Dynamic Situations Research Articles

Communicative Language Teaching (CLT) in Improving Speaking Skills of Tertiary Level EFL Students of Bangladesh

In the English as a Foreign Language (EFL) context, students must be given a proper foundation of communication skills necessary in various dynamic real-world situations. This study investigates learner perception of the effectiveness of Communicative Language Teaching (CLT) in improving the speaking skills of tertiary-level EFL students in Bangladesh. A mixed-methods approach was used to collect and analyze data from 30 students, of different private universities of Bangladesh. The data was gathered by analyzing the results from the survey. The results of the study showed there was a statistically significant improvement in the speaking skills of EFL students after the CLT intervention. The students demonstrated an increase in fluency and complexity in their speaking performance. Furthermore, findings revealed that the students had positive perceptions of CLT and found it effective in enhancing their speaking skills. The findings of this study provide valuable insights into the benefits of using CLT as a teaching method in EFL environments. This suggests the importance of incorporating communicative and interactive activities in language classrooms to promote language learning and student engagement.

Investigation of methyl radical with methane and methanol reactions in the framework of a non-equilibrium approach; dynamic aspect

Within the framework of the non-equilibrium approach, the thermal rate constants of the methyl radical with methane (reaction (1)) and CH and OH bonds of methanol (respectively, reactions (2) and (3)) were calculated in the experimental temperature range: 450–800 K for reaction 1 and 350 – 550 K for reactions (2) and (3); geometry optimization level B3LYP/6-31+G**, SP calculation levels CСSD(T)/6-311++G** for reaction (1) and CСSD(T)/6-311G** for reactions 2 and 3.The analysis of the obtained results demonstrates differences in the dynamics of the H-atom transition. The possibility of describing the dynamic situation in terms of the tunneling time of the H atom and the half-life of the umbrella oscillation of the methyl radical is discussed.

Improving Teachers’ Professional Vision Through a Video-based Reflection Program: A Case Study in Mexican Primary Schools

Enhancing teachers’ professional vision (TPV) may contribute to increasing the quality of teaching-learning processes through higher perceived efficacy, leading to autonomy-supportive environment. This is of particular importance in Physical Education (PE), due to the fact that this subject presents different challenges and more dynamic situations compared to others. One of the latest approaches for enhancing TPV is video-based reflection, which allows teachers to observe recorded lessons and analyze them. The aim of this research was to test the effect of a video-based reflection program on TPV in PE. Two teachers participated in a 3-step video-analysis program consisting of self-reflection, peer reflection, and expert feedback. Notable changes were found in TPV at the end of the 6-month intervention, both in terms of teachers’ selective attention to classroom events and their knowledge-based reasoning. Our findings suggest that video-based reflection programs could represent an important part of any teacher training program aiming to increasing PE teachers’ responsiveness to diverse in-class situations.

Hierarchical online automated planning for a flexible manufacturing system

Task planning and action planning for workshop machines are essential for modern manufacturing. Traditionally, these two problems are solved independently with elaborate manual methods. However, personalized customization introduces more dynamic exogenous events into the manufacturing system, and it is then impossible to consider all possible dynamic scenarios manually. This paper focuses on online automated planning, generating new plans automatically in response to new dynamic situations. We first formulate the planning problem for a flexible manufacturing system as a fully observable nondeterministic planning problem. Second, a hierarchical automated online planning approach is presented. Finally, the effectiveness of the proposed approach is verified by an ARIAC 2022 competition environment.

A Hybrid Preference Interaction Mechanism for Multi-Satellite Imaging Dynamic Mission Planning

The existing multi-satellite dynamic mission planning system hardly satisfies the requirements of fast response time and high mission benefit in highly dynamic situations. In the meantime, a reasonable decision-maker preference mechanism is an additional challenge for multi-satellite imaging dynamic mission planning based on user preferences (MSDMPUP). Therefore, this study proposes the hybrid preference interaction mechanism and knowledge transfer strategy for the multi-objective evolutionary algorithm (HPIM–KTSMOEA). Firstly, an MSDMPUP model based on a task rolling window is constructed to achieve timely updating of the target task importance degree through the simultaneous application of periodic triggering and event triggering methods. Secondly, the hybrid preference interaction mechanism is constructed to plan according to the satellite controller’s preference-based commands in different phases of the optimal search of the mission planning scheme to effectively respond to the dynamic changes in the environment. Finally, a knowledge transfer strategy for the multi-objective evolutionary algorithm is proposed to accelerate population convergence in new environments based on knowledge transfer according to environmental variability. Simulation experiments verify the effectiveness and stability of the method in processing MSDMPUP. This study found that the HPIM–KTSMOEA algorithm has high task benefit, short response time, and high task completion when processing MSDMPUP.

Dynamic Validation of Calibration Accuracy and Structural Robustness of a Multi-Sensor Mobile Robot.

For mobile robots, the high-precision integrated calibration and structural robustness of multi-sensor systems are important prerequisites for ensuring healthy operations in the later stage. Currently, there is no well-established validation method for the calibration accuracy and structural robustness of multi-sensor systems, especially for dynamic traveling situations. This paper presents a novel validation method for the calibration accuracy and structural robustness of a multi-sensor mobile robot. The method employs a ground-object-air cooperation mechanism, termed the "ground surface simulation field (GSSF)-mobile robot -photoelectric transmitter station (PTS)". Firstly, a static high-precision GSSF is established with the true north datum as a unified reference. Secondly, a rotatable synchronous tracking system (PTS) is assembled to conduct real-time pose measurements for a mobile vehicle. The relationship between each sensor and the vehicle body is utilized to measure the dynamic pose of each sensor. Finally, the calibration accuracy and structural robustness of the sensors are dynamically evaluated. In this context, epipolar line alignment is employed to assess the accuracy of the evaluation of relative orientation calibration of binocular cameras. Point cloud projection and superposition are utilized to realize the evaluation of absolute calibration accuracy and structural robustness of individual sensors, including the navigation camera (Navcam), hazard avoidance camera (Hazcam), multispectral camera, time-of-flight depth camera (TOF), and light detection and ranging (LiDAR), with respect to the vehicle body. The experimental results demonstrate that the proposed method offers a reliable means of dynamic validation for the testing phase of a mobile robot.

Holocene alluvial dynamics, soil erosion and settlement in the uplands of Macedonia (Greece): New geoarchaeological insights from Xerolakkos in Grevena

This paper addresses the interplay between Holocene landscape evolution and human settlement dynamics, drawing new evidence from the alluvial history of Xerolakkos, a continental stream in Grevena (Western Macedonia, Greece). We developed an integrated geoarchaeological survey combining remote sensing geomorphological mapping, litho-stratigraphic analysis and radiocarbon dating with the site evidence of a new archaeological survey. Results revealed four major alluviation phases, corresponding to 1) the beginning of the Holocene until the Early Neolithic (∼6300/6200 BCE), 2) the end of the Early and the Middle Neolithic (∼6000–5400 BCE), 3) from the Middle Bronze Age to the Late Roman period (∼1800 BCE – 500 CE), and 4) during the Byzantine and Ottoman eras (∼500–1800 CE), all separated by phases of floodplain incision. Furthermore, the effects of several Holocene Rapid Climatic Changes (RCC) are traced and discussed together with potential human responses; we also provide the first alluvial sequence recording the ∼6200 BCE (8.2 kyr BP) event in the Balkans. While the climate and the local geomorphological setting are considered the primary drivers behind instability and erosion during the Early and Middle Holocene, a landscape change starting in the Middle Bronze Age (after ∼1800 BCE) followed by a re-organisation of the rural economy in the Roman period suggests the increasing involvement of anthropogenic forcing which, by the Ottoman period, evolved into a dynamic situation between climatic variability and adaptive land management. Finally, we demonstrate how soil erosion in the upper catchment constitutes a serious taphonomic bias when studying the regional archaeological record.

Numerical investigation of the effect of perforated almond, tunnel, and bishop shaped pin fin heat sinks on the hydrothermal performance enhancement

The pin-fin design of the heat sink optimizes thermal dissipation by enhancing surface area and enabling efficient heat transfer in high-performance devices. The primary objective of the highly functionalized and convenient heat sink is to provide a competitive advantage in the field of efficient thermal management systems. The primary objective of this study is to investigate various designs of pin-fin heat sinks with unique shapes. These heat sinks are intended to operate in varying dynamic situations and necessitate an efficient convective heat transfer. The current technique has been thoroughly confirmed using earlier research, and computational investigations were conducted to improve the hydrothermal performance of staggered organized pin-fin heat sinks compared to the baseline case adopted from previous studies. Research is underway to examine the collective impact of the fin's unique structure, ideal aerodynamic form, and quality of perforations. A simulation of three-dimensional incompressible flow was conducted using the realizable k- ԑ model to generate turbulence flow that satisfies the relevant boundary conditions for solving the governing equations. When comparing fins shaped like a bishop to the standard hemispherical instance mentioned in recent work, the Nusselt number is 33 % higher. In addition, when the Reynolds number reaches 21,367, the presence of almond-shaped fins with circular perforations leads to a significant reduction in pressure drop, namely by 53.24 %. The almond-shaped hexagonal perforated fins, formed of a copper-diamond composite material, achieved the maximum hydrothermal performance factor (HTPF) of around 1.52 at a Reynolds number of 21,367. These layouts can be considered in various industrial applications.

UAV Multi-Dynamic Target Interception: A Hybrid Intelligent Method Using Deep Reinforcement Learning and Fuzzy Logic

With the rapid development of Artificial Intelligence, AI-enabled Uncrewed Aerial Vehicles have garnered extensive attention since they offer an accessible and cost-effective solution for executing tasks in unknown or complex environments. However, developing secure and effective AI-based algorithms that empower agents to learn, adapt, and make precise decisions in dynamic situations continues to be an intriguing area of study. This paper proposes a hybrid intelligent control framework that integrates an enhanced Soft Actor–Critic method with a fuzzy inference system, incorporating pre-defined expert experience to streamline the learning process. Additionally, several practical algorithms and approaches within this control system are developed. With the synergy of these innovations, the proposed method achieves effective real-time path planning in unpredictable environments under a model-free setting. Crucially, it addresses two significant challenges in RL: dynamic-environment problems and multi-target problems. Diverse scenarios incorporating actual UAV dynamics were designed and simulated to validate the performance in tracking multiple mobile intruder aircraft. A comprehensive analysis and comparison of methods relying solely on RL and other influencing factors, as well as a controller feasibility assessment for real-world flight tests, are conducted, highlighting the advantages of the proposed hybrid architecture. Overall, this research advances the development of AI-driven approaches for UAV safe autonomous navigation under demanding airspace conditions and provides a viable learning-based control solution for different types of robots.

Is there a time-varying nexus between stock market liquidity and informational efficiency? – A cross-regional evidence

PurposeThis study aims to measure the degree of volatility comovement between stock market liquidity and informational efficiency across Asia, Europe, North-South America, Africa, and the Pacific Ocean over three decades. In particular, the authors analyze the extent of the time-varying nexus between different aspects of stock market liquidity and multifractal scaling properties of the stock return series across various regions and diversified market conditions. This study further investigates several factors altering the degree of dynamic conditional correlations (DCCs) between the efficiency and liquidity of the domestic stock markets.Design/methodology/approachThe study measures five aspects of stock market liquidity – tightness, depth, breadth, immediacy, and adjusted immediacy. The authors evaluate the multifractal scaling properties of the stock return series to measure the level of stock market efficiency across the regions and diversified market conditions. The study uses the dynamic conditional correlation-multivariate generalized autoregressive conditional heteroscedasticity framework to quantify the degree of volatility comovement between liquidity and efficiency over the period.FindingsThe study finds the presence of stronger volatility comovement between inefficiency and illiquidity due to the price impact characteristics of the stock markets irrespective of different regions and diversified market conditions. The extent of time-variation increased following the shock periods, indicating the significant role of the financial crisis in increasing the volatility comovement between inefficiency and illiquidity. The highest degree of time-varying correlation is observed in the developed stock markets of Northwestern and Northern Europe compared to the regional and emerging counterparts. On the other hand, weak DCCs are observed in the emerging stock markets of Europe.Originality/valueThe output of the present study assists investors in identifying diversification opportunities across the regions. Additionally, the study has significant implications for market regulators, aiding in predicting future troughs and peaks. The prediction, in turn, helps formulate capital market development plans during dynamic economic situations.

Evaluating the Stability Limits Between Individuals with Mild and Moderate-to-Severe Grades of Forward Head Posture

Background: Forward head posture (FHP) leads to the anterior excursion of the center of gravity, which can affect a person's standing balance. Evaluating the balance in different degrees of severity of FHP can help design and plan appropriate balance exercises for people with FHP. Objectives: This study aimed to evaluate the changes in the limits of stability (LOS) in people with mild and moderate-to-severe grades of FHP. Methods: The participants in this study were 70 individuals suffering from FHP, aged between 17 - 45. They were divided into two groups based on their craniovertebral angle: Mild (> 45.5 degrees) and moderate-to-severe (< 45.5 degrees). The LOS test was performed using a posturography device (NeuroCom, Equitest, USA). Five indices—movement reaction time (RCT), movement velocity (MVL), endpoint excursion (EPE), maximum excursion (MXE), and directional control (DCL)—were evaluated. Results: Based on the results of the LOS test, RCT, MVL, EPE, MXE, and DCL were significantly different between the mild and moderate-to-severe FHP groups in both anterior and posterior directions (P < 0.05). However, in other directions, no significant difference was observed in these variables based on the LOS test (P > 0.05). Conclusions: It can be concluded that individuals with moderate-to-severe FHP are more likely to have postural control deficits. Therefore, it is necessary to design appropriate targeted interventions to prevent falls in these individuals. Specifically, they should receive balance exercises in dynamic situations.

Exploring undergraduate paramedic students’ understanding and experiences of person-centred care while on practice placement

Objective To explore paramedic students’ understanding and experience of the perceived facilitators and barriers to implementing person-centred care in urgent and emergency practice-based placement situations. Aim To explore paramedic students’ understanding of this concept and how it may be applied to clinical practice. Methods A non-probability convenience sample of participants was drawn from a second-year undergraduate Bachelor of Science (Hons) programme in Paramedic Science, at a United Kingdom university. The programme was underpinned by the Person-centred Practice Framework. Undergraduate paramedic students participated in face-to-face, audio-recorded, semi-structured interviews. A qualitative reflexive thematic analysis was then conducted to identify themes arising from the data. Results Ten participants were interviewed. Four key themes emerged from the data: (1) realising person-centred prerequisites which have two sub-themes – curriculum and reality of practice, (2) challenge of high-acuity calls, (3) developing a rapport with vulnerable people and, (4) factors in the macro environment. Conclusion Paramedic students witnessed moments of person-centred practice and were enabled to reflect on their learning experiences in positive ways, by working with paramedics/practice educators. However, their person-centred ideals were constantly challenged as students negotiated to work in complex, dynamic situations and in a health system under pressure.

Is the effective potential effective for dynamics?

We critically examine the applicability of the effective potential within dynamical situations and find, in short, that the answer is negative. An important caveat of the use of an effective potential in dynamical equations of motion is an explicit violation of energy conservation. An effective potential is introduced in a consistent quasistatic approximation, and its narrow regime of validity is discussed. Two ubiquitous instances in which even the adiabatic effective potential is not valid in dynamics are studied in detail: parametric amplification in the case of oscillating mean fields, and spinodal instabilities associated with spontaneous symmetry breaking. In both cases profuse particle production is directly linked to the failure of the effective potential to describe the dynamics. We introduce a consistent, renormalized, energy conserving dynamical framework that is amenable to numerical implementation. Energy conservation leads to the emergence of asymptotic highly excited, entangled stationary states from the dynamical evolution. As a corollary, decoherence via dephasing of the density matrix in the adiabatic basis is argued to lead to an emergent entropy, formally equivalent to the entanglement entropy. The results suggest novel characterization of asymptotic equilibrium states in terms of order parameter vs energy density. Published by the American Physical Society 2024

Leveraging P2P Architecture and Semantic Web for Enhanced Resource Discovery

Web 4.0, also known as the next generation, intelligent internet, possesses the potential to become a widely and universally used communication medium for various types of information. However, its decentralized architecture lacks strong semantic support, resulting in an internet that is disorganized. The current system lacks the capacity to facilitate users' effective information discovery, extraction, and integration from multiple sources. Additionally, it fails to give consumers efficient tools for manipulating and turning acquired data into knowledge that is useful. Peer-to-peer (P2P) overlay technologies have recently come to light as a way to improve resource discovery on the internet. In dynamic and large-scale situations, these technologies provide a scalable framework for allocating, sharing, and gaining access to resources. The purpose of this research is to discuss on semantically enabled web architecture that makes use of P2P overlay technology. This architecture aims to facilitate structured and precise access to internet resources and promote knowledge sharing among community members who share similar interests. The paper examines the core elements of the semantic web architecture, which encompass the services and protocols responsible for resource advertising, discovery, and management, methods and material. It then delve into the hybrid peer-to-peer (P2P) overlay structure, specifically focusing on indexing and resource location, and explores the mechanisms necessary to facilitate scalable routing within a distributed environment.

Pandangan Mahasiswa Terhadap Dinamika Polemik Pemilihan Umum (Pemilu) Tahun 2024

This research aims to find out the opinions of Untirta students regarding the dynamic situation of the polemics in the 2024 general election. The problems discussed in this case are regarding students' understanding of the dynamics of the polemics in the 2024 elections as well as the role of students in students' efforts to improve, supervise and supervise each election. , the role of students is very important in guarding and supervising the election process. In the method of selecting several journals as a literature review, there is an interview technique carried out by interviewing several sources regarding their views as students in looking at the polemic dynamics that occurred in the 2024 election. The results of this research are that regarding the polemic dynamics that occurred in the 2024 election, students are of the view that there are still There is fraud occurring in the 2024 election, as in previous elections, therefore students play an important role in overseeing and supervising each election as a form of effort to improve and maintain the principles of democracy.

The impact of citywide community quarantine policy on the urban fresh food availability: An insight from the topic clout on social media

Numerous Chinese cities implement citywide community quarantine policy (CCQP) to prevent the domestic spread of COVID-19. This kind of policy influences the food availability in the city. Our study proposed an evolutionary analysis framework that utilises the streaming data of topic clout on social media to analyse the dynamic impact of CCQP on food availability. This method contains the Mann–Whitney-U test, Mann–Kendall Trend test, and Grey Rational Analysis. We applied this method in multiple case studies to reflect fresh food availability on both the demand and supply sides. Our study revealed that, on the demand side, cereal products had the highest demand, and vegetables were the most frequently purchased; on the supply side, a rising quantity of fresh food shipment created a corresponding increase in logistics challenges. This study contributes to effectively monitoring the dynamic situation of fresh food supplied to residents throughout the implementation of the CCQP, thereby enhancing the food availability of urban residents.

Dual‐Cooling Textile Enables Vertical Heat Dissipation and Sweat Evaporation For Thermal and Moisture Regulation

AbstractPersonal thermal management textiles have garnered a lot of attention because they can efficiently preserve the body's thermal and moisture comfort while saving energy consumption. Nonetheless, conduction cooling‐based textile research is scarce and frequently encounters obstacles like overlooking through‐plane heat conduction, moisture management, and durability assurance. Here, a dual‐cooling textile (DCT) that combines high‐efficiency heat dissipation and sweat evaporation with a 3D thermal conductive network and Janus wetting structure is demonstrated. The DCT achieves notable in‐plane and through‐plane thermal conductivity (8.57 and 0.70 W m−1 K−1), along with practical mechanical qualities (tensile fracture strength of 65 MPa), under the influence of the 3D multistage thermal conduction network. Additionally, the DCT benefits from its Janus wetting structure, exhibiting unidirectional moisture‐wicking capability (transport index of 1081%) and fast water evaporation performance (0.34 g h−1). Rapid heat dissipation and sweat evaporation are advantageous features for the cooling of the human body in both static and dynamic situations. Compared to cotton fabric, DCT can lower the temperature by up to 3.7 °C. This strategy provides a fresh perspective on the development of advanced functional textiles for personalized cooling and energy savings in buildings.

AI-Enhanced Demand Response Strategies in Smart Grids: Toward Sustainable Energy Future

To accomplish a sustainable energy future, this article researches the consolidation of computerized reasoning (AI) into request reaction components inside smart grids. While considering the joining of sustainable power sources and expanding energy utilization, current energy frameworks depend altogether on load the executives and continuous energy request reaction. Conventional methodologies battle with the intricacies of dynamic energy situations. Results from the examination feature the worth of AI and ML for enhancing energy use. Versatile learning for energy proficiency, exact interest determining, continuous observing, and sustainable power source mix are completely made conceivable by these innovations. An intensive vision for the Smart Lattice is introduced, underscoring financial matters, proficiency, wellbeing, ecological obligation, security, and reliability. We check out at the benefits and downsides of incorporating energy stockpiling gadgets and the job of circulated framework insight. The determination gives a careful future vision to AI-enhanced request reaction in smart grids by featuring research issues connected with self-learning frameworks, complete robotization, self-recuperating grids, fitting and-play advances, network safety, and labor force improvement.

Time and Distance Perception in Highly Dynamic Environments

Abstract Space- and time-based tasks, like flying airplanes, driving cars, or the manual controlled rendezvous and docking of spacecrafts can be very demanding for pilots, drivers, or astronauts, depending on selected trajectories, approaching speeds, or distracting information. One characteristic of highly dynamic environments is that persons have to consider their spatial position in relation to surrounding elements based on passing time, detected speed, and trajectories to avoid collisions with other objects. An inadequate perception of the own position in relation to other objects and passing time can lead to impaired decision-making processes, resulting in errors or collisions. A framework for the explanation of cognitive processes involved in perception, anticipation, and decision-making in dynamic environments is provided by the concept of situation awareness. Based on this framework persons must perceive relevant elements, integrate them in a coherent mental representation and anticipate the development of the current situation in the near future, to plan safe upcoming maneuvers. Thus, for safe maneuvers anticipation processes are playing a major role in decision-making and action selection. In this paper it is proposed that time and distance perceptions are central features of anticipation processes in dynamic situations. It is suggested to combine theories like the attentional-gate model and time-to-contact with the framework of situation awareness to explain anticipation processes in dynamic environments. The major aim is to develop precise cognitive models of persons acting in dynamic situations. Such cognitive models can be the basis for the development and parameterization of assistance systems, supporting anticipation in dynamic environments.

An intelligent thermal comfort control strategy for air conditioning of fuel cell vehicles

Thermal comfort is an important indicator for evaluating vehicle air conditioning, with many influencing factors, but traditional vehicle air conditioning control only take temperature as the control target, neglecting the passenger's actual thermal comfort situation, which cannot automatically adapt to the thermal comfort needs of different passengers. To address this issue, this paper establishes an air conditioning model based on a fuel cell vehicle (FCV) and proposes a control strategy based on thermal comfort, using deep reinforcement learning based on PPO algorithm to establish the control model. Which can automatically control the compressor and blower, this paper conducts simulation analysis under four different environmental conditions which including static and dynamic situations. The results show that when using the intelligent thermal comfort control strategy, the overall thermal sensation values of passengers are 0.006, 0.005, 0.033, and 0.102, respectively; which are 0.088, 0.333, 0.093, and 0.120 lower than the temperature-based control strategy, this proves that the control strategy proposed in this paper can achieve better thermal comfort for passengers.