Friendly Interaction Research Articles

A two-layer low-carbon economic planning method for park-level integrated energy systems with carbon-energy synergistic hub

Building a low-carbon park is crucial for achieving the carbon neutrality goals. However, most research on low-carbon economic planning methods for park-level integrated energy systems (PIES) has focused on multi-energy flow interactions, neglecting the “carbon perspective” and the impact of the dynamic coupling characteristics between multi-energy flows and carbon emission flow (CEF) on carbon reduction and planning schemes. Therefore, this paper proposes a two-layer low-carbon economic planning method for park-level integrated energy systems with carbon-energy synergistic hub (CESH). Firstly, this paper establishes a CESH model for PIES to describe the synergistic relationship between CEF and multi-energy flows from input, conversion, storage, to output. Secondly, a PIES two-layer low-carbon economic planning model with CESH is proposed. The upper model determines the optimal device types and capacities during the planning cycle. The lower model employs the CESH model to promote carbon energy friendly interactions, optimize the daily operation scheme of PIES. The iterative process between the two layers, initiated by a genetic algorithm (GA), ensures the speed and accuracy. Finally, case studies show that, compared to planning methods without the CESH model, the proposed method is effective in reducing carbon emissions and total costs during the planning cycle. From a dual “carbon-energy” perspective, it enhances investment effectiveness and carbon reduction sensitivity by deeply exploring the energy conservation and carbon reduction potential of PIES.

Unraveling the Experience of Affection Across Marital and Friendship Interactions

AbstractFeelings of affection (i.e., fondness and intense positive regard) are a hallmark of close relationships. Existing studies have often examined affection as a trait or behavior, but rarely as an emotional experience in social interactions. In two dyadic observational interaction studies (total N = 314 individuals), 49 US-based married couples (age range: 21–65) and 108 friendship dyads (age range: 15–26) engaged in two naturalistic 10-min conversations about (a) a topic of disagreement (conflict conversation) and (b) something they enjoyed doing together (pleasant conversation) and reported on their subjective emotional experiences (e.g., affection, using an emotion checklist following each conversation) and relationship satisfaction. Conversation transcripts were analyzed using natural language analysis. Results showed that experiences of affection were most strongly associated with experiences of compassion, amusement, and excitement, as well as with less anger, and were unrelated to most other negative emotions. Natural language analysis further showed that greater positive (but not negative) emotional tone was associated with greater affection (especially among friends in the pleasant conversations). Levels of affection were consistently higher in pleasant versus conflict conversations and similar across marital versus friendship interactions. Finally, experiences of affection were associated with greater relationship satisfaction for friends across conversations and for spouses (women) in the pleasant conversation. These findings contribute to our understanding of affection as a foundational emotional experience in close relationships and highlight avenues for future research.

Perception of Tourists on Chatbot Service Usage on Tourism Destination: A Study of Kainji Lake National Park, Nigeria

Quest for satisfying tourists and customers’ expectations across the globe led to the development and application of various information communication technologies (ICT) in the hospitality and tourism industry. These information communication technologies have been adopted by tourism enterprises and managers such as Email, Mobile Phone, Social Media Networking (Facebook, WhatsApp, Zoom, Artificial Intelligence). Also, the quest for providing friendly interaction among tourists and destination managers further led to the development of one of the artificial intelligence algorithms known as chatbot. Chatbots are Artificial Intelligence (AI) test and/or voice-based virtual assistants that aid customers to get what they ask for quickly and accurately through a conversation in natural human language. Chatbots have been reported to be the technology for hotels, travel agencies, and airlines, however, there is no evidence-based research on the factors that explain consumers’ willingness to interact with chatbots. It is on this basis that this research is carried out. The research examined tourists’ usage of chatbots, focusing on the Kainji Lake Park (Nigeria). It is an exploratory research that utilized descriptive statistics to analyze data collected. The findings reveal that tourists are aware of the existence of chatbots as deployed to tourism industry. Also, it found that chatbots enhance destination information search. As an emerging market, stakeholders and management in the tourism industry should integrate chatbots into their main information communication technologies to enhance customer patronage.

Analysis of thermal videos for detection of lie during interrogation

The lie-detection tests are traditionally carried out by well-trained experts using polygraph machines. However, it is time-consuming, invasive, and, overall, a cumbersome process, not admissible by the court of law. Trained individuals can easily flaunt these tests. On the other hand, facial thermal imaging could be more effective as it is noninvasive and could be a stealth method of tracking the facial blood flow patterns, which have been proven to detect deceit. This paper presents a method based on facial thermal imaging to detect deception in human subjects. The major issue in such research is the lack of proper real-life databases which emulate the crime scenes. In this paper, first, we have developed a database based on almost real-life theft incidents with due diligence using isolated subjects over a period of time at a government hospital under the plea of free health checkup. The experiment has been conducted at Midnapore Medical College and Hospital, West Bengal, India, with proper ethical committee approval. The participants are selected at the behest of the police department with habitual crime records. Most of them have been repeatedly charged with petty crimes of pick-pocketing and stealing. They are invited individually at different instances of time under the plea of medical checkup where they have been enticed to steal cash. It is followed by a two-stage process, a friendly interaction followed by a slightly tougher interrogation. Their forehead and periorbital region skin surface temperature are recorded by a hidden thermal camera. Upon analysis, conspicuous changes in the temperature profile and blood flow pattern have been observed in the individuals who stole money and those who did not.

The double-edged sword of workplace friendship: exploring when and how workplace friendship promotes versus inhibits voice behavior

Extant research has demonstrated the positive roles of workplace friendships and has recently found the negative effect or the double-edged effect on employees and organizations. Unfortunately, little is known about the boundary condition of the double-edged effects of workplace friendships and the elaborated understanding of the mechanism of positive and negative effects of workplace friendship simultaneously. Our purpose is to reveal that workplace friendship is a mixed blessing by investigating when and how workplace friendships are likely to promote versus inhibit voice behavior. We propose that the double-edged effect of workplace friendship hinges on the competitive climate. Specifically, when the competitive climate is low, workplace friendship is positively related to employees’ psychological safety, promoting voice behavior. In contrast, workplace friendship is positively related to employees’ face concern, inhibiting voice behavior when the competitive climate is high. Our hypotheses were supported across the three waves of surveys and experimental studies. Taken together, our findings reveal the perils and benefits of workplace friendship and the importance of boundary conditions resulting in employees’ differential psychological processes in friendship interaction.

Selection and integration of adjustable load in multiple scenarios

In the context of the “carbon peaking and carbon neutrality goals”, the new electricity systems are evolving towards source-load friendly interactions. At the same time, the increasing necessity for adjustable loads to participate in the power balance of the new electricity systems is highlighted. Consequently, a large-scale source-grid-load design scheme is proposed. It employs three independent communication channels to facilitate communication between users and intelligent grid-load terminals. Based on analysis of the individual loads and equipment characteristics of each user, principles for user shunt load access principle and adjustable loads are formulated by combining the maximum duration, frequency constraints, and compliance costs. Furthermore, it proposes construction plans for both the customer side in a single distribution room and the customer side distributed across different locations. According to the experimental analysis of 245 users, the response time of the experimental system is less than 600 ms. These advancements enhance the emergency response speed and responsiveness, contributing to the advancement of precise, real-time, and lean management of the demand side of the power grid.

Peak shaving potential and its economic feasibility analysis of V2B mode

Electric vehicles (EVs) as mobile energy-storage devices improve the grid's ability to absorb renewable energy while reducing peak-to-valley load differences. With a focus on smoothing the load curve, this study investigates the peak shaving potential and its economic feasibility analysis of V2B mode. First, based on the virtual microgrid system established in this paper, a Monte Carlo method was used to simulate the driving, charging, and discharging processes of EVs. Second, the effects of the number of charging stations, battery capacity of EVs, and photovoltaic (PV) penetration rate on the peak shaving results were evaluated separately by using the standard deviation of daily loads. Third, the V2B peak shaving strategy and cost composition were explored considering the battery aging costs. Moreover, the economic feasibility and factors influencing the proposed strategy were analyzed. The results indicate that 1) V2B effectively transfers peak power loads between 08:00 h And 20:00 h To low-demand periods at night; 2) as the deployment ratio of charging station increases, the level of load fluctuation decreases significantly. When EV battery capacity is at or above 60 kW h, charging station deployment ratios of 0.43, 0.42, and 0.47 are required for saturated load smoothing in winter, transition period, and summer, respectively; 3) the PV penetration rate for maximizing the collaborative peak shaving capability of V2B and PV power is 30%–40 % and 4) reducing battery costs or extending battery life has the most significant effect on V2B power costs, followed by charging station costs. This study provides a theoretical basis for determining the economic feasibility of charging station planning and provides technical guidance for the rational scheduling of EVs and their friendly interaction with the power grid.

Examining the Longitudinal Bi-Directional Associations of Friend Engagement, Social Functioning, and Depression.

Various components of social functioning predict depression and these associations can vary by gender. Bi-directional associations may be important to consider as social factors may influence depressive symptoms while depressive symptoms may impact social factors. Most previous longitudinal research examining bi-directional effects has traditionally used the cross-lagged panel model (CLPM), which has some inherent weaknesses. This study sought to apply a more comprehensive analysis to examine bi-directional associations between friend engagement, social functioning, and depressive symptoms. Random intercept cross-lagged panel models (RI-CLPM) were tested on three waves from the Wisconsin Longitudinal Study (N = 5890). Average levels of social functioning were positively associated with friend engagement and negatively associated with depression. Fluctuations in social functioning and friend engagement were negatively associated with same-wave depressive symptoms. Lastly, depression was predicted by previous fluctuations in social functioning, although the findings varied by gender. This study showed that the relationships between social factors and depression are apparent within and across large time intervals, even while controlling for between-person associations. These findings add further support to the need to attend to social life as a predictor of depression in older adults. Future research could improve upon this research by examining the characteristics of the friendship interactions and including more diverse samples.

Inferring in-air gestures in complex indoor environment with less supervision

People have high demands for comfort and technology in indoor environments. Gestures, as a natural and friendly human computer interaction (HCI) method, have received widespread attention and have been the subject of many research studies. Traditional approaches are based on wearable devices and cameras, which can be cumbersome to operate and infringe upon users’ privacy. Millimeter-wave (mmWave) radar avoids these problems by detecting gestures in a noninvasive manner. However, it encounters practical challenges in complex indoor environments, such as dynamic disturbance from surroundings, variable usage conditions and diverse gesture patterns, which conventionally require considerable manual effort to address. In this paper, we attempt to minimize human supervision and propose a noninvasive gesture recognition method named RaGe that involves a commercial mmWave indoor radar. First, a parameter optimization framework considering gesture prior constraints is proposed for radar configuration, which functions to weaken the disturbance from surroundings. Second, we alleviate data shortages in variable usage conditions and achieve low-cost data augmentation by applying affine transformations. Third, we combine deformable convolution operations with an unsupervised attention mechanism, thus exploring the intrinsic features involved in diverse gesture patterns. Experimental results show that RaGe is able to recognize 7 gestures with 99.3% accuracy and less human supervision, surpassing the state-of-the-art methods in comparative experiments.

Fast-Swimming Soft Robotic Fish Actuated by Bionic Muscle.

Soft underwater swimming robots actuated by smart materials have unique advantages in exploring the ocean, such as low noise, high flexibility, and friendly environment interaction ability. However, most of them typically exhibit limited swimming speed and flexibility due to the inherent characteristics of soft actuation materials. The actuation method and structural design of soft robots are key elements to improve their motion performance. Inspired by the muscle actuation and swimming mechanism of natural fish, a fast-swimming soft robotic fish actuated by a bionic muscle actuator made of dielectric elastomer is presented. The results show that by controlling the two independent actuating units of a biomimetic actuator, the robotic fish can not only achieve continuous C-shaped body motion similar to natural fish but also have a large bending angle (maximum unidirectional angle is about 40°) and thrust force (peak thrust is about 14 mN). In addition, the coupling relationship between the swimming speed and actuating parameters of the robotic fish is established through experiments and theoretical analysis. By optimizing the control strategy, the robotic fish can demonstrate a fast swimming speed of 76 mm/s (0.76 body length/s), which is much faster than most of the reported soft robotic fish driven by nonbiological soft materials that swim in body and/or caudal fin propulsion mode. What's more, by applying programmed voltage excitation to the actuating units of the bionic muscle, the robotic fish can be steered along specific trajectories, such as continuous turning motions and an S-shaped routine. This study is beneficial for promoting the design and development of high-performance soft underwater robots, and the adopted biomimetic mechanisms, as well as actuating methods, can be extended to other various flexible devices and soft robots.

“Our Social Lives Were Kind of Ruined”: Challenges and Sources of Support During COVID-19 Distance Learning Among Latinx High School Students

The aim of this study was to better understand Latinx adolescents’ experiences during the pandemic and the transition to distance learning. Guided by the community cultural wealth framework, this study focuses on the key challenges and the sources of support that Latinx adolescents relied on during this unique period. Participants included 40 Latinx high school students from Southern California (28 female, 12 male; 75% Mexican or Mexican-American) between the ages of 14 and 17. A semi-structured interview was conducted with each participant; a thematic analysis approach was used to identify the key themes. Five themes emerged as the prominent challenges Latinx adolescents faced during the transition to distance learning. These challenges included disrupted peer relations, academic and motivation difficulties, home distractions, distant teacher relations, and poor mental health. In terms of the sources of support and coping resources to manage these challenges, the four key themes were supportive teacher relations, positive friend interactions, future aspirations, and supportive family relations. The findings provide insights into Latinx adolescents’ experiences and sources of stress and support during distance learning. The findings have implications for how schools can best support Latinx youth with the transition to in-person schooling.

The hidden curves of risk: a nonlinear model of cumulative risk and school bullying victimization among adolescents with autism spectrum disorder

BackgroundSchool bullying victimization (SBV) occurs more frequently in students with autism spectrum disorder (ASD) in general education than in special classes, and there is a cumulative risk effect on SBV exposure among young people with ASD reported by their parents and teachers. However, SBV is a personal experience, the predictive patterns of cumulative risk on SBV reported by themselves and its psychological mechanism remain unclear. This study aims to explore the relationship between cumulative risk and SBV based on self-report, and to test whether internalizing problems mediates this relationship among adolescents with ASD placed in regular classes.MethodsThis study used data from the Taiwan Special Needs Education Longitudinal Study (SNELS) in 2011. The analysis included 508 adolescents with ASD who were in regular classes across Taiwan. The primary variables under study were the quality of friendship interactions, teacher-student relationship, school connection, perceived stigma, the impact caused by the disabilities, internalizing problem, and whether the participants had experienced SBV over the past semester, while control variables were adaptability and social-emotional skills. Established risk factors were summed to form a cumulative risk score.ResultsThe cumulative risk was positively associated with SBV. The relationship was characterized by the nonlinear pattern of the quadratic function (negative acceleration model) between cumulative risk and SBV. Internalizing problem played a partial mediating role in the effect of cumulative risk on SBV.ConclusionsIntervention measures to reduce SBV should include the strategies to reduce the number of risks to which adolescents with ASD in regular classes are exposed, comprehensive prevention targeting each risk factor is needed specially when the number of risks is one or two, and more attention needs to be given to their internalizing problem in various ways.

Green and low-carbon energy-use

<p>Energy decarbonization has been recognized as a crucial measure for addressing the challenge of global climate change. The user side is the primary cause of energy consumption and carbon emissions. Besides, user behavior can directly affect the energy efficiency and carbon emissions of energy-use (EU) systems, as well as the hosting capacity to accommodate renewable energy. Therefore, more attention should be paid to the user side for driving a green and low-carbon energy transition. Based on analyzing the driving mechanisms of the green and low-carbon energy transition from the user side, the author proposed to assign users EU rights (EURs) to describe the right and responsibility of using every EU resource in 2016. Based on the EUR trading, economic value is utilized to drive the flexible resources of EU systems to promote green and low-carbon EU. Moreover, EUR trading involves the allocation and operation of energy resources across multiple stages, as well as mutual conversions among various forms of energy. Considering that, an energy element model, which is used as a unit for measurement and transaction settlement of EUR commodities, is proposed to characterize energy equivalent and value in the EUR trading. Finally, through the integration of the Industrial Internet in the energy sector and the Consumer Internet, an Energy-Use Net and its friendly interaction with the power grid is proposed. The proposed Energy-Use Net uses energy elements as the basic circulation units, to achieve energy efficiency improvement and carbon reduction, thereby promoting the green and low-carbon transition of the whole energy system.</p>

Big Data Analysis and Decision Making Optimization in International Relations Supported by Constructivist Theory

Abstract With the peaceful end of the Cold War and the deepening development of economic globalization, the traditional international relations theory is in trouble, and constructivism comes into being amidst people’s reflections on neorealism and neoliberalism. This paper proposes an optimization method for decision-making in international relations, guided by the constructivist international relations theory system. Big data is used to analyze the decision-making opinions of experts in international relations processing and to fuse complex relationships, and then the dual-consensus feedback mechanism is used to calculate the comprehensive score of each international relations decision-making scheme to obtain the optimal decision-making scheme in international relations. The analysis finds that the solution obtained using the method proposed in this paper is better than the solution obtained using the JIA method and can provide the optimal decision-making solution for processing international relations. In the simulation case, after optimizing its decision-making in international relations, country T actively engages in economic and trade exchanges with country M and jointly establishes several economic cooperation frameworks. The export trade volume of country T to country M increased by about three times from 2016 to 2023, and the total global trade volume of country T doubled by nearly five times (481.97%). The paper’s impact can be seen in the establishment of relatively stable international relations and the realization of the practice of friendly interaction between state subjects.

Bi-level optimal dispatching of distribution network considering friendly interaction with electric vehicle aggregators

The widespread application of electric vehicles (EVs) is a positive force driving green development. However, their widespread penetration also poses significant challenges and threats to the security and stable operation of the power grid. To address this urgent issue, this article constructs a bi-level optimal dispatching model fostering collaboration between electric vehicle aggregators and the distribution network. The upper-level optimization targets the minimization of peak-valley differences in the distribution network via considerably arranging power outputs of gas turbines, while the lower-level one focuses on reducing the charging expense of EV aggregators via efficient charging transfer. Note that the charging expense is not only composed of electric cost but also a dynamic carbon emission factor-based cost, which contributes to the electricity economy and carbon reduction concurrently. A geometric mean optimizer (GMO) is introduced to solve the mode. Its efficiency is evaluated against three typical algorithms, i.e., genetic algorithm, great-wall construction algorithm, and optimization algorithm based on an extended IEEE 33-bus system with different charging behaviors of EVs on both a typical weekday and weekend. Simulation results demonstrate that the GMO outperforms other competitive algorithms in accuracy and stability. The peak-valley difference between the distribution network and the total cost of EV aggregators can be decreased by over 98% and 76%, respectively.

Виктимизация несовершеннолетних в процессе кибергруминга: гендерная и психосексуальная специфика

<p style="text-align: justify;">Addressing the problem of sexual harassment of children and adolescents in online communication (cybergrooming) requires in-depth study. Gender and psychosexual aspects of victimization of victims are of particular importance for preventive work. The article presents the results of content analysis of dialogues between 35 cybergroomers and 94 minors, realized on the Internet. The gender and age structure of the victims is 54 girls and 40 boys from 9 to 16 years old. It was found that depending on the gender and sexual identity of the child, as well as their own criminal goals, the groomers use different tactics of manipulative influence. Boys are significantly more likely to exhibit sexual motive when interacting with abusers, as well as greater victimization (p=0.000). Girls are predominantly oriented towards neutral and friendly interactions and do not allow it to go beyond these limits (p=0.000). It is concluded that prevention of victimization of minors involved in cybergrooming should include the development of skills to assert personal boundaries and critical attitude towards online interlocutors.</p>

The Impact of Spatial Frequency on the Perception of Crowd Emotion: An fMRI Study.

Recognizing the emotions of faces in a crowd is crucial for understanding overall behavior and intention as well as for smooth and friendly social interactions. However, it is unclear whether the spatial frequency of faces affects the discrimination of crowd emotion. Although high- and low-spatial-frequency information for individual faces is processed by distinct neural channels, there is a lack of evidence on how this applies to crowd faces. Here, we used functional magnetic resonance imaging (fMRI) to investigate neural representations of crowd faces at different spatial frequencies. Thirty-three participants were asked to compare whether a test face was happy or more fearful than a crowd face that varied in high, low, and broad spatial frequencies. Our findings revealed that fearful faces with low spatial frequencies were easier to recognize in terms of accuracy (78.9%) and response time (927 ms). Brain regions, such as the fusiform gyrus, located in the ventral visual stream, were preferentially activated in high spatial frequency crowds, which, however, were the most difficult to recognize behaviorally (68.9%). Finally, the right inferior frontal gyrus was found to be better activated in the broad spatial frequency crowds. Our study suggests that people are more sensitive to fearful crowd faces with low spatial frequency and that high spatial frequency does not promote crowd face recognition.

Dog owner mental health is associated with dog behavioural problems, dog care and dog-facilitated social interaction: a prospective cohort study

Despite numerous qualitative and cross-sectional studies investigating how dog-related factors may impact owners’ well-being, empirical studies to test these causal effects are lacking. This prospective cohort study examined the correlation and potential causal effect of 17 dog-related factors with six well-being outcomes (depression, anxiety, loneliness, suicidal ideation, hedonic well-being and eudaimonic well-being) in dog owners. Over a four-week period, 709 adult dog owners reported their weekly well-being and occurrence of each dog-related factor (e.g. how many times they ran with their dogs). A random intercept cross-lagged panel model (RI-CLPM) with significance threshold set at 0.001 was used. Six factors correlated with poorer owner well-being (i.e. aggressive dog behaviour, fearful dog behaviour, poor dog health, failure to provide for the dog, lack of control over the dog, and dog presence). Only ‘friendly conversation with others due to the dog’ correlated with better well-being. Purposeful reductions in the frequency of dog behavioural and health-related issues are likely to improve owner well-being, as well as greater consistency in dog care (i.e. provide for the dog) and more engagement in friendly dog-facilitated social interactions. No potential causal effects were significant. Further studies investigating causal relationships are essential to improve people’s well-being through dog ownership.

Research on Optimal Control Method of Load Side Virtual Power Plant Based on Cloud Edge Collaboration

With the advancement of new power system construction, the large-scale layout of new energy power generation has gradually become a new format, and the overall new energy presents the characteristics of “rapid development of installed capacity, an increased proportion of low-voltage grid connection, and ultra-high penetration rate in some areas”. Under the new situation of power generation, power transmission, power distribution, and power consumption, to solve the problem of efficient and friendly interaction of “source, network, load and storage” in the power system and the consumption of renewable energy, “virtual power plant” came into being. However, there are limitations in aggregating resources in virtual power plants. To improve the effective participation of users, such as medium and low loads in power grid interaction, this article designs and implements a load-side virtual power plant control software system based on cloud-side collaboration. We use the virtual power plant operation control system to realize resource bidding and flexible participation in the response. The system can flexibly aggregate multiple types of resources through deployment verification, effectively realize precise tracking of instructions, and guarantee effective grid interaction.

Design optimization of energy systems for zero energy buildings based on grid-friendly interaction with smart grid

Zero-energy buildings usually achieve annual net-zero energy balance by generating electricity using on-site renewable energies and interconnecting with the power grid. However, the impact of energy mismatch problem in zero-energy buildings design on the grid is often overlooked, which potentially compromises grid's stability. To address this issue, this paper presents an optimization design method based on "grid-friendly interaction" which optimizes the energy system of zero-energy buildings to ensure better alignment between the building's electricity purchase/sale and grid demand. In this study, an indicator of "grid-friendly interaction", which represents the ratio of the net building friendly interaction power to the total annual interaction power, is firstly established to guide buildings in improving their interaction with the grid. Next, the energy supply, demand, and storage schemes of renewable energy systems in the zero-energy building are iteratively adjusted to achieve the best match with grid's expectations. This optimization design method was applied to a practical case in Hong Kong. Results show that, compared to the benchmark building, the optimal system design scheme increases grid friendliness by 83 %, reduces carbon dioxide emissions by 77 %, but also incurs a total cost increase of 180 %. The optimization design method proposed in this paper can effectively mitigate the impact of zero-energy buildings on the power grid, fostering enhanced interplay between the building structures and the grid. The study significantly contributes to the advancement of exploring the potential for energy flexibility in zero-energy buildings, which is of great significance for the safe and stable operation of future grids. The purpose of this study is to explore the energy flexibility potential of zero-energy buildings, which is of great significance for the safe and stable operation of future grids.