Differential pressure difference based altitude control of a stratospheric satellite

An autonomous altitude adjustment system for a stratospheric satellite(StratoSat)platform is proposed.This platform consists of a helium balloon,a ballonet,and a two-way blower.The helium balloon generates lift to balance the platform gravity.The two-way blower inflates and deflates the ballonet to regulate the buoyancy.Altitude adjustment is achieved by tracking the differential pressure difference(DPD),and a threshold switching strategy is used to achieve blower flow control.The vertical acceleration regulation ability is decided not only by the blower flow rate,but also by the designed margin of pressure difference(MPD).Pressure difference is a slow-varying variable compared with altitude,and it is adopted as the control variable.The response speed of the actuator to disturbance can be delayed,and the overshoot caused by the large inertia of the platform is inhibited.This method can maintain a high tracking accuracy and reduce the complexity of model calculation,thus improving the robustness of controller design.

Model of Mediating Determinants of Time Differences in INDYCAR

The IndyCar series distinguishes itself by providing the same design and operation of the single-seater to its pilots.The difference in times is then attributable to the skills of the drivers,but considering the data from the races could test this assumption.The objective of this work was to establish a trajectory model to predict race times.A cross-sectional,correlational,and explanatory work was carried out with a sample of 18,474 records in the period from 2020 to 2023 of the IndyCar series.The results show that the time span predicts the time differences.In relation to the studies of acceptance of the technology,the adjustment of this to human capacities to explain the time differences in the series of racing cars is discussed.

The Impact of Urban and Rural Education Gap on Student Achievement Differences

With our country’s social development,the gap between urban and rural education has become increasingly obvious,especially the difference in student achievement.This study aims to explore the impact of the urban-rural education gap on student achievement.The study adopts a quantitative analysis method to collect and analyze the academic performance,learning resources,and social resources of urban and rural students.The results show that the unbalanced distribution of educational resources in urban and rural areas is the key factor leading to the gap in students’achievement.For example,urban education resources are abundant while rural education resources are relatively scarce.At the same time,the difference in social environment and family economic status also have a significant impact on student achievement.The differences between urban and rural areas,particularly in terms of family economic conditions and their ability to invest in education,further widen the gap between urban and rural education.The results of this study can provide a reference for reducing the gap between urban and rural education and improving the academic performance of rural students.A fair education policy is essential to narrow the gap between urban and rural education resources distribution,so as to improve the equality of education in society.

A Comprehensive Study on Gender Language and Its Differences in China

The study of language and gender,especially the study of gender language differences involves many fields such as psychology,sociology,anthropology,language and literature,news media,education,and so on.Starting from the broad definition of gender language,this paper composes and reviews the research history of domestic gender language and its differences.Around the research history of domestic gender language,the research period is divided according to the timeline into germination,genesis,and growth.Divided by theme and content,the main content is the phenomenon of sexism in language;the second is the study of gender language style differences;the third is the root causes of sexism and verbal gender differences,i.e.,the construction of the corresponding theories;and the fourth is the discussion of the limitations of the study of gender language in foreign countries.

Age-specific differences in the association between prediabetes and cardiovascular diseases in China:A national cross-sectional study

BACKGROUND Cardiovascular disease(CVD)is a leading cause of morbidity and mortality worldwide,the global burden of which is rising.It is still unclear the extent to which prediabetes contributes to the risk of CVD in various age brackets among adults.To develop a focused screening plan and treatment for Chinese adults with prediabetes,it is crucial to identify variations in the connection between prediabetes and the risk of CVD based on age.AIM To examine the clinical features of prediabetes and identify risk factors for CVD in different age groups in China.METHODS The cross-sectional study involved a total of 46239 participants from June 2007 through May 2008.A thorough evaluation was conducted.Individuals with prediabetes were categorized into two groups based on age.Chinese atherosclerotic CVD risk prediction model was employed to evaluate the risk of developing CVD over 10 years.Random forest was established in both age groups.SHapley Additive exPlanation method prioritized the importance of features from the perspective of assessment contribution.RESULTS In total,6948 people were diagnosed with prediabetes in this study.In prediabetes,prevalences of CVD were 5(0.29%)in the younger group and 148(2.85%)in the older group.Overall,11.11%of the younger group and 29.59% of the older group were intermediate/high-risk of CVD for prediabetes without CVD based on the Prediction for ASCVD Risk in China equation in ten years.In the younger age group,the 10-year risk of CVD was found to be more closely linked to family history of CVD rather than lifestyle,whereas in the older age group,resident status was more closely linked.CONCLUSION The susceptibility to CVD is age-specific in newly diagnosed prediabetes.It is necessary to develop targeted approaches for the prevention and management of CVD in adults across various age brackets.

Influences of clean fracturing fluid viscosity and horizontal in-situ stress difference on hydraulic fracture propagation and morphology in coal seam

The viscosity of fracturing fluid and in-situ stress difference are the two important factors that affect the hydraulic fracturing pressure and propagation morphology. In this study, raw coal was used to prepare coal samples for experiments, and clean fracturing fluid samples were prepared using CTAB surfactant. A series of hydraulic fracturing tests were conducted with an in-house developed triaxial hydraulic fracturing simulator and the fracturing process was monitored with an acoustic emission instrument to analyze the influences of fracturing fluid viscosity and horizontal in-situ stress difference on coal fracture propagation. The results show that the number of branched fractures decreased, the fracture pattern became simpler, the fractures width increased obviously, and the distribution of AE event points was concentrated with the increase of the fracturing fluid viscosity or the horizontal in-situ stress difference. The acoustic emission energy decreases with the increase of fracturing fluid viscosity and increases with the increase of horizontal in situ stress difference. The low viscosity clean fracturing fluid has strong elasticity and is easy to be compressed into the tip of fractures, resulting in complex fractures. The high viscosity clean fracturing fluids are the opposite. Our experimental results provide a reference and scientific basis for the design and optimization of field hydraulic fracturing parameters.

Stability and accuracy of central difference method for real-time dynamic substructure testing considering mass participation coefficient

For real-time dynamic substructure testing(RTDST),the influence of the inertia force of fluid specimens on the stability and accuracy of the integration algorithms has never been investigated.Therefore,this study proposes to investigate the stability and accuracy of the central difference method(CDM)for RTDST considering the specimen mass participation coefficient.First,the theory of the CDM for RTDST is presented.Next,the stability and accuracy of the CDM for RTDST considering the specimen mass participation coefficient are investigated.Finally,numerical simulations and experimental tests are conducted for verifying the effectiveness of the method.The study indicates that the stability of the algorithm is affected by the mass participation coefficient of the specimen,and the stability limit first increases and then decreases as the mass participation coefficient increases.In most cases,the mass participation coefficient will increase the stability limit of the algorithm,but in specific circumstances,the algorithm may lose its stability.The stability and accuracy of the CDM considering the mass participation coefficient are verified by numerical simulations and experimental tests on a three-story frame structure with a tuned liquid damper.

TSCND:Temporal Subsequence-Based Convolutional Network with Difference for Time Series Forecasting

Time series forecasting plays an important role in various fields, such as energy, finance, transport, and weather. Temporal convolutional networks (TCNs) based on dilated causal convolution have been widely used in time series forecasting. However, two problems weaken the performance of TCNs. One is that in dilated casual convolution, causal convolution leads to the receptive fields of outputs being concentrated in the earlier part of the input sequence, whereas the recent input information will be severely lost. The other is that the distribution shift problem in time series has not been adequately solved. To address the first problem, we propose a subsequence-based dilated convolution method (SDC). By using multiple convolutional filters to convolve elements of neighboring subsequences, the method extracts temporal features from a growing receptive field via a growing subsequence rather than a single element. Ultimately, the receptive field of each output element can cover the whole input sequence. To address the second problem, we propose a difference and compensation method (DCM). The method reduces the discrepancies between and within the input sequences by difference operations and then compensates the outputs for the information lost due to difference operations. Based on SDC and DCM, we further construct a temporal subsequence-based convolutional network with difference (TSCND) for time series forecasting. The experimental results show that TSCND can reduce prediction mean squared error by 7.3% and save runtime, compared with state-of-the-art models and vanilla TCN.

Fuzzy Difference Equations in Diagnoses of Glaucoma from Retinal Images Using Deep Learning

The intuitive fuzzy set has found important application in decision-making and machine learning.To enrich and utilize the intuitive fuzzy set,this study designed and developed a deep neural network-based glaucoma eye detection using fuzzy difference equations in the domain where the retinal images converge.Retinal image detections are categorized as normal eye recognition,suspected glaucomatous eye recognition,and glaucomatous eye recognition.Fuzzy degrees associated with weighted values are calculated to determine the level of concentration between the fuzzy partition and the retinal images.The proposed model was used to diagnose glaucoma using retinal images and involved utilizing the Convolutional Neural Network(CNN)and deep learning to identify the fuzzy weighted regularization between images.This methodology was used to clarify the input images and make them adequate for the process of glaucoma detection.The objective of this study was to propose a novel approach to the early diagnosis of glaucoma using the Fuzzy Expert System(FES)and Fuzzy differential equation(FDE).The intensities of the different regions in the images and their respective peak levels were determined.Once the peak regions were identified,the recurrence relationships among those peaks were then measured.Image partitioning was done due to varying degrees of similar and dissimilar concentrations in the image.Similar and dissimilar concentration levels and spatial frequency generated a threshold image from the combined fuzzy matrix and FDE.This distinguished between a normal and abnormal eye condition,thus detecting patients with glaucomatous eyes.

Extraction of Acoustic Normal Mode Depth Functions Using Range-Difference Method with Vertical Linear Array Data

Data-derived normal mode extraction is an effective method for extracting normal mode depth functions in the absence of marine environmental data.However,when the corresponding singular vectors become nonunique when two or more singular values obtained from the cross-spectral density matrix diagonalization are nearly equal,this results in unsatisfactory extraction outcomes for the normal mode depth functions.To address this issue,we introduced in this paper a range-difference singular value decomposition method for the extraction of normal mode depth functions.We performed the mode extraction by conducting singular value decomposition on the individual frequency components of the signal's cross-spectral density matrix.This was achieved by using pressure and its range-difference matrices constructed from vertical line array data.The proposed method was validated using simulated data.In addition,modes were successfully extracted from ambient noise.

Analysis of Extended Fisher-Kolmogorov Equation in 2D Utilizing the Generalized Finite Difference Method with Supplementary Nodes

In this study,we propose an efficient numerical framework to attain the solution of the extended Fisher-Kolmogorov(EFK)problem.The temporal derivative in the EFK equation is approximated by utilizing the Crank-Nicolson scheme.Following temporal discretization,the generalized finite difference method(GFDM)with supplementary nodes is utilized to address the nonlinear boundary value problems at each time node.These supplementary nodes are distributed along the boundary to match the number of boundary nodes.By incorporating supplementary nodes,the resulting nonlinear algebraic equations can effectively satisfy the governing equation and boundary conditions of the EFK equation.To demonstrate the efficacy of our approach,we present three numerical examples showcasing its performance in solving this nonlinear problem.

Finite Difference-Peridynamic Differential Operator for Solving Transient Heat Conduction Problems

Transient heat conduction problems widely exist in engineering.In previous work on the peridynamic differential operator(PDDO)method for solving such problems,both time and spatial derivatives were discretized using the PDDO method,resulting in increased complexity and programming difficulty.In this work,the forward difference formula,the backward difference formula,and the centered difference formula are used to discretize the time derivative,while the PDDO method is used to discretize the spatial derivative.Three new schemes for solving transient heat conduction equations have been developed,namely,the forward-in-time and PDDO in space(FT-PDDO)scheme,the backward-in-time and PDDO in space(BT-PDDO)scheme,and the central-in-time and PDDO in space(CT-PDDO)scheme.The stability and convergence of these schemes are analyzed using the Fourier method and Taylor’s theorem.Results show that the FT-PDDO scheme is conditionally stable,whereas the BT-PDDO and CT-PDDO schemes are unconditionally stable.The stability conditions for the FT-PDDO scheme are less stringent than those of the explicit finite element method and explicit finite difference method.The convergence rate in space for these three methods is two.These constructed schemes are applied to solve one-dimensional and two-dimensional transient heat conduction problems.The accuracy and validity of the schemes are verified by comparison with analytical solutions.

Deep reinforcement learning using least-squares truncated temporal-difference

Policy evaluation(PE)is a critical sub-problem in reinforcement learning,which estimates the value function for a given policy and can be used for policy improvement.However,there still exist some limitations in current PE methods,such as low sample efficiency and local convergence,especially on complex tasks.In this study,a novel PE algorithm called Least-Squares Truncated Temporal-Difference learning(LST2D)is proposed.In LST2D,an adaptive truncation mechanism is designed,which effectively takes advantage of the fast convergence property of Least-Squares Temporal Difference learning and the asymptotic convergence property of Temporal Difference learning(TD).Then,two feature pre-training methods are utilised to improve the approximation ability of LST2D.Furthermore,an Actor-Critic algorithm based on LST2D and pre-trained feature representations(ACLPF)is proposed,where LST2D is integrated into the critic network to improve learning-prediction efficiency.Comprehensive simulation studies were conducted on four robotic tasks,and the corresponding results illustrate the effectiveness of LST2D.The proposed ACLPF algorithm outperformed DQN,ACER and PPO in terms of sample efficiency and stability,which demonstrated that LST2D can be applied to online learning control problems by incorporating it into the actor-critic architecture.

A High Order Accurate Bound-Preserving Compact Finite Difference Scheme for Two-Dimensional Incompressible Flow

For solving two-dimensional incompressible flow in the vorticity form by the fourth-order compact finite difference scheme and explicit strong stability preserving temporal discretizations,we show that the simple bound-preserving limiter in Li et al.(SIAM J Numer Anal 56:3308–3345,2018)can enforce the strict bounds of the vorticity,if the velocity field satisfies a discrete divergence free constraint.For reducing oscillations,a modified TVB limiter adapted from Cockburn and Shu(SIAM J Numer Anal 31:607–627,1994)is constructed without affecting the bound-preserving property.This bound-preserving finite difference method can be used for any passive convection equation with a divergence free velocity field.

Interhemispheric and longitudinal differences in the ionosphere-thermosphere coupling process during the May 2024 superstorm

Geomagnetic storm events have a strong influence on the ionosphere–thermosphere(I-T)coupling system.Analyzing the regional response process of the I-T system and its differences across the northern and southern hemispheres is an important but challenging task.In this study,we used a combination of multiple observations and a model simulation to examine the north–south hemispheric difference in the I-T coupling system in the American and Asian sectors during the geomagnetic superstorm that occurred in May 2024.Observations of the total electron content(TEC)showed that the Asian sector had negative storms in the northern hemisphere and positive storms in the southern hemisphere,a process that exacerbated the hemispheric differences in the TEC.However,both hemispheres of the American sector showed negative storms.The thermospheric composition changes also differed between the two sectors,and their variation could partially explain the hemispheric differences caused by positive and negative storms.Moreover,the influence of the thermospheric density change was less than that of the thermospheric composition.Finally,the dynamic effect of the thermospheric wind and the plasma transport processes strongly modulated the north–south differences in the TEC at nighttime in the American and Asian sectors,respectively,during this superstorm.

Efficient Finite Difference WENO Scheme for Hyperbolic Systems withNon-conservativeProducts

Higher order finite difference weighted essentially non-oscillatory(WENO)schemes have been constructed for conservation laws.For multidimensional problems,they offer a high order accuracy at a fraction of the cost of a finite volume WENO or DG scheme of the comparable accuracy.This makes them quite attractive for several science and engineering applications.But,to the best of our knowledge,such schemes have not been extended to non-linear hyperbolic systems with non-conservative products.In this paper,we perform such an extension which improves the domain of the applicability of such schemes.The extension is carried out by writing the scheme in fluctuation form.We use the HLLI Riemann solver of Dumbser and Balsara(J.Comput.Phys.304:275-319,2016)as a building block for carrying out this extension.Because of the use of an HLL building block,the resulting scheme has a proper supersonic limit.The use of anti-diffusive fluxes ensures that stationary discontinuities can be preserved by the scheme,thus expanding its domain of the applicability.Our new finite difference WENO formulation uses the same WENO reconstruction that was used in classical versions,making it very easy for users to transition over to the present formulation.For conservation laws,the new finite difference WENO is shown to perform as well as the classical version of finite difference WENO,with two major advantages:(i)It can capture jumps in stationary linearly degenerate wave families exactly.(i)It only requires the reconstruction to be applied once.Several examples from hyperbolic PDE systems with non-conservative products are shown which indicate that the scheme works and achieves its design order of the accuracy for smooth multidimensional flows.Stringent Riemann problems and several novel multidimensional problems that are drawn from compressible Baer-Nunziato multiphase flow,multiphase debris flow and twolayer shallow water equations are also shown to document the robustness of the method.For some test problems that require well-balancing we have even been able to apply the scheme without any modification and obtain good results.Many useful PDEs may have stiff relaxation source terms for which the finite difference formulation of WENO is shown to provide some genuine advantages.

Study on sex differences and potential clinical value of threedimensional computerized tomography pelvimetry in rectal cancer patients

BACKGROUND Laparoscopic rectal cancer radical surgery is a complex procedure affected by various factors.However,the existing literature lacks standardized parameters for the pelvic region and soft tissues,which hampers the establishment of consistent conclusions.AIM To comprehensively assess 16 pelvic and 7 soft tissue parameters through computerized tomography(CT)-based three-dimensional(3D)reconstruction,providing a strong theoretical basis to address challenges in laparoscopic rectal cancer radical surgery.METHODS We analyzed data from 218 patients who underwent radical laparoscopic surgery for rectal cancer,and utilized CT data for 3D pelvic reconstruction.Specific anatomical points were carefully marked and measured using advanced 3D modeling software.To analyze the pelvic and soft tissue parameters,we emp-loyed statistical methods including paired sample t-tests,Wilcoxon rank-sum tests,and correlation analysis.RESULTS The investigation highlighted significant sex disparities in 14 pelvic bone parameters and 3 soft tissue parameters.Males demonstrated larger measurements in pelvic depth and overall curvature,smaller measurements in pelvic width,a larger mesorectal fat area,and a larger anterior-posterior abdominal diameter.By contrast,females exhibited wider pelvises,shallower depth,smaller overall curvature,and an increased amount of subcutaneous fat tissue.However,there were no significant sex differences observed in certain parameters such as sacral curvature height,superior pubococcygeal diameter,rectal area,visceral fat area,waist circumference,and transverse abdominal diameter.CONCLUSION The reconstruction of 3D CT data enabled accurate pelvic measurements,revealing significant sex differences in both pelvic and soft tissue parameters.This study design offer potential in predicting surgical difficulties and creating personalized surgical plans for male rectal cancer patients with a potentially“difficult pelvis”,ultimately improving surgical outcomes.Further research and utilization of these parameters could lead to enhanced surgical methods and patient care in laparoscopic rectal cancer radical surgery.

Assessment of vegetation cover changes and the contributing factors in the Al-Ahsa Oasis using Normalized Difference Vegetation Index(NDVI)

The abandonment of date palm grove of the former Al-Ahsa Oasis in the eastern region of Saudi Arabia has resulted in the conversion of delicate agricultural area into urban area.The current state of the oasis is influenced by both expansion and degradation factors.Therefore,it is important to study the spatiotemporal variation of vegetation cover for the sustainable management of oasis resources.This study used Landsat satellite images in 1987,2002,and 2021 to monitor the spatiotemporal variation of vegetation cover in the Al-Ahsa Oasis,applied multi-temporal Normalized Difference Vegetation Index(NDVI)data spanning from 1987 to 2021 to assess environmental and spatiotemporal variations that have occurred in the Al-Ahsa Oasis,and investigated the factors influencing these variation.This study reveals that there is a significant improvement in the ecological environment of the oasis during 1987–2021,with increase of NDVI values being higher than 0.10.In 2021,the highest NDVI value is generally above 0.70,while the lowest value remains largely unchanged.However,there is a remarkable increase in NDVI values between 0.20 and 0.30.The area of low NDVI values(0.00–0.20)has remained almost stable,but the region with high NDVI values(above 0.70)expands during 1987–2021.Furthermore,this study finds that in 1987–2002,the increase of vegetation cover is most notable in the northern region of the study area,whereas from 2002 to 2021,the increase of vegetation cover is mainly concentrated in the northern and southern regions of the study area.From 1987 to 2021,NDVI values exhibit the most pronounced variation,with a significant increase in the“green”zone(characterized by NDVI values exceeding 0.40),indicating a substantial enhancement in the ecological environment of the oasis.The NDVI classification is validated through 50 ground validation points in the study area,demonstrating a mean accuracy of 92.00%in the detection of vegetation cover.In general,both the user’s and producer’s accuracies of NDVI classification are extremely high in 1987,2002,and 2021.Finally,this study suggests that environmental authorities should strengthen their overall forestry project arrangements to combat sand encroachment and enhance the ecological environment of the Al-Ahsa Oasis.

Analysis of Regional Difference of Agricultural Land Productivity in Heilongjiang Province

The sustenance of humanity is contingent upon the production of food.The foundation of this production is agriculture,which in turn is dependent upon the cultivation of the land.As a fundamental element of agricultural advancement,the rational development and utilization of land play a pivotal role in the process of rural revitalization.Agricultural land productivity serves as a principal indicator of the efficacy of land utilization and the extent of agricultural advancement.Nevertheless,there is a paucity of research examining the productivity of agricultural land,particularly a lack of specialized research on large agricultural provinces.In light of the aforementioned considerations,this paper presents a comprehensive examination of agricultural land productivity and its regional variations in Heilongjiang Province in 2022,with the aid of pertinent statistical data.The findings of the analysis indicate that among the prefecture-level cities,Daqing and Suihua exhibit the highest levels of agricultural land productivity.Additionally,Zhaodong City,Zhaozhou,Qinggang,Wangkui,and Lanxi counties exhibit high levels of agricultural land productivity within their respective prefecture-level cities.There are notable disparities in agricultural land productivity across various regions,including Yichun,Heihe,Harbin,Daqing,Hegang,and Suihua.In contrast,other regions demonstrate a more balanced spatial distribution.In order to facilitate the prosperous development of the agricultural industry in Heilongjiang Province,it is essential to optimize the spatial planning of the land,to investigate the potential for agricultural development in each region,to establish effective collaboration between resources and industries,and to create a development synergy that will collectively advance rural revitalization.

Temporal and spatial differences in human activities performed in Urban Green Spaces of Vilnius(Lithuania)

Urban green spaces(UGS)are relevant to city well-being,as recognized by the United Nations’Sustainable Development Goals(SDGs).However,few studies have studied the temporal use of UGS.This work assessed the seasonal,weekly,and daily use of three urban green spaces(Vingis Park,Bernardino Garden,and Jomantas Park)in Vilnius(Lithuania).The study is based on an on-site observation-based survey,which recorded users’characteristics,activities,and weather conditions during summer and winter.The results showed that UGS’s seasonal,weekly,and daily use differed according to park and users’characteristics.Parks with a higher diversity of facilities had a high seasonal difference in the number of observed activities.User numbers were higher in the summer for activities with children,social activities,sports,and water activities than in the winter.Jomantas Park had the lowest variability in user characteristics.Weather variables were linked to changes in users’activities.Higher precipitation and lower temperature were associated with reducing the number of users and the diversity of registered activities.Most of the stationary activities were observed during summer.The diversity of the observed activities was associated with the available facilities rather than the park size.The distribution of stationary activities was spatially correlated with facility/equipment(benches,playgrounds,sports,and fitness equipment)and proximity to water features.The results of this study are relevant for UGS design,planning,and management.