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AI-Mediated Intimacy: A Media Psychology Analysis of Young Adults’ Emotional Reliance on Chatbots
No full textArtificial intelligence (AI) plays a vital role in daily life, not only providing information retrieval but also emotional support. New chatbots, as an emerging channel with the ability to generate human-like conversations and display emotional responses, have become a crucial tool for young people to seek emotional support. The public can use chatbots to express themselves without fear of negative consequences. AI chatbots offer an alternative form of mediated intimacy, providing emotional support through interaction that differs from the interpersonal connections humans have. Although users may experience empathy in chatbot responses, this empathy is artificial rather than genuine. Drawing on uses and gratifications theory (UGT), parasocial interaction theory, and social presence theory, this study reviews existing research to explain why young people choose AI chatbots for companionship, stress relief, and self-expression. This study explores the factors that motivate young people to engage with AI chatbots for self-expression and emotional support, as well as their understanding of AI chatbots’ emotional capabilities. The findings have practical implications for addressing concerns about the potential for AI technology to induce deceptive emotions and contribute to mental health issues
Development of AI-driven Language Translation Technology: From Technological Breakthroughs to Cultural Adaptation
No full textThe use of artificial intelligence in linguistics is changing language learning, research, human communication, and translation in a big way. Through the promotion of numerous artificial intelligence language models such as ChatGPT, the natural language processing (NLP) models they employ have greatly assisted users in extracting the necessary information, promoting theoretical research and practical exploration in many fields. Meanwhile, by enhancing the accuracy of language and the ability to recognize multiple languages, the efficiency and accuracy of realtime translation and simultaneous interpretation have been effectively improved. Some article reports highly praise the advanced nature of artificial intelligence. However, the cultural differences and ethical considerations involved still require active communication and close cooperation among workers, scholars, linguists, computer scientists and relevant departments in this field. This study explores the impact of artificial intelligence on crosscultural language communication, language teaching research, and translation for different needs. It is precisely because the future interdisciplinary research and application fields of artificial intelligence and linguistics have broad prospects that issues such as rational use, risk reduction, efficiency optimization, and privacy protection need to be put on the agenda as early as possible
Analysis of technical performance of pencak silat athletes in the sparring category of men's class c, men's class e and women's class b at malang state university
No full textThis research aims to find out the technical performance of pencak silat athletes in the sparring category of class C men, class E men and class B women of State University of Malang through performance analysis. This research uses descriptive qualitative methods with Visual Research Method techniques by analyzing match videos from the three athletes as research samples, there are 22 video recordings of matches from city to national levels as research objects. The results found that the dominant technique of the three athletes was the sickle kick. In men's class C athletes the sickle kick is done with a percentage of 39.1% with a technique success rate of 70%. In male E class athletes with a percentage of 34% and a percentage level of success of 85%. In female B class athletes with a technical percentage of 33% with a percentage of success of 75.4%. the results of the analysis show that, the left sickle kick has a higher success rate. The results of the above analysis can be used as a reference in analyzing technical performance to determine the development of individual abilities so that they can provide evaluations that are relevant to the needs of athletes
Analysis of the physical components affecting 50-meter freestyle swimming performance among undergraduate students of the elementary school physical education study program
No full textThis research is a quantitative descriptive study with a correlational design that aims to analyze the relationship of physical components to the 50-meter freestyle swimming ability of students in the Elementary School Physical Education Study Program, Faculty of Sport and Health Sciences, Universitas Negeri Makassar. The population of the research consists of all students who take the swimming course, with a sample of 30 people selected purposively. The research instruments include the push-up test (arm muscle strength), the beep test (cardiovascular endurance/VO₂ Max), and the vertical jump test (leg explosive power). Swimming ability was measured using a manual stopwatch and an electronic system. Statistical analysis was carried out using SPSS version 25 with a significance level of α = 0.05. The results of the research show a significant positive correlation between arm muscle strength (r = 0.36; p = 0.041), cardiovascular endurance (r = 0.61; p = 0.001), and leg explosive power (r = 0.54; p = 0.002) with 50-meter freestyle swimming ability. Regression analysis shows that the three physical components together contribute 56.9% to swimming performance. These findings confirm the importance of strength, endurance, and explosive power in achieving optimal performance and provide a scientific basis for designing effective training programs
The massive hot subdwarf binary LAMOST J065816.72+094343.1
No full textContext. Massive short-period binaries involving hot subdwarf stars (sdO/Bs) are rare but very relevant to constraining pathways for binary star evolution. Moreover, some of the most promising candidate progenitor systems leading to Type Ia supernovae (SNe Ia) involve sdO/Bs. LAMOST J065816.72+094343.1 has been identified to be such a candidate system.
Aims. To explore the nature and evolutionary future of LAMOST J065816.72+094343.1, we complemented archival spectroscopic data with additional time series spectra as well as high-resolution spectroscopy of the object. After combining these with photometric data, we determined the orbital parameters of the system and the mass of the companion.
Methods. We solved the orbit of the system by analyzing 68 low- and medium-resolution spectra using state-of-the-art mixed local thermodynamic equilibrium (LTE) and non-LTE model atmospheres. Additionally, we gathered nine high-resolution spectra to determine atmospheric parameters and the projected rotational velocity of the sdOB. The inclination angle of the system was constrained assuming tidal synchronization of the sdOB, which was verified via analysis of the ellipsoidal variations in the TESS light curve.
Results. We determine LAMOST J065816.72+094343.1 to be a binary consisting of a massive 0.82 ± 0.17 M⊙ sdOB component with a unseen companion. Due to the companion’s mass being very close to the Chandrasekhar mass limit and high for a white dwarf, it is unclear whether the compact companion is a white dwarf or a neutron star. We find the system to be in a close orbit, with a period of P = 0.31955193 d and an inclination angle of . While the exact nature of the companion remains unknown, we determine the system to either lead to a SN Ia or an intermediate mass binary pulsar, potentially after a phase as an intermediate-mass X-ray binary
Euclid Quick Data Release (Q1). The role of cosmic connectivity in shaping galaxy clusters
No full textThe matter around galaxy clusters is distributed over several filaments, reflecting their positions as nodes in the large-scale cosmic web. The number of filaments connected to a cluster, i.e. its connectivity, is expected to affect the physical properties of clusters. Using the first Euclid galaxy catalogue from the Euclid Quick Release 1 (Q1), we investigated the connectivity of galaxy clusters and how it correlates with their physical and galaxy member properties. Around 220 clusters located within the three fields of Q1 (covering ∼ 63 mathrm deg ^2) were analysed in the redshift range 0.2, 10^ 10.3 , ). In agreement with previous measurements, we recovered the mass-connectivity relation independently of the filament detection algorithm, showing that the most massive clusters are, on average, connected to a larger number of cosmic filaments, consistent with hierarchical structure formation models. Furthermore, we explored the possible correlations between connectivities and two cluster properties: the fraction of early-type galaxies and the Sérsic index of galaxy members. Our result suggests that the clusters populated by early-type galaxies exhibit higher connectivity compared to clusters dominated by late-type galaxies. These preliminary investigations highlight our ability to quantify the impact of the cosmic web's connectivity on cluster properties with Euclid
Éducation thérapeutique du patient et médecine intégrative : quelles perspectives ?
No full textL’éducation thérapeutique du patient (ETP) s’inscrit dans une continuité avec l’éducation à la santé, en s’appuyant sur les mêmes valeurs éthiques et en proposant les mêmes méthodes et outils. De façon plus spécifique, l’ETP s’adresse à une partie de la population, de plus en plus nombreuse, composée de personnes ayant une ou plusieurs maladies chroniques. Des convergences semblent se dessiner avec la médecine intégrative qui combine la médecine conventionnelle et les approches complémentaires, telles que : phytothérapie, aromathérapie, acupuncture, hypnose, sophrologie, méditation, pratiques psychocorporelles et bien d’autres. Dans cette perspective, l’ETP permettrait de développer les ressources et capacités de chacun pour prendre soin de soi par un plus large choix de pratiques de santé intégrant les moyens propres à la médecine conventionnelle et les méthodes complémentaires. Cet article explore la correspondance des approches et les liens entre les pratiques, propose des repères méthodologiques et tente de mettre en lumière quelques perspectives
Determining of iron oxide pellet porosity using image analysis and its effect on the reduction behavior
No full textHydrogen-based reduction of iron oxide is a promising new technology in fossil-free steelmaking. In the process, the iron oxide is usually fed in a form of spherical pellets or briquettes. In solid-gas-reactions, the porosity of the pellets is assumed to enhance the reduction kinetics via the increase of the available reaction surface area at the reaction interface. However, the multivariable and complex dynamics of the reduction system complicates the estimation of this effect, as it is known that the properties of the pellet evolve withing the progression of the reduction.
In the kinetic analysis procedure, determining the pellet porosity is a demanding task. Measuring the porosity of the pellets is commonly performed using tomography analyses. However, image analysis of X-Ray tomography images of pellet cross-section could provide more practical approach as faster method. In this study, a sophisticated image analysis procedure is developed to analyze the pellets and briquettes porosity based on cross-section images. It was found that the porosity based on image analysis correlates reasonably well with the tomography analysis, with the average percentage error between both approaches being 4.3%. In addition, the effect of cross-sectional porosity on the reduction rate of the pellets is analyzed by making use of kinetic analysis
Selective Recovery of Critical Metals from Spent Lithium-Ion Batteries through Direct Bioleaching Using
No full textThe rapid growth of electrified transportation and the widespread adoption of portable electronic devices have significantly increased the demand for efficient energy storage systems. Lithium-ion (Li-ion) batteries are known for having a higher energy density and a longer cycle life than other types of batteries, making them the most reliable and long-lasting choice. However, the escalating accumulation of end-of-life Li-ion batteries has introduced notable environmental and economic challenges. The intricate composition of these batteries complicates the selective recovery of valuable metals. Traditional recycling techniques, including pyrometallurgy and hydrometallurgy, although effective, are associated with high operational costs, substantial energy consumption, and the generation of secondary waste. As a sustainable alternative, bioleaching utilizes specific microorganisms to mediate the selective solubilization of metals from complex battery matrices through their metabolic activities. In this study, direct bioleaching of lithium-ion (Li-ion) battery black mass was performed over a seven-day period employing the mixotrophic bacterium Citrobacter freundii strain SKC-4. Following the bioleaching process, notable metal recoveries were achieved, with extraction efficiencies of 41.4% for lithium (Li), 2.4% for nickel (Ni), 2.9% for cobalt (Co), 9% for copper (Cu), 7.3% for manganese (Mn), and 6.7% for aluminum (Al). These findings demonstrate the efficacy of Citrobacter freundii in the direct bioleaching of spent Li-ion battery black mass and highlight its potential as an environmentally sustainable approach for the selective recovery of valuable metals, contributing to the advancement of circular economy practices in battery recycling
Bio-inspired Novel Liver Cancer algorithm for solving large-scale combined heat and Power economic dispatch problems.
No full textThe possibility of combined heat and power (CHP) systems to enhance the economics and sustainability of the electricity system is garnering more and more attention. The fact that these systems can have numerous generation units whose function is controlled by intricate non-linear physics makes it challenging to determine how to operate them optimally. The complex interconnections within bulk power systems pose significant challenges in solving economic dispatch problems, particularly in large-scale combined heat and power economic dispatch (CHPED) scenarios, which are difficult to address due to intricate thermal and electrical connections in cogeneration units. The current research work proposed a bio-inspired novel Liver cancer algorithm (LCA) to optimize a large-scale Combined heat and power economic dispatch system. The LCA algorithm employs genetic operators and a Random opposition-based learning (ROBL) technique to effectively achieve a balance between local and global searches and thoroughly explore the search space. The mutation rate is adjusted based on the number of iterations, and this higher mutation rate facilitates the exploration of promising new locations and protects the algorithm from being trapped at a local minimum. Hence, a better optimum value can be achieved in less time. To investigate the performance, the proposed method has been demonstrated on CHPED problems of one medium and two different large-scale test systems 48, 96 and 192 units respectively, and the results were compared to other state-of-the-art powerful approaches. The experimental results indicated that the LCA algorithm surpasses other methods to solve medium and large-scale CHPED problems