Dynamic Process Of Interaction Research Articles

Modelling the Relationship Between Resilience to Depression and Recent Stressful Life Events in University Students.

Resilience, or successful coping with the experience of stressful life events (SLEs), protects against depression, but its operational mechanisms are unclear. Views diverge whether resilience intervenes as a trait or as a process of dynamic interactions of protective factors, such as self-esteem, social support and family cohesion. We evaluated five theoretically-based models of how resilience, defined as either a trait or a process, interacts with recent SLEs, to explain depressive symptomatology in 2434 university students. The moderating effect of problematic, age-inappropriate parenting (i.e., helicopter parenting) was also assessed. SLEs moderated both the effects of trait and process resilience on depression, but models conceptualising resilience as a dynamic process of interacting components showed better explanatory power than models conceptualising resilience solely as a trait. Trait resilience was protective through self-esteem at all levels of SLEs exposure (low, mild, moderate or high), and significantly, but less so through hope or social support. Experiencing helicopter parenting weakened the protective influence of process resilience, through decreasing family cohesion in the presence of SLEs. The overall assessment of the five models supports a process conceptualisation of resilience to depression in the face of adversity. However, the results also suggest that not all protective factors are equally important, with self-esteem appearing a significant and strong mediator of resilience to depression in all models including it as a variable. Building process resilience is proposed as a key intervention target for depressive symptoms. Clinical assessments and interventions following SLEs should routinely consider both trait resilience and self-esteem, as the interaction of these two factors protects against depression even at the highest levels of adversity exposure. Depression prevention approaches should address the individual's experience of overparenting, given the deleterious influence of helicopter parenting on resilience.

Context- and Sentiment-Aware Networks for Emotion Recognition in Conversation

Emotion recognition in conversation (ERC) has promising potential in many fields, such as recommendation systems, man–machine interaction, and medical care. In contrast to other emotion identification tasks, conversation is essentially a process of dynamic interaction in which people often convey emotional messages relying on context and common-sense knowledge. In this article, we propose a context- and sentiment-aware framework, termed Sentic GAT, to solve this challenge. In Sentic GAT, common-sense knowledge is dynamically represented by the context- and sentiment-aware graph attention mechanism based on sentimental consistency, and context information is captured by the dialogue transformer (DT) with hierarchical multihead attention (HMAT), where HMAT is used to obtain the dependency of historical utterances on themselves and other utterances for better context representation. Additionally, we explore a contrastive loss to discriminate context-free and context-sensitive utterances in emotion identification to enhance context representation in straightforward conversations that directly express ideas. The experimental results show that context and sentimental information can promote the representation of common-sense knowledge, and the intra- and inter-dependency of contextual utterances effectively improve the performance of Sentic GAT. Moreover, our Sentic GAT using emotional intensity outperforms the most advanced model on the tested datasets.

Coupling Coordination and Interactive Response Analysis of Ecological Environment and Urban Resilience in the Yangtze River Economic Belt.

There is a complex dynamic coupling interaction process between the ecological environment and urban resilience. It is important to clarify the coordination relationship and interactive response mechanism between them for sustainable development construction of the Yangtze River Economic Belt. The coupling coordination degree model and the panel vector autoregressive model (PVAR) were adopted to quantitatively examine the dynamic coordination and interactive response of the ecological environment and urban resilience in the Yangtze River Economic Belt from 2000 to 2019. Our study’s results are the following: (1) The ecological environment index and urban resilience index have a generally positive trend of fluctuation and increase during the study period but show significant regional differentiation. (2) The coupling coordination degree of ecological environment and urban resilience in the Yangtze River Economic Belt increased steadily, forming a spatial distribution pattern of “strong in the east and weak in the west”, with cities in the region mainly at the basic coordination level and generally lagging behind in development. (3) Both the ecological environment and urban resilience systems in the Yangtze River Economic Belt have significant self-reinforcing mechanisms, but the reinforcing effect is gradually decreasing, and the two positively promote each other, with urban resilience showing a more obvious promoting effect on the ecological environment.

INNOVATIVE TECHNOLOGIES IN PREPARATION FUTURE SPECIALISTS FOR PROFESSIONALLY ORIENTED FOREIGN LANGUAGE COMMUNICATION

Based on analysis of the fundamental pedagogical, philological, philosophical, psychological works (A. Vitsyuk, O. Kovalenko, Y. Lavrysh, R. Lozanov, O. Osova, Y. Passov, etc.) the theoretical and methodological principles of using innovative technologies for training future specialists for professionally oriented foreign language communication are substantiated. The author describes the main approaches, principles and didactic possibilities of technological innovations in the training future specialists’ field for professionally oriented foreign language communication.The study found that future specialists` preparation for professionally oriented foreign language communication with the use of innovative pedagogical technologies has a fundamental and interdisciplinary nature; іt is studied by a wide range of scientific research areas. At the same time, it should be noted that the methodological and didactic aspects of the problem need further improvement. It was found that the preparation of future specialists for professionally oriented foreign language communication is a holistic, dynamic process of subject-subject interaction aimed at forming students’ readiness to use technological innovations in future professional activities that integrate learning, language and innovation competencies. Technological innovations in the field of training future specialists for professionally oriented foreign language communication are treated as a set of new methods, techniques, tools, forms of education, specially organized and aimed at implementing an innovative pedagogical process that provides foreign language communicative competence. As a result of studying the problem, the peculiarities of the use of innovative technologies of training future specialists for professionally oriented foreign language communication were revealed. This is reflected in the shift of emphasis: the teacher performs the mission of moderator, coach, tutor, facilitator in the learning process. A characteristic feature of the implementation of innovative technologies for training future specialists for professionally oriented foreign language communication in higher education institutions is their orientation towards the implementation of subject-subject educational activities of teachers and students, intensification of foreign language activities based on cooperation and co-creation strategies.

A Fast and Efficient Ensemble Transfer Entropy and Applications in Neural Signals.

The ensemble transfer entropy () refers to the transfer entropy estimated from an ensemble of realizations. Due to its time-resolved analysis, it is adapted to analyze the dynamic interaction between brain regions. However, in the traditional , multiple sets of surrogate data should be used to construct the null hypothesis distribution, which dramatically increases the computational complexity. To reduce the computational cost, a fast, efficient with a simple statistical test method is proposed here, in which just one set of surrogate data is involved. To validate the improved efficiency, the simulated neural signals are used to compare the characteristics of the novel with those of the traditional . The results show that the time consumption is reduced by two or three magnitudes in the novel . Importantly, the proposed could accurately track the dynamic interaction process and detect the strength and the direction of interaction robustly even in the presence of moderate noises. The novel reaches its steady state with the increased samples, which is slower than the traditional method. Furthermore, the effectiveness of the novel was verified in the actual neural signals. Accordingly, the proposed in this work may provide a suitable way to investigate the dynamic interactions between brain regions.

Application of high content imaging technique in research on effective components of traditional Chinese medicine: a review

High content imaging(HCI) technique that combines automatic high throughput with high-resolution cell imaging, is characterized by abundant data information, high imaging sensitivity, easy visualization and standardization, and is commonly used in the cellular(or subcellular) phenotypic analysis. Abundant phenotypic information can be obtained by using HCI in one experiment, including cellular morphology, cellular structure, and signal transduction pathways of related functions, on the basis of the maintenance of the integrity of cellular structures and functions. Multiple studies have shown that a series of dynamic spatio-temporal interactive change processes were induced by the disturbance of cells by specific factors, making cell phenotypes change accordingly, especially for the slight perturbation response of cells. Generally, the detection of one or several endpoint effect indicators is often difficult to accurately and comprehensively reflect the overall efficacy information of traditional Chinese medicine(TCM) because of its unique characteristics of multi-components and multi-targets. The application of HCI is thus helpful to discover the effective components and their action modes in the complex system of TCM. This paper reviewed the application progress in the HCI technique in the screening of active components and their regulation mechanism to provide references for further research.

CIEGAN: A Deep Learning Tool for Cell Image Enhancement.

Long-term live-cell imaging technology has emerged in the study of cell culture and development, and it is expected to elucidate the differentiation or reprogramming morphology of cells and the dynamic process of interaction between cells. There are some advantages to this technique: it is noninvasive, high-throughput, low-cost, and it can help researchers explore phenomena that are otherwise difficult to observe. Many challenges arise in the real-time process, for example, low-quality micrographs are often obtained due to unavoidable human factors or technical factors in the long-term experimental period. Moreover, some core dynamics in the developmental process are rare and fleeting in imaging observation and difficult to recapture again. Therefore, this study proposes a deep learning method for microscope cell image enhancement to reconstruct sharp images. We combine generative adversarial nets and various loss functions to make blurry images sharp again, which is much more convenient for researchers to carry out further analysis. This technology can not only make up the blurry images of critical moments of the development process through image enhancement but also allows long-term live-cell imaging to find a balance between imaging speed and image quality. Furthermore, the scalability of this technology makes the methods perform well in fluorescence image enhancement. Finally, the method is tested in long-term live-cell imaging of human-induced pluripotent stem cell-derived cardiomyocyte differentiation experiments, and it can greatly improve the image space resolution ratio.

Resonant interaction between phonons and PbTe/PbSe (001) misfit dislocation networks

This work aims at a quantitative and mechanistic understanding of the dynamic process of the phonon-dislocation interaction in PbTe/PbSe (001) heterostructures using the Concurrent Atomistic-Continuum (CAC) method as the simulation tool. The misfit dislocation network and the atomic-scale dislocation core structure obtained in the simulations are found to agree reasonably well with the experimental observations of the PbTe/PbSe (001) interface. Through visualizing the dynamic interaction between phonons and dislocations, as well as quantifying the dislocation vibration amplitude, the phonon energy transmission, and the thermal resistance of the misfit interfaces, this work has illustrated and quantified two mechanisms for phonon-dislocation interaction: (1) phonon scattering by the strain field of dislocations, and (2) phonon scattering by dislocations that vibrate via the local modes of a dislocation network; the latter, leads to resonant phonon-dislocation interaction, which is manifested as local maxima of out-of-phase vibration of the atoms on the two sides of the slip plane, leading to local minima of the energy transmission in the heterostructure that contains one interface. The local vibrational modes are found to be excited only by shear stress induced by transverse phonons. Among various resonant modes, the one with the lowest frequency has the strongest effect. This work has also demonstrated the collective motion of dislocations under ultrafast phonon pulses. In addition, the dynamic properties of the misfit dislocation network localized within one interface are found to be significantly altered by the presence of misfit dislocations at other interfaces, thus further confirming the cooperative dynamic nature of the motion of dislocations and phonons.

Effect of low-temperature annealing on two-different severely cold-rolled steels

The present work is on the effect of low-temperature annealing (or tempering) treatment of two severely cold rolled ultra-high-strength steels. Cold rolling of hot rolled steels significantly enhanced the dislocation density in martensitic and bainitic steels, leading to increase in the YS and UTS of both the steels. Further, these hot rolled high strength steels were cold rolled to about 70% reduction. It is proposed that the cold rolling process might have improved the stability of retained austenite within a range of 15 – 20 mJm–2 through a dynamic interaction process between retained austenite and dislocations during each rolling pass. While the initial passes were associated with the mechanical stability of retained austenite in the steels, the final stage was influenced by the rolling strain and heat generated during cold rolling process. The carbon partitioning at the dislocation sites too had a similar effect on increasing YS and UTS during relatively low-temperature annealing in both the steels. There was a difference in the YS values of two highly deformed steels in post annealing condition, which was due to the intrinsic hardness of the phases present in those steels, nevertheless, both the martensitic and bainitic steels had similar work hardening rates at each annealing temperature. It is also proposed that activities like carbon-dislocation pinning, recovery, and precipitation during annealing in any highly deformed steel may be governed through a similar mechanism, which can work independently irrespective of the phases present in the microstructure.

Analysis of dynamic instability of the wheel set of a railway vehicle using the method of generalized hill determinants

The article considers the tasks associate with the study of dynamic processes of interaction between rolling stock and railways. Studies of the interaction of a wheel with a rail, fitting the vehicle into curves when modeling critical and emergency situations do not allow oversimplification of basic differential equations. And they should be based on exact nonlinear equations that take into account the entire set of geometric and kinematic relationships without simplification. An objective assessment dynamic characteristic of the vehicle can only be obtained by simultaneously taking into account both its vertical and horizontal irregularities. In order to determine boundaries of parametric resonance, article proposes method of generalized Hill’s determinants, the application of which is possible without taking into account small parameters.

Response of extreme precipitation to increasing extratropical cyclonic vortex frequency

Since the 2000s, extratropical extremes have been more frequent, which are closely related to anomalies of planetary-scale and synoptic-scale systems. This study focuses on a key synoptic system, the extratropical cyclonic vortex (ECV) over land, to investigate its relations with extreme precipitation. It was found that ECVs have been more active post-2000, which has induced more extreme precipitation, and such variation is projected to persist along with increasing temperature within 1.5°C of global warming. An enhanced quasi-stationary vortex (QSV) primarily contributes to the ECV, rather than inactive synoptic-scale transient eddies (STEs). Inactive STEs respond to a decline in baroclinicity due to the tendency of the homogeneous temperature gradient. However, such conditions are helpful to widening the westerly jet belt, favoring strong dynamic processes of quasi-resonant amplification and interaction of STEs with the quasi-stationary wave, and the result favors an increasing frequency and persistence of QSVs, contributing to extreme precipitation.摘要自21世纪以来, 热带外极端降水频次增加. 随着中高纬度的显著增温, 经向温度梯度减弱导致低层大气斜压性减小, 由此产生的气旋型瞬变涡天气系统等活动减弱. 然而, 热力分布导致西风急流带变宽, 经向环流加大, 有助于行星尺度波动相关的涡旋异常增加, 如东北冷涡, 中亚涡, 东欧-地中海涡, 北美涡等, 进而增加了气旋涡影响范围的极端降水频次. 在未来变暖背景和1.5°C增温的目标内, 热带外气旋涡增强会进一步促进极端降水发生.

Deep reinforcement learning with the confusion-matrix-based dynamic reward function for customer credit scoring

Customer credit scoring is a dynamic interactive process. Simply designing the static reward function for deep reinforcement learning may be difficult to guide an agent to adapt to the change of the customer credit scoring environment. To solve this problem, we propose the deep Q-network with the confusion-matrix-based dynamic reward function (DQN-CMDRF) model. Especially, the new constructed dynamic reward function can adjust the reward dynamically according to the change of confusion matrix after each deep Q-network model training, which can guide the agent to adapt to the change of environment quickly, so as to improve the customer credit scoring performance of the deep Q-network model. First, we formulate customer credit scoring as a finite Markov decision process. Second, to adjust the reward dynamically according to the customer credit scoring environment, the dynamic reward function is designed based on the confusion matrix. Finally, we introduce the confusion-matrix-based dynamic reward function into the deep Q-network model for customer credit scoring. To verify the effectiveness of the proposed model, we introduce four evaluation measures and make a series of experiments on the five customer credit scoring datasets. The experimental results show that the constructed dynamic reward function can more effectively improve customer credit scoring performance of the deep Q-network model, and the performance of the DQN-CMDRF model is significantly better than that of the other eight traditional classification models. More importantly, we find that the constructed dynamic reward function can accelerate the convergence speed and improve the stability of the deep Q-network model.

Dynamic Analysis of Monopile-Type Offshore Wind Turbine Under Sea Ice Coupling With Fluid-Structure Interaction

The interaction between vertical offshore wind turbine (OWT) and sea ice with fluid is a complex process including local and global crushing of ice fragments and vibration of OWT. It is crucial to study the ice resistance of OWT structures considering the fluid-structure interaction (FSI). This article investigates a complete process of dynamic sea ice-monopile OWT interaction considering soil-structure interaction (SSI) and FSI effects. A fully coupled dynamic collision model of sea ice and OWT incorporating with the explicit non-linear collision tool ANSYS/LS-DYNA is proposed. The simulated ice loads in this study is verified by different simulation methods and international static ice force standards closely related to ice dynamic characteristic parameters. Then, the dynamic response and damage of the OWT structure during ice-structure interaction are studied using the fully interaction model with FSI coupling. The simulated ice force can produce a significant vibration response in the structure coupling with FSI due to occurrence of ice-induced resonance in the ice velocity range of 2.5–3.5 cm/s. Finally, the effect of fluid on the sea ice-OWT interaction in the initial velocity collision of sea ice is analyzed. FSI coupling can cause a certain level of collision hysteresis, accelerate the failure of sea ice breaking and reasonably reduce the energy of the structure.

Artificial intelligence biology—biology V3.0

<p indent="0mm">Despite significant progress, modern biology research is facing a huge bottleneck in its development due to lack of revolutionary theoretical frameworks. The rapid development of artificial intelligence (AI) based on big data and deep learning is spurring “Biology V3.0”—Artificial intelligence biology (AI Biology, AIBIO). We define AI Biology as the science of using the principles and means of AI to study the basic laws of living systems. AI Biology is characterized by its ability to integrate multi-dimensions and multi-factors involved in the dynamic process of intermolecular interactions and regulations, so as to truly understand the basic principles in life sciences. As a new life science discipline, AI Biology has the potential to fundamentally change the existing paradigm of biological research, to expand both the connotation and the complexity of biological research, to answer some of the fundamental questions in biological science, and to achieve substantial breakthroughs in key areas of life science and medical science.

A Study of the Effect of Impact Speed on the Dynamics of Mechanical Interactions of Bodies

The mechanorheological viscoelastic plastic model was used to study the effect of impact speed on the dynamics of mechanical interaction of a spherical body with the surface. An analysis of the impact process made it possible to draw some conclusions. The impact interaction time depends on the impact speed and mechanical properties of the material. The impact time decreases with an increase in the impact speed, a decrease in plasticity, and an increase in elasticity. With an increase in the impact speed, the impact time decreases. During the experiment, the initial impact speed increased 10 times. During the impact interaction, the body deformation increased 6-7 times. According to the calculations, the average body deformation speed also increased 10 times. As a result, the time for travelling a distance equal to the elastic and plastic deformation when loading bodies and the elastic deformation when unloading bodies decreased. The total deformation is composed of elastic and plastic components. With an increase in the impact speed, the plastic component increases, which decreases the unloading time due to a decrease in the elastic component. The impact time is an important characteristic of the dynamic process of interaction. Therefore, when identifying theoretical models to the real processes, these parameters should be congruent. To improve the modeling accuracy and reliability for various technological processes under dynamic loads, it is necessary to take into account various factors.

Human-like driving decision at unsignalized intersections based on game theory

Unsignalized intersection driving is challenging for automated vehicles. For safe and efficient performances, the diverse and dynamic behaviors of interacting vehicles should be considered. Based on a game-theoretic framework, a human-like payoff design methodology is proposed for the automated decision at unsignalized intersections. Prospect Theory is introduced to map the objective collision risk to the subjective driver payoffs, and the driving style can be quantified as a tradeoff between safety and speed. To account for the dynamics of interaction, a probabilistic model is further introduced to describe the acceleration tendency of drivers. Simulation results show that the proposed decision algorithm can describe the dynamic process of two-vehicle interaction in limit cases. Statistics of uniformly-sampled cases simulation indicate that the success rate of safe interaction reaches 98%, while the speed efficiency can also be guaranteed. The proposed approach is further applied and validated in four-vehicle interaction scenarios at a four-arm intersection.

Neutrally charged nanosilver antimicrobial effects: A surface thermodynamic perspective

Nanosilver (AgNP) has a large surface area that contributes to enhanced interactions with bacteria, as well as silver ion release. The actual AgNP antimicrobial effect is determined by the AgNP size. AgNPs with smaller diameters showed better antimicrobial effects because smaller AgNPs had larger surface areas, which led to greater silver ion release and stronger attachment to bacteria. The attachment of AgNPs to bacterial surfaces is attributed to the attractive interactions between the AgNPs and bacteria, which is also a function of the size of AgNPs. Although the antimicrobial activity of AgNPs has been extensively studied, there is a gap between antimicrobial effects of AgNPs on bacteria and their subsequent attachment. To fully understand the antimicrobial effectiveness of different-sized AgNPs, this study investigated the dynamic process of AgNP-bacteria interactions in aqueous media, including AgNP aggregation, AgNP attachment, and antimicrobial effects. AgNP-AgNP and AgNP-bacteria interactions were quantified based on DLVO and surface chemistry theories, which were used to interpret subsequent AgNP aggregation, AgNP-bacteria attachment and AgNP antimicrobial observations.

"It is not O.K to think that you are good just because you have graduated from overseas": Agency and contextual factors affecting Vietnamese returning graduates

AbstractOver the past decade, a growing number of graduates, originally from key source countries of international students such as China and Viet Nam, have returned home after graduation from overseas universities. In particular, there seems to be a recent surge in the number of international graduates heading home due to the high unemployment, tightening migration, rising national protectionism and emerging challenges, exacerbated by the COVID‐19 pandemic, in major host countries such as Australia, the UK and the United States. While there has been emerging empirical research on international returning graduates’ contributions to their home country development, little is known about graduates’ own perceptions of the impacts of the contextual factors on their homecoming decision and their home labour market navigation. Draving on a qualitative study, this article responds to this critical gap in the literature by conceptualising returnee employability as a dynamic interactive process between multiple forces in the host and home labour markets and broader socio‐economic contexts, and between these forces and returnee agency. It identified interrelated contextual factors in the host and home contexts that drive Vietnamese graduates home, including challenges in securing migration, and insecure job prospects facing them in Australia and simultaneously, greater employment and business opportunities at home. In particular, the study found that contextual factors such as sector characteristics, types of employers, economic performance and cultural practices create an institutional environment, in which returnees’ agency is enacted, resulting in different returnees’ labour market navigation experiences and employment outcomes. Significant recommendations for key stakeholders in both home and host countries to support international graduate employability are provided.

The formation of transient defects during high power laser-coating interaction revealed by the variation of electron beam evaporated coatings’ optical constants with temperature

The knowledge of the optical properties of coating materials at high temperatures is important for understanding the dynamic process of high-power laser-material interactions. In this paper, the variations of refractive index and physical thickness of single layer coatings were studied by ellipsometric spectroscopy at different temperatures. From 23 °C to 320 °C, a decrease and then an increase of the refractive index of SiO2, and HfO2 single layer was observed, while the thickness of these layers increased first and then decreased. The inflection points of different coating materials occurred at different temperatures. Water evaporation processes, densification and hydrophilicity of films were used to explain the temperature dependent properties of the dielectric coatings. Results of the variation of refractive index and thickness of single layer coatings at different temperatures in the vacuum proved the mentioned theory. Moreover, HfO2 single layer shows better resistance to both temperature change and vacuum change, indicating that it is promising for high-reflective coatings in photoelectric devices. Besides, the formation of transient defects during high power laser irradiation was interpreted considering the optical properties variation with temperature. Three confusing and debated issues concerning laser-coating interaction are interpreted and explained.

Dynamic Simulation of Power Systems Considering Transmission Lines Icing and Insulators Flashover in Extreme Weather

Global climate deterioration caused by excessive carbon emissions poses a severe threat to the stable operation of power systems. In extreme snow and ice weather, complex faults, such as ice-covered line breakage and insulator flashover, may be triggered. Hybrid simulations to reveal the influence mechanism and dynamic interaction process between extreme weather and power systems have become a research focus. Relationship models between meteorological conditions and grid failure were constructed in ice accretion and insulator flashover scenarios. Based on the above two models, a multi-variable and multi-time scale hybrid simulation of the meteorological process and power system, considering line icing and insulator flashover, was realized. An example was provided to verify the feasibility of the proposed simulation scheme.