Dynamic Situations Research Articles

Establishing Zion in the Heat of Battle

Establishing Zion in the Heat of Battle

Drafting strategies in fantasy football: A study of competitive sequential human decision making

AbstractDrafting is a competitive task in which a set of decision makers choose from a set of resources sequentially, with each resource becoming unavailable once selected. How people make these choices raises basic questions about human decision making, including people’s sensitivity to the statistical regularities of the resource environment, their ability to reason about the behavior of their competitors, and their ability to execute and adapt sophisticated strategies in dynamic situations involving uncertainty. Sports provides one real-world example of drafting behavior, in which a set of teams draft players from an available pool in a well-regulated way. Fantasy sport competitions provide potentially large data sets of drafting behavior. We study fantasy football drafting behavior from the 2017 National Football League (NFL) season based on 1350 leagues hosted by the http://sleeper.app platform. We find people are sensitive to some important environmental regularities in the order in which they draft players, but also present evidence that they use a more narrow range of strategies than is likely optimal in terms of team composition. We find little to no evidence for the use of the complicated but well-documented strategy known as handcuffing, and no evidence of irrational influence from individual-level biases for different NFL teams. We do, however, identify a set of circumstances for which there is clear evidence that people’s choices are strongly influenced by the immediately preceding choice made by a competitor.

Decreased Postural Sway in Women Who Are Visually Impaired: Is it a Learned Protective Mechanism?

Introduction: Comparison of sway parameters of visually impaired participants to that of the sighted population may give insight into the intrinsic risk of falls relative to the surface. Sway is a natural mechanism to adjust the posture and maintain balance. But the sway characteristics on uneven surfaces are ill explored. There is a paucity of evidence on baseline values of sway amplitude in visually impaired women in comparison to sighted women, which underpins the importance of this study. Methods: Eighteen visually impaired young women and an equal number of age-matched sighted peers were recruited by convenience to this prospective observational study. Sway amplitude of the participants were measured using a sway meter on three different surfaces, with eyes opened and closed conditions, using videography and analyzed using Kinovea motion analyzing software. Demographics and participant characteristics were summarized using descriptive statistics. The comparison were performed using independent sample t-test. Results: Visually impaired women demonstrated lower amplitude of sway than sighted young women, irrespective of the surface. Discussion: There was a gradual increase in sway amplitude as the standing surfaces changed from even to sand and pebbles, respectively, for both groups. Implications for Practitioners: Contrary to the existing evidence, the results of this study indicate that visually impaired young individuals may not be not at higher intrinsic risk of falls on various terrains than their sighted peers. The authors hypothesize that the lower sway among visually impaired participants can be attributed to the learned strategy for safety from exposure to real-life pragmatic environments during everyday activities, which enabled them to adopt postural strategies as a safety measure. Hence, this strategy can potentially be used in dynamic situations to decrease the propensity for falls during ambulation in visually impaired individuals.

Continuous development of the semantic search engine preVIEW: from COVID-19 to long COVID.

preVIEW is a freely available semantic search engine for Coronavirus disease (COVID-19)-related preprint publications. Currently, it contains >43 800 documents indexed with >4000 semantic concepts, annotated automatically. During the last 2 years, the dynamic situation of the corona crisis has demanded dynamic development. Whereas new semantic concepts have been added over time—such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of interest—the service has been also extended with several features improving the usability and user friendliness. Most importantly, the user is now able to give feedback on detected semantic concepts, i.e. a user can mark annotations as true positives or false positives. In addition, we expanded our methods to construct search queries. The presented version of preVIEW also includes links to the peer-reviewed journal articles, if available. With the described system, we participated in the BioCreative VII interactive text-mining track and retrieved promising user-in-the-loop feedback. Additionally, as the occurrence of long-term symptoms after an infection with the virus SARS-CoV-2—called long COVID—is getting more and more attention, we have recently developed and incorporated a long COVID classifier based on state-of-the-art methods and manually curated data by experts. The service is freely accessible under https://preview.zbmed.de

Real-Time Generation Method of Oil Painting Style Brushstrokes Based on Inverse Reinforcement Learning

A popular style in modern graphics programs like GIMP, Photoshop, and Painter is brushstroke artwork, a classic artwork that is still extensively practiced today. Regarding successive decision-making situations with ambiguity, reinforcement learning approaches can be quite helpful. In RL, a reward-enabled agent interacts with a dynamic situation to discover a strategy. To use current RL techniques, we must first offer a reward function, a concise depiction of the designer’s purpose. Hence, inverse-RL (IRL), an expansion of RL, was born. It solves this difficulty via developing the reward function from skilled demonstrations. In this article, we present a novel sundry-fidelity Bayesian optimization (SFBO) approach to boost the ability of the IRL regarding oil painting style brushstrokes. Finally, the performance of the proposed approach is examined and compared with the standard approaches to achieve the highest effectiveness in oil painting. The findings are depicted in graphical representation through Origin tool. Approaches based on RL can be quite helpful in ambiguous decision-making situations. Today’s RL approaches must include a reward function, which embodies the designer’s intent. To reduce the dimensions of the data, the proposed SFBO comprises stages of data preprocessing and feature extraction. The proposed technique was evaluated against the existing techniques in terms of accuracy, information loss, average MSE, and time consumption. Compared to the existing approaches, the proposed approach was the most effective.

Multi-missile interception for multi-targets: Dynamic situation assessment, target allocation and cooperative interception in groups

Target allocation is a crucial point in the cooperative interception process. In this paper, a new algorithm of dynamic situation assessment, target allocation and cooperative interception in groups is proposed for multi-target interception with multiple missiles. An effective situation assessment function is proposed, according to which the targets of each intercepting missile are assigned to maximize their efficiency. The new situation assessment function evaluates the flight status and cooperation of missiles, which considers not only the relative position and velocity mentioned in traditional functions, but also relative normal velocity, normal acceleration, maneuverability and cooperation between multiple missiles. During the interception process, the flight status could be evaluated dynamically, thus the allocation of the missiles could be real-time adjusted. To optimize target allocation, a method based on genetic algorithm is applied, which uses the dynamic situation assessment function based proportional navigation guidance law, and we also use proportional navigation guidance law to realize the interception to maneuvering targets with multiple missiles. Simulations for target allocation and target interception validate the effectiveness of the algorithm. Potential adjustments and improvements are proposed according to the simulation results.

Structural transformation of fuzzy analytical hierarchy process: a relevant case for Covid-19

Covid-19 has posed difficult and challenging situations to the supply chains and companies are in fix how to choose the vendors under the uncertainty and complexity in recent years. Therefore, this research aims to incorporate structural transformation of the fuzzy analytical hierarchy process (FAHP) that is most appropriate for the uncertainty and disruption caused by Covid-19 like situation for ensuring supplies from vendors. The conventional approaches for vendor selection and evaluation use numerous multi-criteria decision-making tools that may not ensure reliability in a dynamic situation caused due to Covid-19. In this research, Fleiss’ Kappa method ensures the reliability of responses from eight respondents by using pairwise comparisons and assigning weights as envisaged in FAHP. In addition to determine the reliability of responses, a step under FAHP has been altered. This alteration is demonstrated in the vendor selection case in the Covid-19 scenario. The research suggests a plausible system required to address the uncertainties associated with Covid-19 to select and evaluate vendors by modifying a FAHP. The proposed altered mechanism can be incorporated in a similar type of other decision-making circumstances such as Covid-19, where the decision-makers are more than one, and the situation is very dynamic. The study is likely to facilitate information management, algorithmic development in decision making, or machine-driven decisions in uncertain conditions. The study offers managerial implications to purchase managers to accommodate and combine multiple factors and responses concerning the vendor performances for their evaluation, thus making a process more reliable.

Fundamental insights into the electrical signals of a piezoelectric sensor in a sliding condition

The piezoelectric mechanism represents a promising approach for advanced sensors that measure physical factors such as pressures, strain levels and even temperature responses to various stimuli. However, a conventional analysis of piezoelectric signals is mainly related to the peak output voltage for normal force, meaning that there remain numerous challenges to overcome when analyzing piezoelectric signals over time corresponding to complex or dynamic situations. Here, a fundamental analysis of piezoelectric signals for a dynamic change situation induced by sliding motion and resulting in the partial deformation of a piezoelectric material is introduced. Given that a piezoelectric voltage at a certain time represents the sum value of diploe moments in all piezoelectric material segments, in this respect, some parts are compressed and others are released, and we compared the electric signals between small segments and one unit cell to obtain a clue about the signal process and to confirm the mathematical formula. Based on the results of piezoelectric signal fitting with the exponential and error function, general solutions that can model piezoelectric signals were proposed to create artificial piezoelectric signals which corresponded to each small segment of the piezoelectric material. By comparing the artificial signals and actually measured signals, the general solution was optimized and the induced artificial piezoelectric signals were found to have good reliability and reproducibility. Various depth profiles with sliding motion could be calculated from the combination of artificial signals in the 0.6 mm, 0.9 mm, and 1.2 mm pressing conditions using piezoelectric integral values. In addition, the calculated depth profiles had a resolution of approximately 100 µm, and simultaneously measurable depth profiles were improved with more artificial signals.

Inference of Upcoming Human Grasp Using EMG During Reach-to-Grasp Movement.

Electromyography (EMG) data has been extensively adopted as an intuitive interface for instructing human-robot collaboration. A major challenge to the real-time detection of human grasp intent is the identification of dynamic EMG from hand movements. Previous studies predominantly implemented the steady-state EMG classification with a small number of grasp patterns in dynamic situations, which are insufficient to generate differentiated control regarding the variation of muscular activity in practice. In order to better detect dynamic movements, more EMG variability could be integrated into the model. However, only limited research was conducted on such detection of dynamic grasp motions, and most existing assessments on non-static EMG classification either require supervised ground-truth timestamps of the movement status or only contain limited kinematic variations. In this study, we propose a framework for classifying dynamic EMG signals into gestures and examine the impact of different movement phases, using an unsupervised method to segment and label the action transitions. We collected and utilized data from large gesture vocabularies with multiple dynamic actions to encode the transitions from one grasp intent to another based on natural sequences of human grasp movements. The classifier for identifying the gesture label was constructed afterward based on the dynamic EMG signal, with no supervised annotation of kinematic movements required. Finally, we evaluated the performances of several training strategies using EMG data from different movement phases and explored the information revealed from each phase. All experiments were evaluated in a real-time style with the performance transitions presented over time.

Risk Evaluation of Navigation Environment Based on Dynamic Weight Model and Its Application

In order to scientifically and reasonably evaluate the safety risk of ship navigation, to and better solve the problems of the poor sensitivity of static evaluation and insufficient ability to grasp the overall dynamic situation, in this paper, representative safety evaluation indexes for ship navigation are screened and the initial weight of each index is confirmed in combination with the improved analytic hierarchy process (IAHP), in order to learn the changes of navigation environment and accident samples in the waters in the jurisdiction. Finally, the dynamic risk evaluation is carried out by constructing a dynamic weight evaluation model for the safety risk of the navigation environment based on the weight fusion of subjective and objective impact factors. The waters under the jurisdiction of Sanya, China were selected for the study, and the navigation risk of the waters in the jurisdiction was calculated by using the dynamic weight evaluation model based on navigation risk. The calculation results are highly consistent with the results based on the statistics of historical accidents and the analysis of the characteristics of the navigation environment in the jurisdiction. The navigation risk in this water area is the greatest from May to September every year. The dynamic weight evaluation model can not only overcome the subjective evaluation distortion in the traditional risk evaluation theory of navigation environment in practical applications, but can also provide a scientific theoretical basis for the dynamic evaluation and early warning of the risk of ship navigation environments through continuous sample learning.

The Aspectual Meaning of Non-Aspectual Constructions

The distinction between perfective and imperfective aspect has been identified in many languages across the world. This paper shows that even languages that do not have a dedicated perfective—imperfective distinction may endow a verbal construction that is not specifically aspectual with a perfective value. The crucial diagnostic for identifying perfectivity in a given non-aspectual construction is a difference in the temporal interpretation of clauses involving that construction, licensed by the actionality class of the main predicate: while stative verbs have a present interpretation, dynamic verbs yield a non-present (past or future) interpretation. This pattern of interaction is triggered by a phenomenon that has been referred to as the ‘present perfective paradox’, i.e., the impossibility of aligning dynamic situations with the time of speaking while at the same time conceptualizing them in their entirety. The latter type of construal is argued to be the main function of perfective aspect. The range of non-aspectual constructions with underlying perfective semantics includes ‘iamitive’ markers, an evidential, an epistemic supposition marker, a focus marker, a polar question marker, and a declarative marker. These constructions come from typologically different and genetically unrelated languages, illustrating the cross-linguistic salience of the category of perfective aspect.

Modelling restoration of natural flow regimes in dam impaired systems: Biomorphodynamic effects and recovery times

Dams affect the natural flow regime by altering the magnitude, timing and frequency of high and low flows. Many river ecosystems impaired by dams are currently being restored. Restoration success is difficult to quantify and is often assessed by comparing the restored system to an unimpaired static ‘reference’ system. However, restoring a river to past environmental conditions and assessing restoration success by comparing it to a static situation neglects natural system dynamics and non-linear, adaptive system responses. With this modelling study we evaluate long-term changes in river morphology, morphodynamics, riparian vegetation cover and habitat suitability of two fish species and two types of wetland vegetation in a meandering gravel bed river after removal of an upstream dam and complete restoration of the natural flow regime. We assessed the ecological and hydromorphodynamic recovery of systems impaired by two different dam operating regimes and three different time periods the dam was present by comparing these to a dynamic undisturbed situation. Modelling results show that recovery potential depends on how much the system has been changed by the dam and the system state at the start of the restoration, rather than the duration of the pressure. Even if the conditions shortly after restoration are comparable to pre-disturbance conditions, there can still be a time-lag in the system response where the future state of the restored system continues to deviate from the undisturbed situation. When this happens, the system can develop into an alternative dynamic equilibrium where recovery becomes increasingly difficult. These results stress the importance of considering natural variability in restored systems as well as in reference systems, requiring detailed spatio-temporal monitoring to assess restoration effects.

A Review of the Standard of Care Owed to Australian Firefighters from a Safety Perspective—The Differences between Academic Theory and Legal Obligations

Working in high consequence yet low frequency, events Australian fire service Incident Controllers are required to make critical decisions with limited information in time-poor environments, whilst balancing competing priorities and pressures, to successfully solve dynamic large-scale disaster situations involving dozens of personnel within the Incident Management Team, including of front-line responders from multiple jurisdictions. They must also do this within the boundaries of public and political expectations, industrial agreements, and the legal requirement to maintain a safe workplace for all workers, inclusive of volunteers. In addition to these operational objectives, fire services must also provide realistic training to prepare frontline staff, whilst satisfying legislative requirements to provide a safe workplace under legislation that does not distinguish between emergency services and routine business contexts. In order to explore this challenge, in this article we review the different safety standards expected through industrial and legal lenses, and contextualize the results to the firefighting environment in Australia. Whilst an academic argument may be presented that firefighting is a reasonably unique workplace which exposes workers to a higher level of harm than many other workplaces, and that certain levels of firefighter injury and even fatality are acceptable, no exception or distinction is provided for the firefighting context within the relevant safety legislation. Until such time that fire services adopt the legal interpretations and applications and develop true safety management systems as opposed to relying on “dynamic risk assessment” as a defendable position, the ability of fire services and individual Incident Controllers to demonstrate they have managed risk as so far as reasonably practicable will remain ultimately problematic from a legal perspective.

Research on Active Obstacle Avoidance of Intelligent Vehicles Based on Improved Artificial Potential Field Method

In the study of autonomous obstacle avoidance of intelligent vehicles, the traditional artificial potential field method has the problem that the vehicle may fall into the local minima and lead to obstacle avoidance failure. Therefore, this paper improves the traditional potential field function. Based on the vehicle dynamics model, a strategy of jumping out of local minima based on smaller steering angles is proposed. By finding a smaller steering angle and setting a suitable jump out step length, the intelligent vehicle is enabled to jump out of the local minima. Simulation experiments by MATLAB show that the improved method can jump out of the local minima. By comparing the planned trajectories of the traditional method and the improved method in static and dynamic obstacles situations, the trajectory planned by the improved method is smooth and the curvature is smaller. The planned trajectory is tracked by the Carsim platform, and the test results show that the improved method reduces the front steering wheel angle while the intelligent vehicle satisfies the vehicle dynamics constraints during active obstacle avoidance, which verifies the stability and rationality of the improved method.

Control of COVID-19 Outbreaks under Stochastic Community Dynamics, Bimodality, or Limited Vaccination.

Reaching population immunity against COVID‐19 is proving difficult even in countries with high vaccination levels. Thus, it is critical to identify limits of control and effective measures against future outbreaks. The effects of nonpharmaceutical interventions (NPIs) and vaccination strategies are analyzed with a detailed community‐specific agent‐based model (ABM). The authors demonstrate that the threshold for population immunity is not a unique number, but depends on the vaccination strategy. Prioritizing highly interactive people diminishes the risk for an infection wave, while prioritizing the elderly minimizes fatalities when vaccinations are low. Control over COVID‐19 outbreaks requires adaptive combination of NPIs and targeted vaccination, exemplified for Germany for January–September 2021. Bimodality emerges from the heterogeneity and stochasticity of community‐specific human–human interactions and infection networks, which can render the effects of limited NPIs uncertain. The authors' simulation platform can process and analyze dynamic COVID‐19 epidemiological situations in diverse communities worldwide to predict pathways to population immunity even with limited vaccination.

Dynamic Routing Algorithm for Hazmat Transportation Problems

After a series of gas pipeline explosions in Kaohsiung City, Taiwan, in 2014, the Environmental Protection Administration (EPA) issued regulations in 2017 requiring all chemical tank trucks to be equipped with GPS for real-time monitoring and control. Hazmat transportation problems, along with solution algorithms and applications, have been studied extensively. However, most of the research has focused on the route planning level. Dynamic characteristics should be incorporated to reflect possible dynamic traffic situations with more advanced information and communication capabilities for chemical tank trucks. This research formulates a bi-objective dynamic model and proposes a solution algorithm based on a genetic algorithm (GA) for dynamic hazmat route optimization. A dynamic bi-objective model, including transportation cost and risk, is developed to reflect time-varying traffic conditions. Dynamic traffic characteristics are reflected through traffic volume and travel time, simulated from simulation models. Numerical experiments are conducted in the Kaohsiung City network. The results show that dynamic routes for hazmat transportation vary with respect to traffic flow conditions. The discussions of this research are expected to provide some insights into policy implications.

Tunable topological edge states and rainbow trapping in two dimensional magnetoelastic phononic crystal plates based on an external magnetostatic field

The elastic analogs of topological insulators (TIs) have attracted substantial research interest owing to their potential prospects in wave manipulation and low-loss transmission. However, most work in solid phononic crystal (PC) systems suffering from fixed-structure restrictions lack the active tunability of topological edge states, hindering their practical applications in dynamic situations. Here, we present a new design of tunable elastic TIs made up of smart magnetostrictive materials and perforated silicon plates. The topological phase transition is induced by altering the spatial intensity distribution of external magnetostatic field. Placing two topologically distinct magnetoelastic PC plates adjacent to each other, the pseudospin-Hall edge modes for plate-mode waves are obtained at the interface between them. Moreover, the reconfigurable propagation route and topological robustness of edge states are demonstrated by numerical simulations. Finally, the frequency and group velocity of edge modes can be continuously adjusted by an interfacial magnetic field. Utilizing such a contactless tunability, a reconfigurable topological rainbow is attained by reconstructing the gradient-descent interfacial magnetic field along the topological interface. The proposed system with magnetically tunable edge states can become a stepping-stone platform towards the designs of elastic wave devices with more applicability for dynamic conditions, such as waveguides, energy harvesters and buffers.

Traffic Dataset for Dynamic Routing Algorithm in Traffic Simulation

The purpose of this research is to create a simulated environment for teaching algorithms, big data processing, and machine learning. The environment is similar to Google Maps, with the capacity of finding the fastest path between two points in dynamic traffic situations. However, the system is significantly simplified for educational purposes. Students can choose different traffic patterns and program a car to navigate through the traffic dynamically based on the changing traffic. The environments used in the project are VIPLE (Visual IoT/Robotics Programming Language Environment) and a traffic simulator developed in the Unity game engine. This paper focuses on creating realistic traffic data for the traffic simulator and implementing dynamic routing algorithms in VIPLE. The traffic data is generated from the recorded real traffic data published on the Arizona Maricopa County website. Based on the generated traffic data, VIPLE programs are developed to implement the traffic simulation with support for dynamic changing data.

Sustainable structural, morphological and magnetic properties of MgFe2O4 nanoparticles under dynamic shock wave exposure

In this article, the authors have explored the changes caused in structural, morphological and magnetic properties of magnesium ferrite nanoparticles (MgFe2O4 NPs) under dynamic shock wave exposure situations. Interestingly, the observed XRD and VSM results reveal that the MgFe2O4 NPs have outstanding crystallographic and magnetic phase stability against the impact of shock waves and found that the title NPs are having higher shock resistance than other potential materials such as TiO2, Co3O4 and ZnFe2O4 NPs.

The field of expertise modulates the time course of neural processes associated with inhibitory control in a sport decision-making task

Inhibitory control (IC), the ability to suppress inappropriate actions, can be improved by regularly facing complex and dynamic situations requiring flexible behaviors, such as in the context of intensive sport practice. However, researchers have not clearly determined whether and how this improvement in IC transfers to ecological and nonecological computer-based tasks. We explored the spatiotemporal dynamics of changes in the brain activity of three groups of athletes performing sport-nonspecific and sport-specific Go/NoGo tasks with video footages of table tennis situations to address this question. We compared table tennis players (n = 20), basketball players (n = 20) and endurance athletes (n = 17) to identify how years of practicing a sport in an unpredictable versus predictable environment shape the IC brain networks and increase the transfer effects to untrained tasks. Overall, the table tennis group responded faster than the two other groups in both Go/NoGo tasks. The electrical neuroimaging analyses performed in the sport-specific Go/NoGo task revealed that this faster response time was supported by an early engagement of brain structures related to decision-making processes in a time window where inhibition processes typically occur. Our collective findings have relevant applied perspectives, as they highlight the importance of designing more ecological domain-related tasks to effectively capture the complex decision-making processes acquired in real-life situations. Finally, the limited effects from sport practice to laboratory-based tasks found in this study question the utility of cognitive training intervention, whose effects would remain specific to the practice environment.