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Aims. Our objectives are to map the filamentary network around the Fornax-Eridanus complex and probe the influence of the local environment on galaxy morphology. Methods. We employed the novel machine-learning tool, named, 1-Dimensional, Recovery, Extraction, and Analysis of Manifolds (1-DREAM) to detect and model filaments around the Fornax cluster. We then used the morphology-density relation of galaxies to examine the variation in the galaxies' morphology with respect to their distance from the central axis of the detected filaments. Results. We detected 27 filaments that vary in length and galaxy-number density around the Fornax-Eridanus complex. We find that 81% of galaxies in our catalogue belong to filaments and 19% of galaxies are located outside filaments. The filaments around the Fornax-Eridanus complex showcase a variety of environments: some filaments encompass groups and clusters, while others are only inhabited by galaxies in pristine filamentary environments. In this context, we reveal a well-known structure, namely: the Fornax Wall, which passes through the Dorado group, Fornax cluster, and Eridanus supergroup. With regard to the morphology of galaxies, we find that early-type galaxies (ETGs) populate high-density filaments and high-density regions of the Fornax Wall. Furthermore, the fraction of the ETG-population decreases as the distance to the central axis of the filament increases. The fraction of late-type galaxies (LTGs; 8%) is lower than that of ETGs (12%) at 0.5 Mpc/h from the filament spine. Of the total galaxy population in filaments around the Fornax-Eridanus complex, ∼7% are ETGs and ∼24% are LTGs located in pristine environments of filaments, while ∼27% are ETGs and ∼42% are LTGs in groups and clusters within filaments. Among the galaxies in the filamentary network around the Fornax-Eridanus complex, 44% of them belong to the Fornax Wall. Conclusions. This study reveals the cosmic web around the Fornax cluster, which exhibits a variety of filamentary environments. With this, our research asserts that filamentary environments are heterogeneous in nature. When investigating the role of the environment on galaxy morphology, it is essential to consider both the local number-density and a galaxy's proximity to the filament spine (i.e. the filament core). Within this framework, we ascribe the observed morphological segregation in the Fornax Wall to the pre-processing of galaxies among groups embedded in it. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive analysis of the dynamics of Mpox viral transmission using a compartmental mathematical model. The model incorporates the impact of immunization, isolation, and hospitalization on disease management, as well as the interaction between humans and rodents. Through numerical simulations, the study highlights the effectiveness of isolation in mitigating disease transmission and emphasizes the significance of mathematical modeling and simulation techniques in understanding disease dynamics. The utilization of Caputo's fractional differential equation in the human dynamical model is shown to be effective in regulating disease in all compartments. Sensitivity analysis is conducted to identify the most influential parameters in virus transmission. The findings contribute valuable insights for public health strategies and provide a foundation for further research in disease control and management. [ABSTRACT FROM AUTHOR]

An additional tool for swaying public opinion on social media is to present recent developments in the creation of natural language. The term "Deep fake" originates from deep learning technology, which effortlessly and seamlessly steers someone toward digital media. Artificial Intelligence (AI) techniques are a crucial component of deep fakes. The generative powers of generative capabilities greatly reinforce the advancements in language modeling for content generation. Due to low-cost computing infrastructure, sophisticated tools, and readily available content on social media, deep fakes propagate misinformation and hoaxes. These technologies make it simple to produce misinformation that spreads fear and confusion to everyone. As such, distinguishing between authentic and fraudulent content can be challenging. This study presents a novel automated approach for the identification of deep fakes, based on Adaptive Gaining Sharing Knowledge (AGSK) and using DenseNet121 architecture. During pre-processing, the image's sensitive data variance or noise is eliminated. Following that, CapsuleNet is used to extract the feature vectors. The deep fake is identified from the resulting feature vectors by an AGSK with DenseNet121 architecture, together with the hyper-parameter that has been optimized using the AGSK model. Propaganda and defamation pose less of a concern, and the results of the suggested deepfake image recognition model show how reliable and successful the model is. The accuracy of detection is 98% higher than other cutting-edge models. [ABSTRACT FROM AUTHOR]

This study investigates a novel class of electrode materials known as mixed transition-metal oxides (MMOs) for their improved electrochemical capabilities. Specifically, a one-pot hydrothermal method is employed to successfully synthesize binary mixed-metal oxides comprising manganese oxide and copper oxide (Mn2O3/CuO). The interest in MMOs lies in their potential to enhance multifunctional performance compared to single metal oxides, prompting a comprehensive examination of their structure and properties. Various analytical techniques are utilized to investigate the crystal structures, functional groups and surface morphology of the single and binary MMOs. Moreover, electrochemical experiments are conducted to assess their electrochemical behaviour. The results reveal that the Mn2O3 and CuO MMOs' electrodes exhibit pseudocapacitor-like characteristics, outperforming single metal oxides in terms of specific capacitance. At a current density of 1 A g−1, the Mn2O3/CuO MMOs electrodes achieve a specific capacitance of 342.85 F g−1. Notably, the symmetric device demonstrates excellent retentivity (89.97%) even after 5000 repeated cycles, showcasing its exceptional supercapacitive attributes for maximum energy storage capability. [ABSTRACT FROM AUTHOR]

The paper emphasis on the teaching learning process by evaluating the Emotional Maturity and Metacognition of high school teachers. Metacognitive strategies are essential for the teachers of 21st century. This may enable teachers to successfully cope with and handle new situations. For this they should be able to regulate their thinking. So, it is the main duty of a teacher to impart knowledge and also they should make the students to think and to think over their thinking and to act accordingly. The metacognitive knowledge is encompassed with all the information about a proposed task that is available to a teacher. The emotional maturity of teachers should find expression in all domains, whether it is teaching, talking, playing, or walking. Emotionally mature teachers are likely to produce emotionally balanced learners and this transfer of maturity enables a teacher to manage or control his class irrespective of the conditions it has. If the teachers are emotionally matured, they can manage the situations effectively. When the teachers think, plan, and be aware of their classroom activities, they would be emotionally balanced and stable. The research was a survey type, which consists of random sampling of 800 high school teachers in Dindigul and Madurai districts. The investigator has constructed and validated the Metacognition Scale and Emotional Maturity Scale by self under the guidance of his research guide. Personal data sheet was prepared by the investigator. The interpretation of data was done with statistical methods in percentage analysis, mean, standard deviation, and 't'-test and correlation. The result showed that there is significant relationship between the Emotional Maturity and Metacognition of high school teachers.