On calculating glacial isostatic adjustment

Modeling the earth's fluid and elastic response to the melting of the glaciers of the last ice age is the most direct way to infer the earth's radial viscosity profile.Here,we compare two methods for calculating the viscoelastic response to surface loading.In one,the elastic equation of motion is converted to a viscoelastic equation using the Correspondence Principle.In the other,elastic deformation is added to the viscous flow as isostatic adjustment proceeds.The two modeling methods predict adjustment histories that are different enough to potentially impact the interpretation of the observed glacial isostatic adjustment(GIA).The differences arise from buoyancy and whether fluid displacements are subjected to hydrostatic pre-stress.The methods agree if they use the same equations and boundary conditions.The origin of the differences is determined by varying the boundary conditions and pre-stress application.

Adjustment mechanism of blasting dynamic-static action in the water decoupling charge

Water decoupling charge blasting excels in rock breaking,relying on its uniform pressure transmission and low energy dissipation.The water decoupling coefficients can adjust the contributions of the stress wave and quasi-static pressure.However,the quantitative relationship between the two contributions is unclear,and it is difficult to provide reasonable theoretical support for the design of water decoupling blasting.In this study,a theoretical model of blasting fracturing partitioning is established.The mechanical mechanism and determination method of the optimal decoupling coefficient are obtained.The reliability is verified through model experiments and a field test.The results show that with the increasing of decoupling coefficient,the rock breaking ability of blasting dynamic action decreases,while quasi-static action increases and then decreases.The ability of quasi-static action to wedge into cracks changes due to the spatial adjustment of the blast hole and crushed zone.The quasi-static action plays a leading role in the fracturing range,determining an optimal decoupling coefficient.The optimal water decoupling coefficient is not a fixed value,which can be obtained by the proposed theoretical model.Compared with the theoretical results,the maximum error in the model experiment results is 8.03%,and the error in the field test result is 3.04%.

Impact of an official accountability audit on industrial structure adjustment:a case study of environmental regulation in China

As a unique environmental regulation in China,the official accountability audit was piloted in 2014.With a focus on prioritizing the ecological environment,officials in pilot districts have implemented economic construction,adjusted industrial structures,and promoted coordinated development between the economy and environment.The effects of implementation have garnered widespread attention from society.However,there is limited research on the impact of an accountability audit on industrial structure adjustments.Using the“Accountability Audit of Officials for Natural Resource Assets(Trial)”released in 2015 as a quasi-natural experiment,this study collected panel data from 279 cities between 2013 and 2017.It then empirically analyzed the impact mechanism and effects of the accountability audit on industrial structure adjustment using the Propensity Score Matching and Difference-in-Differences model.The research findings indicate that the accountability audit directly impacted industrial structure adjustment,promoting the upgrading of the primary industry to the secondary industry and restricting the development of the tertiary industry.In addition,the audit is beneficial for enterprise entry,but not conducive to technological innovation,and has no significant impact on foreign direct investment.This conclusion fills a gap in the existing research and provides valuable insights for policymakers.

Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations.To accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response capabilities.Firstly,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation resources.On this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation capabilities.Secondly,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within clusters.Simultaneously,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of resources.This model can provide scientific guidance for the economic dispatch of the distribution station area.Finally,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of the distribution station area.

Adjustment of Administrative Divisions and Upgrading of Industrial Structure in Hefei Metropolitan Area:Taking"Partitions of Chaohu"as a Quasi-natural Experiment

Administrative regions are an important environment for the operation of China's market economy.The relevant economic subjects cannot predict the policy of adjustment of administrative divisions and carry out conscious migration behavior,adjustment of administrative divisions can be regarded as a quasi-natural experiment.The three cities of Hefei,Wuhu,and Ma'anshan,which are directly related to the adjustment of the administrative division of Chaohu,are taken as the treatment group,and the seven adjacent cities of Lu'an,Huainan,Chuzhou,Bengbu,Anqing,Chizhou,and Tongling are taken as the control group.Differences-in-Differences method and relevant control variables affecting the upgrading of industrial structure are used to test.The test results show that"Partitions of Chaohu"has a significant industrial structure upgrading effect by promoting the optimization of spatial layout,the cross-regional flow of production factors and the effective management of Chaohu Lake Basin.At the same time,the increase of total retail sales of consumer goods,urban fixed assets investment,public utility expenses in science,education,culture and health,and population plays a significant positive role in promoting the upgrading of industrial structure,while foreign direct investment plays a certain inhibition role in the upgrading of industrial structure.In order to meet the ever-developing space demands and enhance the impact on surrounding areas,the Hefei metropolitan area should be driven by technological innovation,strengthen the integration of industrial chains,improve the business environment and transportation network,and continuously promote the upgrading of industrial structure and the formation and development of new productive forces.

Cross-Cultural Adjustment and Coping:U.S.Students in Taiwan Residents Higher Education

The aim of this study was to investigate the adjustment problems of students from the United States enrolled in universities in the East,specifically in Taiwan,their problems related to cultural adaptation,and the process of adjustment to student life in Taiwan.Under investigation were cultural adjustment and coping skills as these students transitioned from West to East.Qualitative data were collected from interviews with participants and faculty members as well as participant observations.Results indicated that U.S.students found their own ways to acclimate to their new academic setting as well as to social relations,cross-cultural issues,and the linguistic environment in Taiwan to achieve effective adaptation.They made changes in themselves to cope with all situations they encountered.This study provides suggestions for international students abroad in Taiwan,for the Taiwan Residents government,and for universities or colleges in terms of what they should offer to current and future international students.

Cameroon Climate Predictions Using the SARIMA-LSTM Machine Learning Model: Adjustment of a Climate Model for the Sudano-Sahelian Zone of Cameroon

It is acknowledged today within the scientific community that two types of actions must be considered to limit global warming: mitigation actions by reducing GHG emissions, to contain the rate of global warming, and adaptation actions to adapt societies to Climate Change, to limit losses and damages [1] [2]. As far as adaptation actions are concerned, numerical simulation, due to its results, its costs which require less investment than tests carried out on complex mechanical structures, and its implementation facilities, appears to be a major step in the design and prediction of complex mechanical systems. However, despite the quality of the results obtained, biases and inaccuracies related to the structure of the models do exist. Therefore, there is a need to validate the results of this SARIMA-LSTM-digital learning model adjusted by a matching approach, “calculating-test”, in order to assess the quality of the results and the performance of the model. The methodology consists of exploiting two climatic databases (temperature and precipitation), one of which is in-situ and the other spatial, all derived from grid points. Data from the dot grids are processed and stored in specific formats and, through machine learning approaches, complex mathematical equations are worked out and interconnections within the climate system established. Through this mathematical approach, it is possible to predict the future climate of the Sudano-Sahelian zone of Cameroon and to propose adaptation strategies.

Optimized CUDA Implementation to Improve the Performance of Bundle Adjustment Algorithm on GPUs

The 3D reconstruction pipeline uses the Bundle Adjustment algorithm to refine the camera and point parameters. The Bundle Adjustment algorithm is a compute-intensive algorithm, and many researchers have improved its performance by implementing the algorithm on GPUs. In the previous research work, “Improving Accuracy and Computational Burden of Bundle Adjustment Algorithm using GPUs,” the authors demonstrated first the Bundle Adjustment algorithmic performance improvement by reducing the mean square error using an additional radial distorting parameter and explicitly computed analytical derivatives and reducing the computational burden of the Bundle Adjustment algorithm using GPUs. The naïve implementation of the CUDA code, a speedup of 10× for the largest dataset of 13,678 cameras, 4,455,747 points, and 28,975,571 projections was achieved. In this paper, we present the optimization of the Bundle Adjustment algorithm CUDA code on GPUs to achieve higher speedup. We propose a new data memory layout for the parameters in the Bundle Adjustment algorithm, resulting in contiguous memory access. We demonstrate that it improves the memory throughput on the GPUs, thereby improving the overall performance. We also demonstrate an increase in the computational throughput of the algorithm by optimizing the CUDA kernels to utilize the GPU resources effectively. A comparative performance study of explicitly computing an algorithm parameter versus using the Jacobians instead is presented. In the previous work, the Bundle Adjustment algorithm failed to converge for certain datasets due to several block matrices of the cameras in the augmented normal equation, resulting in rank-deficient matrices. In this work, we identify the cameras that cause rank-deficient matrices and preprocess the datasets to ensure the convergence of the BA algorithm. Our optimized CUDA implementation achieves convergence of the Bundle Adjustment algorithm in around 22 seconds for the largest dataset compared to 654 seconds for the sequential implementation, resulting in a speedup of 30×. Our optimized CUDA implementation presented in this paper has achieved a 3× speedup for the largest dataset compared to the previous naïve CUDA implementation.

A Self-calibration Bundle Adjustment Algorithm Based on Block Matrix Cholesky Decomposition Technology

In this study,the problem of bundle adjustment was revisited,and a novel algorithm based on block matrix Cholesky decomposition was proposed to solve the thorny problem of self-calibration bundle adjustment.The innovation points are reflected in the following aspects:①The proposed algorithm is not dependent on the Schur complement,and the calculation process is simple and clear;②The complexities of time and space tend to O(n)in the context of world point number is far greater than that of images and cameras,so the calculation magnitude and memory consumption can be reduced significantly;③The proposed algorithm can carry out self-calibration bundle adjustment in single-camera,multi-camera,and variable-camera modes;④Some measures are employed to improve the optimization effects.Experimental tests showed that the proposed algorithm has the ability to achieve state-of-the-art performance in accuracy and robustness,and it has a strong adaptability as well,because the optimized results are accurate and robust even if the initial values have large deviations from the truth.This study could provide theoretical guidance and technical support for the image-based positioning and 3D reconstruction in the fields of photogrammetry,computer vision and robotics.

Vertical deformation analysis based on combined adjustment for GNSS and leveling data

A method is proposed to fuse the velocity data of the global navigation satellite system(GNSS) and leveling height via combined adjustment with constraints. First, stable GNSS-leveling points are uniformly selected, and the constraints of the geodetic height change velocity and normal height change velocity are given. Then, the GNSS vertical velocities and leveling height difference are used as observations of combined adjustment, and robust least-squares estimation are used to estimate the velocities of the unknown points. Finally, a vertical movement model is established with the GNSS vertical velocities and leveling vertical velocities obtained via combined adjustment. Data from the second-order leveling network and GNSS control points in Shandong Province are taken as test data, and eight calculation schemes are used for discussion. One of the schemes, the bifactor robust combined adjustment method based on variance component estimation with two kinds of vertical velocity constraints achieves the optimal results. The method applied in the scheme can be recommended for data fusion of GNSS and leveling, further improving the reliability of vertical crustal movement in Shandong Province.

Verification of Depth Adjustment Factor in Eurocode 5 for Tropical Hardwood Timbers

The depth adjustment factor for bending strength stated in Eurocode 5(EC5)is only applicable to timbers having a characteristic density below 700 kg/m^(3).However,most Malaysian timbers are hardwood,some with a characteristic density reaching above 700 kg/m^(3).Therefore,the objective of this study was to examine whether the depth adjustment factor stipulated in EC5 is valid for Malaysian hardwood timbers.Six timber species were selected for this study,namely Kapur(Dryobalanops C.F.Gaertn.),Kempas(Koompassia Maingay ex Benth.),Keruing(Dipterocarpus C.F.Gaertn.),Light red meranti(Shorea Roxb.ex C.F.Gaertn.),Geronggang(Cratoxylum Blume)and Balau(Shorea Roxb.ex C.F.Gaertn.).The determination of bending strength and characteristic density was conducted according to BS EN 408:2010 and BS EN 384:2016,respectively.A graph for mean bending strength vs.(150/h)was plotted for each timber species.The power function was selected to analyze the relationship between the two variables.The power of the regression equations varied depending on the characteristic density of the timber species.For species with a characteristic density below 700 kg/m^(3),such as Kapur,Keruing,and Light red meranti,the power was between 0.16 to 0.17.In contrast,for species having a characteristic density above 700 kg/m^(3),namely Kempas and Balau,the power was higher at 0.23 and 0.24,respectively.Geronggang was an exception to this pattern.These values are close to the depth adjustment factor given in EC5,which is 0.2.Based on the results,it can be suggested that the adjustment factor of 0.2 is also applicable to Malaysian hardwood timbers with a characteristic density above 700 kg/m^(3).

Construction of Psychological Adjustment Function Model of Music Education Based on Emotional Tendency Analysis

In the face offierce competition in the social environment,mental health problems gradually get the attention of the public,in order to achieve accurate mental health data analysis,the construction of music education is based on emotional tendency analysis of psychological adjustment function model.Design emotional tendency analysis of music education psychological adjustment function architecture,music teaching goal as psychological adjust-ment function architecture building orientation,music teaching content as a foundation for psychological adjust-ment function architecture and music teaching process as a psychological adjustment function architecture building,music teaching evaluation as the key of building key regulating function architecture,Establish a core literacy oriented evaluation system.Different evaluation methods were used to obtain the evaluation results.Four levels of psychological adjustment function model of music education are designed,and the psychological adjust-ment function of music education is put forward,thus completing the construction of psychological adjustment function model of music education.The experimental results show that the absolute value of the data acquisition error of the designed model is minimum,which is not more than 0.2.It is less affected by a bad coefficient and has good performance.It can quickly converge to the best state in the actual prediction process and has a strong con-vergence ability.

Proposing Adjustments to the Dry Season Inter-Reservoir Operation Rules of the Red River System to Improve Water Use Efficiency of the Reservoirs

The Red-Thai Binh River system is an important water resource to the Northern Delta, serving the development of agriculture, people’s livelihood and other economic sectors through its upstream reservoirs and a system of water abstraction works along the rivers. However, due to the impact of climate change and pressure from socio-economic development, the operation of the reservoir system according to Decision No. 740/QD-TTg was issued on June 17, 2019 by the Prime Minister of Government promulgating the Red-Thai Binh River system inter-reservoir operation rules (Operation rules 740) has some shortcomings that need adjustments for higher water use efficiency, meeting downstream water demand and power generation benefits. Through the results of water balance calculation and analysis of economic benefits from water use scenarios, this research proposed adjustment to the inter-reservoir operation during dry season in the Red River system. The result showed that an average water level of 1.0 - 1.7 m should be maintained at Hanoi during the increased release period.

An Investigation of Purely Azimuthal Passive Localization and Position Adjustment in Attempted UAV Formation Flights

When a cluster of unmanned aerial vehicles (UAVs) is flying in formation, it is crucial to maintain the formation and not to be interfered by external electromagnetic wave signals. In order to maintain the formation, this paper proposes to use pure azimuth passive positioning to adjust the position of UAVs, i.e., certain UAVs in the formation transmit signals, the rest of the UAVs receive the signals passively, and extract the orientation information from them to adjust the position of the UAVs [1] [2] [3]. In this paper, the position adjustment problem of UAVs in “circular” formation flight under three models is investigated. To address the problem of “how to obtain the position of the receiving UAV when there are two UAVs with known numbers and evenly distributed on the circumference in addition to the UAV transmitting at the known center of the circle, and the rest of the UAVs with slight deviations in their positions are receiving the signals”, two purely mathematical geometric methods, namely, triangular localization method and polar co-ordinate method, are proposed respectively. We have determined the position of the receiving UAV;we have used the exhaustive method and the construction and disproof method to solve the problem of “how many UAVs are needed to transmit signals in order to realize the effective positioning of the UAVs when it is known that a certain UAV with a slight deviation in its position receives the signals emitted by two UAVs at the same time”, and the results show that: in addition to the known signals emitted by two UAVs, it is also necessary to transmit the signals emitted by two UAVs. The results show that in addition to the known two UAVs transmitting signals, two additional UAVs are required to transmit signals for precise po-sitioning. When the position of UAVs has deviation at the initial moment, the ideal approximation method and the target delimitation method are pro-posed, and the target of nine UAVs uniformly distributed on a circle of a spe-cific radius is achieved through several adjustments, after which the ad-vantages and disadvantages of each model are analyzed, and suggestions for improvement are put forward. The purely azimuthal passive localization method and the constructed model approach proposed in this paper can be extended to other fields, such as spacecraft formations in space and battle-ship formations at sea, as well as other formation flight position adjustment problems.

Improving Accuracy and Computational Burden of Bundle Adjustment Algorithm Using GPUs

Bundle adjustment is a camera and point refinement technique in a 3D scene reconstruction pipeline. The camera parameters and the 3D points are refined by minimizing the difference between computed projection and observed projection of the image points formulated as a non-linear least-square problem. Levenberg-Marquardt method is used to solve the non-linear least-square problem. Solving the non-linear least-square problem is computationally expensive, proportional to the number of cameras, points, and projections. In this paper, we implement the Bundle Adjustment (BA) algorithm and analyze techniques to improve algorithmic performance by reducing the mean square error. We investigate using an additional radial distortion camera parameter in the BA algorithm and demonstrate better convergence of the mean square error. We also demonstrate the use of explicitly computed analytical derivatives. In addition, we implement the BA algorithm on GPUs using the CUDA parallel programming model to reduce the computational time burden of the BA algorithm. CUDA Streams, atomic operations, and cuBLAS library in the CUDA programming model are proposed, implemented, and demonstrated to improve the performance of the BA algorithm. Our implementation has demonstrated better convergence of the BA algorithm and achieved a speedup of up to 16× on the use of the BA algorithm on various datasets.

Impacts of automated passenger cars on the capacity of a freeway basic section: applicability in the determination of vehicle adjustment factors in mixed traffic

The highway capacity manual(HCM)provides a formula to calculate the heavy vehicle adjustment factor(fHV)as a function of passenger car equivalent factors for the heavy vehicle(ET).However,a significant drawback is that the methodology was established solely based on human-driven passenger cars(HDPC)and human-driven heavy vehicles(HDHV).Due to automated passenger cars(APCs),a new adjustment factor(fAV)might be expected.This study simulated traffic flows at different percentages of HDHVs and APCs to investigate the impacts of HDHVs and APCs on freeway capacity by analyzing their influence on fHV and fAV values.The simulation determined observed adjustment factors at different percentages of HDHVs and APCs(fobserved).The HCM formula was used to calculate(fHCM).Modifications to the HCM formula are proposed,and vehicle adjustment factors due to HDHVs and APCs were calculated(fproposed).Results showed that,in the presence of APCs,while fobserved and fHCM were statistically significantly different,fobserved and fproposed were statistically equal.Hence,this study recommends using the proposed formula when determining vehicle adjustment factors(fproposed)due to HDHVs and APCs in the traffic stream.

计及成本和价值的长周期负荷侧调节能力投入策略

随着新型电力系统的发展,负荷侧调节能力建设日益受到关注,对于负荷侧调节能力成本、价值及其投入策略的研究,具有重要意义。基于近10 a来中国电力工业发展的基础数据,结合新型电力系统发展态势,分析了负荷侧调节能力需求的背景,通过对发用电两侧调节能力特点的比较,从电力系统整体角度梳理了负荷侧调节能力的投入所带来的增量价值,分析了负荷侧调节能力的应用价值盈余,进一步结合具体需求提出了3种长周期下负荷侧调节能力投入的优化策略模型,并进行了算例分析。结果显示:负荷侧调节能力的投入有利于降低电力系统的总成本、增加系统调节能力,但是由于其成本曲线的变化以及“非持久特性”等因素,其投入策略需要综合长周期市场发展需求和发用电两侧成本因素进行权衡,所提出的3种优化模型各有其适用场景。

基于试点地区医疗服务价格调整机制的思考

目的:优化医疗服务价格调整机制,为深入推进医疗服务价格改革提供参考。方法:采用描述性分析,对我国五个试点地区的医疗服务项目调价机制进行梳理。结果:医疗服务项目分类缺乏具体量化指标,调价触发机制不够完善,调价总量指标还需优化,分类定价机制亟需进一步明晰。结论:以“医保患”三方平衡为主旨,优化医疗服务价格调整的主要环节,在群众负担总体稳定、医保基金可承受、公立医疗机构健康发展的基础上,合理调整医疗服务价格。

1990-2019年中国成年人归因于糖尿病的心血管疾病负担研究

背景在全球老龄化不断深化的背景下,慢性病患者不断增加,多病共存现象愈加严重。在普遍认知中,心血管疾病与2型糖尿病大多属于老年病,但随着居民生活节奏与饮食等行为方式的改变,很多疾病呈现年轻化趋势。现也有研究表明,与一般人群相比,年轻时患糖尿病的患者的心血管疾病风险及死亡率会相对增加。目的探究1990—2019年中国成年人归因于糖尿病的心血管疾病负担情况,为共病预防提供依据。方法基于2019年全球疾病负担研究(GBD)数据,主要采用死亡率、伤残调整寿命年(DALY)率和计算获取的年估计变化百分比(EAPC)等指标评估我国心血管疾病(包括缺血性心脏病、脑卒中和外周动脉疾病3类)归因于糖尿病的疾病负担情况,并对年龄段(25~49岁、50~69岁、≥70岁)及性别进行分层分析,最后对疾病负担的时间趋势进行分析。结果中国25岁及以上人群归因于糖尿病的心血管疾病死亡数从1990年的29.805万例上升到2019年的70.034万例。男性归因于糖尿病的心血管疾病标化死亡率较1990年升高,而女性标化死亡率有所降低,且男性标化死亡率始终高于女性。2019年归因于糖尿病的心血管疾病DALY为1358.585万人年,按年龄划分的死亡率和DALY率随年龄增长而增加。女性标化DALY率下降趋势较男性明显(女性:EAPC=-0.32%,95%CI=-0.49%~-0.11%;男性:EAPC=-0.01%,95%CI=-0.26%~0.29%)。2019年归因于糖尿病的缺血性心脏病、外周动脉疾病患者3个年龄段的死亡率和DALY率较1990年大部分上升,而2019年归因于糖尿病的脑卒中患者3个年龄段的死亡率较1990年下降。1990—2019年心血管疾病中3类心血管疾病归因于糖尿病的标化DALY率占比呈波动性变化,但在2019年归因于糖尿病的3类心血管疾病标化DALY率占比均高于1990年。结论1990—2019年我国成年人归因于糖尿病的心血管疾病的死亡率和DALY率总体呈现上升趋势,人群糖尿病及心血管疾病共病风险较大,应注重在糖尿病患者中筛查心血管疾病或患心血管疾病风险高的个体,重点关注男性、高龄人群以及不良生活习惯较多的年轻人,对其进行早期的健康干预,减少共病疾病负担。

水利工程供水价格常态化调整机制探索

为纠正水利工程供水成本长期大幅偏离价格,激励水利工程单位主动强化成本管理,需要建立水利工程供水价格常态化调整机制。水价调整既要考虑外围价格环境的传导作用引起的成本刚性增长,也要考虑供水服务质量和管理单位成本控制因素,构建水利工程供水价格与生产管理要素价格的联动机制。