Dam managers schedule bathymetric measurement companies to estimate the quantities of mud deposited in reservoirs. These companies are neither regular in time nor generalized on the 152 large dams of the Kingdom because of the high cost of the bathymetry operations. In our research work, the bathymetric data available for about a century were collected, checked, corrected, and sorted to be exploited.In the next step, we extrapolated over time and updated the siltation rates for each dam according to the trend curves of the evolution of silted volume. Most of these trend curves were linear. For the nonlinear curves, we looked for explanations throughout history. These are dams whose reservoirs have undergone human intervention such as desilting operations or emptying of reservoirs, or following natural phenomena such as drought or exceptional floods. The research work subsequently made it possible to estimate the annual siltation rates for 53 large dams whose reservoir capacities total approximately 92% of that of the entire country. It also revealed an overall siltation rate of 18.14% for the entire country and rates ranging from 10% to 52% for each watershed. The discussions of these results in this article give explanations on the highest rates, based on the natural data of the watersheds in question. These results will help decision-makers to define the priorities of desilting operations or the construction of new dams, help investors and industrialists wishing to extract and use mud from dam reservoirs as raw material, and can also be used in various scientific fields such as dam reservoir management, flood risk prevention, environmental impact studies, spatial planning, and research and development studies.

Bitemarks and 3D scanner: An objective comparison for bitemarks. A pilot study

The marks left by the bite of a subject (bitemark) represent an unequivocal character, being useful in identifying the possible perpetrator of a crime. To date, the analysis of bitemarks is mainly based on the direct vision of photographic finds and on the visual comparison with the teeth of the hypothetically responsible person. However, the bitemark also retains three-dimensional characteristics detectable with a 3D scanner. In this pilot study, an innovative method of bitemark analysis, utilizing a three-dimensional scanner and some software, will be introduced, enabling a quantitative comparison of bitemarks and their corresponding human dentitions. For this purpose, 10 complete plaster models (human dentitions) of 10 adult subjects were used to make 20 experimental bitemarks on dentistry wax. All materials were individually scanned with the iTero® 3D scanner and reworked with MeshMixer software. A visual analysis of the characteristics and a computerized analysis with the CloudCompare software were also performed. Study showed a different trend of the distribution curves of the points which were obtained comparing the human dentition and coincident and non-coincident bitemarks. Current results support that the intraoral 3D scanner allows the fast record and the preservation of the three-dimensional characteristics of the bitemarks, and it allows computerized analyses to be carried out.

The Role of the 18F-FDG PET/CT in the Management of Patients Suspected of Cardiac Implantable Electronic Devices' Infection.

Background: Infection of Cardiac Implantable Electronic Devices (CIEDI) is a real public health problem. The main aim of this study was to determine the diagnostic performance of 18F-FDG PET/CT in the diagnosis of CIEDI. Methods: A total of 48 patients, who performed 18F-FDG PET/CT for the clinical suspicion of CIEDI were retrospectively analyzed; all patients were provided with a model with procedural recommendations before the exam. Sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy (DA) of 18F-FDG PET/CT were calculated; the reproducibility of qualitative analysis was assessed with Cohen's κ test. The semi-quantitative parameters (SUVmax, SQR and TBR) were evaluated in CIEDI+ and CIEDI- patients using the Student' t-test; ROC curves were elaborated to detect cut-off values. The trend of image quality with regards to procedural recommendation adherence was evaluated. Results: Se, Sp, PPV, NPV and DA were respectively 96.2%, 81.8%, 86.2%, 94.7% and 89.6%. The reproducibility of qualitative analysis was excellent (K = 0.89). Semiquantitative parameters resulted statistically different in CIEDI+ and CIEDI- patients. Cut-off values were SUVmax = 2.625, SQR = 3.766 and TBR = 1.29. Trend curves showed increasing image quality due to adherence to procedural recommendations. Conclusions:18F-FDG-PET/CT is a valid tool in the management of patients suspected of CIEDI and adherence to procedural recommendations improves its image quality.

Experimental Study on the Mechanical Properties of Hybrid Basalt-Polypropylene Fibre-Reinforced Gangue Concrete

Incomplete data indicate that coal gangue is accumulated in China, with over 2000 gangue hills covering an area exceeding 200,000 mu and an annual growth rate surpassing 800 million tons. This accumulation not only signifies a substantial waste of resources but also poses a significant danger to the environment. Utilizing coal gangue as an aggregate in the production of coal-gangue concrete offers an effective avenue for coal-gangue recycling. However, compared with ordinary concrete, the strength and ductility of coal-gangue concrete require enhancement. Due to coal-gangue concrete having higher brittleness and lower deformation resistance than ordinary concrete, basalt fibre (BF) is a green, high-performance fibre that exhibits excellent bonding properties with cement-based materials, and polypropylene fibre (PF) is a flexible fibre with high deformability; thus, we determine if adding BF and PF to coal-gangue concrete can enhance its ductility and strength. In this paper, the stress–strain curve trends of different hybrid basalt–polypropylene fibre-reinforced coal-gangue concrete (HBPRGC) specimens under uniaxial compression are studied when the matrix strengths are C20 and C30. The effects of BF and PF on the mechanical and energy conversion behaviours of coal-gangue concrete are analysed. The results show that the ductile deformation of coal-gangue concrete can be markedly enhanced at a 0.1% hybrid-fibre volume content; HBPRGC-20-0.1 and HBPRGC-30-0.1 have elevations of 53.66% and 51.45% in total strain energy and 54.11% and 50% in dissipative energy, respectively. And HBPRGC-20-0.2 and HBPRGC-30-0.2 have elevations of 31.95% and 30.32% in total strain energy and −3.46% and 28.71% in dissipative energy, respectively. With hybrid-fibre volume content increased, the elastic modulus, the total strain energy, and the dissipative energy all show a downward trend. Therefore, 0.1% seems to be the optimum hybrid-fibre volume content for well-enhancing the ductility and strength of coal-gangue concrete. Finally, the damage evolution and deformation trends of coal-gangue concrete doped with fibre under uniaxial action are studied theoretically, and the constitutive model and damage evolution equation of HBPRGC are established based on Weibull theory The model and the equation are in good agreement with the experimental results.

Digital Twin-based Predictive Maintenance for Sheet Metal Bending

This paper focuses on the implementation of predictive maintenance processes using both physics-based and data-driven methods, specifically applied to a Salvagnini panel bender. The primary objective is to enhance production data analysis through digital twin predictions, enabling the calculation of process parameters that cannot be directly measured. Two key aspects are addressed in this study: Firstly, two global measures of the effective cumulative load on a machine during its lifetime are formulated. These measures can be used as criteria for estimating the health condition of a machine and for comparing different machines. To achieve this, dimensionless parameters are derived from actual production data. Secondly, a remaining useful life (RUL) model is developed for two machine components relying on production data analysis and digital twin predictions. The first component under consideration is a hybrid hydraulic actuator. Internal leakage prediction for this component is performed based on its data history, resulting in a corresponding trend curve. Additionally, wear of critical bearings is calculated using an analytical model that depends on the production history log. Through the proposed hybrid approach, this paper aims to enhance the predictive maintenance process by leveraging both physics-based and data-driven methodologies. The findings from this study can offer valuable insights for optimizing maintenance strategies and improving the overall efficiency of similar manufacturing systems.

Strategies based on nido-carborane embedded indole fluorescent polymers: their synthesis, spectral properties and cell imaging studies.

The continuous preparation scheme EPO-Poly-indol-nido-carborane (E-P-INDOLCAB), L100-55-Poly-indol-nido-carborane (L-P-INDOLCAB), RS-Poly-indol-nido-carborane (S-P-INDOLCAB), and RL-Poly-indol-nido-carborane (R-P-INDOLCAB) were used to prepare the four types of acrylic resin-coated nido-carborane indole fluorescent polymers. After testing their spectral properties and the fluorescence stability curve trend at various acidic pH values (3.4 and 5.5, respectively), L-P-INDOLCAB and S-P-INDOLCAB were determined to be the best polymers. The stable states of the two polymers and the dispersion of the nanoparticles on the system's surface during Atomic Force Microscope (AFM) test are shown by the zeta potentials of -23 and -42mV. The dispersion of nanoparticles on the system's surface and the stable condition of the two polymers were examined using zeta potential and atomic force microscopy (AFM). Transmission electron microscopy (TEM) can also confirm these findings, showing that the acrylic resin securely encases the interior to form an eyeball. Both polymers' biocompatibility with HELA cells was enhanced in cell imaging, closely enclosing the target cells. The two complexes displayed strong inhibitory effects on PC-3 and HeLa cells when the concentration was 20ug/mL, as validated by subsequent cell proliferation toxicity studies.

Comparison of leaf chlorophyll content retrieval performance of citrus using FOD and CWT methods with field-based full-spectrum hyperspectral reflectance data

Citrus is one of the most economically valuable fruit trees in the world, for which leaf chlorophyll content (LCC) serves as a crucial indicator for evaluating its growth and health status. However, the quantitative estimation of LCC using remote-sensing techniques is still challenging owing to unclear sensitive spectral ranges, baseline drift and overlapping spectrum peaks. To resolve these issues, we clarified the spectral response characteristics of citrus LCC using fractional-order derivatives (FOD) and continuous wavelet transform (CWT) methods to determine its sensitive spectral range with in situ full-spectrum leaf hyperspectral data. We proposed a novel method for estimating the LCC of citrus by combining an ensemble learning regression model based on Hyperopt optimization (H-ELR) with partial least squares regression (PLSR) using the ultra-high dimensional feature variables produced by dual- and tri-band combination strategies. We evaluated the retrieval performance of LCC between the FOD- and CWT-based optimal spectral feature variables. Besides, we further examined the feasibility of improving the estimation accuracy of LCC by the combination of their optimal feature variables. Finally, we evaluated the effect of the spectral curve trend changes and different dimensional spectral features on LCC estimation. The results showed that: (1) The FOD- and CWT-based methods improved the correlation between original spectral reflectance and LCC, with the correlation coefficient increasing by 0.046 and 0.054, respectively. We confirmed that 425–740 nm is the optimal spectral range for LCC estimation. (2) We found that the 0.9 order derivative Tri-band index (TBI2 (R571, R1697, R740)) constructed by combining the sensitive spectral bands of leaf water content achieved a high-precision LCC estimation (R2 = 0.876). In addition, the MERIS terrestrial chlorophyll index (MTCI) constructed based on the scale6 of CWT also gained good retrieval accuracy (R2 = 0.806). (3) We demonstrated that a combination of FOD-based and CWT-based sensitive spectral features improves estimation accuracies (R2 = 0.891) of LCC and revealed that the reflectance peaks and slope peaks at 550 and 750 nm are essential variables for predicting the citrus LCC. (4) The combination of PLSR and H-ELR model provided a good retrieval performance of citrus LCC with the kurtosis (γ = 3.2) and skewness (Sk = 0.066) of the residual prediction values. Our proposed method can provide a scientific basis for estimating LCC and other physiological parameters of citrus and other crop types, which is also important to optimize agricultural management practices and improve crop yield.