Dynamic Situations Research Articles

Two inconsistent rounds of feedback enhance the framing effect: Coding two consecutive outcome evaluations

Previous experience often guides people's decision-making. How the corresponding consecutive outcomes in the gain-loss frame modulate feedback evaluation in dynamic situations remains unclear. In this study, we used event-related potentials (ERPs) with a Balloon Analogue Risk Task (BART) to investigate the effect of the consistency with previous feedback on current choices under the gain-loss frame and the neural mechanism by coding ERP signals evoked by consecutive outcomes among adults (N = 42). Results indicated that the framing effect on feedback-related negativity (FRN) amplitudes following current feedback in decision-making was insensitive to prior feedback. In contrast, the P300 amplitudes following two inconsistent consecutive rounds of feedback were greater than that following two consistent consecutive rounds of feedback in the gain frame, while this effect was absent in the loss frame, revealing a more significant valance-framing effect. These findings demonstrate that two inconsistent rounds of feedback enhance the framing effect, and suggest that the framing effect is sensitive to prior feedback in a late cognitive appraisal stage in decision-making under uncertainty, rather than in an early feedback processing stage. The present study provides novel insights into how consecutive outcomes in the gain-loss frame modulate feedback evaluation in dynamic situations.

The Role of Artificial Lighting in Achieving Dynamism in Commercial Building

Human interest in building design has become general, including the design of artificial lighting for building facades. Therefore, in the priorities of many owners and designers. Commercial buildings are always looking for different means that contribute to improving the process of displaying products and providing the right environment to attract customers. This paper investigates the role of artificial lighting in architectural aspects. So, the objectives of the research are to evaluate the properties of artificial lighting, and its role in the formation of the building facade elements during the night, in order to make the building successful in terms of form and function (reviving architecture at night). The research problem arises in the lack of interest in applying the role of artificial lighting properties such as (intensity, beam angle, and color) in studying the dynamic state of the commercial building facade elements (line, shape, and texture). A hypothesis should be formed: If the characteristics of artificial lighting are adjusted, it will have an effect on achieving the dynamic state of the elements of the commercial building facade. The results determined the role and effects of artificial lighting properties on the dynamic situation, such as the elements forming the facades of commercial buildings during the night period.

Continuum-Body-Pose Estimation From Partial Sensor Information Using Recurrent Neural Networks

Soft continuum arms have significant potential for use in various applications due to their extremely high degrees of freedom. For example, these soft arms can be used for grasping and manipulating fragile materials in the deep sea or carrying a human to rescue in unstructured environments. However, in these situations, the environment is often dark and visual cues are not always usable. Therefore, these arms must estimate their pose from proprioceptive sensors to control their behavior and execute their tasks in dark places. Estimating the pose in a dynamic situation is still challenging because of the arms' high dimensionality and the complex structural changes in the body shape. Therefore, this study demonstrates a novel method for estimating the pose of proprioceptive bending sensors using recurrent neural networks (RNNs). In particular, an RNN framework known as deep reservoir computing was used for this purpose. Results from experiments using an octopus-inspired soft robotic arm clearly indicate that the proposed method significantly outperforms existing methods using long short-term memory models or linear models. We expect that our proposed method will enable behavioral control of these arms in dark places such as the deep sea, space, and inside the human body in future applications.

Investigation of Creeping Wave Characteristics Using Cross-Slot Antenna on 12-Cylinder Phantom Model

This letter presents the systematic study of the EM wave propagation in on to on-body involving the 12-cylinder phantom model, which aids in static as well as dynamic system modeling using systematic simulation and experimental measurements. The 12-cylinder phantom model is a simplified human body model featuring the critical parts of human body. For the study of on-to on-body transmission characteristics two cross-slot antennas having omnidirectional radiation pattern are used. An in-depth investigation of creeping waves and double arm swing activity using the 12-cylinder model under different configurations and dynamic situations are executed with transmission characteristics.

Top 5 bovine emergencies - solved!

Veterinarians face dynamic and changing situations daily as a matter of routine, but life-threatening emergencies on large animals can really take a toll, especially to the new graduate. Here, we will cover five common emergencies presented to bo¬vine veterinarians: bloat, down cow, dystocia, uterine prolapse, and the down neonate.

Communicating Uncertainty Information in a Dynamic Decision Environment

Abstract The likelihood of threatening events is often simplified for members of the public and presented as risk categories such as the “watches” and “warnings” currently issued by National Weather Service in the United States. However, research (e.g., Joslyn and LeClerc) suggests that explicit numeric uncertainty information—for example, 30%—improves people’s understanding as well as their decisions. Whether this benefit extends to dynamic situations in which users must process multiple forecast updates is as yet unknown. It may be that other likelihood expressions, such as color coding, are required under those circumstances. The experimental study reported here compared the effect of the categorical expressions “watches” and “warnings” with both color-coded and numeric percent chance expressions of the likelihood of a tornado in a situation with multiple updates. Participants decided whether and when to take shelter to protect themselves from a tornado on each of 40 trials, each with seven updated tornado forecasts. Understanding, decision quality, and trust were highest in conditions that provided percent chance information. Color-coded likelihood information inspired the least trust and led to the greatest overestimation of likelihood and confusion with severity information of all expressions.

Operating Surplus and its Importance in Financing Local Government Tasks on the Example of Municipalities of the Małopolskie Voivodeship

The operating surplus is a positive subtraction result of the revenue and current expenditures of a local government units. The level of operating surplus determines the scope and quality of task implementation, as well as investment and development opportunities of a local government unit. In periods of economic slowdown, the surplus can serve as a kind of buffer and guarantee for the continuous and effective functioning of a local government unit. The aim of the research was to assess the operating surplus and the ability to perform local government tasks based on the balance of current revenue and expenditure in the current economic conditions. The analysis was carried out on the example of the municipalities of the Małopolskie Voivodeship in Poland, and the research period covered the years 2014-2021. According to the conducted research, the most dynamic situation in the operating surplus development took place in urban municipalities. These municipalities maintained the highest average level of operating surplus, but it was characterized by large fluctuations, e.g. in 2020 due to the Covid-19 pandemic. This may result from the fact of high budget revenues and the widest range of obligatory tasks, as well as from the sensitivity to economic changes of budget revenues that are significant in cities. As a consequence, the implementation of tasks in a continuous manner and at a constant level of quality in periods of downturn may be at risk in the case of these cities, and the lower level of operating surplus may force these local governments to incur liabilities.

Hardware Implementation of Attitude Estimation Methods Using Multiple GPS Receivers

This paper deals with the attitude estimation issue for navigation of Unmanned Aerial Vehicles (UAVs). We propose a new multi-GPS sensor fusion, based on Extended Kalman Filter (EKF) and Smooth Variable Structure Filter (SVSF), using an Inertial Measurement Unit (IMU) and three GPS receivers. Two methods; the Direct Computing Method (DCM) and the Least Square Method (LSM) are used to estimate the full attitude of the UAV. Performance and robustness are tested with numerical simulation. Experimental validation is carried out on fixed-wing aircraft to evaluate the capabilities of the proposed approaches in attitude estimation. Through this framework, it is proven that subdegrees order of estimation error can be guaranteed when real dynamic situations are applied to the aircraft.

Can Risk Aversion Survive the Long Run?

AbstractCan it be rational to be risk-averse? It seems plausible that the answer is yes—that normative decision theory should accommodate risk aversion. But there is a seemingly compelling class of arguments against our most promising methods of doing so. These long-run arguments point out that, in practice, each decision an agent makes is just one in a very long sequence of such decisions. Given this form of dynamic choice situation and the (Strong) Law of Large Numbers, they conclude that those theories which accommodate risk aversion end up delivering the same verdicts as risk-neutral theories in nearly all practical cases. If so, why not just accept a simpler, risk-neutral theory? The resulting practical verdicts seem to be much the same. In this paper, I show that these arguments do not in fact condemn those risk-aversion-accommodating theories. Risk aversion can indeed survive in the long run.

Relations between entrepreneur's social identity and strategic entrepreneurship: Sustainable leadership as mediator.

Although there are studies verifying that strategic entrepreneurship is positively related to the risk resistance and performance of enterprises, it is unclear how enterprises can implement effective strategic entrepreneurial activities in dynamic situations. This research aims to explore why and how the entrepreneur’s social identity influences and drives firm’s strategic entrepreneurial activities. In this study, it applied case study method to interview a technology-based family firms that have effectively conducted strategic entrepreneurial activities to meet challenges, and uses grounded theory for data analysis. The research finds that (1) the social identity of entrepreneurs actively promotes the strategic entrepreneurial activities of enterprises; (2) sustainable leadership mediates the relationship between social identity and strategic entrepreneurship; (3) at different stages of enterprise development, entrepreneurs dynamically adjust their social identity types to enhance sustainable leadership; (4) through the focus and extension of technological advantages, sustainable leadership ensures that enterprises can promote the implementation of strategic entrepreneurial behavior by disintegrating and integrating the value chain. This study explores the strategic entrepreneurship path of family firms and also provides new insights for future research on the strategic entrepreneurship and sustainable growth of such firms.

Enhanced Second-Order Sliding Mode Control Technique for a Five-Phase Induction Motor

Recently, several research papers have addressed multiphase induction motor (IM) drives, owing to their several benefits compared to the three-phase motors, including increasing the torque pulsations frequency and reducing the rotor harmonic current losses. Thus, designing a robust controller to ensure the proper operation of such motors became a challenge. The present study reports the design of an effective second-order sliding mode control (SO-SMC) approach for a five-phase IM drive. The proposed control approach finds its strongest justification for the problem of using a law of nonlinear control robust to the system uncertainties of the model without affecting the system’s simplicity. The formulation of the proposed SO-SMC approach is a prescribed process to ensure the stability and proper dynamics of the five-phase IM. A detailed stability analysis is also presented for this purpose. To validate the effectiveness of the proposed controller, the five-phase IM drive is tested under different dynamic situations, including load changes and system uncertainties. The presented numerical results prove the ability of the designed SO-SMC to handle high system nonlinearities and maintain high robustness against uncertainties.

Conceptualizing and Measuring Megacity Resilience with an Integrated Approach: The Case of China

Megacities play an essential role in social interaction and relationship formation. There is a need for megacity resilience to achieve both safety and sustainability. This paper set out to develop a contextualized conceptual framework and an applied megacity resilience comprehensive index (MRCI). The study provides a multi-model named the technique for order preference by similarity to ideal solution (TOPSIS), extending the criteria importance through inter-criteria correlation and entropy (CRITIC-Entropy) weight and introducing the time-ordered weighted averaging (TOWA) to a dynamic situation. The results show that, while the performance of resilience in Nanjing was the highest, the growth ratio of resilience in Zhengzhou was the fastest. In addition, a coupling relationship of pressure, state, and response resilience was verified, and response resilience was more correlated and showed similar trends with the MRCI. The findings indicate that response resilience is still an obstacle factor in the criterion layer in Dalian. Moreover, identified key obstacle factors in the index layer may differ by district or functional zones and need to improve unified and point to area operation. Issues around resilient culture and citizenship were found to be common. Improving public service in Zhengzhou, enhancing support for applied research in Nanjing, and optimizing the ecological industry layout in Dalian were identified as key focuses. This study should be of value for similar megacities in developed or developing countries to improve their resilience.

Intelligent Robotics to Boost Collaboration Between People and Devices and Helping Robots to Adapt to Dynamic Situations and Communicate Naturally with People

Enhancement of collaboration with the aid of intelligent robotics and building efficient communication between people and devices presents a larger-scale advantage for practical application. The paper aims at exploring the capacity of intelligent robots to boost collaboration between people and devices and help robots to adapt to dynamic situations and communicate naturally with people. The paper adopts a deductive and qualitative methodology to conduct an empirical study on the topic. The paper elaborates on the use of 3D estimations and the usage of deep learning for pattern recognition to enhance natural communication between robots and humans. The challenges regarding coherence, swiftness and accuracy are also discussed, illustrating the necessity to build a deep neural network that can accommodate the features of intelligent robotics. Therefore, the possibility of enhancing collaboration through the establishment of response patterns that can create effective and communicative relationships between people and devices is present with the help of intelligent robotics. Keywords : AI, collaboration, communication, deep learning, human-robot interactions, intelligent robotics.

Clear-sky spectral radiance modeling under variable aerosol conditions

The distribution of diffuse radiance over the sky hemisphere is an important quantity that is required in many applications. Its spectral variation is useful when considering processes having a spectral dependence, such as photovoltaics (PV). Here, a clear-sky spectral radiance model is developed from radiative transfer theory, using appropriate parameterizations to make the model suitable for rapid engineering-type calculations. The phase function of various aerosol mixtures combines three conventional Henyey-Greenstein functions. This procedure provides an effective solution to the problem of modeling the strong radiance within the circumsolar region, while being also accurate in low-energy areas of the clear sky. The dependence on wavelength of the coefficients of the simplified phase functions is efficiently described by polynomial ratios. The radiance is shown to vary from a relatively isotropic distribution in the UV to a very anisotropic one over the rest of the solar spectrum. The radiance model can be used to describe either ideal atmospheric situations or dynamic situations, for which the hourly outputs from the MERRA-2 reanalysis provide the optical properties of the aerosol mixture at any location. Examples of ideal radiance distributions include those corresponding to the reference spectra used for the performance characterization of PV cells. By integrating the modeled radiance over all wavelengths with appropriate weighting, both the broadband radiance and luminance can be derived. Although these two distributions are generally not identical, they are found sufficiently close, even under hazy conditions, to make them interchangeable in practice, within reasonable error limits. Compared to common empirical luminance distributions of the literature, the model appears more universal, because responsive to strong changes in aerosol composition.

Option-Based Multi-Agent Reinforcement Learning for Painting With Multiple Large-Sized Robots

To ensure an efficient and conflict-free task allocation, this paper presents an option-based multi-agent reinforcement learning (OMARL) method for a cooperative multi-station multi-robot system in aircraft painting application. The problem can be described as a fully-connected graph, whose nodes and edges represent stations and trajectories between stations, respectively. The aim is to minimize the maximum execution time of conflict-free aircraft painting with multiple robots. Traditional methods cannot handle mutual collision avoidance well when robots are in large size. Therefore, this work solved the planning problem with multi-agent reinforcement learning algorithm based on option framework. The moving trajectories were pre-planned by a simplified 2D A* algorithm, which is fast and reduces rotations. The agents would finish the whole task with less time, and potential collisions were punished at every time step. Hierarchical option-based model with shared network parameters greatly reduced the complexity of training for painting planning scenarios. A fuzzy clustering method was introduced, and the clustering scores of stations would contribute to greedy agents. Comparisons were made on static and dynamic situations among several planning methods. OMARL can give optimal schedules as well as, or better than the most efficient traditional method does. Furthermore, OMARL can provide satisfactory adjustments in real time when practical process is different from plan or there is one broken robot. In contrast, traditional methods take lots of time to recalculate the plan. The results indicate that OMARL can achieve better performance in multi-station multi-robot task allocation when the collision between robots cannot be ignored.

Formation of management and technological maturity levels of enterprises for their dynamic development

Abstract Currently, the market environment contains many factors influencing the enterprise’s competitiveness. Instability, the unpredictability of events, and insufficiently effective functioning of market mechanisms alter the management focus and processes engaged in an enterprise’s functioning. Some of them are intensive in terms of required resources and finance. Such a dynamic situation requires the enterprise management to build innovative solutions to flexibly respond and timely adapt to change. Therefore, this study aims to develop theoretical and applied approaches to determining the level of managerial and technological maturity of the basic set of technologies implemented in enterprises. In the context of this issue’s development and aiming to achieve the purpose, the study proposed a model approach where the introduction of individual technologies allows combining the rules for determining the enterprise’s management and the technological maturity level, i.e., its readiness for such changes. The construction of the model was based on the analysis and calculation of statistical data from four groups of technologies (corporate, industrial, decision support, and information technologies, which are divided into subclasses) and based on the theory of dynamic innovation development. The results were tested at seven food industry enterprises in Ukraine. Based on the study, the actual level of managerial and technological maturity of enterprises was determined, creating one complex set of technologies that depend on the level and structural changes in management and the level of technological maturity of enterprises. It can be used as a typical model for differently sized enterprises representing various industries.

Analysis of activated colloidal crud in advanced and modular reactor under pump coastdown with kinetic corrosion

The analysis of rapid flow transients in Reactor Coolant Pumps (RCP) is essential for a reactor safety study. An accurate and precise analysis of the RCP coastdown is necessary for the reactor design. The coastdown of RCP affects the coolant temperature and the colloidal crud in the primary coolant. A realistic and kinetic model has been used to investigate the behavior of activated colloidal crud in the primary coolant and steam generator that solves the pump speed analytically. The analytic solution of the non-dimensional flow rate has been determined by the energy ratio β. The kinetic energy of the coolant fluid and the kinetic energy stored in the rotating parts of a pump are two essential parameters in the form of β. Under normal operation, the pump's speed and moment of inertia are constant. However, in a coastdown situation, kinetic damping in the interval has been implemented. A dynamic model ACCP-SMART has been developed for System Integrated Modular and Advanced Reactor (SMART) to investigate the corrosion due to activated colloidal crud. The Fickian diffusion model has been implemented as the reference corrosion model for the constituent component of the primary loop of the SMART reactor. The activated colloidal crud activity in the primary coolant and steam generator of the SMART reactor has been studied for different equilibrium corrosion rates, linear increase in corrosion rate, and dynamic RCP coastdown situation energy ratio β. The coolant specific activity of SMART reactor equilibrium corrosion (4.0 mg s−1) has been found 9.63 × 10−3 μCi cm−3, 3.53 × 10−3 μC cm−3, 2.39 × 10−2 μC cm−3, 8.10 × 10−3 μC cm−3, 6.77 × 10−3 μC cm−3, 4.95 × 10−4 μC cm−3, 1.19 × 10−3 μC cm−3, and 7.87 × 10−4 μC cm−3 for 24Na, 54Mn, 56Mn, 59Fe, 58Co, 60Co, 99Mo, and 51Cr which are 14.95%, 5.48%, 37.08%, 12.57%, 10.51%, 0.77%, 18.50%, and 0.12% respectively. For linear and exponential coastdown with a constant corrosion rate, the total coolant and steam generator activity approaches a higher saturation value than the normal values. The coolant and steam generator activity changes considerably with kinetic corrosion rate, equilibrium corrosion, growth of corrosion rate (ΔC/Δt), and RCP coastdown situations. The effect of the RCP coastdown on the specific activity of the steam generators is smeared by linearly rising corrosion rates, equilibrium corrosion, and rapid coasting down of the RCP. However, the time taken to reach the saturation activity is also influenced by the slope of corrosion rate, coastdown situation, equilibrium corrosion rate, and energy ratio β.

Design of a novel micro‐Zone adaptive Energy‐Trust evaluation Active On‐Demand Vector protocol to optimize communication in challenging and attacked mobile network

SummaryHigh congestion, mobility, and energy restrictions are the critical challenges to mobile networks. The conventional routing protocols are unable to ensure effective and reliable communication in such dynamic and unpredictable situations. In this paper, a novel micro‐Zone adaptive Energy‐Trust evaluation Active On‐Demand Vector (mZ‐ETAODV) protocol is designed to provide routing solutions in extreme conditions. In this work, the complete network is divided into smaller zones of nxn. The extreme zone position‐based evaluation is conducted to handle the stability and to identify the next intermediate node. The zone‐covered neighbors are further computed under energy and trust measures to identify the most reliable neighbor. The proposed protocol is simulated under high mobility, congestion and man‐in‐middle attack situations. The analytical observations are recorded in terms of Packet Delivery Ratio (PDR) ratio, energy consumption, delay and communication loss parameters. The comparative results are generated against AODV, SAODV, PSAODV, PDS‐AODV, NVS‐AODV, iNVS‐AODV, Tripathy et al., DFMCRP, FBSSR, MBDP‐AODV, AGHA, and Singh et al. protocols. The experimentation is conducted in a highly challenging mobile network with high congestion, high mobility, energy restriction, existence of blackhole, grayhole, DDOS, and mixed attacks. These attacks are performed with 0% to 10% density, and analysis is conducted against PDR ratio, communication delay, route switching, dead node count, remaining energy, and attack detection rate measures. The analysis results identified that the proposed protocol reduced the communication delay and energy consumption and achieved significant gain in attack detection rate, network life and PDR ratio.

Dynamic Immune Profile in French Toxoplasmosis Patients.

Toxoplasma gondii infection is usually benign in Europe due to the strong predominance of type II strains. Few studies have been conducted to examine the immunological course of infection in humans and have yielded conflicting results, maybe influenced by heterogeneous parasite strains. We measured 23 immune mediators in 39, 40, and 29 sera of French noninfected, acutely infected, and chronically infected immunocompetent pregnant women, respectively. Four different cytokine patterns were identified regarding their dynamics through infection phases. For 11 of the cytokines (IFN-β, IFN-γ, IL-4, IL5, IL-6, IL-10, IL-12, IL-15, CXCL9, CCL2, and CSF2) the serum levels were significantly elevated during acute infection. The inflammatory mediators IL-1β, IL-17A, IL-18, TNF-α, and CSF3 remained unchanged during acute infection, while they were significantly lower in chronically infected compared to noninfected patients. As for the anti-inflammatory cytokines TGF-β and CCL5, their levels remained significantly elevated during chronic infection. We also observed a significant negative correlation of several cytokine concentrations with IgG levels, indicating a rapid decline of serum concentrations during the acute phase. These results indicate an anti-inflammatory pattern in chronically infected patients in a type II dominated setting and demonstrate the highly dynamic immune situation during acute infection.

Dynamic leader role modeling for self‐organizing crowd evacuation simulation

AbstractThe role of the leader in the self‐organizing crowd has a significant influence on the crowd evacuation when an emergency occurs. However, current crowd evacuation models either ignore the leadership characteristics of pedestrians or predefine an invariable leader identity. This article clearly distinguishes leaders from followers in a crowd and evaluates the impact of the leader's role on crowd evacuation under dynamic situations. First, the leadership model of the pedestrian is built based on the classic OCEAN personality parameters. Social dominance tendency is measured for more credibility. Then, the dynamic leader role model (DLRM) is proposed to describe the relationship between leaders and followers, considering the interaction among pedestrians during the evacuation. Finally, a novel crowd simulation algorithm based on the above DLRM is presented using the extended social force model. Various experiments in several typical scenarios verified that our proposed simulation model has better realism.