Capacity Building for the Integration of Climate Adaptation into Urban Planning Processes: The Dutch Experience

The institutions of the Dutch (urban) planning system face four challenging characteristics of climate adaptation measures. These measures are uncertain in their effects, in competition with other interests, multifaceted, and inherently complex. Capacity building is a key issue for the implementation of climate adaptation measures in urban planning processes, which aim to achieve Climate-Proof Cities (CPC). For successful capacity building, it is important to define the relevant stakeholders and tailor the adaptation strategies first to (the position of) these stakeholders and next to the specific urban conditions and issues. In addition, scientific insights and tools can be of assistance, and the use of climate maps can help to create a common language. Such common understanding of climate problems can lead to “goal entwinement” between actors, which can support the implementation of climate adaptation strategies in urban planning. Awareness, recognition and urgency are the most important components of this common understanding, which may differ for each stage in every urban planning process. In order to overcome the pragmatism that rules in day-to-day urban planning processes, multi-level arrangements between different tiers of government must be employed to improve the penetration of climate adaptation measures. After all, it still remains a soft interest in a hard process.

Climate Change Mitigation and Adaptation in Agriculture

Mitigation and adaptation are two principle strategies for managing human-induced climate change. Agriculture plays a duet role in climate change. It has been a major source of greenhouse gases to the atmosphere. It is also one of the sectors most vulnerable to the risks and impacts of global climate change. This paper first indentified the mitigative and adaptative options and potential in agriculture, then addressed the integrated analysis of mitigation and adaptation and its benefits for agriculture. Finally, it discussed the implications to Chinese agriculture in dealing with the global climate change.

Modulation of neuronal dynamic range using two different adaptation mechanisms

The capability of neurons to discriminate between intensity of external stimulus is measured by its dynamic range.A larger dynamic range indicates a greater probability of neuronal survival.In this study,the potential roles of adaptation mechanisms（ion currents） in modulating neuronal dynamic range were numerically investigated.Based on the adaptive exponential integrate-and-fire model,which includes two different adaptation mechanisms,i.e.subthreshold and suprathreshold（spike-triggered） adaptation,our results reveal that the two adaptation mechanisms exhibit rather different roles in regulating neuronal dynamic range.Specifically,subthreshold adaptation acts as a negative factor that observably decreases the neuronal dynamic range,while suprathreshold adaptation has little influence on the neuronal dynamic range.Moreover,when stochastic noise was introduced into the adaptation mechanisms,the dynamic range was apparently enhanced,regardless of what state the neuron was in,e.g.adaptive or non-adaptive.Our model results suggested that the neuronal dynamic range can be differentially modulated by different adaptation mechanisms.Additionally,noise was a non-ignorable factor,which could effectively modulate the neuronal dynamic range.

ON INTEGRATION AND ADAPTATION IN COMPLEX SERVICE SYSTEMS

The services sector employs a large and growing proportion of workers in the industrialized nations, and it is increasingly dependent on information and communication technologies. While the interdependences, similarities and complementarities of manufacturing and services are significant, there are considerable differences between goods and services, including the shift in focus from mass production to mass customization （whereby a service is produced and delivered in response to a customer＇s stated or imputed needs）. In general, services can be considered to be knowledge-intensive agents or components which work together as providers and consumers to create or co-produce value. Like manufacturing systems, an efficient service system must be an integrated system of systems, leading to greater connectivity and interdependence. Integration must occur over the physical, temporal, organizational and functional dimensions, and must include methods concerned with the component, the management, and the system. Moreover, an effective service system must also be an adaptable system, leading to greater value and responsiveness. Adaptation must occur over the dimensions of monitoring, feedback, cybernetics and learning, and must include methods concerned with space, time, and system. In sum, service systems are indeed complex, especially due to the uncertainties associated with the human-centered aspects of such systems. Moreover, the system complexities can only be dealt with methods that enhance system integration and adaptation. The paper concludes with several insights, including a plea to shift the current misplaced focus on developing a science or discipline for services to further developing a systems engineering approach to services, an approach based on the integration and adaptation of a host of sciences or disciplines （e.g., physics, mathematics, statistics, psychology, sociology, etc.）. In fact, what is required is a services-related transdisciplinary - beyond a single disciplinary - ontology or taxonomy as a basis for disciplinary integration and adaptation.

Equilibrium Reconstruction and Its Integration in J-TEXT

The equilibrium fitting code （EFIT） and its application in the J-TEXT tokamak are integrated by the Matlab language. The function of analysis and visualization to the results is added. In addition, the experiment data measured by soft X-ray （SXR） are used to calculate plasma equilibrium as a constraint condition. The improved EFIT code is used for J-TEXT discharge and the profiles of plasma parameters such as flux function, safety factor q, pressure and current density are obtained from the reconstructed configurations.

Vector-borne disease and climate change adaptation in African dryland socialecological systems

Background:Drylands,which are among the biosphere's most naturally limiting and environmentally variable ecosystems,constitute three-quarters of the African continent.As a result,environmental sustainability and human development along with vector-borne disease(VBD)control historically have been especially challenging in Africa,particularly in the sub-Saharan and Sahelian drylands.Here,the VBD burden,food insecurity,environmental degradation,and social vulnerability are particularly severe.Changing climate can exacerbate the legion of environmental health threats in Africa,the social dimensions of which are now part of the international development agenda.Accordingly,the need to better understand the dynamics and complex coupling of populations and environments as exemplified by drylands is increasingly recognized as critical to the design of more sustainable interventions.Main body:This scoping review examines the challenge of vector-borne disease control in drylands with a focus on Africa,and the dramatic,ongoing environmental and social changes taking place.Dryland societies persisted and even flourished in the past despite changing climates,extreme and unpredictable weather,and marginal conditions for agriculture.Yet intrusive forces largely out of the control of traditional dryland societies,along with the negative impacts of globalization,have contributed to the erosion of dryland's cultural and natural resources.This has led to the loss of resilience underlying the adaptive capacity formerly widely exhibited among dryland societies.A growing body of evidence from studies of environmental and natural resource management demonstrates how,in light of dryland system's inherent complexity,these factors and top-down interventions can impede sustainable development and vector-borne disease control.Strengthening adaptive capacity through community-based,participatory methods that build on local knowledge and are tailored to local ecological conditions,hold the best promise of reversing current trends.Conclusions:A significant opportunity exists to simultaneously address the increasing threat of vector-borne diseases and climate change through methods aimed at strengthening adaptive capacity.The integrative framework and methods based on social-ecological systems and resilience theory offers a novel set of tools that allow multiple threats and sources of vulnerability to be addressed in combination.Integration of recent advances in vector borne disease ecology and wider deployment of these tools could help reverse the negative social and environmental trends currently seen in African drylands.

Fast and accurate covariance matrix reconstruction for adaptive beamforming using Gauss-Legendre quadrature

Most of the reconstruction-based robust adaptive beamforming(RAB)algorithms require the covariance matrix reconstruction(CMR)by high-complexity integral computation.A Gauss-Legendre quadrature(GLQ)method with the highest algebraic precision in the interpolation-type quadrature is proposed to reduce the complexity.The interference angular sector in RAB is regarded as the GLQ integral range,and the zeros of the threeorder Legendre orthogonal polynomial is selected as the GLQ nodes.Consequently,the CMR can be efficiently obtained by simple summation with respect to the three GLQ nodes without integral.The new method has significantly reduced the complexity as compared to most state-of-the-art reconstruction-based RAB techniques,and it is able to provide the similar performance close to the optimal.These advantages are verified by numerical simulations.

Integration Interval Determination and Decision Threshold Optimization for Improved TRPC-UWB Communication Systems

Integration interval and decision threshold issues were investigated for improved transmitted reference pulse cluster （iTRPC-） ultra-wideband （UWB） systems. Our analysis shows that the bit error rate （BER） performance of iTRPC-UWB systems can be significantly improved via integration interval determination （IID） and decision threshold optimization. For this purpose, two modifications can be made at the autocorrelation receiver as follows. Firstly, the liD processing is performed for autocorrelation operation to capture multi-path energy as much as possible. Secondly, adaptive decision threshold （ADT） instead of zero decision threshold （ZDT）, is used as estimated optimal decision threshold for symbol detection. Performance of iTRPCUWB systems using liD and ADT was evaluated in realistic IEEE 802.15.4a UWB channel models and the simulation results demonstrated our theoretical analysis.

Preliminary clinical application of an adaptive iterative statistical reconstruction algorithm inhead and neck computed tomography angiography with low tube voltage and a low concentration of contrast medium

Objective To evaluate the feasibility of using a low concentration of contrast medium （Visipaque 270 mgl/mL）, low tube voltage, and an advanced image reconstruction algorithm in head and neck computed tomography angiography （CTA）. Methods Forty patients （22 men and 18 women; average age 48.7 ± 14.25 years; average body mass index 23.9 ± 3.7 kg/m^2） undergoing CTA for suspected vascular diseases were randomly assigned into two groups. Group A （n = 20） was administered 370 mgl/mL contrast medium, and group B （n = 20） was administered 270 mgl/mL contrast medium. Both groups were administered at a rate of 4.8 mL/s and an injection volume of 0.8 mL/kg. Images of group A were obtained with 120 kVp and filtered back projection （FBP） reconstruction, whereas images of group B were obtained with 80 kVp and 80% adaptive iterative statistical reconstruction algorithm （ASiR）. The CT values and standard deviations of intracranial arteries and image noise on the corona radiata were measured to calculate the contrast-to-noise ratio （CNR） and signal-to-noise ratio （SNR）. The beam-hardening artifacts （BHAs） around the skull base were calculated. Two readers evaluated the image quality with volume rendered images using scores from 1 to 5. The values between the two groups were statistically compared. Results The mean CT value of the intracranial arteries in group B was significantly higher than that in group A （P 〈 0.001）. The CNR and SNR values in group B were also statistically higher than those in group A （P 〈 0.001）. Image noise and BHAs were not significantly different between the two groups. The image quality score of VR images of in group B was significantly higher than that in group A （P = 0.001）. However, the quality scores of axial enhancement images in group B became significantly smaller than those in group A （P〈 0.001）. The CT dose index volume and dose-length product were decreased by 63.8% and 64%, respectively, in group B （P 〈 0.001 for both）. Conclusion Visipaque combined with 80 kVp and 80% ASiR provided similar image quality in intracranial CTA with 64% radiation dose reduction compared with the use of lopamidol, 120 kVp, and FBP reconstruc-tion.

TRACKING AND RECONSTRUCTION METHODS FOR MOVING-INTERFACES

A simple,efficient and accurate high resolution method to tracking moving-interfaces-the characteristic integral-averaging finite volume method on unstructured meshes is proposed. And some numerical tests and evaluation of six main efficient methods for interface reconstruction are made. Through strict numerical simulation,their characters,advantages and shortcomings are compared,analyzed and commended in particular.

Green’s Function Technique and Global Optimization in Reconstruction of Elliptic Objects in the Regular Triangle

The reconstruction problem for elliptic voids located in the regular (equilateral) triangle is studied. A known point source is applied to the boundary of the domain, and it is assumed that the input data is obtained from the free-surface input data over a certain finite-length interval of the outer boundary. In the case when the boundary contour of the internal object is unknown, we propose a new algorithm to reconstruct its position and size on the basis of the input data. The key specific character of the proposed method is the construction of a special explicit-form Green's function satisfying the boundary condition over the outer boundary of the triangular domain. Some numerical examples demonstrate good stability of the proposed algorithm.

One-and Multi-dimensional CWENOZ Reconstructions for Implementing Boundary Conditions Without Ghost Cells

We address the issue of point value reconstructions from cell averages in the context of third-order finite volume schemes,focusing in particular on the cells close to the boundaries of the domain.In fact,most techniques in the literature rely on the creation of ghost cells outside the boundary and on some form of extrapolation from the inside that,taking into account the boundary conditions,fills the ghost cells with appropriate values,so that a standard reconstruction can be applied also in the boundary cells.In Naumann et al.(Appl.Math.Comput.325:252–270.https://doi.org/10.1016/j.amc.2017.12.041,2018),motivated by the difficulty of choosing appropriate boundary conditions at the internal nodes of a network,a different technique was explored that avoids the use of ghost cells,but instead employs for the boundary cells a different stencil,biased towards the interior of the domain.In this paper,extending that approach,which does not make use of ghost cells,we propose a more accurate reconstruction for the one-dimensional case and a two-dimensional one for Cartesian grids.In several numerical tests,we compare the novel reconstruction with the standard approach using ghost cells.

Command filtered integrated estimation guidance and control for strapdown missiles with circular field of view

In this paper,an integrated estimation guidance and control(IEGC)system is designed based on the command filtered backstepping approach for circular field-of-view(FOV)strapdown missiles.The threedimensional integrated estimation guidance and control nonlinear model with limited actuator deflection angle is established considering the seeker's FOV constraint.The boundary time-varying integral barrier Lyapunov function(IBLF)is employed in backstepping design to constrain the body line-of-sight(BLOS)in IEGC system to fit a circular FOV.Then,the nonlinear adaptive controller is designed to estimate the changing aerodynamic parameters.The generalized extended state observer(GESO)is designed to estimate the acceleration of the maneuvering targets and the unmatched time-varying disturbances for improving tracking accuracy.Furthermore,the command filters are used to solve the"differential expansion"problem during the backstepping design.The Lyapunov theory is used to prove the stability of the overall closed-loop IEGC system.Finally,the simulation results validate the integrated system's effectiveness,achieving high accuracy strikes against maneuvering targets.

Identification of time-varying system and energy-based optimization of adaptive control in seismically excited structure

The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.

Innovation and Practice of Teaching Methods in Digital and Adaptive Learning:Taking Communication Engineering Major as an Example

This paper proposes teaching reforms in communication engineering majors,emphasizing the implementation of digital and adaptive teaching methodologies,integrating emerging technologies,breaking free from the constraints of traditional education,and fostering high-caliber talents.The reform measures encompass fundamental data collection,recognition of individual characteristics,recommendation of adaptive learning resources,process-oriented teaching management,adaptive student guidance and early warning systems,personalized evaluation,and the construction of an integrated service platform.These measures,when combined,form a comprehensive system that is expected to enhance teaching quality and efficiency,and facilitate student development.

Enhancing the Quality and Adaptability of Vocational Education to Promote High-Quality Development:Taking Hainan Vocational University of Science and Technology as an Example

This paper aims to explore effective strategies for overcoming the five core challenges currently faced by vocational education:challenges in defining the educational type,variations in the quality of incoming students and their learning abilities,the need to improve teaching quality and effectiveness,urgent requirements for optimizing the quality of teaching staff,and insufficient depth in the integration of industry and education.By analyzing the root causes of these challenges,this paper proposes a series of targeted strategies and measures.Taking the School of Chemistry and Materials Engineering at Hainan Vocational University of Science and Technology as an example,the paper elaborates on how the school has significantly enhanced the adaptability and teaching quality of vocational education through precise positioning of vocational education types,strengthening the construction of teaching staff,optimizing teaching methods and content,and deepening the integration of industry and education.The research results indicate that these initiatives not only effectively address key issues in vocational education but also promote comprehensive improvements in students’overall qualities and employment competitiveness,providing valuable insights and practical references for advancing the high-quality development of vocational education.Furthermore,by introducing the practice of the School of Chemistry and Materials Engineering at Hainan Vocational University of Science and Technology in tailoring vocational education development to local conditions,this paper validates the reliability and feasibility of the proposed solutions.

Integrated Guidance and Control of Homing Missiles Against Ground Fixed Targets

This paper presents a scheme of integrated guidance and autopilot design for homing missiles against ground fixed targets. An integrated guidance and control model in the pitch plane is formulated and further changed into a normal form by nonlinear coordinate transformation. By adopting the sliding mode control approach, an adaptive nonlinear control law of the system is designed so that the missile can hit the target accurately with a desired impact attitude angle. The stability analysis of the closed-loop system is also conducted. The numerical simulation has confirmed the usefulness of the proposed design scheme.

外电场作用下改进的Leaky Integrate-And-Fire模型的峰放电频率适应性研究

峰放电频率适应性是神经元在信息处理过程中重要的动力学特性之一.当神经系统受到外电场作用时,会对其动力学行为以及神经电信息的产生、传导产生影响.我们基于Leaky integrate-and-fire(LIF)神经元模型,建立了外电场作用下改进的LIF神经元模型.采用随时间演化的膜电位曲线和峰放电频率曲线,以及随外电场变化的起始峰放电频率曲线和稳态峰放电频率曲线,研究不同强度、频率外电场作用下改进的LIF模型的适应性变化.此外,还利用相邻峰峰间期(ISI)之间的相关性进一步阐明外电场对神经元适应性的影响.

Multiphasic bone-ligament-bone integrated scaffold enhances ligamentization and graft-bone integration after anterior cruciate ligament reconstruction

The escalating prevalence of anterior cruciate ligament(ACL)injuries in sports necessitates innovative strategies for ACL reconstruction.In this study,we propose a multiphasic bone-ligament-bone(BLB)integrated scaffold as a potential solution.The BLB scaffold comprised two polylactic acid(PLA)/deferoxamine(DFO)@mesoporous hydroxyapatite(MHA)thermally induced phase separation(TIPS)scaffolds bridged by silk fibroin(SF)/connective tissue growth factor(CTGF)@Poly(L-lactide-co-ε-caprolactone)(PLCL)nanofiber yarn braided scaffold.This combination mimics the native architecture of the ACL tissue.The mechanical properties of the BLB scaffolds were determined to be compatible with the human ACL.In vitro experiments demonstrated that CTGF induced the expression of ligament-related genes,while TIPS scaffolds loaded with MHA and DFO enhanced the osteogenic-related gene expression of bone marrow stem cells(BMSCs)and promoted the migration and tubular formation of human umbilical vein endothelial cells(HUVECs).In rabbit models,the BLB scaffold efficiently facilitated ligamentization and graft-bone integration processes by providing bioactive substances.The double delivery of DFO and calcium ions by the BLB scaffold synergistically promoted bone regeneration,while CTGF improved collagen formation and ligament healing.Collectively,the findings indicate that the BLB scaffold exhibits substantial promise for ACL reconstruction.Additional investigation and advancement of this scaffold may yield enhanced results in the management of ACL injuries.

基于循环一致对抗学习的段码液晶仪表读数识别方法

为解决自然场景中仪表图像受复杂光照、背景及其他随机干扰所造成的读数识别难题,提出一种基于循环一致对抗学习的段码液晶仪表读数识别方法。该方法使用M-CRAFT作为字符检测网络,获取段码读数区域和段码字符位置,通过后处理算法分割得到段码字符子图像,然后以循环一致对抗域自适应网络CYCADA为基础,增加感知损失和重构损失并设计分类器,构建了一种改进的字符背景分离与识别网络I-CYCADA,用于将具有复杂背景的段码字符图像转换为清晰直观的二值图像,从而使读数识别变得更为简单和准确。为了验证该方法的有效性,构建了由多种复杂场景下的液晶段码仪表图像组成的数据集。实验结果表明,I-CYCADA可与不同CNN分类网络结合使用,均能提升转换后的段码字符图像的识别准确率,本文方法在自建数据集上的字符级识别准确率达95.39%,完整读数识别准确率达86.65%,有效改善了对困难样本的识别效果,且轻量级设计可满足实时性要求。