Optimizing Grey Wolf Optimization: A Novel Agents’ Positions Updating Technique for Enhanced Efficiency and Performance

Grey Wolf Optimization (GWO) is a nature-inspired metaheuristic algorithm that has gained popularity for solving optimization problems. In GWO, the success of the algorithm heavily relies on the efficient updating of the agents’ positions relative to the leader wolves. In this paper, we provide a brief overview of the Grey Wolf Optimization technique and its significance in solving complex optimization problems. Building upon the foundation of GWO, we introduce a novel technique for updating agents’ positions, which aims to enhance the algorithm’s effectiveness and efficiency. To evaluate the performance of our proposed approach, we conduct comprehensive experiments and compare the results with the original Grey Wolf Optimization technique. Our comparative analysis demonstrates that the proposed technique achieves superior optimization outcomes. These findings underscore the potential of our approach in addressing optimization challenges effectively and efficiently, making it a valuable contribution to the field of optimization algorithms.

Collaborative positioning for swarms:A brief survey of vision,LiDAR and wireless sensors based methods

As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.

FPGA-based position reconstruction method for neutron beam flux spatial distribution measurement in BNCT

A new measurement method for the spatial distribution of neutron beam flux in boron neutron capture therapy(BNCT)is being developed based on the two-dimensional Micromegas detector.To address the issue of long processing times in traditional offline position reconstruction methods,this paper proposes a field programmable gate array based online position reconstruction method utilizing the micro-time projection chamber principle.This method encapsulates key technical aspects:a self-adaptive serial link technique built upon the dynamical adjustment of the delay chain length,fast sorting,a coordinate-matching technique based on the mapping between signal timestamps and random access memory(RAM)addresses,and a precise start point-merging technique utilizing a circular combined RAM.The performance test of the selfadaptive serial link shows that the bit error rate of the link is better than 10-12 at a confidence level of 99%,ensuring reliable data transmission.The experiment utilizing the readout electronics and Micromegas detector shows a spatial resolution of approximately 1.4 mm,surpassing the current method’s resolution level of 5 mm.The beam experiment confirms that the readout electronics system can obtain the flux spatial distribution of neutron beams online,thus validating the feasibility of the position reconstruction method.The online position reconstruction method avoids traditional methods,such as bubble sorting and traversal searching,simplifies the design of the logic firmware,and reduces the time complexity from O(n2)to O(n).This study contributes to the advancement in measuring neutron beam flux for BNCT.

An improved particle filter indoor fusion positioning approach based on Wi-Fi/PDR/geomagnetic field

The existing indoor fusion positioning methods based on Pedestrian Dead Reckoning(PDR)and geomagnetic technology have the problems of large initial position error,low sensor accuracy,and geomagnetic mismatch.In this study,a novel indoor fusion positioning approach based on the improved particle filter algorithm by geomagnetic iterative matching is proposed,where Wi-Fi,PDR,and geomagnetic signals are integrated to improve indoor positioning performances.One important contribution is that geomagnetic iterative matching is firstly proposed based on the particle filter algorithm.During the positioning process,an iterative window and a constraint window are introduced to limit the particle generation range and the geomagnetic matching range respectively.The position is corrected several times based on geomagnetic iterative matching in the location correction stage when the pedestrian movement is detected,which made up for the shortage of only one time of geomagnetic correction in the existing particle filter algorithm.In addition,this study also proposes a real-time step detection algorithm based on multi-threshold constraints to judge whether pedestrians are moving,which satisfies the real-time requirement of our fusion positioning approach.Through experimental verification,the average positioning accuracy of the proposed approach reaches 1.59 m,which improves 33.2%compared with the existing particle filter fusion positioning algorithms.

Experimental and numerical simulation study of the effect for the anode positions on the discharge characteristics of 300W class low power Hall thrusters

Low-power Hall thruster(LHT) generally has poor discharge efficiency characteristics due to the large surface-to-volume ratio.Aiming to further refine and improve the performance of 300 W class LHT in terms of thrust and efficiency,and to obtain the most optimal operating point,the experimental study of the discharge characteristics for three different anode positions was conducted under the operation of various discharge voltages(100-400 V) and anode mass flow rates(0.65 mg·s-1and 0.95 mg·s-1).The experimental results indicated that the thruster has the most excellent performance in terms of thrust and efficiency etc at a channel length of 27 mm for identical operating conditions.In addition,particle in cell simulations,employed to reveal the underlying physical mechanisms,show that the ionization and acceleration zone is pushed downwards towards the channel exit as the anode moves towards the exit.At the identical operating point,when the channel length is reduced from 32 to 27 mm,the ionization and acceleration zone moves towards the exit,and the parameters such as thrust and efficiency increase due to the high ionization rate,ion number density,and axial electric field.When the channel length is further moved to 24 mm,the parameters in terms of thrust(F) and efficiency(ηa) are reduced as a result of the decreasing ionization efficiency(ηm) and the larger plume divergence angle(α).In this paper,the results indicated that an optimum anode position(ΔL=27 mm) exists for the optimum performance.

Uncertainties in landslide susceptibility prediction:Influence rule of different levels of errors in landslide spatial position

The accuracy of landslide susceptibility prediction(LSP)mainly depends on the precision of the landslide spatial position.However,the spatial position error of landslide survey is inevitable,resulting in considerable uncertainties in LSP modeling.To overcome this drawback,this study explores the influence of positional errors of landslide spatial position on LSP uncertainties,and then innovatively proposes a semi-supervised machine learning model to reduce the landslide spatial position error.This paper collected 16 environmental factors and 337 landslides with accurate spatial positions taking Shangyou County of China as an example.The 30e110 m error-based multilayer perceptron(MLP)and random forest(RF)models for LSP are established by randomly offsetting the original landslide by 30,50,70,90 and 110 m.The LSP uncertainties are analyzed by the LSP accuracy and distribution characteristics.Finally,a semi-supervised model is proposed to relieve the LSP uncertainties.Results show that:(1)The LSP accuracies of error-based RF/MLP models decrease with the increase of landslide position errors,and are lower than those of original data-based models;(2)70 m error-based models can still reflect the overall distribution characteristics of landslide susceptibility indices,thus original landslides with certain position errors are acceptable for LSP;(3)Semi-supervised machine learning model can efficiently reduce the landslide position errors and thus improve the LSP accuracies.

Determining beam transverse absolute position by triangulation of multi-electrode signal phase differences

Accurate measurement of the transverse position of a beam is crucial in particle accelerators because it plays a key role in determining the beam parameters.Existing methods for beam-position measurement rely on the detection of image currents induced on electrodes or narrow-band wake field induced by a beam passing through a cavity-type structure.However,these methods have limitations.The indirect measurement of multiple parameters is computationally complex,requiring external calibration to determine the system parameters in advance.Furthermore,the utilization of the beam signal information is incomplete.Hence,this study proposes a novel method for measuring the absolute electron beam transverse position.By utilizing the geometric relationship between the center position of the measured electron beam and multiple detection electrodes and by analyzing the differences in the arrival times of the beam signals detected by these electrodes,the absolute transverse position of the electron beam crossing the electrode plane can be calculated.This method features absolute position measurement,a position sensitivity coefficient independent of vacuum chamber apertures,and no requirement for a symmetrical detector electrode layout.The feasibility of this method is validated through numerical simulations and beam experiments.

Effect of Prone Position in Severe Covid-19 Patients in a Referral Center: A Cohort Retrospective Study

Introduction: Covid-19 is defined as a pandemic disease by WHO, in November 2023, WHO recorded 772.1 million confirmed cases and 6.9 million deaths, including 68,382 confirmed cases and 1426 deaths in Madagascar. The management of severe cases of Covid-19 remains a challenge for the healthcare system in a resource-limited country, due to the consumption of human resources, the shortage of medical resources and the lack of capacity in resource-limited countries. Prone position (PP) improves survival in acute respiratory distress, and numerous studies have shown that during Covid-19, it reduces mortality rates at 28 and 90 days, and increases the number of days without mechanical ventilation. However, data on the beneficial effects of PP remain limited in low-income countries. In this context, our study aims to evaluate the benefits of the prone position for severe Covid-19 patients in a referral center in Madagascar. Method: This is a retrospective cohort study, during the 2nd and 3rd waves of COVID-19, over a period of 11 months in two wards managing COVID-19 cases. We included all patients aged 15 and over with severe forms of COVID-19 who required 6 l/min of oxygen therapy. Results: We enrolled 123 patients, including 40 in the prone position and 83 in the supine position, with a mean age of 60.5 ± 12 years. The prone position (DV) reduced the risk of probable complications of COVID-19 with a strong association in terms of use of respiratory assistance (OR = 0.15;95% CI = 0.05 - 0.47), respiratory deterioration (OR = 0.22;95% CI = 0.09 - 0.58), shock (OR = 0.30;95% CI = 0.11 - 0.79) and hemodynamic instability (OR = 0.33;95% CI = 0.12 - 0.95). Univariate analysis of the effect of prone position on SpO2 showed improvement with significant associations with SpO2 at Day 1- Day 3, D4 - D7, D8 - D14, and persisting even at D15 - D21, D3 and D2 before discharge, and at discharge. In the overall population, the mean length of hospital stay was 22.8 ± 22.1 days, with extremes of 1 and 67 days. Univariate analysis of the effect of the prone position showed a reduction in length of hospital stay with a strong association (p = 0.001) and a mean difference of 14 days. The prone position reduced mortality with a significant association (OR = 0.44;95% CI = 0.20 - 0.98). Conclusion: Awake prone position prevents complications of COVID, improves SPO2 even up to hospital discharge and reduces hospital stay. This practice is simple, less costly and suitable in low income countries.

Tuning the diffusion constant to optimize the readout of positional information of spatial concentration patterns

Positional information encoded in spatial concentration patterns is crucial for the development of multicellular organisms.However,it is still unclear how such information is affected by the physically dissipative diffusion process.Here we study one-dimensional patterning systems with analytical derivation and numerical simulations.We find that the diffusion constant of the patterning molecules exhibits a nonmonotonic effect on the readout of the positional information from the concentration patterns.Specifically,there exists an optimal diffusion constant that maximizes the positional information.Moreover,we find that the energy dissipation due to the physical diffusion imposes a fundamental upper limit on the positional information.

Assessment of Liver Fibrosis in HBsAg-Negative and Anti HBc Positive Patients

Background: Surface antigen (HBsAg) is the mean marker of hepatitis B virus infection. During the course of the infection, some patients lose the HBsAg and only the presence of anti-HBc antibody indicates previous contact with the virus. Among these patients, some have detectable viral load (occult infection) but most without viral replication. There is no guideline regarding these patients. The aim of this study was to assess hepatic fibrosis in patients with only the hepatitis B virus contact marker “total anti-HBc”. Patients and methods: it was a descriptive and analytical cross-sectional study, conducted in three private hospitals from January to August 2022. Were included HBsAg-negative and HBc-positive patients, consulting in Gastroenterology departments. Noninvasive methods (APRI, FIB-4 and FIBROSCAN) were used to evaluate liver stiffness because of their easy accessibility and low-cost. The hepatic fibrosis was considered significant when the score determined by APRI, FIB-4 and FIBROSCAN® tests was respectively greater than 1.5;2.67 and 8 kPa corresponding to fibrosis level 2 (F2). Results: A total of 63 HBsAg-negative/total HBcAg-positive patients were included. The mean age was 49.9 ± 13.4 years. The male/female sex ratio was 1.78. Of the 63 patients, 19 had significant liver fibrosis (30.1%) among which 9 patients had HCC. The FIB-4 score outperformed the APRI score in assessing liver fibrosis, with a sensitivity of 84.2%, a specificity of 100% and a negative predictive value of 93.6%. In univariate analysis, there was a significant association between the occurrence of significant liver fibrosis and age over 40 years, dyslipidaemia, obesity, alcohol consumption, smoking, herbal medicine, negative anti-HBs immunological status and detectable viral load. Conclusion: Our study revealed a high prevalence of significant to severe hepatic fibrosis in anti-HBc positive patients. In most of the cases, the fibrosis was severe. Progression to HCC has also been possible. There is no consensus on the follow-up strategy for those patients. However, screening for hepatic fibrosis using noninvasive methods should be recommended for patients aged over 40 years, alcohol or herbal medicine users, patients with metabolic syndrome or occult hepatitis B. In HBsAg-negative/anti-HBc-positive patients, liver stiffness should be evaluated and if it is greater than F2, HCC screening should be started.

Method for determining the position of landslide slip-surface with a typical inclinometric curves

In the actual monitoring of deep hole displacement,the identification of slip surfaces is primarily based on abrupt changes observed in the inclinometric curve.In conventional identification methods,inclinometric curves exhibiting indications of sliding can be categorized into three types:B-type,D-type,and r-type.The position of the slip surface is typically determined by identifying the depth corresponding to the point of maximum displacement mutation.However,this method is sensitive to the interval of measurement points and the observation scale of the coordinate axes and suffers from unclear sliding surfaces and uncertain values.Based on the variation characteristics of these diagonal curves,we classified the landslide into three components:the sliding body,the sliding interval,and the immobile body.Moreover,three different generalization models were established to analyze the relationships between the curve form and the slip surface location based on different physical indicators such as displacement rate,relative displacement,and acceleration.The results show that the displacement rate curves of an r-type slope exhibit a clustering feature in the sliding interval,and by solving for the depth of discrete points within the step phase,it is possible to determine the location of the slip surface.On the other hand,D-type slopes have inflection points in the relative displacement curve located at the slip surface.The acceleration curves of B-type slopes exhibit clustering characteristics during the sliding interval,while the scattered acceleration data demonstrate wandering characteristics.Consequently,the slip surface location can be revealed by solving the depth corresponding to the maximum acceleration with cubic spline interpolation.The approach proposed in this paper was applied to the monitoring data of a landslide in Yunnan Province,China.The results indicate that our approach can accurately identify the slip surface location and enable computability of its position,thereby enhancing applicability and reliability of the deep-hole displacement monitoring data.

Effects of the initiation position on the damage and fracture characteristics of linear-charge blasting in rock

To study the effects of the initiation position on the damage and fracture characteristics of linear-charge blasting, blasting model experiments were conducted in this study using computed tomography scanning and three-dimensional reconstruction methods. The fractal damage theory was used to quantify the crack distribution and damage degree of sandstone specimens after blasting. The results showed that regardless of an inverse or top initiation, due to compression deformation and sliding frictional resistance, the plugging medium of the borehole is effective. The energy of the explosive gas near the top of the borehole is consumed. This affects the effective crushing of rocks near the top of the borehole, where the extent of damage to Sections Ⅰ and Ⅱ is less than that of Sections Ⅲ and Ⅳ. In addition, the analysis revealed that under conditions of top initiation, the reflected tensile damage of the rock at the free face of the top of the borehole and the compression deformation of the plug and friction consume more blasting energy, resulting in lower blasting energy efficiency for top initiation. As a result, the overall damage degree of the specimens in the top-initiation group was significantly smaller than that in the inverse-initiation group. Under conditions of inverse initiation, the blasting energy efficiency is greater, causing the specimen to experience greater damage. Therefore, in the engineering practice of rock tunnel cut blasting, to utilize blasting energy effectively and enhance the effects of rock fragmentation, using the inverse-initiation method is recommended. In addition, in three-dimensional(3D) rock blasting, the bottom of the borehole has obvious end effects under the conditions of inverse initiation, and the crack distribution at the bottom of the borehole is trumpet-shaped. The occurrence of an end effect in the 3D linear-charge blasting model experiment is related to the initiation position and the blocking condition.

Developing a highly scalable synthetic strategy for 5-amino-4-nitrobenzo[1,2-c:3,4-c']bis([1,2,5]oxadiazole)1,b-dioxide(CL-18)and investigating the influence of crystal engineering and positional isomerization on its safety and laser ignition performance

5-amino-4-nitrobenzo[1,2-c:3,4-c']bis([1,2,5]oxadiazole)1,6-dioxide(CL-18)exhibits significant potential as an initiating explosive.However,its current synthesis process remains non-scalable due to low yields and safety risks.In this study,we have developed a simple and safe synthetic route for CL-18.It was synthesized from 3,5-dihaloanisole in a four-step reaction with an overall yield exceeding 60%,surpassing all reported yields in the literature.Subsequently,recrystallization of CL-18 was successfully achieved by carefully selecting appropriate solvents and antisolvents to reduce its mechanical sensitivity.Ultimately,when DMF-ethanol was employed as the recrystallization solvent system,satisfactory product yield(>90%)and reduced mechanical sensitivity(IS=15 J;FS=216 N)were obtained.Additionally,CL-18 is derived from the rearrangement of oxygen atoms on i-CL-18 furoxan,and a comparative analysis of their physicochemical properties was conducted.The thermal stability of both compounds is similar,with onset decomposition temperatures recorded at 186 and 182℃respectively.Similarly,they exhibit 5 s breaking point temperatures of 236 and 237℃.Additionally,we present novel insights into the positional-isomerization-laser-ignition performance of CL-18 and its isomer i-CL-18 using laser irradiation for the first time.Remarkably,our findings demonstrate that i-CL-18 exhibits enhanced laser sensitivity,as it can be directly ignited by a 1064 nm wavelength laser,whereas CL-18 lacks this characteristic.

Open AccessAmplifying colorectal cancer progression:impact of a PDIA4/SP1 positive feedback loop by circPDIA4 sponging miR-9-5p

Objective:Colorectal cancer(CRC)is a prevalent malignant tumor with a high fatality rate.CircPDIA4 has been shown to have a vital role in cancer development by acting as a facilitator.Nevertheless,the impact of the circPDIA4/miR-9-5p/SP1 axis on development of CRC has not been studied.Methods:Western blot,immunohistochemistry,and reverse transcription-quantitative polymerase chain reaction assays were used to analyze gene expression.The CCK-8 assay was used to assess cell growth.The Transwell assay was used to detect invasion and migration of cells.The luciferase reporter and RNA immunoprecipitation tests were used to determine if miR-9-5p and circPDIA4(or SP1)bind to one another.An in vivo assay was used to measure tumor growth.Results:It was shown that circPDIA4 expression was greater in CRC cell lines and tissues than healthy cell lines and tissues.CircPDIA4 knockdown prevented the invasion,migration,and proliferation of cells in CRC.Additionally,the combination of circPDIA4 and miR-9-5p was confirmed,as well as miR-9-5p binding to SP1.Rescue experiments also showed that the circPDIA4/miR-9-5p/SP1 axis accelerated the development of CRC.In addition,SP1 combined with the promoter region of circPDIA4 and induced circPDIA4 transcription.CircPDIA4 was shown to facilitate tumor growth in an in vivo assay.Conclusions:The circPDIA4/miR-9-5p/SP1 feedback loop was shown to aggravate CRC progression.This finding suggests that the ceRNA axis may be a promising biomarker for CRC patient treatment.

Adaptive H_(∞)Filtering Algorithm for Train Positioning Based on Prior Combination Constraints

To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.

Wireless Positioning:Technologies,Applications,Challenges,and Future Development Trends

The development of the fifth-generation(5G)mobile communication systems has entered the commercialization stage.5G has a high data rate,low latency,and high reliability that can meet the basic demands of most industries and daily life,such as the Internet of Things(IoT),intelligent transportation systems,positioning,and navigation.The continuous progress and development of society have aroused wide concern.Positioning accuracy is the core demand for the applications,especially in complex environments such as airports,warehouses,supermarkets,and basements.However,many factors also affect the accuracy of positioning in those environments,for example,multipath effects,non-line-of-sight,and clock synchronization errors.This paper provides a comprehensive review of the existing works about positioning for the future wireless network and discusses its key techniques and algorithms,as well as the current development and future directions.We first outline the current traditional positioning technologies and algorithms,which are discussed and analyzed with the relevant literature.In addition,we also discuss application scenarios for wireless localization.By comparing different positioning systems,the challenges and future development directions of existing wireless positioning systems are prospected.

Synthetic Aperture Positioning: A Review

Obtaining precise position of interested emitters passively has wide applications in both civilian and military fields.Different from traditional parameter measurement and direct position determination(DPD)method,recently a new passive localization method based on synthetic aper-ture technique,named synthetic aperture positioning(SAP),has been proposed.The method com-pensates for the nonlinear phase produced by relative motion between the moving platform and the emitter,achieving coherent summation of intercepted signals.The SAP can obtain high-resolution and high-precision localization results at a low signal-to-noise ratio.This paper summarizes the research progress of SAP,including localization principles,spaceborne applications,and application scope analysis.Besides,the possible future outlook of SAP is considered.

Hybrid pedestrian positioning system using wearable inertial sensors and ultrasonic ranging

Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional PPS is limited by the cumulative error of inertial sensors,complex motion modes of pedestrians,and the low robustness of the multi-sensor collaboration structure.This paper presents a hybrid pedestrian positioning system using the combination of wearable inertial sensors and ultrasonic ranging(H-PPS).A robust two nodes integration structure is developed to adaptively combine the motion data acquired from the single waist-mounted and foot-mounted node,and enhanced by a novel ellipsoid constraint model.In addition,a deep-learning-based walking speed estimator is proposed by considering all the motion features provided by different nodes,which effectively reduces the cumulative error originating from inertial sensors.Finally,a comprehensive data and model dual-driven model is presented to effectively combine the motion data provided by different sensor nodes and walking speed estimator,and multi-level constraints are extracted to further improve the performance of the overall system.Experimental results indicate that the proposed H-PPS significantly improves the performance of the single PPS and outperforms existing algorithms in accuracy index under complex indoor scenarios.

Combined application of organic fertilizer and chemical fertilizer alleviates the kernel position effect in summer maize by promoting post-silking nitrogen uptake and dry matter accumulation

Adjusting agronomic measures to alleviate the kernel position effect in maize is important for ensuring high yields.In order to clarify whether the combined application of organic fertilizer and chemical fertilizer(CAOFCF)can alleviate the kernel position effect of summer maize,field experiments were conducted during the 2019 and 2020 growing seasons,and five treatments were assessed:CF,100%chemical fertilizer;OFCF1,15%organic fertilizer+85%chemical fertilizer;OFCF2,30%organic fertilizer+70%chemical fertilizer;OFCF3,45%organic fertilizer+55%chemical fertilizer;and OFCF4,60%organic fertilizer+40%chemical fertilizer.Compared with the CF treatment,the OFCF1 and OFCF2 treatments significantly alleviated the kernel position effect by increasing the weight ratio of inferior kernels to superior kernels and reducing the weight gap between the superior and inferior kernels.These effects were largely due to the improved filling and starch accumulation of inferior kernels.However,there were no obvious differences in the kernel position effect among plants treated with CF,OFCF3,or OFCF4 in most cases.Leaf area indexes,post-silking photosynthetic rates,and net assimilation rates were higher in plants treated with OFCF1 or OFCF2 than in those treated with CF,reflecting an enhanced photosynthetic capacity and improved postsilking dry matter accumulation(DMA)in the plants treated with OFCF1 or OFCF2.Compared with the CF treatment,the OFCF1 and OFCF2 treatments increased post-silking N uptake by 66.3 and 75.5%,respectively,which was the major factor driving post-silking photosynthetic capacity and DMA.Moreover,the increases in root DMA and zeatin riboside content observed following the OFCF1 and OFCF2 treatments resulted in reduced root senescence,which is associated with an increased post-silking N uptake.Analyses showed that post-silking N uptake,DMA,and grain yield in summer maize were negatively correlated with the kernel position effect.In conclusion,the combined application of 15-30%organic fertilizer and 70-85%chemical fertilizer alleviated the kernel position effect in summer maize by improving post-silking N uptake and DMA.These results provide new insights into how CAOFCF can be used to improve maize productivity.