Consideration Of Dynamics Research Articles

The Role of Recent Climate Change in Explaining the Statistical Yield Increase of Maize in Northern Bavaria—A Model Study

Maize yields in many regions of the world have increased significantly since the 1960s. The increase is mainly attributed to technological improvements and climate change. On a regional scale and in recent decades, climate change has altered growth conditions of maize and this, in turn, has influenced changes in yield. In order to analyze the contribution of different factors to yield changes, and to obtain a model setup that could be used for further analyses of yield development, this study systematically investigated the effects of recent climate change, irrigation, cultivar selection and nutrient availability on historical yields in Northern Bavaria. Four sets of simulations were conducted with the mechanistic plant growth model PROMET, during the time period between 1997 and 2020, and the resulting yields were compared to county statistics. In addition, three scenarios were simulated in order to determine yield increase potentials for the highly mechanized agricultural region of Northern Bavaria. The results showed a good agreement with the observed yields (R2 = 0.76), when considering altered nutrient availability, suggesting that an increase in nutrient uptake by plants plays a key role in reproducing yield statistics and has a main contribution to the observed increasing yield trends. Moreover, other factors considered individually, such as recent climate change, irrigation and cultivar selection, could not explain the yield levels and trends shown by the statistics. The scenario simulations demonstrated potential increases in yield due to irrigation and cultivar adaptation. The yield response to irrigation shows a trend, with recent climate change progressing, of 0–25% when irrigating currently grown cultivars and 10–50% when irrigating an adapted cultivar; rainfed cultivar adaptation consistently increased the level of yields by approximately 10%. This study highlights the importance of a dynamic consideration of growth conditions in the course of climate change, rather than static assumptions of model parameters, and emphasizes the importance of the second-order effects of climate change.

How workplaces produce or reduce disability along the career paths of young people with cystic fibrosis.

Using the theoretical perspective of "social participation" as considered in the Human Development-Disability Creation Process, this article examines certain obstacles and facilitators to sustainable access to work among young French adults with cystic fibrosis. Drawing from the analyses of 29 qualitative interviews, the results show how such obstacles do not depend solely on their health status or on the medical management of the illness, but also on the work environments that these young professionals have recently entered or are trying to access. In these contexts, managing information about the illness can represent a means of obtaining cooperation from colleagues and superiors to reduce material or organizational obstacles (e.g. adapted work schedules), as well as a means of preventing socially uncomfortable or disabling situations. In this light, the social participation model can complement Corbin and Strauss' illness trajectory model, by setting the multi-factorial disabling or participatory situations along illness or medical trajectories. This enables dynamic consideration of how workplaces contribute to producing or reducing disability, in interaction with the actions taken by young people with cystic fibrosis to manage their career paths but also the evolution of illness, symptoms, or medical requirements.

Price and quantity discovery without commitment

Wholesale electricity markets solve a complex allocation problem: electricity is not storable, demand is uncertain, and production involves dynamic cost considerations and indivisibilities. The New Zealand wholesale electricity market attempts to solve this complex allocation problem by using an indicative price and quantity discovery mechanism that ends at dispatch. Can such a market mechanism without commitment provide useful information? We document that indicative prices and quantities are increasingly informative of the final prices and quantities and that bid revisions are consistent with information-based updating. We argue that the reason why the predispatch market is informative despite the lack of commitment is that it generates private benefits in terms of improved intertemporal optimization of production plans.

THE POST-INDUSTRIAL CONTEXT OF THE DEVELOPMENT OF THE PRINCIPLES OF MANAGERIAL CONSTITUTIONALISM

The article examines the problems of formation and development of the principles of managerial constitutionalism. The position on the need for research and practical implementation of the principles of managerial constitutionalism is presented. A list of principles of managerial (management) constitutionalism is offered. Features and strategic directions of development of this process are determined. The key parameters of each principle are analyzed with the definition of the main feature and features of their further practical implementation. The rationale for the necessity of the term "managerial constitutionalism" is presented. Special attention is paid to the consideration of the semantic dynamics of the process of formation and practical use of the ten basic principles of managerial constitutionalism. Attention is drawn to the need for systemic changes in the training of management personnel in the conditions of postmodern development of an innovative society. The importance of innovative dynamics in the personnel policy system in relation to each principle of managerial constitutionalism is shown. The objective necessity of fundamental and innovative training of managers is determined as a basis for their orientation towards the systematic development of the managerial profession. Approaches to the implementation of the principles of managerial constitutionalism in Ukraine are considered. The need to transform the professional qualities of management personnel with an emphasis on each principle of managerial constitutionalism is proven. Attention is focused on the need to develop socio-cultural indicators of management professionalization. The need to create conditions for the formation of the integral quality of the professional management system is proved. The position on the role of the managerial elite in the development of an innovative society is presented.

Mosquito bed net use and associated factors among pregnant women in Rwanda: a nationwide survey

BackgroundIn malaria-endemic countries such as Rwanda, the appropriate use of mosquito bed nets is an effective intervention for malaria prevention. Despite being one of the demographics most impacted by malaria, there is a dearth of literature on the usage of mosquito bed nets by pregnant women in Rwanda. The study aimed to assess the prevalence and associated factors for mosquito bed net use among pregnant women in Rwanda.MethodsWe used weighted data from the 2020 Rwanda Demographic and Health Survey of 870 pregnant women, and multistage stratified sampling was used to select participants. Multivariable logistic regression was conducted to determine the factors associated with mosquito bed net use, using SPSS (version 26).ResultsOf the 870 pregnant women, 57.9% (95%CI: 54.6–61.1) used mosquito bed nets. However, 16.7% did not use bed nets among those owning bed nets. On one hand, older age (AOR = 1.59, 95%CI: 1.04–2.44), primary education (AOR = 1.18, 95%CI: 1.07–2.23), being married (AOR = 2.17, 95%CI: 1.43–3.20), being from Kigali region (AOR = 1.97, 95%CI: 1.19–3.91), partner’s education (AOR = 1.22, 95%CI: 1.13–3.41), having recently visited a health facility (AOR = 2.07, 95%CI: 1.35–3.18), and being in the third pregnancy trimester (AOR = 2.14, 95%CI: 1.44–3.18) were positively associated with mosquito bed net use. On the other hand, low wealth index (AOR = 0.13, 95%CI: 0.07–0.24), and being from Eastern region (AOR = 0.42, 95% CI: 0.26–0.66) had a negative association.ConclusionsAbout half of the pregnant women in Rwanda used mosquito bed nets and the usage was associated with various socio-demographics. There is a need for appropriate risk communication and continuous sensitisation to improve mosquito net use among pregnant women. Early antenatal care attendance and partner engagement in malaria prevention and mosquito net use, as well as consideration of household dynamics, are also crucial in improving not only mosquito net coverage but also utilization.

Model-Based Control and Model-Free Control Techniques for Autonomous Vehicles: A Technical Survey

Autonomous driving has the potential to revolutionize mobility and transportation by reducing road accidents, alleviating traffic congestion, and mitigating air pollution. This transformation can result in energy efficiency, enhanced convenience, and increased productivity, as valuable driving time can be repurposed for other activities. The main objective of this paper is to provide a comprehensive technical survey of the latest research in the field of lateral, longitudinal, and integrated control techniques for autonomous vehicles. The survey aims to explore a wide range of techniques and methodologies employed to achieve precise steering control while also considering longitudinal aspects. Model-based control techniques form the foundation for control, utilizing mathematical models of vehicle dynamics to design controllers that effectively track desired speeds and/or steering behavior. Unlike model-free control techniques such as reinforcement learning and deep learning algorithms facilitate the integration of longitudinal and lateral control by learning control policies directly from data and without explicit knowledge of the underlying dynamics. Through this survey, the paper delves into the strengths, limitations, and advancements in both model-based and model-free control approaches for autonomous vehicles. It investigates their performance in real-world scenarios and addresses the technical challenges associated with their implementation. These challenges may include uncertainties in the environment, adaptability to dynamic conditions, robustness, safety considerations, and computational complexity.

Israeli‐Palestinian conflict: The archaic fraternal complex

AbstractThe Israeli–Palestinian conflict is one of the world's most persistent and intractable conflicts. Despite extensive and in‐depth analyses to help understand and transform it, the parties have failed to reach sustainable peace. In this article, I extend group and family psychoanalytic theories to analyze the unconscious dynamics that potentially underlie this relationship, interpreting it in light of the biblical narrative of Abraham, his wives—Sarah and Hagar, and sons—Isaac and Ishmael. Using the above‐mentioned framework, I interpret the Israeli–Palestinian conflict over land as an enactment of the archaic fraternal complex, whereby each sibling unconsciously entertains the fantasy of returning to the maternal womb and aspires to be the exclusive owner of maternal space and the mother's phallus. Consideration of the archaic fraternal complex dynamics offers psychoanalytically oriented mediators an additional tool to understand conflicts, especially land‐related disputes. To work through intractable conflict, these mediators can help the belligerent parties perform the psychic work of trauma and primal mourning to stop enacting the fantasy of returning to the maternal womb and to accept symbolic castration. This work could contribute to the warring parties' ability to renounce their rigid ideological positions and seal new fraternal pacts under the aegis of the law of reason. Their fraternal complex would thus be transformed from archaic and talionic to symbolic and Oedipal.

A Survey of Intelligent Driving Vehicle Trajectory Tracking Based on Vehicle Dynamics

<div>Trajectory tracking control, as one of the core technologies of intelligent driving vehicles, determines the driving performance and safety of intelligent driving vehicles and has received extensive attention and research. In recent years, most of the research results of trajectory tracking control are only applicable to conventional working conditions; however, the actual operating conditions of intelligent driving vehicles are complex and variable, so the research of trajectory tracking control algorithm should be extended to the high-speed low-adhesion coefficient, large curvature, variable curvature, and other compound limit working conditions. This requires more consideration of the vehicle dynamics in the controller design. In this article, a comprehensive review of trajectory tracking control under extreme operating conditions is conducted from three levels: vehicle dynamics model, vehicle speed tracking (longitudinal motion control), and path tracking (transverse motion control), and the existing research results are analyzed and summarized to obtain the research trends and pain points and difficulties in each field. On this basis, the future outlook of trajectory tracking control is proposed, which is expected to provide some help and inspiration to the research workers in this field.</div>

A spatiotemporal fuzzy control approach for complex distributed parameter system with application to thermal processes

Many industrial processes belong to distributed parameter systems (DPSs) with unknown spatiotemporal dynamics and complex boundary conditions. However, attentions to both temporal and spatial dynamics in the control law are less paid in the existing control methods, which often makes them challenging to achieve accurate control. Here, a spatiotemporal fuzzy control approach with consideration of both temporal and spatial dynamics is proposed for unknown and complex DPSs. First, a spatiotemporal fuzzy model is developed to reconstruct dynamics of nonlinear DPS. Since it constructs a two-layer fuzzy rules (i.e., temporal fuzzy rule and spatial fuzzy rule) to consider both the nonlinear dynamics on time and the nonlinear energy transfer on space, it can effectively achieve the model of DPSs. On this basis, a spatiotemporal fuzzy controller is developed according to the developed two-layer fuzzy rules, which means that this derived control law considers both temporal and spatial dynamics. Then, a two-step solution method is designed for the spatiotemporal control law. Stability conditions of the control system are rigorously deduced by transforming the solving process to a series of linear matrix inequalities (LMIs). The stability and effect of the proposed spatiotemporal control strategy are demonstrated by mathematical proof and case studies. Comparison results demonstrate that the proposed method has better control performance (relative errors and mean absolute percentage errors are bounded in 4%).

Tradable performance standards in a dynamic context

Many sectors of the economy that are targets of emissions reduction policy exhibit price-responsive demand, long-lived capital, capacity constraints, and foresighted decision-making. I explore how these features affect the efficiency and dynamics of tradable performance standards (TPS) using analytical and numerical equilibrium models. While I show these dynamic considerations alone do not lead to conflicts with existing theory on the overall efficiency and cost-effectiveness of the TPS relative to a first-best policy, they do affect the transition path and steady state. Most notably, under all but the smallest discount rates, the TPS can lead to a more cost-effective post-transition steady state than the equivalent emissions cap. Given the intergenerational transition that comes with decarbonization, this result suggests some classes of present and future consumers may prefer a TPS to an emissions cap.

Hierarchical Control Strategy with Battery Dynamic Consideration for a Dual Fuel Cell/Battery Tramway

This paper proposes a hierarchical energy control strategy for a hybrid dual fuel cell/battery tramway, combining online and offline optimization methods while considering the battery’s dynamic behavior. In the upper layer, an online band-pass filter-based extremum-seeking control (BFESC) is employed to estimate the reference power between the dual fuel cell system and battery. In addition, the battery’s dynamic behavior is considered a penalty function of the BFESC to maintain its parameters within the desired boundaries. In the middle layer, the power requirement for each fuel cell system is calculated by using an offline method called the map search method. Finally, the fuel cell and battery provide the required power to the DC bus through DC/DC converters, which are controlled by PID controllers in the lower layer. To verify the effectiveness of the proposed control strategy, a simulation model is built in Matlab/Simulink. The results demonstrate that the dual fuel cell/battery system under the control of the proposed energy management strategy (EMS) can operate efficiently while improving the battery’s durability. The efficiency of the fuel cell system when using the proposed EMS was lower than 4% compared with the non-constraint EMS. However, the capacity loss of the battery could improve up to 25.9% in high-current and high-SOC cases.

Vessel-following model for inland waterways based on deep reinforcement learning

With the growth of traffic on inland waterways, autonomous driving technologies for vessels will gain increasing significance to ensure traffic flow and safety. Inspired by car-following models for road traffic, which demonstrated their strength to reduce stop-and-go waves and increase efficiency and safety, we propose a vessel-following model for inland waterways based on deep reinforcement learning (RL). Our model is trained under consideration of realistic vessel dynamics and environmental influences, such as varying stream velocity and river profile, and with a reward function favoring observed following behavior and comfort. Aiming at high generalization capabilities, we propose a training environment that uses stochastic processes to model leading the trajectory and river dynamics. Our model demonstrated safe and comfortable driving in different unseen scenarios, including realistic vessel-following on the Middle Rhine. In comparison with an existing model, our model was able to early anticipate safety–critical situations, resulting in higher safety while maintaining comparable efficiency and comfort. In further experiments, the proposed approach demonstrated its potential to dampen traffic oscillations and reduce congestion by using a sequence of followers.

Effects of myocardial sheetlet sliding on left ventricular function

Left ventricle myocardium has a complex micro-architecture, which was revealed to consist of myocyte bundles arranged in a series of laminar sheetlets. Recent imaging studies demonstrated that these sheetlets re-orientated and likely slided over each other during the deformations between systole and diastole, and that sheetlet dynamics were altered during cardiomyopathy. However, the biomechanical effect of sheetlet sliding is not well-understood, which is the focus here. We conducted finite element simulations of the left ventricle (LV) coupled with a windkessel lumped parameter model to study sheetlet sliding, based on cardiac MRI of a healthy human subject, and modifications to account for hypertrophic and dilated geometric changes during cardiomyopathy remodeling. We modeled sheetlet sliding as a reduced shear stiffness in the sheet-normal direction and observed that (1) the diastolic sheetlet orientations must depart from alignment with the LV wall plane in order for sheetlet sliding to have an effect on cardiac function, that (2) sheetlet sliding modestly aided cardiac function of the healthy and dilated hearts, in terms of ejection fraction, stroke volume, and systolic pressure generation, but its effects were amplified during hypertrophic cardiomyopathy and diminished during dilated cardiomyopathy due to both sheetlet angle configuration and geometry, and that (3) where sheetlet sliding aided cardiac function, it increased tissue stresses, particularly in the myofibre direction. We speculate that sheetlet sliding is a tissue architectural adaptation to allow easier deformations of the LV walls so that LV wall stiffness will not hinder function, and to provide a balance between function and tissue stresses. A limitation here is that sheetlet sliding is modeled as a simple reduction in shear stiffness, without consideration of micro-scale sheetlet mechanics and dynamics.

Consensus-Based Control Strategy for Mixed Platoon under Delayed V2X Environment

This paper develops a mixed platoon control strategy incorporating vehicle dynamics and time-varying vehicle-to-everything (V2X) delays to guarantee the consensus of a mixed platoon and reduce the impacts caused by the inconstant driving behavior of human-driven vehicles (HVs). In particular, a system control framework is established for a mixed vehicle platoon, which bears HVs and connected automated vehicles (CAVs). More precisely, this system control framework considers directly controlling CAVs and indirectly guiding the HVs to improve the consensus of the whole platoon with respect to velocity error and headway. Furthermore, based on the third-order closed-loop dynamic model, the consideration of vehicle dynamics and time-varying delays are taken into account. Then, theoretical analysis employs Lyapunov–Krasovskii theory to derive the delay boundary that determines the asymptotic stability and local string stability. Finally, a performance comparison with the existing algorithm is carried out to further demonstrate the advantages of the proposed strategy.

Chromatic confocal sensor-based on-machine measurement for microstructured optical surfaces featuring a self-aligned spiral center.

Chromatic confocal sensor-based on-machine measurement is effective for identifying and compensating for form errors of the ultra-precisely machined components. In this study, an on-machine measurement system was developed for an ultra-precision diamond turning machine to generate microstructured optical surfaces, for which the sensor probe adopts a uniform spiral scanning motion. To avoid the tedious spiral center alignment, a self-alignment method was proposed without additional equipment or artefact, which identified the deviation of the optical axis to the spindle axis by matching the measured surface points and the designed surface. The feasibility of the proposed method was demonstrated by numerical simulation with full consideration of noises and system dynamics. Practically, taking a typical microstructured surface as an example, the on-machine measured points were reconstructed after calibrating the alignment deviation, which was then verified by off-machine white light interferometry measurement. Avoiding tedious operations and special artefacts may significantly simplify the on-machine measurement process, thereby greatly improving the efficiency and flexibility for the measurement.

The Hidden Behavior of a D-Latch

For clock and data transitions in close temporal proximity, synchronous memory elements potentially enter metastability, which leads to unintended output behavior. Although respective analyses in literature have already derived suitable explanations, almost all of them modeled the control (clock) signal transition with negligible rise/fall time. In modern circuits this assumption is, however, not reasonable any more. In fact, due to a finite slope, intermediate clock signal values have to be considered during a large share of the storage process, while their concrete impact is not yet sufficiently explored. In this paper we thus use static and dynamic considerations to thoroughly investigate the behavior of a latch for arbitrary analog control, data and output values, i.e., during the storage process. Basic circuit considerations allow us to derive a unified model which identifies the latch as a Schmitt Trigger with vastly varying hysteresis. We verify the correctness of our predictions by comparison to analog SPICE simulations. Finally we are able to generalize our findings and thus provide explanations for yet unexplained behavior reported in literature.

Forming intracluster gas in a galaxy protocluster at a redshift of 2.16

Galaxy clusters are the most massive gravitationally bound structures in the Universe, comprising thousands of galaxies and pervaded by a diffuse, hot intracluster medium (ICM) that dominates the baryonic content of these systems. The formation and evolution of the ICM across cosmic time1 is thought to be driven by the continuous accretion of matter from the large-scale filamentary surroundings and energetic merger events with other clusters or groups. Until now, however, direct observations of the intracluster gas have been limited only to mature clusters in the later three-quarters of the history of the Universe, and we have been lacking a direct view of the hot, thermalized cluster atmosphere at the epoch when the first massive clusters formed. Here we report the detection (about 6σ) of the thermal Sunyaev–Zeldovich (SZ) effect2 in the direction of a protocluster. In fact, the SZ signal reveals the ICM thermal energy in a way that is insensitive to cosmological dimming, making it ideal for tracing the thermal history of cosmic structures3. This result indicates the presence of a nascent ICM within the Spiderweb protocluster at redshift z = 2.156, around 10 billion years ago. The amplitude and morphology of the detected signal show that the SZ effect from the protocluster is lower than expected from dynamical considerations and comparable with that of lower-redshift group-scale systems, consistent with expectations for a dynamically active progenitor of a local galaxy cluster.

Forecast‐ready models to support fisheries' adaptation to global variability and change

AbstractOcean and climate drivers affect the distribution and abundance of marine life on a global scale. Marine ecological forecasting seeks to predict how living marine resources respond to physical variability and change, enabling proactive decision‐making to support climate adaptation. However, the skill of ecological forecasts is constrained by the skill of underlying models of both ocean state and species‐environment relationships. As a test of the skill of data‐driven forecasts for fisheries, we developed predictive models of catch‐per‐unit‐effort (CPUE) of tuna and billfish across the south‐west Pacific Ocean, using a 12‐year time series of catch data and a large ensemble climate reanalysis. Descriptors of water column structure, particularly temperature at depth and upper ocean heat content, emerged as useful predictors of CPUE across species. Enhancing forecast skill over sub‐seasonal to multi‐year timescales in any system is likely to require the inclusion of sub‐surface ocean data and explicit consideration of regional physical dynamics.

Event-Driven Energy-Efficient Driving Control in Urban Traffic for Connected Electric Vehicles

The traffic light in urban areas dominates the traffic flow, resulting in variation of energy consumption of the vehicles involved. To mitigate the impact of traffic bias on the energy efficiency of electric vehicles (EVs), this article proposes an event-driven energy-efficient driving control (EEDC) strategy based on a receding horizon two-stage control framework, which harnesses the Internet of Vehicles to incorporate the traffic light and preceding vehicle for adaption of different driving scenarios. At the core of the first stage are the vehicle driving event classification rules, which classified the urban traffic scenarios into four events. This article contributes to empirical solutions on the design of the traffic scenario classifier considering conflict goals, including driving efficiency and safety. In the second stage, the speed trajectory in each driving event is optimized using Pontryagin’s minimum principle to reduce vehicle energy consumption. A real-time solution for the energy-efficient driving problem is derived with the consideration of vehicle dynamics, control input, and speed limit constraints. Finally, extensive simulations and road tests are conducted to evaluate the effectiveness of the EEDC. The results show that the EEDC is excellent in energy efficiency improvement over two benchmark strategies in different traffic scenarios while satisfying the constraints in inter-vehicle driving safety and travel time. Moreover, the road tests demonstrate that the EEDC is capable of energy saving in real-world driving.

Digital twins for performance management in the built environment

Recent events worldwide of climate and geological origins highlight the vulnerability of our infrastructures and stress the often dramatic consequences on our environment. Accurate digital models are needed to understand how climate change and associated risks affect buildings, while informing on ways of enhancing their adaptability and resilience. This requires a paradigm shift in design and engineering interventions as the potential for adaptation and resilience should be embedded into initial brief formulation, design, engineering, construction and facility maintenance methods. This paper argues the need for smarter and digital interventions for buildings and infrastructures and their underpinning data systems that factor in topology (including geometry), mereology, and behavioural (dynamic) considerations. Digital models can be used as a basis to understand the complex interplay between environmental variables and performance, and explore real-time response strategies (including control and actuation) to known and uncertain solicitations enabled by a new generation of technologies. The paper proposes a digital twin model for the construction and industrial assets that paves the way to a new generation of buildings and infrastructures that (a) address lifetime requirements, (b) are capable of performing optimally within the constraints of unknown future scenarios, and (c) achieve acceptable levels of adaptability, efficiency and resilience.